diff --git a/llmeval-env/lib/python3.10/site-packages/certifi-2024.2.2.dist-info/INSTALLER b/llmeval-env/lib/python3.10/site-packages/certifi-2024.2.2.dist-info/INSTALLER new file mode 100644 index 0000000000000000000000000000000000000000..a1b589e38a32041e49332e5e81c2d363dc418d68 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/certifi-2024.2.2.dist-info/INSTALLER @@ -0,0 +1 @@ +pip diff --git a/llmeval-env/lib/python3.10/site-packages/certifi-2024.2.2.dist-info/LICENSE b/llmeval-env/lib/python3.10/site-packages/certifi-2024.2.2.dist-info/LICENSE new file mode 100644 index 0000000000000000000000000000000000000000..62b076cdee58ec8f34034141ba0befd9015b0c7e --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/certifi-2024.2.2.dist-info/LICENSE @@ -0,0 +1,20 @@ +This package contains a modified version of ca-bundle.crt: + +ca-bundle.crt -- Bundle of CA Root Certificates + +This is a bundle of X.509 certificates of public Certificate Authorities +(CA). These were automatically extracted from Mozilla's root certificates +file (certdata.txt). This file can be found in the mozilla source tree: +https://hg.mozilla.org/mozilla-central/file/tip/security/nss/lib/ckfw/builtins/certdata.txt +It contains the certificates in PEM format and therefore +can be directly used with curl / libcurl / php_curl, or with +an Apache+mod_ssl webserver for SSL client authentication. +Just configure this file as the SSLCACertificateFile.# + +***** BEGIN LICENSE BLOCK ***** +This Source Code Form is subject to the terms of the Mozilla Public License, +v. 2.0. If a copy of the MPL was not distributed with this file, You can obtain +one at http://mozilla.org/MPL/2.0/. + +***** END LICENSE BLOCK ***** +@(#) $RCSfile: certdata.txt,v $ $Revision: 1.80 $ $Date: 2011/11/03 15:11:58 $ diff --git a/llmeval-env/lib/python3.10/site-packages/certifi-2024.2.2.dist-info/METADATA b/llmeval-env/lib/python3.10/site-packages/certifi-2024.2.2.dist-info/METADATA new file mode 100644 index 0000000000000000000000000000000000000000..c688a62848560861b62738ef0b70d373c4980baf --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/certifi-2024.2.2.dist-info/METADATA @@ -0,0 +1,66 @@ +Metadata-Version: 2.1 +Name: certifi +Version: 2024.2.2 +Summary: Python package for providing Mozilla's CA Bundle. +Home-page: https://github.com/certifi/python-certifi +Author: Kenneth Reitz +Author-email: me@kennethreitz.com +License: MPL-2.0 +Project-URL: Source, https://github.com/certifi/python-certifi +Classifier: Development Status :: 5 - Production/Stable +Classifier: Intended Audience :: Developers +Classifier: License :: OSI Approved :: Mozilla Public License 2.0 (MPL 2.0) +Classifier: Natural Language :: English +Classifier: Programming Language :: Python +Classifier: Programming Language :: Python :: 3 +Classifier: Programming Language :: Python :: 3 :: Only +Classifier: Programming Language :: Python :: 3.6 +Classifier: Programming Language :: Python :: 3.7 +Classifier: Programming Language :: Python :: 3.8 +Classifier: Programming Language :: Python :: 3.9 +Classifier: Programming Language :: Python :: 3.10 +Classifier: Programming Language :: Python :: 3.11 +Requires-Python: >=3.6 +License-File: LICENSE + +Certifi: Python SSL Certificates +================================ + +Certifi provides Mozilla's carefully curated collection of Root Certificates for +validating the trustworthiness of SSL certificates while verifying the identity +of TLS hosts. It has been extracted from the `Requests`_ project. + +Installation +------------ + +``certifi`` is available on PyPI. Simply install it with ``pip``:: + + $ pip install certifi + +Usage +----- + +To reference the installed certificate authority (CA) bundle, you can use the +built-in function:: + + >>> import certifi + + >>> certifi.where() + '/usr/local/lib/python3.7/site-packages/certifi/cacert.pem' + +Or from the command line:: + + $ python -m certifi + /usr/local/lib/python3.7/site-packages/certifi/cacert.pem + +Enjoy! + +.. _`Requests`: https://requests.readthedocs.io/en/master/ + +Addition/Removal of Certificates +-------------------------------- + +Certifi does not support any addition/removal or other modification of the +CA trust store content. This project is intended to provide a reliable and +highly portable root of trust to python deployments. Look to upstream projects +for methods to use alternate trust. diff --git a/llmeval-env/lib/python3.10/site-packages/certifi-2024.2.2.dist-info/RECORD b/llmeval-env/lib/python3.10/site-packages/certifi-2024.2.2.dist-info/RECORD new file mode 100644 index 0000000000000000000000000000000000000000..3f70d91915cf10dffe340302ca51705e29b6f520 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/certifi-2024.2.2.dist-info/RECORD @@ -0,0 +1,14 @@ +certifi-2024.2.2.dist-info/INSTALLER,sha256=zuuue4knoyJ-UwPPXg8fezS7VCrXJQrAP7zeNuwvFQg,4 +certifi-2024.2.2.dist-info/LICENSE,sha256=6TcW2mucDVpKHfYP5pWzcPBpVgPSH2-D8FPkLPwQyvc,989 +certifi-2024.2.2.dist-info/METADATA,sha256=1noreLRChpOgeSj0uJT1mehiBl8ngh33Guc7KdvzYYM,2170 +certifi-2024.2.2.dist-info/RECORD,, +certifi-2024.2.2.dist-info/WHEEL,sha256=oiQVh_5PnQM0E3gPdiz09WCNmwiHDMaGer_elqB3coM,92 +certifi-2024.2.2.dist-info/top_level.txt,sha256=KMu4vUCfsjLrkPbSNdgdekS-pVJzBAJFO__nI8NF6-U,8 +certifi/__init__.py,sha256=ljtEx-EmmPpTe2SOd5Kzsujm_lUD0fKJVnE9gzce320,94 +certifi/__main__.py,sha256=xBBoj905TUWBLRGANOcf7oi6e-3dMP4cEoG9OyMs11g,243 +certifi/__pycache__/__init__.cpython-310.pyc,, +certifi/__pycache__/__main__.cpython-310.pyc,, +certifi/__pycache__/core.cpython-310.pyc,, +certifi/cacert.pem,sha256=ejR8qP724p-CtuR4U1WmY1wX-nVeCUD2XxWqj8e9f5I,292541 +certifi/core.py,sha256=qRDDFyXVJwTB_EmoGppaXU_R9qCZvhl-EzxPMuV3nTA,4426 +certifi/py.typed,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0 diff --git a/llmeval-env/lib/python3.10/site-packages/certifi-2024.2.2.dist-info/WHEEL b/llmeval-env/lib/python3.10/site-packages/certifi-2024.2.2.dist-info/WHEEL new file mode 100644 index 0000000000000000000000000000000000000000..98c0d20b7a64f4f998d7913e1d38a05dba20916c --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/certifi-2024.2.2.dist-info/WHEEL @@ -0,0 +1,5 @@ +Wheel-Version: 1.0 +Generator: bdist_wheel (0.42.0) +Root-Is-Purelib: true +Tag: py3-none-any + diff --git a/llmeval-env/lib/python3.10/site-packages/certifi-2024.2.2.dist-info/top_level.txt b/llmeval-env/lib/python3.10/site-packages/certifi-2024.2.2.dist-info/top_level.txt new file mode 100644 index 0000000000000000000000000000000000000000..963eac530b9bc28d704d1bc410299c68e3216d4d --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/certifi-2024.2.2.dist-info/top_level.txt @@ -0,0 +1 @@ +certifi diff --git a/llmeval-env/lib/python3.10/site-packages/nltk/VERSION b/llmeval-env/lib/python3.10/site-packages/nltk/VERSION new file mode 100644 index 0000000000000000000000000000000000000000..0603aab1e29c286f7779a50891582571b616825c --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/nltk/VERSION @@ -0,0 +1 @@ +3.8.1 diff --git a/llmeval-env/lib/python3.10/site-packages/nltk/__init__.py b/llmeval-env/lib/python3.10/site-packages/nltk/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..b87cf230510581745ced457e373a7ecc7c3c9006 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/nltk/__init__.py @@ -0,0 +1,209 @@ +# Natural Language Toolkit (NLTK) +# +# Copyright (C) 2001-2023 NLTK Project +# Authors: Steven Bird +# Edward Loper +# URL: +# For license information, see LICENSE.TXT + +""" +The Natural Language Toolkit (NLTK) is an open source Python library +for Natural Language Processing. A free online book is available. +(If you use the library for academic research, please cite the book.) + +Steven Bird, Ewan Klein, and Edward Loper (2009). +Natural Language Processing with Python. O'Reilly Media Inc. +https://www.nltk.org/book/ + +isort:skip_file +""" + +import os + +# ////////////////////////////////////////////////////// +# Metadata +# ////////////////////////////////////////////////////// + +# Version. For each new release, the version number should be updated +# in the file VERSION. +try: + # If a VERSION file exists, use it! + version_file = os.path.join(os.path.dirname(__file__), "VERSION") + with open(version_file) as infile: + __version__ = infile.read().strip() +except NameError: + __version__ = "unknown (running code interactively?)" +except OSError as ex: + __version__ = "unknown (%s)" % ex + +if __doc__ is not None: # fix for the ``python -OO`` + __doc__ += "\n@version: " + __version__ + + +# Copyright notice +__copyright__ = """\ +Copyright (C) 2001-2023 NLTK Project. + +Distributed and Licensed under the Apache License, Version 2.0, +which is included by reference. +""" + +__license__ = "Apache License, Version 2.0" +# Description of the toolkit, keywords, and the project's primary URL. +__longdescr__ = """\ +The Natural Language Toolkit (NLTK) is a Python package for +natural language processing. NLTK requires Python 3.7, 3.8, 3.9, 3.10 or 3.11.""" +__keywords__ = [ + "NLP", + "CL", + "natural language processing", + "computational linguistics", + "parsing", + "tagging", + "tokenizing", + "syntax", + "linguistics", + "language", + "natural language", + "text analytics", +] +__url__ = "https://www.nltk.org/" + +# Maintainer, contributors, etc. +__maintainer__ = "NLTK Team" +__maintainer_email__ = "nltk.team@gmail.com" +__author__ = __maintainer__ +__author_email__ = __maintainer_email__ + +# "Trove" classifiers for Python Package Index. +__classifiers__ = [ + "Development Status :: 5 - Production/Stable", + "Intended Audience :: Developers", + "Intended Audience :: Education", + "Intended Audience :: Information Technology", + "Intended Audience :: Science/Research", + "License :: OSI Approved :: Apache Software License", + "Operating System :: OS Independent", + "Programming Language :: Python :: 3.7", + "Programming Language :: Python :: 3.8", + "Programming Language :: Python :: 3.9", + "Programming Language :: Python :: 3.10", + "Programming Language :: Python :: 3.11", + "Topic :: Scientific/Engineering", + "Topic :: Scientific/Engineering :: Artificial Intelligence", + "Topic :: Scientific/Engineering :: Human Machine Interfaces", + "Topic :: Scientific/Engineering :: Information Analysis", + "Topic :: Text Processing", + "Topic :: Text Processing :: Filters", + "Topic :: Text Processing :: General", + "Topic :: Text Processing :: Indexing", + "Topic :: Text Processing :: Linguistic", +] + +from nltk.internals import config_java + +# support numpy from pypy +try: + import numpypy +except ImportError: + pass + +# Override missing methods on environments where it cannot be used like GAE. +import subprocess + +if not hasattr(subprocess, "PIPE"): + + def _fake_PIPE(*args, **kwargs): + raise NotImplementedError("subprocess.PIPE is not supported.") + + subprocess.PIPE = _fake_PIPE +if not hasattr(subprocess, "Popen"): + + def _fake_Popen(*args, **kwargs): + raise NotImplementedError("subprocess.Popen is not supported.") + + subprocess.Popen = _fake_Popen + +########################################################### +# TOP-LEVEL MODULES +########################################################### + +# Import top-level functionality into top-level namespace + +from nltk.collocations import * +from nltk.decorators import decorator, memoize +from nltk.featstruct import * +from nltk.grammar import * +from nltk.probability import * +from nltk.text import * +from nltk.util import * +from nltk.jsontags import * + +########################################################### +# PACKAGES +########################################################### + +from nltk.chunk import * +from nltk.classify import * +from nltk.inference import * +from nltk.metrics import * +from nltk.parse import * +from nltk.tag import * +from nltk.tokenize import * +from nltk.translate import * +from nltk.tree import * +from nltk.sem import * +from nltk.stem import * + +# Packages which can be lazily imported +# (a) we don't import * +# (b) they're slow to import or have run-time dependencies +# that can safely fail at run time + +from nltk import lazyimport + +app = lazyimport.LazyModule("app", locals(), globals()) +chat = lazyimport.LazyModule("chat", locals(), globals()) +corpus = lazyimport.LazyModule("corpus", locals(), globals()) +draw = lazyimport.LazyModule("draw", locals(), globals()) +toolbox = lazyimport.LazyModule("toolbox", locals(), globals()) + +# Optional loading + +try: + import numpy +except ImportError: + pass +else: + from nltk import cluster + +from nltk.downloader import download, download_shell + +try: + import tkinter +except ImportError: + pass +else: + try: + from nltk.downloader import download_gui + except RuntimeError as e: + import warnings + + warnings.warn( + "Corpus downloader GUI not loaded " + "(RuntimeError during import: %s)" % str(e) + ) + +# explicitly import all top-level modules (ensuring +# they override the same names inadvertently imported +# from a subpackage) + +from nltk import ccg, chunk, classify, collocations +from nltk import data, featstruct, grammar, help, inference, metrics +from nltk import misc, parse, probability, sem, stem, wsd +from nltk import tag, tbl, text, tokenize, translate, tree, util + + +# FIXME: override any accidentally imported demo, see https://github.com/nltk/nltk/issues/2116 +def demo(): + print("To run the demo code for a module, type nltk.module.demo()") diff --git a/llmeval-env/lib/python3.10/site-packages/nltk/book.py b/llmeval-env/lib/python3.10/site-packages/nltk/book.py new file mode 100644 index 0000000000000000000000000000000000000000..704f84d426fdf87b4233454c8ceb9915d7db3161 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/nltk/book.py @@ -0,0 +1,213 @@ +# Natural Language Toolkit: Some texts for exploration in chapter 1 of the book +# +# Copyright (C) 2001-2023 NLTK Project +# Author: Steven Bird +# +# URL: +# For license information, see LICENSE.TXT + +from nltk.corpus import ( + genesis, + gutenberg, + inaugural, + nps_chat, + treebank, + webtext, + wordnet, +) +from nltk.probability import FreqDist +from nltk.text import Text +from nltk.util import bigrams + +print("*** Introductory Examples for the NLTK Book ***") +print("Loading text1, ..., text9 and sent1, ..., sent9") +print("Type the name of the text or sentence to view it.") +print("Type: 'texts()' or 'sents()' to list the materials.") + +text1 = Text(gutenberg.words("melville-moby_dick.txt")) +print("text1:", text1.name) + +text2 = Text(gutenberg.words("austen-sense.txt")) +print("text2:", text2.name) + +text3 = Text(genesis.words("english-kjv.txt"), name="The Book of Genesis") +print("text3:", text3.name) + +text4 = Text(inaugural.words(), name="Inaugural Address Corpus") +print("text4:", text4.name) + +text5 = Text(nps_chat.words(), name="Chat Corpus") +print("text5:", text5.name) + +text6 = Text(webtext.words("grail.txt"), name="Monty Python and the Holy Grail") +print("text6:", text6.name) + +text7 = Text(treebank.words(), name="Wall Street Journal") +print("text7:", text7.name) + +text8 = Text(webtext.words("singles.txt"), name="Personals Corpus") +print("text8:", text8.name) + +text9 = Text(gutenberg.words("chesterton-thursday.txt")) +print("text9:", text9.name) + + +def texts(): + print("text1:", text1.name) + print("text2:", text2.name) + print("text3:", text3.name) + print("text4:", text4.name) + print("text5:", text5.name) + print("text6:", text6.name) + print("text7:", text7.name) + print("text8:", text8.name) + print("text9:", text9.name) + + +sent1 = ["Call", "me", "Ishmael", "."] +sent2 = [ + "The", + "family", + "of", + "Dashwood", + "had", + "long", + "been", + "settled", + "in", + "Sussex", + ".", +] +sent3 = [ + "In", + "the", + "beginning", + "God", + "created", + "the", + "heaven", + "and", + "the", + "earth", + ".", +] +sent4 = [ + "Fellow", + "-", + "Citizens", + "of", + "the", + "Senate", + "and", + "of", + "the", + "House", + "of", + "Representatives", + ":", +] +sent5 = [ + "I", + "have", + "a", + "problem", + "with", + "people", + "PMing", + "me", + "to", + "lol", + "JOIN", +] +sent6 = [ + "SCENE", + "1", + ":", + "[", + "wind", + "]", + "[", + "clop", + "clop", + "clop", + "]", + "KING", + "ARTHUR", + ":", + "Whoa", + "there", + "!", +] +sent7 = [ + "Pierre", + "Vinken", + ",", + "61", + "years", + "old", + ",", + "will", + "join", + "the", + "board", + "as", + "a", + "nonexecutive", + "director", + "Nov.", + "29", + ".", +] +sent8 = [ + "25", + "SEXY", + "MALE", + ",", + "seeks", + "attrac", + "older", + "single", + "lady", + ",", + "for", + "discreet", + "encounters", + ".", +] +sent9 = [ + "THE", + "suburb", + "of", + "Saffron", + "Park", + "lay", + "on", + "the", + "sunset", + "side", + "of", + "London", + ",", + "as", + "red", + "and", + "ragged", + "as", + "a", + "cloud", + "of", + "sunset", + ".", +] + + +def sents(): + print("sent1:", " ".join(sent1)) + print("sent2:", " ".join(sent2)) + print("sent3:", " ".join(sent3)) + print("sent4:", " ".join(sent4)) + print("sent5:", " ".join(sent5)) + print("sent6:", " ".join(sent6)) + print("sent7:", " ".join(sent7)) + print("sent8:", " ".join(sent8)) + print("sent9:", " ".join(sent9)) diff --git a/llmeval-env/lib/python3.10/site-packages/nltk/ccg/__init__.py b/llmeval-env/lib/python3.10/site-packages/nltk/ccg/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..43c5876b74dcf07ea70c9d90c1dcd41971e515a4 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/nltk/ccg/__init__.py @@ -0,0 +1,34 @@ +# Natural Language Toolkit: Combinatory Categorial Grammar +# +# Copyright (C) 2001-2023 NLTK Project +# Author: Graeme Gange +# URL: +# For license information, see LICENSE.TXT + +""" +Combinatory Categorial Grammar. + +For more information see nltk/doc/contrib/ccg/ccg.pdf +""" + +from nltk.ccg.chart import CCGChart, CCGChartParser, CCGEdge, CCGLeafEdge +from nltk.ccg.combinator import ( + BackwardApplication, + BackwardBx, + BackwardCombinator, + BackwardComposition, + BackwardSx, + BackwardT, + DirectedBinaryCombinator, + ForwardApplication, + ForwardCombinator, + ForwardComposition, + ForwardSubstitution, + ForwardT, + UndirectedBinaryCombinator, + UndirectedComposition, + UndirectedFunctionApplication, + UndirectedSubstitution, + UndirectedTypeRaise, +) +from nltk.ccg.lexicon import CCGLexicon diff --git a/llmeval-env/lib/python3.10/site-packages/nltk/ccg/__pycache__/__init__.cpython-310.pyc b/llmeval-env/lib/python3.10/site-packages/nltk/ccg/__pycache__/__init__.cpython-310.pyc new file mode 100644 index 0000000000000000000000000000000000000000..19c36a347955a5ff08444da1f6952dc30e934e0d Binary files /dev/null and b/llmeval-env/lib/python3.10/site-packages/nltk/ccg/__pycache__/__init__.cpython-310.pyc differ diff --git a/llmeval-env/lib/python3.10/site-packages/nltk/ccg/__pycache__/api.cpython-310.pyc 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b/llmeval-env/lib/python3.10/site-packages/nltk/ccg/__pycache__/logic.cpython-310.pyc differ diff --git a/llmeval-env/lib/python3.10/site-packages/nltk/ccg/api.py b/llmeval-env/lib/python3.10/site-packages/nltk/ccg/api.py new file mode 100644 index 0000000000000000000000000000000000000000..f0d1355cfadca031cf0017584d819fe794ffaea3 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/nltk/ccg/api.py @@ -0,0 +1,358 @@ +# Natural Language Toolkit: CCG Categories +# +# Copyright (C) 2001-2023 NLTK Project +# Author: Graeme Gange +# URL: +# For license information, see LICENSE.TXT + +from abc import ABCMeta, abstractmethod +from functools import total_ordering + +from nltk.internals import raise_unorderable_types + + +@total_ordering +class AbstractCCGCategory(metaclass=ABCMeta): + """ + Interface for categories in combinatory grammars. + """ + + @abstractmethod + def is_primitive(self): + """ + Returns true if the category is primitive. + """ + + @abstractmethod + def is_function(self): + """ + Returns true if the category is a function application. + """ + + @abstractmethod + def is_var(self): + """ + Returns true if the category is a variable. + """ + + @abstractmethod + def substitute(self, substitutions): + """ + Takes a set of (var, category) substitutions, and replaces every + occurrence of the variable with the corresponding category. + """ + + @abstractmethod + def can_unify(self, other): + """ + Determines whether two categories can be unified. + - Returns None if they cannot be unified + - Returns a list of necessary substitutions if they can. + """ + + # Utility functions: comparison, strings and hashing. + @abstractmethod + def __str__(self): + pass + + def __eq__(self, other): + return ( + self.__class__ is other.__class__ + and self._comparison_key == other._comparison_key + ) + + def __ne__(self, other): + return not self == other + + def __lt__(self, other): + if not isinstance(other, AbstractCCGCategory): + raise_unorderable_types("<", self, other) + if self.__class__ is other.__class__: + return self._comparison_key < other._comparison_key + else: + return self.__class__.__name__ < other.__class__.__name__ + + def __hash__(self): + try: + return self._hash + except AttributeError: + self._hash = hash(self._comparison_key) + return self._hash + + +class CCGVar(AbstractCCGCategory): + """ + Class representing a variable CCG category. + Used for conjunctions (and possibly type-raising, if implemented as a + unary rule). + """ + + _maxID = 0 + + def __init__(self, prim_only=False): + """Initialize a variable (selects a new identifier) + + :param prim_only: a boolean that determines whether the variable is + restricted to primitives + :type prim_only: bool + """ + self._id = self.new_id() + self._prim_only = prim_only + self._comparison_key = self._id + + @classmethod + def new_id(cls): + """ + A class method allowing generation of unique variable identifiers. + """ + cls._maxID = cls._maxID + 1 + return cls._maxID - 1 + + @classmethod + def reset_id(cls): + cls._maxID = 0 + + def is_primitive(self): + return False + + def is_function(self): + return False + + def is_var(self): + return True + + def substitute(self, substitutions): + """If there is a substitution corresponding to this variable, + return the substituted category. + """ + for (var, cat) in substitutions: + if var == self: + return cat + return self + + def can_unify(self, other): + """If the variable can be replaced with other + a substitution is returned. + """ + if other.is_primitive() or not self._prim_only: + return [(self, other)] + return None + + def id(self): + return self._id + + def __str__(self): + return "_var" + str(self._id) + + +@total_ordering +class Direction: + """ + Class representing the direction of a function application. + Also contains maintains information as to which combinators + may be used with the category. + """ + + def __init__(self, dir, restrictions): + self._dir = dir + self._restrs = restrictions + self._comparison_key = (dir, tuple(restrictions)) + + # Testing the application direction + def is_forward(self): + return self._dir == "/" + + def is_backward(self): + return self._dir == "\\" + + def dir(self): + return self._dir + + def restrs(self): + """A list of restrictions on the combinators. + '.' denotes that permuting operations are disallowed + ',' denotes that function composition is disallowed + '_' denotes that the direction has variable restrictions. + (This is redundant in the current implementation of type-raising) + """ + return self._restrs + + def is_variable(self): + return self._restrs == "_" + + # Unification and substitution of variable directions. + # Used only if type-raising is implemented as a unary rule, as it + # must inherit restrictions from the argument category. + def can_unify(self, other): + if other.is_variable(): + return [("_", self.restrs())] + elif self.is_variable(): + return [("_", other.restrs())] + else: + if self.restrs() == other.restrs(): + return [] + return None + + def substitute(self, subs): + if not self.is_variable(): + return self + + for (var, restrs) in subs: + if var == "_": + return Direction(self._dir, restrs) + return self + + # Testing permitted combinators + def can_compose(self): + return "," not in self._restrs + + def can_cross(self): + return "." not in self._restrs + + def __eq__(self, other): + return ( + self.__class__ is other.__class__ + and self._comparison_key == other._comparison_key + ) + + def __ne__(self, other): + return not self == other + + def __lt__(self, other): + if not isinstance(other, Direction): + raise_unorderable_types("<", self, other) + if self.__class__ is other.__class__: + return self._comparison_key < other._comparison_key + else: + return self.__class__.__name__ < other.__class__.__name__ + + def __hash__(self): + try: + return self._hash + except AttributeError: + self._hash = hash(self._comparison_key) + return self._hash + + def __str__(self): + r_str = "" + for r in self._restrs: + r_str = r_str + "%s" % r + return f"{self._dir}{r_str}" + + # The negation operator reverses the direction of the application + def __neg__(self): + if self._dir == "/": + return Direction("\\", self._restrs) + else: + return Direction("/", self._restrs) + + +class PrimitiveCategory(AbstractCCGCategory): + """ + Class representing primitive categories. + Takes a string representation of the category, and a + list of strings specifying the morphological subcategories. + """ + + def __init__(self, categ, restrictions=[]): + self._categ = categ + self._restrs = restrictions + self._comparison_key = (categ, tuple(restrictions)) + + def is_primitive(self): + return True + + def is_function(self): + return False + + def is_var(self): + return False + + def restrs(self): + return self._restrs + + def categ(self): + return self._categ + + # Substitution does nothing to a primitive category + def substitute(self, subs): + return self + + # A primitive can be unified with a class of the same + # base category, given that the other category shares all + # of its subclasses, or with a variable. + def can_unify(self, other): + if not other.is_primitive(): + return None + if other.is_var(): + return [(other, self)] + if other.categ() == self.categ(): + for restr in self._restrs: + if restr not in other.restrs(): + return None + return [] + return None + + def __str__(self): + if self._restrs == []: + return "%s" % self._categ + restrictions = "[%s]" % ",".join(repr(r) for r in self._restrs) + return f"{self._categ}{restrictions}" + + +class FunctionalCategory(AbstractCCGCategory): + """ + Class that represents a function application category. + Consists of argument and result categories, together with + an application direction. + """ + + def __init__(self, res, arg, dir): + self._res = res + self._arg = arg + self._dir = dir + self._comparison_key = (arg, dir, res) + + def is_primitive(self): + return False + + def is_function(self): + return True + + def is_var(self): + return False + + # Substitution returns the category consisting of the + # substitution applied to each of its constituents. + def substitute(self, subs): + sub_res = self._res.substitute(subs) + sub_dir = self._dir.substitute(subs) + sub_arg = self._arg.substitute(subs) + return FunctionalCategory(sub_res, sub_arg, self._dir) + + # A function can unify with another function, so long as its + # constituents can unify, or with an unrestricted variable. + def can_unify(self, other): + if other.is_var(): + return [(other, self)] + if other.is_function(): + sa = self._res.can_unify(other.res()) + sd = self._dir.can_unify(other.dir()) + if sa is not None and sd is not None: + sb = self._arg.substitute(sa).can_unify(other.arg().substitute(sa)) + if sb is not None: + return sa + sb + return None + + # Constituent accessors + def arg(self): + return self._arg + + def res(self): + return self._res + + def dir(self): + return self._dir + + def __str__(self): + return f"({self._res}{self._dir}{self._arg})" diff --git a/llmeval-env/lib/python3.10/site-packages/nltk/ccg/chart.py b/llmeval-env/lib/python3.10/site-packages/nltk/ccg/chart.py new file mode 100644 index 0000000000000000000000000000000000000000..bf9e61036199016f89e89a8b0980d38d856ac4dd --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/nltk/ccg/chart.py @@ -0,0 +1,480 @@ +# Natural Language Toolkit: Combinatory Categorial Grammar +# +# Copyright (C) 2001-2023 NLTK Project +# Author: Graeme Gange +# URL: +# For license information, see LICENSE.TXT + +""" +The lexicon is constructed by calling +``lexicon.fromstring()``. + +In order to construct a parser, you also need a rule set. +The standard English rules are provided in chart as +``chart.DefaultRuleSet``. + +The parser can then be constructed by calling, for example: +``parser = chart.CCGChartParser(, )`` + +Parsing is then performed by running +``parser.parse(.split())``. + +While this returns a list of trees, the default representation +of the produced trees is not very enlightening, particularly +given that it uses the same tree class as the CFG parsers. +It is probably better to call: +``chart.printCCGDerivation()`` +which should print a nice representation of the derivation. + +This entire process is shown far more clearly in the demonstration: +python chart.py +""" + +import itertools + +from nltk.ccg.combinator import * +from nltk.ccg.combinator import ( + BackwardApplication, + BackwardBx, + BackwardComposition, + BackwardSx, + BackwardT, + ForwardApplication, + ForwardComposition, + ForwardSubstitution, + ForwardT, +) +from nltk.ccg.lexicon import Token, fromstring +from nltk.ccg.logic import * +from nltk.parse import ParserI +from nltk.parse.chart import AbstractChartRule, Chart, EdgeI +from nltk.sem.logic import * +from nltk.tree import Tree + + +# Based on the EdgeI class from NLTK. +# A number of the properties of the EdgeI interface don't +# transfer well to CCGs, however. +class CCGEdge(EdgeI): + def __init__(self, span, categ, rule): + self._span = span + self._categ = categ + self._rule = rule + self._comparison_key = (span, categ, rule) + + # Accessors + def lhs(self): + return self._categ + + def span(self): + return self._span + + def start(self): + return self._span[0] + + def end(self): + return self._span[1] + + def length(self): + return self._span[1] - self.span[0] + + def rhs(self): + return () + + def dot(self): + return 0 + + def is_complete(self): + return True + + def is_incomplete(self): + return False + + def nextsym(self): + return None + + def categ(self): + return self._categ + + def rule(self): + return self._rule + + +class CCGLeafEdge(EdgeI): + """ + Class representing leaf edges in a CCG derivation. + """ + + def __init__(self, pos, token, leaf): + self._pos = pos + self._token = token + self._leaf = leaf + self._comparison_key = (pos, token.categ(), leaf) + + # Accessors + def lhs(self): + return self._token.categ() + + def span(self): + return (self._pos, self._pos + 1) + + def start(self): + return self._pos + + def end(self): + return self._pos + 1 + + def length(self): + return 1 + + def rhs(self): + return self._leaf + + def dot(self): + return 0 + + def is_complete(self): + return True + + def is_incomplete(self): + return False + + def nextsym(self): + return None + + def token(self): + return self._token + + def categ(self): + return self._token.categ() + + def leaf(self): + return self._leaf + + +class BinaryCombinatorRule(AbstractChartRule): + """ + Class implementing application of a binary combinator to a chart. + Takes the directed combinator to apply. + """ + + NUMEDGES = 2 + + def __init__(self, combinator): + self._combinator = combinator + + # Apply a combinator + def apply(self, chart, grammar, left_edge, right_edge): + # The left & right edges must be touching. + if not (left_edge.end() == right_edge.start()): + return + + # Check if the two edges are permitted to combine. + # If so, generate the corresponding edge. + if self._combinator.can_combine(left_edge.categ(), right_edge.categ()): + for res in self._combinator.combine(left_edge.categ(), right_edge.categ()): + new_edge = CCGEdge( + span=(left_edge.start(), right_edge.end()), + categ=res, + rule=self._combinator, + ) + if chart.insert(new_edge, (left_edge, right_edge)): + yield new_edge + + # The representation of the combinator (for printing derivations) + def __str__(self): + return "%s" % self._combinator + + +# Type-raising must be handled slightly differently to the other rules, as the +# resulting rules only span a single edge, rather than both edges. + + +class ForwardTypeRaiseRule(AbstractChartRule): + """ + Class for applying forward type raising + """ + + NUMEDGES = 2 + + def __init__(self): + self._combinator = ForwardT + + def apply(self, chart, grammar, left_edge, right_edge): + if not (left_edge.end() == right_edge.start()): + return + + for res in self._combinator.combine(left_edge.categ(), right_edge.categ()): + new_edge = CCGEdge(span=left_edge.span(), categ=res, rule=self._combinator) + if chart.insert(new_edge, (left_edge,)): + yield new_edge + + def __str__(self): + return "%s" % self._combinator + + +class BackwardTypeRaiseRule(AbstractChartRule): + """ + Class for applying backward type raising. + """ + + NUMEDGES = 2 + + def __init__(self): + self._combinator = BackwardT + + def apply(self, chart, grammar, left_edge, right_edge): + if not (left_edge.end() == right_edge.start()): + return + + for res in self._combinator.combine(left_edge.categ(), right_edge.categ()): + new_edge = CCGEdge(span=right_edge.span(), categ=res, rule=self._combinator) + if chart.insert(new_edge, (right_edge,)): + yield new_edge + + def __str__(self): + return "%s" % self._combinator + + +# Common sets of combinators used for English derivations. +ApplicationRuleSet = [ + BinaryCombinatorRule(ForwardApplication), + BinaryCombinatorRule(BackwardApplication), +] +CompositionRuleSet = [ + BinaryCombinatorRule(ForwardComposition), + BinaryCombinatorRule(BackwardComposition), + BinaryCombinatorRule(BackwardBx), +] +SubstitutionRuleSet = [ + BinaryCombinatorRule(ForwardSubstitution), + BinaryCombinatorRule(BackwardSx), +] +TypeRaiseRuleSet = [ForwardTypeRaiseRule(), BackwardTypeRaiseRule()] + +# The standard English rule set. +DefaultRuleSet = ( + ApplicationRuleSet + CompositionRuleSet + SubstitutionRuleSet + TypeRaiseRuleSet +) + + +class CCGChartParser(ParserI): + """ + Chart parser for CCGs. + Based largely on the ChartParser class from NLTK. + """ + + def __init__(self, lexicon, rules, trace=0): + self._lexicon = lexicon + self._rules = rules + self._trace = trace + + def lexicon(self): + return self._lexicon + + # Implements the CYK algorithm + def parse(self, tokens): + tokens = list(tokens) + chart = CCGChart(list(tokens)) + lex = self._lexicon + + # Initialize leaf edges. + for index in range(chart.num_leaves()): + for token in lex.categories(chart.leaf(index)): + new_edge = CCGLeafEdge(index, token, chart.leaf(index)) + chart.insert(new_edge, ()) + + # Select a span for the new edges + for span in range(2, chart.num_leaves() + 1): + for start in range(0, chart.num_leaves() - span + 1): + # Try all possible pairs of edges that could generate + # an edge for that span + for part in range(1, span): + lstart = start + mid = start + part + rend = start + span + + for left in chart.select(span=(lstart, mid)): + for right in chart.select(span=(mid, rend)): + # Generate all possible combinations of the two edges + for rule in self._rules: + edges_added_by_rule = 0 + for newedge in rule.apply(chart, lex, left, right): + edges_added_by_rule += 1 + + # Output the resulting parses + return chart.parses(lex.start()) + + +class CCGChart(Chart): + def __init__(self, tokens): + Chart.__init__(self, tokens) + + # Constructs the trees for a given parse. Unfortnunately, the parse trees need to be + # constructed slightly differently to those in the default Chart class, so it has to + # be reimplemented + def _trees(self, edge, complete, memo, tree_class): + assert complete, "CCGChart cannot build incomplete trees" + + if edge in memo: + return memo[edge] + + if isinstance(edge, CCGLeafEdge): + word = tree_class(edge.token(), [self._tokens[edge.start()]]) + leaf = tree_class((edge.token(), "Leaf"), [word]) + memo[edge] = [leaf] + return [leaf] + + memo[edge] = [] + trees = [] + + for cpl in self.child_pointer_lists(edge): + child_choices = [self._trees(cp, complete, memo, tree_class) for cp in cpl] + for children in itertools.product(*child_choices): + lhs = ( + Token( + self._tokens[edge.start() : edge.end()], + edge.lhs(), + compute_semantics(children, edge), + ), + str(edge.rule()), + ) + trees.append(tree_class(lhs, children)) + + memo[edge] = trees + return trees + + +def compute_semantics(children, edge): + if children[0].label()[0].semantics() is None: + return None + + if len(children) == 2: + if isinstance(edge.rule(), BackwardCombinator): + children = [children[1], children[0]] + + combinator = edge.rule()._combinator + function = children[0].label()[0].semantics() + argument = children[1].label()[0].semantics() + + if isinstance(combinator, UndirectedFunctionApplication): + return compute_function_semantics(function, argument) + elif isinstance(combinator, UndirectedComposition): + return compute_composition_semantics(function, argument) + elif isinstance(combinator, UndirectedSubstitution): + return compute_substitution_semantics(function, argument) + else: + raise AssertionError("Unsupported combinator '" + combinator + "'") + else: + return compute_type_raised_semantics(children[0].label()[0].semantics()) + + +# -------- +# Displaying derivations +# -------- +def printCCGDerivation(tree): + # Get the leaves and initial categories + leafcats = tree.pos() + leafstr = "" + catstr = "" + + # Construct a string with both the leaf word and corresponding + # category aligned. + for (leaf, cat) in leafcats: + str_cat = "%s" % cat + nextlen = 2 + max(len(leaf), len(str_cat)) + lcatlen = (nextlen - len(str_cat)) // 2 + rcatlen = lcatlen + (nextlen - len(str_cat)) % 2 + catstr += " " * lcatlen + str_cat + " " * rcatlen + lleaflen = (nextlen - len(leaf)) // 2 + rleaflen = lleaflen + (nextlen - len(leaf)) % 2 + leafstr += " " * lleaflen + leaf + " " * rleaflen + print(leafstr.rstrip()) + print(catstr.rstrip()) + + # Display the derivation steps + printCCGTree(0, tree) + + +# Prints the sequence of derivation steps. +def printCCGTree(lwidth, tree): + rwidth = lwidth + + # Is a leaf (word). + # Increment the span by the space occupied by the leaf. + if not isinstance(tree, Tree): + return 2 + lwidth + len(tree) + + # Find the width of the current derivation step + for child in tree: + rwidth = max(rwidth, printCCGTree(rwidth, child)) + + # Is a leaf node. + # Don't print anything, but account for the space occupied. + if not isinstance(tree.label(), tuple): + return max( + rwidth, 2 + lwidth + len("%s" % tree.label()), 2 + lwidth + len(tree[0]) + ) + + (token, op) = tree.label() + + if op == "Leaf": + return rwidth + + # Pad to the left with spaces, followed by a sequence of '-' + # and the derivation rule. + print(lwidth * " " + (rwidth - lwidth) * "-" + "%s" % op) + # Print the resulting category on a new line. + str_res = "%s" % (token.categ()) + if token.semantics() is not None: + str_res += " {" + str(token.semantics()) + "}" + respadlen = (rwidth - lwidth - len(str_res)) // 2 + lwidth + print(respadlen * " " + str_res) + return rwidth + + +### Demonstration code + +# Construct the lexicon +lex = fromstring( + """ + :- S, NP, N, VP # Primitive categories, S is the target primitive + + Det :: NP/N # Family of words + Pro :: NP + TV :: VP/NP + Modal :: (S\\NP)/VP # Backslashes need to be escaped + + I => Pro # Word -> Category mapping + you => Pro + + the => Det + + # Variables have the special keyword 'var' + # '.' prevents permutation + # ',' prevents composition + and => var\\.,var/.,var + + which => (N\\N)/(S/NP) + + will => Modal # Categories can be either explicit, or families. + might => Modal + + cook => TV + eat => TV + + mushrooms => N + parsnips => N + bacon => N + """ +) + + +def demo(): + parser = CCGChartParser(lex, DefaultRuleSet) + for parse in parser.parse("I might cook and eat the bacon".split()): + printCCGDerivation(parse) + + +if __name__ == "__main__": + demo() diff --git a/llmeval-env/lib/python3.10/site-packages/nltk/ccg/combinator.py b/llmeval-env/lib/python3.10/site-packages/nltk/ccg/combinator.py new file mode 100644 index 0000000000000000000000000000000000000000..6efe6adf40d1aea7c98df1aceccdf9cf5c7b5c31 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/nltk/ccg/combinator.py @@ -0,0 +1,339 @@ +# Natural Language Toolkit: Combinatory Categorial Grammar +# +# Copyright (C) 2001-2023 NLTK Project +# Author: Graeme Gange +# URL: +# For license information, see LICENSE.TXT +""" +CCG Combinators +""" + +from abc import ABCMeta, abstractmethod + +from nltk.ccg.api import FunctionalCategory + + +class UndirectedBinaryCombinator(metaclass=ABCMeta): + """ + Abstract class for representing a binary combinator. + Merely defines functions for checking if the function and argument + are able to be combined, and what the resulting category is. + + Note that as no assumptions are made as to direction, the unrestricted + combinators can perform all backward, forward and crossed variations + of the combinators; these restrictions must be added in the rule + class. + """ + + @abstractmethod + def can_combine(self, function, argument): + pass + + @abstractmethod + def combine(self, function, argument): + pass + + +class DirectedBinaryCombinator(metaclass=ABCMeta): + """ + Wrapper for the undirected binary combinator. + It takes left and right categories, and decides which is to be + the function, and which the argument. + It then decides whether or not they can be combined. + """ + + @abstractmethod + def can_combine(self, left, right): + pass + + @abstractmethod + def combine(self, left, right): + pass + + +class ForwardCombinator(DirectedBinaryCombinator): + """ + Class representing combinators where the primary functor is on the left. + + Takes an undirected combinator, and a predicate which adds constraints + restricting the cases in which it may apply. + """ + + def __init__(self, combinator, predicate, suffix=""): + self._combinator = combinator + self._predicate = predicate + self._suffix = suffix + + def can_combine(self, left, right): + return self._combinator.can_combine(left, right) and self._predicate( + left, right + ) + + def combine(self, left, right): + yield from self._combinator.combine(left, right) + + def __str__(self): + return f">{self._combinator}{self._suffix}" + + +class BackwardCombinator(DirectedBinaryCombinator): + """ + The backward equivalent of the ForwardCombinator class. + """ + + def __init__(self, combinator, predicate, suffix=""): + self._combinator = combinator + self._predicate = predicate + self._suffix = suffix + + def can_combine(self, left, right): + return self._combinator.can_combine(right, left) and self._predicate( + left, right + ) + + def combine(self, left, right): + yield from self._combinator.combine(right, left) + + def __str__(self): + return f"<{self._combinator}{self._suffix}" + + +class UndirectedFunctionApplication(UndirectedBinaryCombinator): + """ + Class representing function application. + Implements rules of the form: + X/Y Y -> X (>) + And the corresponding backwards application rule + """ + + def can_combine(self, function, argument): + if not function.is_function(): + return False + + return not function.arg().can_unify(argument) is None + + def combine(self, function, argument): + if not function.is_function(): + return + + subs = function.arg().can_unify(argument) + if subs is None: + return + + yield function.res().substitute(subs) + + def __str__(self): + return "" + + +# Predicates for function application. + +# Ensures the left functor takes an argument on the right +def forwardOnly(left, right): + return left.dir().is_forward() + + +# Ensures the right functor takes an argument on the left +def backwardOnly(left, right): + return right.dir().is_backward() + + +# Application combinator instances +ForwardApplication = ForwardCombinator(UndirectedFunctionApplication(), forwardOnly) +BackwardApplication = BackwardCombinator(UndirectedFunctionApplication(), backwardOnly) + + +class UndirectedComposition(UndirectedBinaryCombinator): + """ + Functional composition (harmonic) combinator. + Implements rules of the form + X/Y Y/Z -> X/Z (B>) + And the corresponding backwards and crossed variations. + """ + + def can_combine(self, function, argument): + # Can only combine two functions, and both functions must + # allow composition. + if not (function.is_function() and argument.is_function()): + return False + if function.dir().can_compose() and argument.dir().can_compose(): + return not function.arg().can_unify(argument.res()) is None + return False + + def combine(self, function, argument): + if not (function.is_function() and argument.is_function()): + return + if function.dir().can_compose() and argument.dir().can_compose(): + subs = function.arg().can_unify(argument.res()) + if subs is not None: + yield FunctionalCategory( + function.res().substitute(subs), + argument.arg().substitute(subs), + argument.dir(), + ) + + def __str__(self): + return "B" + + +# Predicates for restricting application of straight composition. +def bothForward(left, right): + return left.dir().is_forward() and right.dir().is_forward() + + +def bothBackward(left, right): + return left.dir().is_backward() and right.dir().is_backward() + + +# Predicates for crossed composition +def crossedDirs(left, right): + return left.dir().is_forward() and right.dir().is_backward() + + +def backwardBxConstraint(left, right): + # The functors must be crossed inwards + if not crossedDirs(left, right): + return False + # Permuting combinators must be allowed + if not left.dir().can_cross() and right.dir().can_cross(): + return False + # The resulting argument category is restricted to be primitive + return left.arg().is_primitive() + + +# Straight composition combinators +ForwardComposition = ForwardCombinator(UndirectedComposition(), forwardOnly) +BackwardComposition = BackwardCombinator(UndirectedComposition(), backwardOnly) + +# Backward crossed composition +BackwardBx = BackwardCombinator( + UndirectedComposition(), backwardBxConstraint, suffix="x" +) + + +class UndirectedSubstitution(UndirectedBinaryCombinator): + r""" + Substitution (permutation) combinator. + Implements rules of the form + Y/Z (X\Y)/Z -> X/Z ( N\N +def innermostFunction(categ): + while categ.res().is_function(): + categ = categ.res() + return categ + + +class UndirectedTypeRaise(UndirectedBinaryCombinator): + """ + Undirected combinator for type raising. + """ + + def can_combine(self, function, arg): + # The argument must be a function. + # The restriction that arg.res() must be a function + # merely reduces redundant type-raising; if arg.res() is + # primitive, we have: + # X Y\X =>((>) Y + # which is equivalent to + # X Y\X =>(<) Y + if not (arg.is_function() and arg.res().is_function()): + return False + + arg = innermostFunction(arg) + + # left, arg_categ are undefined! + subs = left.can_unify(arg_categ.arg()) + if subs is not None: + return True + return False + + def combine(self, function, arg): + if not ( + function.is_primitive() and arg.is_function() and arg.res().is_function() + ): + return + + # Type-raising matches only the innermost application. + arg = innermostFunction(arg) + + subs = function.can_unify(arg.arg()) + if subs is not None: + xcat = arg.res().substitute(subs) + yield FunctionalCategory( + xcat, FunctionalCategory(xcat, function, arg.dir()), -(arg.dir()) + ) + + def __str__(self): + return "T" + + +# Predicates for type-raising +# The direction of the innermost category must be towards +# the primary functor. +# The restriction that the variable must be primitive is not +# common to all versions of CCGs; some authors have other restrictions. +def forwardTConstraint(left, right): + arg = innermostFunction(right) + return arg.dir().is_backward() and arg.res().is_primitive() + + +def backwardTConstraint(left, right): + arg = innermostFunction(left) + return arg.dir().is_forward() and arg.res().is_primitive() + + +# Instances of type-raising combinators +ForwardT = ForwardCombinator(UndirectedTypeRaise(), forwardTConstraint) +BackwardT = BackwardCombinator(UndirectedTypeRaise(), backwardTConstraint) diff --git a/llmeval-env/lib/python3.10/site-packages/nltk/ccg/logic.py b/llmeval-env/lib/python3.10/site-packages/nltk/ccg/logic.py new file mode 100644 index 0000000000000000000000000000000000000000..2e347b7531f723b3d8fe0caa84c22e8fcb659a6c --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/nltk/ccg/logic.py @@ -0,0 +1,60 @@ +# Natural Language Toolkit: Combinatory Categorial Grammar +# +# Copyright (C) 2001-2023 NLTK Project +# Author: Tanin Na Nakorn (@tanin) +# URL: +# For license information, see LICENSE.TXT +""" +Helper functions for CCG semantics computation +""" + +from nltk.sem.logic import * + + +def compute_type_raised_semantics(semantics): + core = semantics + parent = None + while isinstance(core, LambdaExpression): + parent = core + core = core.term + + var = Variable("F") + while var in core.free(): + var = unique_variable(pattern=var) + core = ApplicationExpression(FunctionVariableExpression(var), core) + + if parent is not None: + parent.term = core + else: + semantics = core + + return LambdaExpression(var, semantics) + + +def compute_function_semantics(function, argument): + return ApplicationExpression(function, argument).simplify() + + +def compute_composition_semantics(function, argument): + assert isinstance(argument, LambdaExpression), ( + "`" + str(argument) + "` must be a lambda expression" + ) + return LambdaExpression( + argument.variable, ApplicationExpression(function, argument.term).simplify() + ) + + +def compute_substitution_semantics(function, argument): + assert isinstance(function, LambdaExpression) and isinstance( + function.term, LambdaExpression + ), ("`" + str(function) + "` must be a lambda expression with 2 arguments") + assert isinstance(argument, LambdaExpression), ( + "`" + str(argument) + "` must be a lambda expression" + ) + + new_argument = ApplicationExpression( + argument, VariableExpression(function.variable) + ).simplify() + new_term = ApplicationExpression(function.term, new_argument).simplify() + + return LambdaExpression(function.variable, new_term) diff --git a/llmeval-env/lib/python3.10/site-packages/nltk/chunk/__init__.py b/llmeval-env/lib/python3.10/site-packages/nltk/chunk/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..208da9f5678f4b79282d5e6886502627ab9161ab --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/nltk/chunk/__init__.py @@ -0,0 +1,197 @@ +# Natural Language Toolkit: Chunkers +# +# Copyright (C) 2001-2023 NLTK Project +# Author: Steven Bird +# Edward Loper +# URL: +# For license information, see LICENSE.TXT +# + +""" +Classes and interfaces for identifying non-overlapping linguistic +groups (such as base noun phrases) in unrestricted text. This task is +called "chunk parsing" or "chunking", and the identified groups are +called "chunks". The chunked text is represented using a shallow +tree called a "chunk structure." A chunk structure is a tree +containing tokens and chunks, where each chunk is a subtree containing +only tokens. For example, the chunk structure for base noun phrase +chunks in the sentence "I saw the big dog on the hill" is:: + + (SENTENCE: + (NP: ) + + (NP: ) + + (NP: )) + +To convert a chunk structure back to a list of tokens, simply use the +chunk structure's ``leaves()`` method. + +This module defines ``ChunkParserI``, a standard interface for +chunking texts; and ``RegexpChunkParser``, a regular-expression based +implementation of that interface. It also defines ``ChunkScore``, a +utility class for scoring chunk parsers. + +RegexpChunkParser +================= + +``RegexpChunkParser`` is an implementation of the chunk parser interface +that uses regular-expressions over tags to chunk a text. Its +``parse()`` method first constructs a ``ChunkString``, which encodes a +particular chunking of the input text. Initially, nothing is +chunked. ``parse.RegexpChunkParser`` then applies a sequence of +``RegexpChunkRule`` rules to the ``ChunkString``, each of which modifies +the chunking that it encodes. Finally, the ``ChunkString`` is +transformed back into a chunk structure, which is returned. + +``RegexpChunkParser`` can only be used to chunk a single kind of phrase. +For example, you can use an ``RegexpChunkParser`` to chunk the noun +phrases in a text, or the verb phrases in a text; but you can not +use it to simultaneously chunk both noun phrases and verb phrases in +the same text. (This is a limitation of ``RegexpChunkParser``, not of +chunk parsers in general.) + +RegexpChunkRules +---------------- + +A ``RegexpChunkRule`` is a transformational rule that updates the +chunking of a text by modifying its ``ChunkString``. Each +``RegexpChunkRule`` defines the ``apply()`` method, which modifies +the chunking encoded by a ``ChunkString``. The +``RegexpChunkRule`` class itself can be used to implement any +transformational rule based on regular expressions. There are +also a number of subclasses, which can be used to implement +simpler types of rules: + + - ``ChunkRule`` chunks anything that matches a given regular + expression. + - ``StripRule`` strips anything that matches a given regular + expression. + - ``UnChunkRule`` will un-chunk any chunk that matches a given + regular expression. + - ``MergeRule`` can be used to merge two contiguous chunks. + - ``SplitRule`` can be used to split a single chunk into two + smaller chunks. + - ``ExpandLeftRule`` will expand a chunk to incorporate new + unchunked material on the left. + - ``ExpandRightRule`` will expand a chunk to incorporate new + unchunked material on the right. + +Tag Patterns +~~~~~~~~~~~~ + +A ``RegexpChunkRule`` uses a modified version of regular +expression patterns, called "tag patterns". Tag patterns are +used to match sequences of tags. Examples of tag patterns are:: + + r'(
||)+' + r'+' + r'' + +The differences between regular expression patterns and tag +patterns are: + + - In tag patterns, ``'<'`` and ``'>'`` act as parentheses; so + ``'+'`` matches one or more repetitions of ``''``, not + ``''``. + - Whitespace in tag patterns is ignored. So + ``'
| '`` is equivalent to ``'
|'`` + - In tag patterns, ``'.'`` is equivalent to ``'[^{}<>]'``; so + ``''`` matches any single tag starting with ``'NN'``. + +The function ``tag_pattern2re_pattern`` can be used to transform +a tag pattern to an equivalent regular expression pattern. + +Efficiency +---------- + +Preliminary tests indicate that ``RegexpChunkParser`` can chunk at a +rate of about 300 tokens/second, with a moderately complex rule set. + +There may be problems if ``RegexpChunkParser`` is used with more than +5,000 tokens at a time. In particular, evaluation of some regular +expressions may cause the Python regular expression engine to +exceed its maximum recursion depth. We have attempted to minimize +these problems, but it is impossible to avoid them completely. We +therefore recommend that you apply the chunk parser to a single +sentence at a time. + +Emacs Tip +--------- + +If you evaluate the following elisp expression in emacs, it will +colorize a ``ChunkString`` when you use an interactive python shell +with emacs or xemacs ("C-c !"):: + + (let () + (defconst comint-mode-font-lock-keywords + '(("<[^>]+>" 0 'font-lock-reference-face) + ("[{}]" 0 'font-lock-function-name-face))) + (add-hook 'comint-mode-hook (lambda () (turn-on-font-lock)))) + +You can evaluate this code by copying it to a temporary buffer, +placing the cursor after the last close parenthesis, and typing +"``C-x C-e``". You should evaluate it before running the interactive +session. The change will last until you close emacs. + +Unresolved Issues +----------------- + +If we use the ``re`` module for regular expressions, Python's +regular expression engine generates "maximum recursion depth +exceeded" errors when processing very large texts, even for +regular expressions that should not require any recursion. We +therefore use the ``pre`` module instead. But note that ``pre`` +does not include Unicode support, so this module will not work +with unicode strings. Note also that ``pre`` regular expressions +are not quite as advanced as ``re`` ones (e.g., no leftward +zero-length assertions). + +:type CHUNK_TAG_PATTERN: regexp +:var CHUNK_TAG_PATTERN: A regular expression to test whether a tag + pattern is valid. +""" + +from nltk.chunk.api import ChunkParserI +from nltk.chunk.regexp import RegexpChunkParser, RegexpParser +from nltk.chunk.util import ( + ChunkScore, + accuracy, + conllstr2tree, + conlltags2tree, + ieerstr2tree, + tagstr2tree, + tree2conllstr, + tree2conlltags, +) +from nltk.data import load + +# Standard treebank POS tagger +_BINARY_NE_CHUNKER = "chunkers/maxent_ne_chunker/english_ace_binary.pickle" +_MULTICLASS_NE_CHUNKER = "chunkers/maxent_ne_chunker/english_ace_multiclass.pickle" + + +def ne_chunk(tagged_tokens, binary=False): + """ + Use NLTK's currently recommended named entity chunker to + chunk the given list of tagged tokens. + """ + if binary: + chunker_pickle = _BINARY_NE_CHUNKER + else: + chunker_pickle = _MULTICLASS_NE_CHUNKER + chunker = load(chunker_pickle) + return chunker.parse(tagged_tokens) + + +def ne_chunk_sents(tagged_sentences, binary=False): + """ + Use NLTK's currently recommended named entity chunker to chunk the + given list of tagged sentences, each consisting of a list of tagged tokens. + """ + if binary: + chunker_pickle = _BINARY_NE_CHUNKER + else: + chunker_pickle = _MULTICLASS_NE_CHUNKER + chunker = load(chunker_pickle) + return chunker.parse_sents(tagged_sentences) diff --git a/llmeval-env/lib/python3.10/site-packages/nltk/chunk/__pycache__/__init__.cpython-310.pyc b/llmeval-env/lib/python3.10/site-packages/nltk/chunk/__pycache__/__init__.cpython-310.pyc new file mode 100644 index 0000000000000000000000000000000000000000..14da0f2c4a74758fd0b4c427116343374f55f3f6 Binary files /dev/null and b/llmeval-env/lib/python3.10/site-packages/nltk/chunk/__pycache__/__init__.cpython-310.pyc differ diff --git a/llmeval-env/lib/python3.10/site-packages/nltk/chunk/__pycache__/api.cpython-310.pyc b/llmeval-env/lib/python3.10/site-packages/nltk/chunk/__pycache__/api.cpython-310.pyc new file mode 100644 index 0000000000000000000000000000000000000000..d423b5516be5f287c5087fec0008591fe61680d9 Binary files /dev/null and b/llmeval-env/lib/python3.10/site-packages/nltk/chunk/__pycache__/api.cpython-310.pyc differ diff --git a/llmeval-env/lib/python3.10/site-packages/nltk/chunk/__pycache__/named_entity.cpython-310.pyc b/llmeval-env/lib/python3.10/site-packages/nltk/chunk/__pycache__/named_entity.cpython-310.pyc new file mode 100644 index 0000000000000000000000000000000000000000..baed95e1f45e5c246481524e5b3ccd89cf5153ab Binary files /dev/null and b/llmeval-env/lib/python3.10/site-packages/nltk/chunk/__pycache__/named_entity.cpython-310.pyc differ diff --git a/llmeval-env/lib/python3.10/site-packages/nltk/chunk/__pycache__/regexp.cpython-310.pyc b/llmeval-env/lib/python3.10/site-packages/nltk/chunk/__pycache__/regexp.cpython-310.pyc new file mode 100644 index 0000000000000000000000000000000000000000..c06a5731c1f645664a681510c39cc4d207560f50 Binary files /dev/null and b/llmeval-env/lib/python3.10/site-packages/nltk/chunk/__pycache__/regexp.cpython-310.pyc differ diff --git a/llmeval-env/lib/python3.10/site-packages/nltk/chunk/__pycache__/util.cpython-310.pyc b/llmeval-env/lib/python3.10/site-packages/nltk/chunk/__pycache__/util.cpython-310.pyc new file mode 100644 index 0000000000000000000000000000000000000000..59273f61dcaeb883a469a9cc5847eabd2f3dfe13 Binary files /dev/null and b/llmeval-env/lib/python3.10/site-packages/nltk/chunk/__pycache__/util.cpython-310.pyc differ diff --git a/llmeval-env/lib/python3.10/site-packages/nltk/chunk/api.py b/llmeval-env/lib/python3.10/site-packages/nltk/chunk/api.py new file mode 100644 index 0000000000000000000000000000000000000000..858490a7abb82375fba271d98037e53da6a17129 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/nltk/chunk/api.py @@ -0,0 +1,56 @@ +# Natural Language Toolkit: Chunk parsing API +# +# Copyright (C) 2001-2023 NLTK Project +# Author: Edward Loper +# Steven Bird (minor additions) +# URL: +# For license information, see LICENSE.TXT + +##////////////////////////////////////////////////////// +## Chunk Parser Interface +##////////////////////////////////////////////////////// + +from nltk.chunk.util import ChunkScore +from nltk.internals import deprecated +from nltk.parse import ParserI + + +class ChunkParserI(ParserI): + """ + A processing interface for identifying non-overlapping groups in + unrestricted text. Typically, chunk parsers are used to find base + syntactic constituents, such as base noun phrases. Unlike + ``ParserI``, ``ChunkParserI`` guarantees that the ``parse()`` method + will always generate a parse. + """ + + def parse(self, tokens): + """ + Return the best chunk structure for the given tokens + and return a tree. + + :param tokens: The list of (word, tag) tokens to be chunked. + :type tokens: list(tuple) + :rtype: Tree + """ + raise NotImplementedError() + + @deprecated("Use accuracy(gold) instead.") + def evaluate(self, gold): + return self.accuracy(gold) + + def accuracy(self, gold): + """ + Score the accuracy of the chunker against the gold standard. + Remove the chunking the gold standard text, rechunk it using + the chunker, and return a ``ChunkScore`` object + reflecting the performance of this chunk parser. + + :type gold: list(Tree) + :param gold: The list of chunked sentences to score the chunker on. + :rtype: ChunkScore + """ + chunkscore = ChunkScore() + for correct in gold: + chunkscore.score(correct, self.parse(correct.leaves())) + return chunkscore diff --git a/llmeval-env/lib/python3.10/site-packages/nltk/chunk/named_entity.py b/llmeval-env/lib/python3.10/site-packages/nltk/chunk/named_entity.py new file mode 100644 index 0000000000000000000000000000000000000000..b8ab97742c9f0721a0bc1744703871ea278aba07 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/nltk/chunk/named_entity.py @@ -0,0 +1,352 @@ +# Natural Language Toolkit: Chunk parsing API +# +# Copyright (C) 2001-2023 NLTK Project +# Author: Edward Loper +# URL: +# For license information, see LICENSE.TXT + +""" +Named entity chunker +""" + +import os +import pickle +import re +from xml.etree import ElementTree as ET + +from nltk.tag import ClassifierBasedTagger, pos_tag + +try: + from nltk.classify import MaxentClassifier +except ImportError: + pass + +from nltk.chunk.api import ChunkParserI +from nltk.chunk.util import ChunkScore +from nltk.data import find +from nltk.tokenize import word_tokenize +from nltk.tree import Tree + + +class NEChunkParserTagger(ClassifierBasedTagger): + """ + The IOB tagger used by the chunk parser. + """ + + def __init__(self, train): + ClassifierBasedTagger.__init__( + self, train=train, classifier_builder=self._classifier_builder + ) + + def _classifier_builder(self, train): + return MaxentClassifier.train( + train, algorithm="megam", gaussian_prior_sigma=1, trace=2 + ) + + def _english_wordlist(self): + try: + wl = self._en_wordlist + except AttributeError: + from nltk.corpus import words + + self._en_wordlist = set(words.words("en-basic")) + wl = self._en_wordlist + return wl + + def _feature_detector(self, tokens, index, history): + word = tokens[index][0] + pos = simplify_pos(tokens[index][1]) + if index == 0: + prevword = prevprevword = None + prevpos = prevprevpos = None + prevshape = prevtag = prevprevtag = None + elif index == 1: + prevword = tokens[index - 1][0].lower() + prevprevword = None + prevpos = simplify_pos(tokens[index - 1][1]) + prevprevpos = None + prevtag = history[index - 1][0] + prevshape = prevprevtag = None + else: + prevword = tokens[index - 1][0].lower() + prevprevword = tokens[index - 2][0].lower() + prevpos = simplify_pos(tokens[index - 1][1]) + prevprevpos = simplify_pos(tokens[index - 2][1]) + prevtag = history[index - 1] + prevprevtag = history[index - 2] + prevshape = shape(prevword) + if index == len(tokens) - 1: + nextword = nextnextword = None + nextpos = nextnextpos = None + elif index == len(tokens) - 2: + nextword = tokens[index + 1][0].lower() + nextpos = tokens[index + 1][1].lower() + nextnextword = None + nextnextpos = None + else: + nextword = tokens[index + 1][0].lower() + nextpos = tokens[index + 1][1].lower() + nextnextword = tokens[index + 2][0].lower() + nextnextpos = tokens[index + 2][1].lower() + + # 89.6 + features = { + "bias": True, + "shape": shape(word), + "wordlen": len(word), + "prefix3": word[:3].lower(), + "suffix3": word[-3:].lower(), + "pos": pos, + "word": word, + "en-wordlist": (word in self._english_wordlist()), + "prevtag": prevtag, + "prevpos": prevpos, + "nextpos": nextpos, + "prevword": prevword, + "nextword": nextword, + "word+nextpos": f"{word.lower()}+{nextpos}", + "pos+prevtag": f"{pos}+{prevtag}", + "shape+prevtag": f"{prevshape}+{prevtag}", + } + + return features + + +class NEChunkParser(ChunkParserI): + """ + Expected input: list of pos-tagged words + """ + + def __init__(self, train): + self._train(train) + + def parse(self, tokens): + """ + Each token should be a pos-tagged word + """ + tagged = self._tagger.tag(tokens) + tree = self._tagged_to_parse(tagged) + return tree + + def _train(self, corpus): + # Convert to tagged sequence + corpus = [self._parse_to_tagged(s) for s in corpus] + + self._tagger = NEChunkParserTagger(train=corpus) + + def _tagged_to_parse(self, tagged_tokens): + """ + Convert a list of tagged tokens to a chunk-parse tree. + """ + sent = Tree("S", []) + + for (tok, tag) in tagged_tokens: + if tag == "O": + sent.append(tok) + elif tag.startswith("B-"): + sent.append(Tree(tag[2:], [tok])) + elif tag.startswith("I-"): + if sent and isinstance(sent[-1], Tree) and sent[-1].label() == tag[2:]: + sent[-1].append(tok) + else: + sent.append(Tree(tag[2:], [tok])) + return sent + + @staticmethod + def _parse_to_tagged(sent): + """ + Convert a chunk-parse tree to a list of tagged tokens. + """ + toks = [] + for child in sent: + if isinstance(child, Tree): + if len(child) == 0: + print("Warning -- empty chunk in sentence") + continue + toks.append((child[0], f"B-{child.label()}")) + for tok in child[1:]: + toks.append((tok, f"I-{child.label()}")) + else: + toks.append((child, "O")) + return toks + + +def shape(word): + if re.match(r"[0-9]+(\.[0-9]*)?|[0-9]*\.[0-9]+$", word, re.UNICODE): + return "number" + elif re.match(r"\W+$", word, re.UNICODE): + return "punct" + elif re.match(r"\w+$", word, re.UNICODE): + if word.istitle(): + return "upcase" + elif word.islower(): + return "downcase" + else: + return "mixedcase" + else: + return "other" + + +def simplify_pos(s): + if s.startswith("V"): + return "V" + else: + return s.split("-")[0] + + +def postag_tree(tree): + # Part-of-speech tagging. + words = tree.leaves() + tag_iter = (pos for (word, pos) in pos_tag(words)) + newtree = Tree("S", []) + for child in tree: + if isinstance(child, Tree): + newtree.append(Tree(child.label(), [])) + for subchild in child: + newtree[-1].append((subchild, next(tag_iter))) + else: + newtree.append((child, next(tag_iter))) + return newtree + + +def load_ace_data(roots, fmt="binary", skip_bnews=True): + for root in roots: + for root, dirs, files in os.walk(root): + if root.endswith("bnews") and skip_bnews: + continue + for f in files: + if f.endswith(".sgm"): + yield from load_ace_file(os.path.join(root, f), fmt) + + +def load_ace_file(textfile, fmt): + print(f" - {os.path.split(textfile)[1]}") + annfile = textfile + ".tmx.rdc.xml" + + # Read the xml file, and get a list of entities + entities = [] + with open(annfile) as infile: + xml = ET.parse(infile).getroot() + for entity in xml.findall("document/entity"): + typ = entity.find("entity_type").text + for mention in entity.findall("entity_mention"): + if mention.get("TYPE") != "NAME": + continue # only NEs + s = int(mention.find("head/charseq/start").text) + e = int(mention.find("head/charseq/end").text) + 1 + entities.append((s, e, typ)) + + # Read the text file, and mark the entities. + with open(textfile) as infile: + text = infile.read() + + # Strip XML tags, since they don't count towards the indices + text = re.sub("<(?!/?TEXT)[^>]+>", "", text) + + # Blank out anything before/after + def subfunc(m): + return " " * (m.end() - m.start() - 6) + + text = re.sub(r"[\s\S]*", subfunc, text) + text = re.sub(r"[\s\S]*", "", text) + + # Simplify quotes + text = re.sub("``", ' "', text) + text = re.sub("''", '" ', text) + + entity_types = {typ for (s, e, typ) in entities} + + # Binary distinction (NE or not NE) + if fmt == "binary": + i = 0 + toks = Tree("S", []) + for (s, e, typ) in sorted(entities): + if s < i: + s = i # Overlapping! Deal with this better? + if e <= s: + continue + toks.extend(word_tokenize(text[i:s])) + toks.append(Tree("NE", text[s:e].split())) + i = e + toks.extend(word_tokenize(text[i:])) + yield toks + + # Multiclass distinction (NE type) + elif fmt == "multiclass": + i = 0 + toks = Tree("S", []) + for (s, e, typ) in sorted(entities): + if s < i: + s = i # Overlapping! Deal with this better? + if e <= s: + continue + toks.extend(word_tokenize(text[i:s])) + toks.append(Tree(typ, text[s:e].split())) + i = e + toks.extend(word_tokenize(text[i:])) + yield toks + + else: + raise ValueError("bad fmt value") + + +# This probably belongs in a more general-purpose location (as does +# the parse_to_tagged function). +def cmp_chunks(correct, guessed): + correct = NEChunkParser._parse_to_tagged(correct) + guessed = NEChunkParser._parse_to_tagged(guessed) + ellipsis = False + for (w, ct), (w, gt) in zip(correct, guessed): + if ct == gt == "O": + if not ellipsis: + print(f" {ct:15} {gt:15} {w}") + print(" {:15} {:15} {2}".format("...", "...", "...")) + ellipsis = True + else: + ellipsis = False + print(f" {ct:15} {gt:15} {w}") + + +def build_model(fmt="binary"): + print("Loading training data...") + train_paths = [ + find("corpora/ace_data/ace.dev"), + find("corpora/ace_data/ace.heldout"), + find("corpora/ace_data/bbn.dev"), + find("corpora/ace_data/muc.dev"), + ] + train_trees = load_ace_data(train_paths, fmt) + train_data = [postag_tree(t) for t in train_trees] + print("Training...") + cp = NEChunkParser(train_data) + del train_data + + print("Loading eval data...") + eval_paths = [find("corpora/ace_data/ace.eval")] + eval_trees = load_ace_data(eval_paths, fmt) + eval_data = [postag_tree(t) for t in eval_trees] + + print("Evaluating...") + chunkscore = ChunkScore() + for i, correct in enumerate(eval_data): + guess = cp.parse(correct.leaves()) + chunkscore.score(correct, guess) + if i < 3: + cmp_chunks(correct, guess) + print(chunkscore) + + outfilename = f"/tmp/ne_chunker_{fmt}.pickle" + print(f"Saving chunker to {outfilename}...") + + with open(outfilename, "wb") as outfile: + pickle.dump(cp, outfile, -1) + + return cp + + +if __name__ == "__main__": + # Make sure that the pickled object has the right class name: + from nltk.chunk.named_entity import build_model + + build_model("binary") + build_model("multiclass") diff --git a/llmeval-env/lib/python3.10/site-packages/nltk/chunk/regexp.py b/llmeval-env/lib/python3.10/site-packages/nltk/chunk/regexp.py new file mode 100644 index 0000000000000000000000000000000000000000..4369119706106db2892e47675ffd039e85db888d --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/nltk/chunk/regexp.py @@ -0,0 +1,1475 @@ +# Natural Language Toolkit: Regular Expression Chunkers +# +# Copyright (C) 2001-2023 NLTK Project +# Author: Edward Loper +# Steven Bird (minor additions) +# URL: +# For license information, see LICENSE.TXT + +import re + +import regex + +from nltk.chunk.api import ChunkParserI +from nltk.tree import Tree + +# ////////////////////////////////////////////////////// +# ChunkString +# ////////////////////////////////////////////////////// + + +class ChunkString: + """ + A string-based encoding of a particular chunking of a text. + Internally, the ``ChunkString`` class uses a single string to + encode the chunking of the input text. This string contains a + sequence of angle-bracket delimited tags, with chunking indicated + by braces. An example of this encoding is:: + + {
}{
}<.>{
}<.> + + ``ChunkString`` are created from tagged texts (i.e., lists of + ``tokens`` whose type is ``TaggedType``). Initially, nothing is + chunked. + + The chunking of a ``ChunkString`` can be modified with the ``xform()`` + method, which uses a regular expression to transform the string + representation. These transformations should only add and remove + braces; they should *not* modify the sequence of angle-bracket + delimited tags. + + :type _str: str + :ivar _str: The internal string representation of the text's + encoding. This string representation contains a sequence of + angle-bracket delimited tags, with chunking indicated by + braces. An example of this encoding is:: + + {
}{
}<.>{
}<.> + + :type _pieces: list(tagged tokens and chunks) + :ivar _pieces: The tagged tokens and chunks encoded by this ``ChunkString``. + :ivar _debug: The debug level. See the constructor docs. + + :cvar IN_CHUNK_PATTERN: A zero-width regexp pattern string that + will only match positions that are in chunks. + :cvar IN_STRIP_PATTERN: A zero-width regexp pattern string that + will only match positions that are in strips. + """ + + CHUNK_TAG_CHAR = r"[^\{\}<>]" + CHUNK_TAG = r"(<%s+?>)" % CHUNK_TAG_CHAR + + IN_CHUNK_PATTERN = r"(?=[^\{]*\})" + IN_STRIP_PATTERN = r"(?=[^\}]*(\{|$))" + + # These are used by _verify + _CHUNK = r"(\{%s+?\})+?" % CHUNK_TAG + _STRIP = r"(%s+?)+?" % CHUNK_TAG + _VALID = re.compile(r"^(\{?%s\}?)*?$" % CHUNK_TAG) + _BRACKETS = re.compile(r"[^\{\}]+") + _BALANCED_BRACKETS = re.compile(r"(\{\})*$") + + def __init__(self, chunk_struct, debug_level=1): + """ + Construct a new ``ChunkString`` that encodes the chunking of + the text ``tagged_tokens``. + + :type chunk_struct: Tree + :param chunk_struct: The chunk structure to be further chunked. + :type debug_level: int + :param debug_level: The level of debugging which should be + applied to transformations on the ``ChunkString``. The + valid levels are: + + - 0: no checks + - 1: full check on to_chunkstruct + - 2: full check on to_chunkstruct and cursory check after + each transformation. + - 3: full check on to_chunkstruct and full check after + each transformation. + + We recommend you use at least level 1. You should + probably use level 3 if you use any non-standard + subclasses of ``RegexpChunkRule``. + """ + self._root_label = chunk_struct.label() + self._pieces = chunk_struct[:] + tags = [self._tag(tok) for tok in self._pieces] + self._str = "<" + "><".join(tags) + ">" + self._debug = debug_level + + def _tag(self, tok): + if isinstance(tok, tuple): + return tok[1] + elif isinstance(tok, Tree): + return tok.label() + else: + raise ValueError("chunk structures must contain tagged " "tokens or trees") + + def _verify(self, s, verify_tags): + """ + Check to make sure that ``s`` still corresponds to some chunked + version of ``_pieces``. + + :type verify_tags: bool + :param verify_tags: Whether the individual tags should be + checked. If this is false, ``_verify`` will check to make + sure that ``_str`` encodes a chunked version of *some* + list of tokens. If this is true, then ``_verify`` will + check to make sure that the tags in ``_str`` match those in + ``_pieces``. + + :raise ValueError: if the internal string representation of + this ``ChunkString`` is invalid or not consistent with _pieces. + """ + # Check overall form + if not ChunkString._VALID.match(s): + raise ValueError( + "Transformation generated invalid " "chunkstring:\n %s" % s + ) + + # Check that parens are balanced. If the string is long, we + # have to do this in pieces, to avoid a maximum recursion + # depth limit for regular expressions. + brackets = ChunkString._BRACKETS.sub("", s) + for i in range(1 + len(brackets) // 5000): + substr = brackets[i * 5000 : i * 5000 + 5000] + if not ChunkString._BALANCED_BRACKETS.match(substr): + raise ValueError( + "Transformation generated invalid " "chunkstring:\n %s" % s + ) + + if verify_tags <= 0: + return + + tags1 = (re.split(r"[\{\}<>]+", s))[1:-1] + tags2 = [self._tag(piece) for piece in self._pieces] + if tags1 != tags2: + raise ValueError( + "Transformation generated invalid " "chunkstring: tag changed" + ) + + def to_chunkstruct(self, chunk_label="CHUNK"): + """ + Return the chunk structure encoded by this ``ChunkString``. + + :rtype: Tree + :raise ValueError: If a transformation has generated an + invalid chunkstring. + """ + if self._debug > 0: + self._verify(self._str, 1) + + # Use this alternating list to create the chunkstruct. + pieces = [] + index = 0 + piece_in_chunk = 0 + for piece in re.split("[{}]", self._str): + + # Find the list of tokens contained in this piece. + length = piece.count("<") + subsequence = self._pieces[index : index + length] + + # Add this list of tokens to our pieces. + if piece_in_chunk: + pieces.append(Tree(chunk_label, subsequence)) + else: + pieces += subsequence + + # Update index, piece_in_chunk + index += length + piece_in_chunk = not piece_in_chunk + + return Tree(self._root_label, pieces) + + def xform(self, regexp, repl): + """ + Apply the given transformation to the string encoding of this + ``ChunkString``. In particular, find all occurrences that match + ``regexp``, and replace them using ``repl`` (as done by + ``re.sub``). + + This transformation should only add and remove braces; it + should *not* modify the sequence of angle-bracket delimited + tags. Furthermore, this transformation may not result in + improper bracketing. Note, in particular, that bracketing may + not be nested. + + :type regexp: str or regexp + :param regexp: A regular expression matching the substring + that should be replaced. This will typically include a + named group, which can be used by ``repl``. + :type repl: str + :param repl: An expression specifying what should replace the + matched substring. Typically, this will include a named + replacement group, specified by ``regexp``. + :rtype: None + :raise ValueError: If this transformation generated an + invalid chunkstring. + """ + # Do the actual substitution + s = re.sub(regexp, repl, self._str) + + # The substitution might have generated "empty chunks" + # (substrings of the form "{}"). Remove them, so they don't + # interfere with other transformations. + s = re.sub(r"\{\}", "", s) + + # Make sure that the transformation was legal. + if self._debug > 1: + self._verify(s, self._debug - 2) + + # Commit the transformation. + self._str = s + + def __repr__(self): + """ + Return a string representation of this ``ChunkString``. + It has the form:: + + }{
}'> + + :rtype: str + """ + return "" % repr(self._str) + + def __str__(self): + """ + Return a formatted representation of this ``ChunkString``. + This representation will include extra spaces to ensure that + tags will line up with the representation of other + ``ChunkStrings`` for the same text, regardless of the chunking. + + :rtype: str + """ + # Add spaces to make everything line up. + str = re.sub(r">(?!\})", r"> ", self._str) + str = re.sub(r"([^\{])<", r"\1 <", str) + if str[0] == "<": + str = " " + str + return str + + +# ////////////////////////////////////////////////////// +# Chunking Rules +# ////////////////////////////////////////////////////// + + +class RegexpChunkRule: + """ + A rule specifying how to modify the chunking in a ``ChunkString``, + using a transformational regular expression. The + ``RegexpChunkRule`` class itself can be used to implement any + transformational rule based on regular expressions. There are + also a number of subclasses, which can be used to implement + simpler types of rules, based on matching regular expressions. + + Each ``RegexpChunkRule`` has a regular expression and a + replacement expression. When a ``RegexpChunkRule`` is "applied" + to a ``ChunkString``, it searches the ``ChunkString`` for any + substring that matches the regular expression, and replaces it + using the replacement expression. This search/replace operation + has the same semantics as ``re.sub``. + + Each ``RegexpChunkRule`` also has a description string, which + gives a short (typically less than 75 characters) description of + the purpose of the rule. + + This transformation defined by this ``RegexpChunkRule`` should + only add and remove braces; it should *not* modify the sequence + of angle-bracket delimited tags. Furthermore, this transformation + may not result in nested or mismatched bracketing. + """ + + def __init__(self, regexp, repl, descr): + """ + Construct a new RegexpChunkRule. + + :type regexp: regexp or str + :param regexp: The regular expression for this ``RegexpChunkRule``. + When this rule is applied to a ``ChunkString``, any + substring that matches ``regexp`` will be replaced using + the replacement string ``repl``. Note that this must be a + normal regular expression, not a tag pattern. + :type repl: str + :param repl: The replacement expression for this ``RegexpChunkRule``. + When this rule is applied to a ``ChunkString``, any substring + that matches ``regexp`` will be replaced using ``repl``. + :type descr: str + :param descr: A short description of the purpose and/or effect + of this rule. + """ + if isinstance(regexp, str): + regexp = re.compile(regexp) + self._repl = repl + self._descr = descr + self._regexp = regexp + + def apply(self, chunkstr): + # Keep docstring generic so we can inherit it. + """ + Apply this rule to the given ``ChunkString``. See the + class reference documentation for a description of what it + means to apply a rule. + + :type chunkstr: ChunkString + :param chunkstr: The chunkstring to which this rule is applied. + :rtype: None + :raise ValueError: If this transformation generated an + invalid chunkstring. + """ + chunkstr.xform(self._regexp, self._repl) + + def descr(self): + """ + Return a short description of the purpose and/or effect of + this rule. + + :rtype: str + """ + return self._descr + + def __repr__(self): + """ + Return a string representation of this rule. It has the form:: + + }'->''> + + Note that this representation does not include the + description string; that string can be accessed + separately with the ``descr()`` method. + + :rtype: str + """ + return ( + "" + + repr(self._repl) + + ">" + ) + + @staticmethod + def fromstring(s): + """ + Create a RegexpChunkRule from a string description. + Currently, the following formats are supported:: + + {regexp} # chunk rule + }regexp{ # strip rule + regexp}{regexp # split rule + regexp{}regexp # merge rule + + Where ``regexp`` is a regular expression for the rule. Any + text following the comment marker (``#``) will be used as + the rule's description: + + >>> from nltk.chunk.regexp import RegexpChunkRule + >>> RegexpChunkRule.fromstring('{
?+}') + ?+'> + """ + # Split off the comment (but don't split on '\#') + m = re.match(r"(?P(\\.|[^#])*)(?P#.*)?", s) + rule = m.group("rule").strip() + comment = (m.group("comment") or "")[1:].strip() + + # Pattern bodies: chunk, strip, split, merge + try: + if not rule: + raise ValueError("Empty chunk pattern") + if rule[0] == "{" and rule[-1] == "}": + return ChunkRule(rule[1:-1], comment) + elif rule[0] == "}" and rule[-1] == "{": + return StripRule(rule[1:-1], comment) + elif "}{" in rule: + left, right = rule.split("}{") + return SplitRule(left, right, comment) + elif "{}" in rule: + left, right = rule.split("{}") + return MergeRule(left, right, comment) + elif re.match("[^{}]*{[^{}]*}[^{}]*", rule): + left, chunk, right = re.split("[{}]", rule) + return ChunkRuleWithContext(left, chunk, right, comment) + else: + raise ValueError("Illegal chunk pattern: %s" % rule) + except (ValueError, re.error) as e: + raise ValueError("Illegal chunk pattern: %s" % rule) from e + + +class ChunkRule(RegexpChunkRule): + """ + A rule specifying how to add chunks to a ``ChunkString``, using a + matching tag pattern. When applied to a ``ChunkString``, it will + find any substring that matches this tag pattern and that is not + already part of a chunk, and create a new chunk containing that + substring. + """ + + def __init__(self, tag_pattern, descr): + """ + Construct a new ``ChunkRule``. + + :type tag_pattern: str + :param tag_pattern: This rule's tag pattern. When + applied to a ``ChunkString``, this rule will + chunk any substring that matches this tag pattern and that + is not already part of a chunk. + :type descr: str + :param descr: A short description of the purpose and/or effect + of this rule. + """ + self._pattern = tag_pattern + regexp = re.compile( + "(?P%s)%s" + % (tag_pattern2re_pattern(tag_pattern), ChunkString.IN_STRIP_PATTERN) + ) + RegexpChunkRule.__init__(self, regexp, r"{\g}", descr) + + def __repr__(self): + """ + Return a string representation of this rule. It has the form:: + + '> + + Note that this representation does not include the + description string; that string can be accessed + separately with the ``descr()`` method. + + :rtype: str + """ + return "" + + +class StripRule(RegexpChunkRule): + """ + A rule specifying how to remove strips to a ``ChunkString``, + using a matching tag pattern. When applied to a + ``ChunkString``, it will find any substring that matches this + tag pattern and that is contained in a chunk, and remove it + from that chunk, thus creating two new chunks. + """ + + def __init__(self, tag_pattern, descr): + """ + Construct a new ``StripRule``. + + :type tag_pattern: str + :param tag_pattern: This rule's tag pattern. When + applied to a ``ChunkString``, this rule will + find any substring that matches this tag pattern and that + is contained in a chunk, and remove it from that chunk, + thus creating two new chunks. + :type descr: str + :param descr: A short description of the purpose and/or effect + of this rule. + """ + self._pattern = tag_pattern + regexp = re.compile( + "(?P%s)%s" + % (tag_pattern2re_pattern(tag_pattern), ChunkString.IN_CHUNK_PATTERN) + ) + RegexpChunkRule.__init__(self, regexp, r"}\g{", descr) + + def __repr__(self): + """ + Return a string representation of this rule. It has the form:: + + '> + + Note that this representation does not include the + description string; that string can be accessed + separately with the ``descr()`` method. + + :rtype: str + """ + return "" + + +class UnChunkRule(RegexpChunkRule): + """ + A rule specifying how to remove chunks to a ``ChunkString``, + using a matching tag pattern. When applied to a + ``ChunkString``, it will find any complete chunk that matches this + tag pattern, and un-chunk it. + """ + + def __init__(self, tag_pattern, descr): + """ + Construct a new ``UnChunkRule``. + + :type tag_pattern: str + :param tag_pattern: This rule's tag pattern. When + applied to a ``ChunkString``, this rule will + find any complete chunk that matches this tag pattern, + and un-chunk it. + :type descr: str + :param descr: A short description of the purpose and/or effect + of this rule. + """ + self._pattern = tag_pattern + regexp = re.compile(r"\{(?P%s)\}" % tag_pattern2re_pattern(tag_pattern)) + RegexpChunkRule.__init__(self, regexp, r"\g", descr) + + def __repr__(self): + """ + Return a string representation of this rule. It has the form:: + + '> + + Note that this representation does not include the + description string; that string can be accessed + separately with the ``descr()`` method. + + :rtype: str + """ + return "" + + +class MergeRule(RegexpChunkRule): + """ + A rule specifying how to merge chunks in a ``ChunkString``, using + two matching tag patterns: a left pattern, and a right pattern. + When applied to a ``ChunkString``, it will find any chunk whose end + matches left pattern, and immediately followed by a chunk whose + beginning matches right pattern. It will then merge those two + chunks into a single chunk. + """ + + def __init__(self, left_tag_pattern, right_tag_pattern, descr): + """ + Construct a new ``MergeRule``. + + :type right_tag_pattern: str + :param right_tag_pattern: This rule's right tag + pattern. When applied to a ``ChunkString``, this + rule will find any chunk whose end matches + ``left_tag_pattern``, and immediately followed by a chunk + whose beginning matches this pattern. It will + then merge those two chunks into a single chunk. + :type left_tag_pattern: str + :param left_tag_pattern: This rule's left tag + pattern. When applied to a ``ChunkString``, this + rule will find any chunk whose end matches + this pattern, and immediately followed by a chunk + whose beginning matches ``right_tag_pattern``. It will + then merge those two chunks into a single chunk. + + :type descr: str + :param descr: A short description of the purpose and/or effect + of this rule. + """ + # Ensure that the individual patterns are coherent. E.g., if + # left='(' and right=')', then this will raise an exception: + re.compile(tag_pattern2re_pattern(left_tag_pattern)) + re.compile(tag_pattern2re_pattern(right_tag_pattern)) + + self._left_tag_pattern = left_tag_pattern + self._right_tag_pattern = right_tag_pattern + regexp = re.compile( + "(?P%s)}{(?=%s)" + % ( + tag_pattern2re_pattern(left_tag_pattern), + tag_pattern2re_pattern(right_tag_pattern), + ) + ) + RegexpChunkRule.__init__(self, regexp, r"\g", descr) + + def __repr__(self): + """ + Return a string representation of this rule. It has the form:: + + ', ''> + + Note that this representation does not include the + description string; that string can be accessed + separately with the ``descr()`` method. + + :rtype: str + """ + return ( + "" + ) + + +class SplitRule(RegexpChunkRule): + """ + A rule specifying how to split chunks in a ``ChunkString``, using + two matching tag patterns: a left pattern, and a right pattern. + When applied to a ``ChunkString``, it will find any chunk that + matches the left pattern followed by the right pattern. It will + then split the chunk into two new chunks, at the point between the + two pattern matches. + """ + + def __init__(self, left_tag_pattern, right_tag_pattern, descr): + """ + Construct a new ``SplitRule``. + + :type right_tag_pattern: str + :param right_tag_pattern: This rule's right tag + pattern. When applied to a ``ChunkString``, this rule will + find any chunk containing a substring that matches + ``left_tag_pattern`` followed by this pattern. It will + then split the chunk into two new chunks at the point + between these two matching patterns. + :type left_tag_pattern: str + :param left_tag_pattern: This rule's left tag + pattern. When applied to a ``ChunkString``, this rule will + find any chunk containing a substring that matches this + pattern followed by ``right_tag_pattern``. It will then + split the chunk into two new chunks at the point between + these two matching patterns. + :type descr: str + :param descr: A short description of the purpose and/or effect + of this rule. + """ + # Ensure that the individual patterns are coherent. E.g., if + # left='(' and right=')', then this will raise an exception: + re.compile(tag_pattern2re_pattern(left_tag_pattern)) + re.compile(tag_pattern2re_pattern(right_tag_pattern)) + + self._left_tag_pattern = left_tag_pattern + self._right_tag_pattern = right_tag_pattern + regexp = re.compile( + "(?P%s)(?=%s)" + % ( + tag_pattern2re_pattern(left_tag_pattern), + tag_pattern2re_pattern(right_tag_pattern), + ) + ) + RegexpChunkRule.__init__(self, regexp, r"\g}{", descr) + + def __repr__(self): + """ + Return a string representation of this rule. It has the form:: + + ', '
'> + + Note that this representation does not include the + description string; that string can be accessed + separately with the ``descr()`` method. + + :rtype: str + """ + return ( + "" + ) + + +class ExpandLeftRule(RegexpChunkRule): + """ + A rule specifying how to expand chunks in a ``ChunkString`` to the left, + using two matching tag patterns: a left pattern, and a right pattern. + When applied to a ``ChunkString``, it will find any chunk whose beginning + matches right pattern, and immediately preceded by a strip whose + end matches left pattern. It will then expand the chunk to incorporate + the new material on the left. + """ + + def __init__(self, left_tag_pattern, right_tag_pattern, descr): + """ + Construct a new ``ExpandRightRule``. + + :type right_tag_pattern: str + :param right_tag_pattern: This rule's right tag + pattern. When applied to a ``ChunkString``, this + rule will find any chunk whose beginning matches + ``right_tag_pattern``, and immediately preceded by a strip + whose end matches this pattern. It will + then merge those two chunks into a single chunk. + :type left_tag_pattern: str + :param left_tag_pattern: This rule's left tag + pattern. When applied to a ``ChunkString``, this + rule will find any chunk whose beginning matches + this pattern, and immediately preceded by a strip + whose end matches ``left_tag_pattern``. It will + then expand the chunk to incorporate the new material on the left. + + :type descr: str + :param descr: A short description of the purpose and/or effect + of this rule. + """ + # Ensure that the individual patterns are coherent. E.g., if + # left='(' and right=')', then this will raise an exception: + re.compile(tag_pattern2re_pattern(left_tag_pattern)) + re.compile(tag_pattern2re_pattern(right_tag_pattern)) + + self._left_tag_pattern = left_tag_pattern + self._right_tag_pattern = right_tag_pattern + regexp = re.compile( + r"(?P%s)\{(?P%s)" + % ( + tag_pattern2re_pattern(left_tag_pattern), + tag_pattern2re_pattern(right_tag_pattern), + ) + ) + RegexpChunkRule.__init__(self, regexp, r"{\g\g", descr) + + def __repr__(self): + """ + Return a string representation of this rule. It has the form:: + + ', ''> + + Note that this representation does not include the + description string; that string can be accessed + separately with the ``descr()`` method. + + :rtype: str + """ + return ( + "" + ) + + +class ExpandRightRule(RegexpChunkRule): + """ + A rule specifying how to expand chunks in a ``ChunkString`` to the + right, using two matching tag patterns: a left pattern, and a + right pattern. When applied to a ``ChunkString``, it will find any + chunk whose end matches left pattern, and immediately followed by + a strip whose beginning matches right pattern. It will then + expand the chunk to incorporate the new material on the right. + """ + + def __init__(self, left_tag_pattern, right_tag_pattern, descr): + """ + Construct a new ``ExpandRightRule``. + + :type right_tag_pattern: str + :param right_tag_pattern: This rule's right tag + pattern. When applied to a ``ChunkString``, this + rule will find any chunk whose end matches + ``left_tag_pattern``, and immediately followed by a strip + whose beginning matches this pattern. It will + then merge those two chunks into a single chunk. + :type left_tag_pattern: str + :param left_tag_pattern: This rule's left tag + pattern. When applied to a ``ChunkString``, this + rule will find any chunk whose end matches + this pattern, and immediately followed by a strip + whose beginning matches ``right_tag_pattern``. It will + then expand the chunk to incorporate the new material on the right. + + :type descr: str + :param descr: A short description of the purpose and/or effect + of this rule. + """ + # Ensure that the individual patterns are coherent. E.g., if + # left='(' and right=')', then this will raise an exception: + re.compile(tag_pattern2re_pattern(left_tag_pattern)) + re.compile(tag_pattern2re_pattern(right_tag_pattern)) + + self._left_tag_pattern = left_tag_pattern + self._right_tag_pattern = right_tag_pattern + regexp = re.compile( + r"(?P%s)\}(?P%s)" + % ( + tag_pattern2re_pattern(left_tag_pattern), + tag_pattern2re_pattern(right_tag_pattern), + ) + ) + RegexpChunkRule.__init__(self, regexp, r"\g\g}", descr) + + def __repr__(self): + """ + Return a string representation of this rule. It has the form:: + + ', ''> + + Note that this representation does not include the + description string; that string can be accessed + separately with the ``descr()`` method. + + :rtype: str + """ + return ( + "" + ) + + +class ChunkRuleWithContext(RegexpChunkRule): + """ + A rule specifying how to add chunks to a ``ChunkString``, using + three matching tag patterns: one for the left context, one for the + chunk, and one for the right context. When applied to a + ``ChunkString``, it will find any substring that matches the chunk + tag pattern, is surrounded by substrings that match the two + context patterns, and is not already part of a chunk; and create a + new chunk containing the substring that matched the chunk tag + pattern. + + Caveat: Both the left and right context are consumed when this + rule matches; therefore, if you need to find overlapping matches, + you will need to apply your rule more than once. + """ + + def __init__( + self, + left_context_tag_pattern, + chunk_tag_pattern, + right_context_tag_pattern, + descr, + ): + """ + Construct a new ``ChunkRuleWithContext``. + + :type left_context_tag_pattern: str + :param left_context_tag_pattern: A tag pattern that must match + the left context of ``chunk_tag_pattern`` for this rule to + apply. + :type chunk_tag_pattern: str + :param chunk_tag_pattern: A tag pattern that must match for this + rule to apply. If the rule does apply, then this pattern + also identifies the substring that will be made into a chunk. + :type right_context_tag_pattern: str + :param right_context_tag_pattern: A tag pattern that must match + the right context of ``chunk_tag_pattern`` for this rule to + apply. + :type descr: str + :param descr: A short description of the purpose and/or effect + of this rule. + """ + # Ensure that the individual patterns are coherent. E.g., if + # left='(' and right=')', then this will raise an exception: + re.compile(tag_pattern2re_pattern(left_context_tag_pattern)) + re.compile(tag_pattern2re_pattern(chunk_tag_pattern)) + re.compile(tag_pattern2re_pattern(right_context_tag_pattern)) + + self._left_context_tag_pattern = left_context_tag_pattern + self._chunk_tag_pattern = chunk_tag_pattern + self._right_context_tag_pattern = right_context_tag_pattern + regexp = re.compile( + "(?P%s)(?P%s)(?P%s)%s" + % ( + tag_pattern2re_pattern(left_context_tag_pattern), + tag_pattern2re_pattern(chunk_tag_pattern), + tag_pattern2re_pattern(right_context_tag_pattern), + ChunkString.IN_STRIP_PATTERN, + ) + ) + replacement = r"\g{\g}\g" + RegexpChunkRule.__init__(self, regexp, replacement, descr) + + def __repr__(self): + """ + Return a string representation of this rule. It has the form:: + + ', '', '
'> + + Note that this representation does not include the + description string; that string can be accessed + separately with the ``descr()`` method. + + :rtype: str + """ + return "".format( + self._left_context_tag_pattern, + self._chunk_tag_pattern, + self._right_context_tag_pattern, + ) + + +# ////////////////////////////////////////////////////// +# Tag Pattern Format Conversion +# ////////////////////////////////////////////////////// + +# this should probably be made more strict than it is -- e.g., it +# currently accepts 'foo'. +CHUNK_TAG_PATTERN = re.compile( + r"^(({}|<{}>)*)$".format(r"([^\{\}<>]|\{\d+,?\}|\{\d*,\d+\})+", r"[^\{\}<>]+") +) + + +def tag_pattern2re_pattern(tag_pattern): + """ + Convert a tag pattern to a regular expression pattern. A "tag + pattern" is a modified version of a regular expression, designed + for matching sequences of tags. The differences between regular + expression patterns and tag patterns are: + + - In tag patterns, ``'<'`` and ``'>'`` act as parentheses; so + ``'+'`` matches one or more repetitions of ``''``, not + ``''``. + - Whitespace in tag patterns is ignored. So + ``'
| '`` is equivalent to ``'
|'`` + - In tag patterns, ``'.'`` is equivalent to ``'[^{}<>]'``; so + ``''`` matches any single tag starting with ``'NN'``. + + In particular, ``tag_pattern2re_pattern`` performs the following + transformations on the given pattern: + + - Replace '.' with '[^<>{}]' + - Remove any whitespace + - Add extra parens around '<' and '>', to make '<' and '>' act + like parentheses. E.g., so that in '+', the '+' has scope + over the entire ''; and so that in '', the '|' has + scope over 'NN' and 'IN', but not '<' or '>'. + - Check to make sure the resulting pattern is valid. + + :type tag_pattern: str + :param tag_pattern: The tag pattern to convert to a regular + expression pattern. + :raise ValueError: If ``tag_pattern`` is not a valid tag pattern. + In particular, ``tag_pattern`` should not include braces; and it + should not contain nested or mismatched angle-brackets. + :rtype: str + :return: A regular expression pattern corresponding to + ``tag_pattern``. + """ + # Clean up the regular expression + tag_pattern = re.sub(r"\s", "", tag_pattern) + tag_pattern = re.sub(r"<", "(<(", tag_pattern) + tag_pattern = re.sub(r">", ")>)", tag_pattern) + + # Check the regular expression + if not CHUNK_TAG_PATTERN.match(tag_pattern): + raise ValueError("Bad tag pattern: %r" % tag_pattern) + + # Replace "." with CHUNK_TAG_CHAR. + # We have to do this after, since it adds {}[]<>s, which would + # confuse CHUNK_TAG_PATTERN. + # PRE doesn't have lookback assertions, so reverse twice, and do + # the pattern backwards (with lookahead assertions). This can be + # made much cleaner once we can switch back to SRE. + def reverse_str(str): + lst = list(str) + lst.reverse() + return "".join(lst) + + tc_rev = reverse_str(ChunkString.CHUNK_TAG_CHAR) + reversed = reverse_str(tag_pattern) + reversed = re.sub(r"\.(?!\\(\\\\)*($|[^\\]))", tc_rev, reversed) + tag_pattern = reverse_str(reversed) + + return tag_pattern + + +# ////////////////////////////////////////////////////// +# RegexpChunkParser +# ////////////////////////////////////////////////////// + + +class RegexpChunkParser(ChunkParserI): + """ + A regular expression based chunk parser. ``RegexpChunkParser`` uses a + sequence of "rules" to find chunks of a single type within a + text. The chunking of the text is encoded using a ``ChunkString``, + and each rule acts by modifying the chunking in the + ``ChunkString``. The rules are all implemented using regular + expression matching and substitution. + + The ``RegexpChunkRule`` class and its subclasses (``ChunkRule``, + ``StripRule``, ``UnChunkRule``, ``MergeRule``, and ``SplitRule``) + define the rules that are used by ``RegexpChunkParser``. Each rule + defines an ``apply()`` method, which modifies the chunking encoded + by a given ``ChunkString``. + + :type _rules: list(RegexpChunkRule) + :ivar _rules: The list of rules that should be applied to a text. + :type _trace: int + :ivar _trace: The default level of tracing. + + """ + + def __init__(self, rules, chunk_label="NP", root_label="S", trace=0): + """ + Construct a new ``RegexpChunkParser``. + + :type rules: list(RegexpChunkRule) + :param rules: The sequence of rules that should be used to + generate the chunking for a tagged text. + :type chunk_label: str + :param chunk_label: The node value that should be used for + chunk subtrees. This is typically a short string + describing the type of information contained by the chunk, + such as ``"NP"`` for base noun phrases. + :type root_label: str + :param root_label: The node value that should be used for the + top node of the chunk structure. + :type trace: int + :param trace: The level of tracing that should be used when + parsing a text. ``0`` will generate no tracing output; + ``1`` will generate normal tracing output; and ``2`` or + higher will generate verbose tracing output. + """ + self._rules = rules + self._trace = trace + self._chunk_label = chunk_label + self._root_label = root_label + + def _trace_apply(self, chunkstr, verbose): + """ + Apply each rule of this ``RegexpChunkParser`` to ``chunkstr``, in + turn. Generate trace output between each rule. If ``verbose`` + is true, then generate verbose output. + + :type chunkstr: ChunkString + :param chunkstr: The chunk string to which each rule should be + applied. + :type verbose: bool + :param verbose: Whether output should be verbose. + :rtype: None + """ + print("# Input:") + print(chunkstr) + for rule in self._rules: + rule.apply(chunkstr) + if verbose: + print("#", rule.descr() + " (" + repr(rule) + "):") + else: + print("#", rule.descr() + ":") + print(chunkstr) + + def _notrace_apply(self, chunkstr): + """ + Apply each rule of this ``RegexpChunkParser`` to ``chunkstr``, in + turn. + + :param chunkstr: The chunk string to which each rule should be + applied. + :type chunkstr: ChunkString + :rtype: None + """ + + for rule in self._rules: + rule.apply(chunkstr) + + def parse(self, chunk_struct, trace=None): + """ + :type chunk_struct: Tree + :param chunk_struct: the chunk structure to be (further) chunked + :type trace: int + :param trace: The level of tracing that should be used when + parsing a text. ``0`` will generate no tracing output; + ``1`` will generate normal tracing output; and ``2`` or + higher will generate verbose tracing output. This value + overrides the trace level value that was given to the + constructor. + :rtype: Tree + :return: a chunk structure that encodes the chunks in a given + tagged sentence. A chunk is a non-overlapping linguistic + group, such as a noun phrase. The set of chunks + identified in the chunk structure depends on the rules + used to define this ``RegexpChunkParser``. + """ + if len(chunk_struct) == 0: + print("Warning: parsing empty text") + return Tree(self._root_label, []) + + try: + chunk_struct.label() + except AttributeError: + chunk_struct = Tree(self._root_label, chunk_struct) + + # Use the default trace value? + if trace is None: + trace = self._trace + + chunkstr = ChunkString(chunk_struct) + + # Apply the sequence of rules to the chunkstring. + if trace: + verbose = trace > 1 + self._trace_apply(chunkstr, verbose) + else: + self._notrace_apply(chunkstr) + + # Use the chunkstring to create a chunk structure. + return chunkstr.to_chunkstruct(self._chunk_label) + + def rules(self): + """ + :return: the sequence of rules used by ``RegexpChunkParser``. + :rtype: list(RegexpChunkRule) + """ + return self._rules + + def __repr__(self): + """ + :return: a concise string representation of this + ``RegexpChunkParser``. + :rtype: str + """ + return "" % len(self._rules) + + def __str__(self): + """ + :return: a verbose string representation of this ``RegexpChunkParser``. + :rtype: str + """ + s = "RegexpChunkParser with %d rules:\n" % len(self._rules) + margin = 0 + for rule in self._rules: + margin = max(margin, len(rule.descr())) + if margin < 35: + format = " %" + repr(-(margin + 3)) + "s%s\n" + else: + format = " %s\n %s\n" + for rule in self._rules: + s += format % (rule.descr(), repr(rule)) + return s[:-1] + + +# ////////////////////////////////////////////////////// +# Chunk Grammar +# ////////////////////////////////////////////////////// + + +class RegexpParser(ChunkParserI): + r""" + A grammar based chunk parser. ``chunk.RegexpParser`` uses a set of + regular expression patterns to specify the behavior of the parser. + The chunking of the text is encoded using a ``ChunkString``, and + each rule acts by modifying the chunking in the ``ChunkString``. + The rules are all implemented using regular expression matching + and substitution. + + A grammar contains one or more clauses in the following form:: + + NP: + {} # chunk determiners and adjectives + }<[\.VI].*>+{ # strip any tag beginning with V, I, or . + <.*>}{
# split a chunk at a determiner + {} # merge chunk ending with det/adj + # with one starting with a noun + + The patterns of a clause are executed in order. An earlier + pattern may introduce a chunk boundary that prevents a later + pattern from executing. Sometimes an individual pattern will + match on multiple, overlapping extents of the input. As with + regular expression substitution more generally, the chunker will + identify the first match possible, then continue looking for matches + after this one has ended. + + The clauses of a grammar are also executed in order. A cascaded + chunk parser is one having more than one clause. The maximum depth + of a parse tree created by this chunk parser is the same as the + number of clauses in the grammar. + + When tracing is turned on, the comment portion of a line is displayed + each time the corresponding pattern is applied. + + :type _start: str + :ivar _start: The start symbol of the grammar (the root node of + resulting trees) + :type _stages: int + :ivar _stages: The list of parsing stages corresponding to the grammar + + """ + + def __init__(self, grammar, root_label="S", loop=1, trace=0): + """ + Create a new chunk parser, from the given start state + and set of chunk patterns. + + :param grammar: The grammar, or a list of RegexpChunkParser objects + :type grammar: str or list(RegexpChunkParser) + :param root_label: The top node of the tree being created + :type root_label: str or Nonterminal + :param loop: The number of times to run through the patterns + :type loop: int + :type trace: int + :param trace: The level of tracing that should be used when + parsing a text. ``0`` will generate no tracing output; + ``1`` will generate normal tracing output; and ``2`` or + higher will generate verbose tracing output. + """ + self._trace = trace + self._stages = [] + self._grammar = grammar + self._loop = loop + + if isinstance(grammar, str): + self._read_grammar(grammar, root_label, trace) + else: + # Make sur the grammar looks like it has the right type: + type_err = ( + "Expected string or list of RegexpChunkParsers " "for the grammar." + ) + try: + grammar = list(grammar) + except BaseException as e: + raise TypeError(type_err) from e + for elt in grammar: + if not isinstance(elt, RegexpChunkParser): + raise TypeError(type_err) + self._stages = grammar + + def _read_grammar(self, grammar, root_label, trace): + """ + Helper function for __init__: read the grammar if it is a + string. + """ + rules = [] + lhs = None + pattern = regex.compile("(?P(\\.|[^:])*)(:(?P.*))") + for line in grammar.split("\n"): + line = line.strip() + + # New stage begins if there's an unescaped ':' + m = pattern.match(line) + if m: + # Record the stage that we just completed. + self._add_stage(rules, lhs, root_label, trace) + # Start a new stage. + lhs = m.group("nonterminal").strip() + rules = [] + line = m.group("rule").strip() + + # Skip blank & comment-only lines + if line == "" or line.startswith("#"): + continue + + # Add the rule + rules.append(RegexpChunkRule.fromstring(line)) + + # Record the final stage + self._add_stage(rules, lhs, root_label, trace) + + def _add_stage(self, rules, lhs, root_label, trace): + """ + Helper function for __init__: add a new stage to the parser. + """ + if rules != []: + if not lhs: + raise ValueError("Expected stage marker (eg NP:)") + parser = RegexpChunkParser( + rules, chunk_label=lhs, root_label=root_label, trace=trace + ) + self._stages.append(parser) + + def parse(self, chunk_struct, trace=None): + """ + Apply the chunk parser to this input. + + :type chunk_struct: Tree + :param chunk_struct: the chunk structure to be (further) chunked + (this tree is modified, and is also returned) + :type trace: int + :param trace: The level of tracing that should be used when + parsing a text. ``0`` will generate no tracing output; + ``1`` will generate normal tracing output; and ``2`` or + higher will generate verbose tracing output. This value + overrides the trace level value that was given to the + constructor. + :return: the chunked output. + :rtype: Tree + """ + if trace is None: + trace = self._trace + for i in range(self._loop): + for parser in self._stages: + chunk_struct = parser.parse(chunk_struct, trace=trace) + return chunk_struct + + def __repr__(self): + """ + :return: a concise string representation of this ``chunk.RegexpParser``. + :rtype: str + """ + return "" % len(self._stages) + + def __str__(self): + """ + :return: a verbose string representation of this + ``RegexpParser``. + :rtype: str + """ + s = "chunk.RegexpParser with %d stages:\n" % len(self._stages) + margin = 0 + for parser in self._stages: + s += "%s\n" % parser + return s[:-1] + + +# ////////////////////////////////////////////////////// +# Demonstration code +# ////////////////////////////////////////////////////// + + +def demo_eval(chunkparser, text): + """ + Demonstration code for evaluating a chunk parser, using a + ``ChunkScore``. This function assumes that ``text`` contains one + sentence per line, and that each sentence has the form expected by + ``tree.chunk``. It runs the given chunk parser on each sentence in + the text, and scores the result. It prints the final score + (precision, recall, and f-measure); and reports the set of chunks + that were missed and the set of chunks that were incorrect. (At + most 10 missing chunks and 10 incorrect chunks are reported). + + :param chunkparser: The chunkparser to be tested + :type chunkparser: ChunkParserI + :param text: The chunked tagged text that should be used for + evaluation. + :type text: str + """ + from nltk import chunk + from nltk.tree import Tree + + # Evaluate our chunk parser. + chunkscore = chunk.ChunkScore() + + for sentence in text.split("\n"): + print(sentence) + sentence = sentence.strip() + if not sentence: + continue + gold = chunk.tagstr2tree(sentence) + tokens = gold.leaves() + test = chunkparser.parse(Tree("S", tokens), trace=1) + chunkscore.score(gold, test) + print() + + print("/" + ("=" * 75) + "\\") + print("Scoring", chunkparser) + print("-" * 77) + print("Precision: %5.1f%%" % (chunkscore.precision() * 100), " " * 4, end=" ") + print("Recall: %5.1f%%" % (chunkscore.recall() * 100), " " * 6, end=" ") + print("F-Measure: %5.1f%%" % (chunkscore.f_measure() * 100)) + + # Missed chunks. + if chunkscore.missed(): + print("Missed:") + missed = chunkscore.missed() + for chunk in missed[:10]: + print(" ", " ".join(map(str, chunk))) + if len(chunkscore.missed()) > 10: + print(" ...") + + # Incorrect chunks. + if chunkscore.incorrect(): + print("Incorrect:") + incorrect = chunkscore.incorrect() + for chunk in incorrect[:10]: + print(" ", " ".join(map(str, chunk))) + if len(chunkscore.incorrect()) > 10: + print(" ...") + + print("\\" + ("=" * 75) + "/") + print() + + +def demo(): + """ + A demonstration for the ``RegexpChunkParser`` class. A single text is + parsed with four different chunk parsers, using a variety of rules + and strategies. + """ + + from nltk import Tree, chunk + + text = """\ + [ the/DT little/JJ cat/NN ] sat/VBD on/IN [ the/DT mat/NN ] ./. + [ John/NNP ] saw/VBD [the/DT cats/NNS] [the/DT dog/NN] chased/VBD ./. + [ John/NNP ] thinks/VBZ [ Mary/NN ] saw/VBD [ the/DT cat/NN ] sit/VB on/IN [ the/DT mat/NN ]./. + """ + + print("*" * 75) + print("Evaluation text:") + print(text) + print("*" * 75) + print() + + grammar = r""" + NP: # NP stage + {
?*} # chunk determiners, adjectives and nouns + {+} # chunk proper nouns + """ + cp = chunk.RegexpParser(grammar) + demo_eval(cp, text) + + grammar = r""" + NP: + {<.*>} # start by chunking each tag + }<[\.VI].*>+{ # unchunk any verbs, prepositions or periods + {} # merge det/adj with nouns + """ + cp = chunk.RegexpParser(grammar) + demo_eval(cp, text) + + grammar = r""" + NP: {
?*} # chunk determiners, adjectives and nouns + VP: {?} # VP = verb words + """ + cp = chunk.RegexpParser(grammar) + demo_eval(cp, text) + + grammar = r""" + NP: {<.*>*} # start by chunking everything + }<[\.VI].*>+{ # strip any verbs, prepositions or periods + <.*>}{
# separate on determiners + PP: {} # PP = preposition + noun phrase + VP: {*} # VP = verb words + NPs and PPs + """ + cp = chunk.RegexpParser(grammar) + demo_eval(cp, text) + + # Evaluation + + from nltk.corpus import conll2000 + + print() + print("Demonstration of empty grammar:") + + cp = chunk.RegexpParser("") + print(chunk.accuracy(cp, conll2000.chunked_sents("test.txt", chunk_types=("NP",)))) + + print() + print("Demonstration of accuracy evaluation using CoNLL tags:") + + grammar = r""" + NP: + {<.*>} # start by chunking each tag + }<[\.VI].*>+{ # unchunk any verbs, prepositions or periods + {} # merge det/adj with nouns + """ + cp = chunk.RegexpParser(grammar) + print(chunk.accuracy(cp, conll2000.chunked_sents("test.txt")[:5])) + + print() + print("Demonstration of tagged token input") + + grammar = r""" + NP: {<.*>*} # start by chunking everything + }<[\.VI].*>+{ # strip any verbs, prepositions or periods + <.*>}{
# separate on determiners + PP: {} # PP = preposition + noun phrase + VP: {*} # VP = verb words + NPs and PPs + """ + cp = chunk.RegexpParser(grammar) + print( + cp.parse( + [ + ("the", "DT"), + ("little", "JJ"), + ("cat", "NN"), + ("sat", "VBD"), + ("on", "IN"), + ("the", "DT"), + ("mat", "NN"), + (".", "."), + ] + ) + ) + + +if __name__ == "__main__": + demo() diff --git a/llmeval-env/lib/python3.10/site-packages/nltk/chunk/util.py b/llmeval-env/lib/python3.10/site-packages/nltk/chunk/util.py new file mode 100644 index 0000000000000000000000000000000000000000..64ab90f52d1cecd133d3c6511c71e10e44b7bbf1 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/nltk/chunk/util.py @@ -0,0 +1,643 @@ +# Natural Language Toolkit: Chunk format conversions +# +# Copyright (C) 2001-2023 NLTK Project +# Author: Edward Loper +# Steven Bird (minor additions) +# URL: +# For license information, see LICENSE.TXT + +import re + +from nltk.metrics import accuracy as _accuracy +from nltk.tag.mapping import map_tag +from nltk.tag.util import str2tuple +from nltk.tree import Tree + +##////////////////////////////////////////////////////// +## EVALUATION +##////////////////////////////////////////////////////// + + +def accuracy(chunker, gold): + """ + Score the accuracy of the chunker against the gold standard. + Strip the chunk information from the gold standard and rechunk it using + the chunker, then compute the accuracy score. + + :type chunker: ChunkParserI + :param chunker: The chunker being evaluated. + :type gold: tree + :param gold: The chunk structures to score the chunker on. + :rtype: float + """ + + gold_tags = [] + test_tags = [] + for gold_tree in gold: + test_tree = chunker.parse(gold_tree.flatten()) + gold_tags += tree2conlltags(gold_tree) + test_tags += tree2conlltags(test_tree) + + # print 'GOLD:', gold_tags[:50] + # print 'TEST:', test_tags[:50] + return _accuracy(gold_tags, test_tags) + + +# Patched for increased performance by Yoav Goldberg , 2006-01-13 +# -- statistics are evaluated only on demand, instead of at every sentence evaluation +# +# SB: use nltk.metrics for precision/recall scoring? +# +class ChunkScore: + """ + A utility class for scoring chunk parsers. ``ChunkScore`` can + evaluate a chunk parser's output, based on a number of statistics + (precision, recall, f-measure, misssed chunks, incorrect chunks). + It can also combine the scores from the parsing of multiple texts; + this makes it significantly easier to evaluate a chunk parser that + operates one sentence at a time. + + Texts are evaluated with the ``score`` method. The results of + evaluation can be accessed via a number of accessor methods, such + as ``precision`` and ``f_measure``. A typical use of the + ``ChunkScore`` class is:: + + >>> chunkscore = ChunkScore() # doctest: +SKIP + >>> for correct in correct_sentences: # doctest: +SKIP + ... guess = chunkparser.parse(correct.leaves()) # doctest: +SKIP + ... chunkscore.score(correct, guess) # doctest: +SKIP + >>> print('F Measure:', chunkscore.f_measure()) # doctest: +SKIP + F Measure: 0.823 + + :ivar kwargs: Keyword arguments: + + - max_tp_examples: The maximum number actual examples of true + positives to record. This affects the ``correct`` member + function: ``correct`` will not return more than this number + of true positive examples. This does *not* affect any of + the numerical metrics (precision, recall, or f-measure) + + - max_fp_examples: The maximum number actual examples of false + positives to record. This affects the ``incorrect`` member + function and the ``guessed`` member function: ``incorrect`` + will not return more than this number of examples, and + ``guessed`` will not return more than this number of true + positive examples. This does *not* affect any of the + numerical metrics (precision, recall, or f-measure) + + - max_fn_examples: The maximum number actual examples of false + negatives to record. This affects the ``missed`` member + function and the ``correct`` member function: ``missed`` + will not return more than this number of examples, and + ``correct`` will not return more than this number of true + negative examples. This does *not* affect any of the + numerical metrics (precision, recall, or f-measure) + + - chunk_label: A regular expression indicating which chunks + should be compared. Defaults to ``'.*'`` (i.e., all chunks). + + :type _tp: list(Token) + :ivar _tp: List of true positives + :type _fp: list(Token) + :ivar _fp: List of false positives + :type _fn: list(Token) + :ivar _fn: List of false negatives + + :type _tp_num: int + :ivar _tp_num: Number of true positives + :type _fp_num: int + :ivar _fp_num: Number of false positives + :type _fn_num: int + :ivar _fn_num: Number of false negatives. + """ + + def __init__(self, **kwargs): + self._correct = set() + self._guessed = set() + self._tp = set() + self._fp = set() + self._fn = set() + self._max_tp = kwargs.get("max_tp_examples", 100) + self._max_fp = kwargs.get("max_fp_examples", 100) + self._max_fn = kwargs.get("max_fn_examples", 100) + self._chunk_label = kwargs.get("chunk_label", ".*") + self._tp_num = 0 + self._fp_num = 0 + self._fn_num = 0 + self._count = 0 + self._tags_correct = 0.0 + self._tags_total = 0.0 + + self._measuresNeedUpdate = False + + def _updateMeasures(self): + if self._measuresNeedUpdate: + self._tp = self._guessed & self._correct + self._fn = self._correct - self._guessed + self._fp = self._guessed - self._correct + self._tp_num = len(self._tp) + self._fp_num = len(self._fp) + self._fn_num = len(self._fn) + self._measuresNeedUpdate = False + + def score(self, correct, guessed): + """ + Given a correctly chunked sentence, score another chunked + version of the same sentence. + + :type correct: chunk structure + :param correct: The known-correct ("gold standard") chunked + sentence. + :type guessed: chunk structure + :param guessed: The chunked sentence to be scored. + """ + self._correct |= _chunksets(correct, self._count, self._chunk_label) + self._guessed |= _chunksets(guessed, self._count, self._chunk_label) + self._count += 1 + self._measuresNeedUpdate = True + # Keep track of per-tag accuracy (if possible) + try: + correct_tags = tree2conlltags(correct) + guessed_tags = tree2conlltags(guessed) + except ValueError: + # This exception case is for nested chunk structures, + # where tree2conlltags will fail with a ValueError: "Tree + # is too deeply nested to be printed in CoNLL format." + correct_tags = guessed_tags = () + self._tags_total += len(correct_tags) + self._tags_correct += sum( + 1 for (t, g) in zip(guessed_tags, correct_tags) if t == g + ) + + def accuracy(self): + """ + Return the overall tag-based accuracy for all text that have + been scored by this ``ChunkScore``, using the IOB (conll2000) + tag encoding. + + :rtype: float + """ + if self._tags_total == 0: + return 1 + return self._tags_correct / self._tags_total + + def precision(self): + """ + Return the overall precision for all texts that have been + scored by this ``ChunkScore``. + + :rtype: float + """ + self._updateMeasures() + div = self._tp_num + self._fp_num + if div == 0: + return 0 + else: + return self._tp_num / div + + def recall(self): + """ + Return the overall recall for all texts that have been + scored by this ``ChunkScore``. + + :rtype: float + """ + self._updateMeasures() + div = self._tp_num + self._fn_num + if div == 0: + return 0 + else: + return self._tp_num / div + + def f_measure(self, alpha=0.5): + """ + Return the overall F measure for all texts that have been + scored by this ``ChunkScore``. + + :param alpha: the relative weighting of precision and recall. + Larger alpha biases the score towards the precision value, + while smaller alpha biases the score towards the recall + value. ``alpha`` should have a value in the range [0,1]. + :type alpha: float + :rtype: float + """ + self._updateMeasures() + p = self.precision() + r = self.recall() + if p == 0 or r == 0: # what if alpha is 0 or 1? + return 0 + return 1 / (alpha / p + (1 - alpha) / r) + + def missed(self): + """ + Return the chunks which were included in the + correct chunk structures, but not in the guessed chunk + structures, listed in input order. + + :rtype: list of chunks + """ + self._updateMeasures() + chunks = list(self._fn) + return [c[1] for c in chunks] # discard position information + + def incorrect(self): + """ + Return the chunks which were included in the guessed chunk structures, + but not in the correct chunk structures, listed in input order. + + :rtype: list of chunks + """ + self._updateMeasures() + chunks = list(self._fp) + return [c[1] for c in chunks] # discard position information + + def correct(self): + """ + Return the chunks which were included in the correct + chunk structures, listed in input order. + + :rtype: list of chunks + """ + chunks = list(self._correct) + return [c[1] for c in chunks] # discard position information + + def guessed(self): + """ + Return the chunks which were included in the guessed + chunk structures, listed in input order. + + :rtype: list of chunks + """ + chunks = list(self._guessed) + return [c[1] for c in chunks] # discard position information + + def __len__(self): + self._updateMeasures() + return self._tp_num + self._fn_num + + def __repr__(self): + """ + Return a concise representation of this ``ChunkScoring``. + + :rtype: str + """ + return "" + + def __str__(self): + """ + Return a verbose representation of this ``ChunkScoring``. + This representation includes the precision, recall, and + f-measure scores. For other information about the score, + use the accessor methods (e.g., ``missed()`` and ``incorrect()``). + + :rtype: str + """ + return ( + "ChunkParse score:\n" + + (f" IOB Accuracy: {self.accuracy() * 100:5.1f}%%\n") + + (f" Precision: {self.precision() * 100:5.1f}%%\n") + + (f" Recall: {self.recall() * 100:5.1f}%%\n") + + (f" F-Measure: {self.f_measure() * 100:5.1f}%%") + ) + + +# extract chunks, and assign unique id, the absolute position of +# the first word of the chunk +def _chunksets(t, count, chunk_label): + pos = 0 + chunks = [] + for child in t: + if isinstance(child, Tree): + if re.match(chunk_label, child.label()): + chunks.append(((count, pos), child.freeze())) + pos += len(child.leaves()) + else: + pos += 1 + return set(chunks) + + +def tagstr2tree( + s, chunk_label="NP", root_label="S", sep="/", source_tagset=None, target_tagset=None +): + """ + Divide a string of bracketted tagged text into + chunks and unchunked tokens, and produce a Tree. + Chunks are marked by square brackets (``[...]``). Words are + delimited by whitespace, and each word should have the form + ``text/tag``. Words that do not contain a slash are + assigned a ``tag`` of None. + + :param s: The string to be converted + :type s: str + :param chunk_label: The label to use for chunk nodes + :type chunk_label: str + :param root_label: The label to use for the root of the tree + :type root_label: str + :rtype: Tree + """ + + WORD_OR_BRACKET = re.compile(r"\[|\]|[^\[\]\s]+") + + stack = [Tree(root_label, [])] + for match in WORD_OR_BRACKET.finditer(s): + text = match.group() + if text[0] == "[": + if len(stack) != 1: + raise ValueError(f"Unexpected [ at char {match.start():d}") + chunk = Tree(chunk_label, []) + stack[-1].append(chunk) + stack.append(chunk) + elif text[0] == "]": + if len(stack) != 2: + raise ValueError(f"Unexpected ] at char {match.start():d}") + stack.pop() + else: + if sep is None: + stack[-1].append(text) + else: + word, tag = str2tuple(text, sep) + if source_tagset and target_tagset: + tag = map_tag(source_tagset, target_tagset, tag) + stack[-1].append((word, tag)) + + if len(stack) != 1: + raise ValueError(f"Expected ] at char {len(s):d}") + return stack[0] + + +### CONLL + +_LINE_RE = re.compile(r"(\S+)\s+(\S+)\s+([IOB])-?(\S+)?") + + +def conllstr2tree(s, chunk_types=("NP", "PP", "VP"), root_label="S"): + """ + Return a chunk structure for a single sentence + encoded in the given CONLL 2000 style string. + This function converts a CoNLL IOB string into a tree. + It uses the specified chunk types + (defaults to NP, PP and VP), and creates a tree rooted at a node + labeled S (by default). + + :param s: The CoNLL string to be converted. + :type s: str + :param chunk_types: The chunk types to be converted. + :type chunk_types: tuple + :param root_label: The node label to use for the root. + :type root_label: str + :rtype: Tree + """ + + stack = [Tree(root_label, [])] + + for lineno, line in enumerate(s.split("\n")): + if not line.strip(): + continue + + # Decode the line. + match = _LINE_RE.match(line) + if match is None: + raise ValueError(f"Error on line {lineno:d}") + (word, tag, state, chunk_type) = match.groups() + + # If it's a chunk type we don't care about, treat it as O. + if chunk_types is not None and chunk_type not in chunk_types: + state = "O" + + # For "Begin"/"Outside", finish any completed chunks - + # also do so for "Inside" which don't match the previous token. + mismatch_I = state == "I" and chunk_type != stack[-1].label() + if state in "BO" or mismatch_I: + if len(stack) == 2: + stack.pop() + + # For "Begin", start a new chunk. + if state == "B" or mismatch_I: + chunk = Tree(chunk_type, []) + stack[-1].append(chunk) + stack.append(chunk) + + # Add the new word token. + stack[-1].append((word, tag)) + + return stack[0] + + +def tree2conlltags(t): + """ + Return a list of 3-tuples containing ``(word, tag, IOB-tag)``. + Convert a tree to the CoNLL IOB tag format. + + :param t: The tree to be converted. + :type t: Tree + :rtype: list(tuple) + """ + + tags = [] + for child in t: + try: + category = child.label() + prefix = "B-" + for contents in child: + if isinstance(contents, Tree): + raise ValueError( + "Tree is too deeply nested to be printed in CoNLL format" + ) + tags.append((contents[0], contents[1], prefix + category)) + prefix = "I-" + except AttributeError: + tags.append((child[0], child[1], "O")) + return tags + + +def conlltags2tree( + sentence, chunk_types=("NP", "PP", "VP"), root_label="S", strict=False +): + """ + Convert the CoNLL IOB format to a tree. + """ + tree = Tree(root_label, []) + for (word, postag, chunktag) in sentence: + if chunktag is None: + if strict: + raise ValueError("Bad conll tag sequence") + else: + # Treat as O + tree.append((word, postag)) + elif chunktag.startswith("B-"): + tree.append(Tree(chunktag[2:], [(word, postag)])) + elif chunktag.startswith("I-"): + if ( + len(tree) == 0 + or not isinstance(tree[-1], Tree) + or tree[-1].label() != chunktag[2:] + ): + if strict: + raise ValueError("Bad conll tag sequence") + else: + # Treat as B-* + tree.append(Tree(chunktag[2:], [(word, postag)])) + else: + tree[-1].append((word, postag)) + elif chunktag == "O": + tree.append((word, postag)) + else: + raise ValueError(f"Bad conll tag {chunktag!r}") + return tree + + +def tree2conllstr(t): + """ + Return a multiline string where each line contains a word, tag and IOB tag. + Convert a tree to the CoNLL IOB string format + + :param t: The tree to be converted. + :type t: Tree + :rtype: str + """ + lines = [" ".join(token) for token in tree2conlltags(t)] + return "\n".join(lines) + + +### IEER + +_IEER_DOC_RE = re.compile( + r"\s*" + r"(\s*(?P.+?)\s*\s*)?" + r"(\s*(?P.+?)\s*\s*)?" + r"(\s*(?P.+?)\s*\s*)?" + r"\s*" + r"(\s*(?P.+?)\s*\s*)?" + r"(?P.*?)\s*" + r"\s*\s*", + re.DOTALL, +) + +_IEER_TYPE_RE = re.compile(r']*?type="(?P\w+)"') + + +def _ieer_read_text(s, root_label): + stack = [Tree(root_label, [])] + # s will be None if there is no headline in the text + # return the empty list in place of a Tree + if s is None: + return [] + for piece_m in re.finditer(r"<[^>]+>|[^\s<]+", s): + piece = piece_m.group() + try: + if piece.startswith(".... + m = _IEER_DOC_RE.match(s) + if m: + return { + "text": _ieer_read_text(m.group("text"), root_label), + "docno": m.group("docno"), + "doctype": m.group("doctype"), + "date_time": m.group("date_time"), + #'headline': m.group('headline') + # we want to capture NEs in the headline too! + "headline": _ieer_read_text(m.group("headline"), root_label), + } + else: + return _ieer_read_text(s, root_label) + + +def demo(): + + s = "[ Pierre/NNP Vinken/NNP ] ,/, [ 61/CD years/NNS ] old/JJ ,/, will/MD join/VB [ the/DT board/NN ] ./." + import nltk + + t = nltk.chunk.tagstr2tree(s, chunk_label="NP") + t.pprint() + print() + + s = """ +These DT B-NP +research NN I-NP +protocols NNS I-NP +offer VBP B-VP +to TO B-PP +the DT B-NP +patient NN I-NP +not RB O +only RB O +the DT B-NP +very RB I-NP +best JJS I-NP +therapy NN I-NP +which WDT B-NP +we PRP B-NP +have VBP B-VP +established VBN I-VP +today NN B-NP +but CC B-NP +also RB I-NP +the DT B-NP +hope NN I-NP +of IN B-PP +something NN B-NP +still RB B-ADJP +better JJR I-ADJP +. . O +""" + + conll_tree = conllstr2tree(s, chunk_types=("NP", "PP")) + conll_tree.pprint() + + # Demonstrate CoNLL output + print("CoNLL output:") + print(nltk.chunk.tree2conllstr(conll_tree)) + print() + + +if __name__ == "__main__": + demo() diff --git a/llmeval-env/lib/python3.10/site-packages/nltk/cli.py b/llmeval-env/lib/python3.10/site-packages/nltk/cli.py new file mode 100644 index 0000000000000000000000000000000000000000..1a36a14f49e6cce0a0655767eddc4d82894f36d6 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/nltk/cli.py @@ -0,0 +1,55 @@ +# Natural Language Toolkit: NLTK Command-Line Interface +# +# Copyright (C) 2001-2023 NLTK Project +# URL: +# For license information, see LICENSE.TXT + + +import click +from tqdm import tqdm + +from nltk import word_tokenize +from nltk.util import parallelize_preprocess + +CONTEXT_SETTINGS = dict(help_option_names=["-h", "--help"]) + + +@click.group(context_settings=CONTEXT_SETTINGS) +@click.version_option() +def cli(): + pass + + +@cli.command("tokenize") +@click.option( + "--language", + "-l", + default="en", + help="The language for the Punkt sentence tokenization.", +) +@click.option( + "--preserve-line", + "-l", + default=True, + is_flag=True, + help="An option to keep the preserve the sentence and not sentence tokenize it.", +) +@click.option("--processes", "-j", default=1, help="No. of processes.") +@click.option("--encoding", "-e", default="utf8", help="Specify encoding of file.") +@click.option( + "--delimiter", "-d", default=" ", help="Specify delimiter to join the tokens." +) +def tokenize_file(language, preserve_line, processes, encoding, delimiter): + """This command tokenizes text stream using nltk.word_tokenize""" + with click.get_text_stream("stdin", encoding=encoding) as fin: + with click.get_text_stream("stdout", encoding=encoding) as fout: + # If it's single process, joblib parallelization is slower, + # so just process line by line normally. + if processes == 1: + for line in tqdm(fin.readlines()): + print(delimiter.join(word_tokenize(line)), end="\n", file=fout) + else: + for outline in parallelize_preprocess( + word_tokenize, fin.readlines(), processes, progress_bar=True + ): + print(delimiter.join(outline), end="\n", file=fout) diff --git a/llmeval-env/lib/python3.10/site-packages/nltk/collections.py b/llmeval-env/lib/python3.10/site-packages/nltk/collections.py new file mode 100644 index 0000000000000000000000000000000000000000..89ade62b665a4b51e63d49e26ef4ce41001efcd1 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/nltk/collections.py @@ -0,0 +1,661 @@ +# Natural Language Toolkit: Collections +# +# Copyright (C) 2001-2023 NLTK Project +# Author: Steven Bird +# URL: +# For license information, see LICENSE.TXT + +import bisect + +# this unused import is for python 2.7 +from collections import Counter, defaultdict, deque +from functools import total_ordering +from itertools import chain, islice + +from nltk.internals import raise_unorderable_types, slice_bounds + +########################################################################## +# Ordered Dictionary +########################################################################## + + +class OrderedDict(dict): + def __init__(self, data=None, **kwargs): + self._keys = self.keys(data, kwargs.get("keys")) + self._default_factory = kwargs.get("default_factory") + if data is None: + dict.__init__(self) + else: + dict.__init__(self, data) + + def __delitem__(self, key): + dict.__delitem__(self, key) + self._keys.remove(key) + + def __getitem__(self, key): + try: + return dict.__getitem__(self, key) + except KeyError: + return self.__missing__(key) + + def __iter__(self): + return (key for key in self.keys()) + + def __missing__(self, key): + if not self._default_factory and key not in self._keys: + raise KeyError() + return self._default_factory() + + def __setitem__(self, key, item): + dict.__setitem__(self, key, item) + if key not in self._keys: + self._keys.append(key) + + def clear(self): + dict.clear(self) + self._keys.clear() + + def copy(self): + d = dict.copy(self) + d._keys = self._keys + return d + + def items(self): + # returns iterator under python 3 and list under python 2 + return zip(self.keys(), self.values()) + + def keys(self, data=None, keys=None): + if data: + if keys: + assert isinstance(keys, list) + assert len(data) == len(keys) + return keys + else: + assert ( + isinstance(data, dict) + or isinstance(data, OrderedDict) + or isinstance(data, list) + ) + if isinstance(data, dict) or isinstance(data, OrderedDict): + return data.keys() + elif isinstance(data, list): + return [key for (key, value) in data] + elif "_keys" in self.__dict__: + return self._keys + else: + return [] + + def popitem(self): + if not self._keys: + raise KeyError() + + key = self._keys.pop() + value = self[key] + del self[key] + return (key, value) + + def setdefault(self, key, failobj=None): + dict.setdefault(self, key, failobj) + if key not in self._keys: + self._keys.append(key) + + def update(self, data): + dict.update(self, data) + for key in self.keys(data): + if key not in self._keys: + self._keys.append(key) + + def values(self): + # returns iterator under python 3 + return map(self.get, self._keys) + + +###################################################################### +# Lazy Sequences +###################################################################### + + +@total_ordering +class AbstractLazySequence: + """ + An abstract base class for read-only sequences whose values are + computed as needed. Lazy sequences act like tuples -- they can be + indexed, sliced, and iterated over; but they may not be modified. + + The most common application of lazy sequences in NLTK is for + corpus view objects, which provide access to the contents of a + corpus without loading the entire corpus into memory, by loading + pieces of the corpus from disk as needed. + + The result of modifying a mutable element of a lazy sequence is + undefined. In particular, the modifications made to the element + may or may not persist, depending on whether and when the lazy + sequence caches that element's value or reconstructs it from + scratch. + + Subclasses are required to define two methods: ``__len__()`` + and ``iterate_from()``. + """ + + def __len__(self): + """ + Return the number of tokens in the corpus file underlying this + corpus view. + """ + raise NotImplementedError("should be implemented by subclass") + + def iterate_from(self, start): + """ + Return an iterator that generates the tokens in the corpus + file underlying this corpus view, starting at the token number + ``start``. If ``start>=len(self)``, then this iterator will + generate no tokens. + """ + raise NotImplementedError("should be implemented by subclass") + + def __getitem__(self, i): + """ + Return the *i* th token in the corpus file underlying this + corpus view. Negative indices and spans are both supported. + """ + if isinstance(i, slice): + start, stop = slice_bounds(self, i) + return LazySubsequence(self, start, stop) + else: + # Handle negative indices + if i < 0: + i += len(self) + if i < 0: + raise IndexError("index out of range") + # Use iterate_from to extract it. + try: + return next(self.iterate_from(i)) + except StopIteration as e: + raise IndexError("index out of range") from e + + def __iter__(self): + """Return an iterator that generates the tokens in the corpus + file underlying this corpus view.""" + return self.iterate_from(0) + + def count(self, value): + """Return the number of times this list contains ``value``.""" + return sum(1 for elt in self if elt == value) + + def index(self, value, start=None, stop=None): + """Return the index of the first occurrence of ``value`` in this + list that is greater than or equal to ``start`` and less than + ``stop``. Negative start and stop values are treated like negative + slice bounds -- i.e., they count from the end of the list.""" + start, stop = slice_bounds(self, slice(start, stop)) + for i, elt in enumerate(islice(self, start, stop)): + if elt == value: + return i + start + raise ValueError("index(x): x not in list") + + def __contains__(self, value): + """Return true if this list contains ``value``.""" + return bool(self.count(value)) + + def __add__(self, other): + """Return a list concatenating self with other.""" + return LazyConcatenation([self, other]) + + def __radd__(self, other): + """Return a list concatenating other with self.""" + return LazyConcatenation([other, self]) + + def __mul__(self, count): + """Return a list concatenating self with itself ``count`` times.""" + return LazyConcatenation([self] * count) + + def __rmul__(self, count): + """Return a list concatenating self with itself ``count`` times.""" + return LazyConcatenation([self] * count) + + _MAX_REPR_SIZE = 60 + + def __repr__(self): + """ + Return a string representation for this corpus view that is + similar to a list's representation; but if it would be more + than 60 characters long, it is truncated. + """ + pieces = [] + length = 5 + for elt in self: + pieces.append(repr(elt)) + length += len(pieces[-1]) + 2 + if length > self._MAX_REPR_SIZE and len(pieces) > 2: + return "[%s, ...]" % ", ".join(pieces[:-1]) + return "[%s]" % ", ".join(pieces) + + def __eq__(self, other): + return type(self) == type(other) and list(self) == list(other) + + def __ne__(self, other): + return not self == other + + def __lt__(self, other): + if type(other) != type(self): + raise_unorderable_types("<", self, other) + return list(self) < list(other) + + def __hash__(self): + """ + :raise ValueError: Corpus view objects are unhashable. + """ + raise ValueError("%s objects are unhashable" % self.__class__.__name__) + + +class LazySubsequence(AbstractLazySequence): + """ + A subsequence produced by slicing a lazy sequence. This slice + keeps a reference to its source sequence, and generates its values + by looking them up in the source sequence. + """ + + MIN_SIZE = 100 + """ + The minimum size for which lazy slices should be created. If + ``LazySubsequence()`` is called with a subsequence that is + shorter than ``MIN_SIZE``, then a tuple will be returned instead. + """ + + def __new__(cls, source, start, stop): + """ + Construct a new slice from a given underlying sequence. The + ``start`` and ``stop`` indices should be absolute indices -- + i.e., they should not be negative (for indexing from the back + of a list) or greater than the length of ``source``. + """ + # If the slice is small enough, just use a tuple. + if stop - start < cls.MIN_SIZE: + return list(islice(source.iterate_from(start), stop - start)) + else: + return object.__new__(cls) + + def __init__(self, source, start, stop): + self._source = source + self._start = start + self._stop = stop + + def __len__(self): + return self._stop - self._start + + def iterate_from(self, start): + return islice( + self._source.iterate_from(start + self._start), max(0, len(self) - start) + ) + + +class LazyConcatenation(AbstractLazySequence): + """ + A lazy sequence formed by concatenating a list of lists. This + underlying list of lists may itself be lazy. ``LazyConcatenation`` + maintains an index that it uses to keep track of the relationship + between offsets in the concatenated lists and offsets in the + sublists. + """ + + def __init__(self, list_of_lists): + self._list = list_of_lists + self._offsets = [0] + + def __len__(self): + if len(self._offsets) <= len(self._list): + for _ in self.iterate_from(self._offsets[-1]): + pass + return self._offsets[-1] + + def iterate_from(self, start_index): + if start_index < self._offsets[-1]: + sublist_index = bisect.bisect_right(self._offsets, start_index) - 1 + else: + sublist_index = len(self._offsets) - 1 + + index = self._offsets[sublist_index] + + # Construct an iterator over the sublists. + if isinstance(self._list, AbstractLazySequence): + sublist_iter = self._list.iterate_from(sublist_index) + else: + sublist_iter = islice(self._list, sublist_index, None) + + for sublist in sublist_iter: + if sublist_index == (len(self._offsets) - 1): + assert ( + index + len(sublist) >= self._offsets[-1] + ), "offsets not monotonic increasing!" + self._offsets.append(index + len(sublist)) + else: + assert self._offsets[sublist_index + 1] == index + len( + sublist + ), "inconsistent list value (num elts)" + + yield from sublist[max(0, start_index - index) :] + + index += len(sublist) + sublist_index += 1 + + +class LazyMap(AbstractLazySequence): + """ + A lazy sequence whose elements are formed by applying a given + function to each element in one or more underlying lists. The + function is applied lazily -- i.e., when you read a value from the + list, ``LazyMap`` will calculate that value by applying its + function to the underlying lists' value(s). ``LazyMap`` is + essentially a lazy version of the Python primitive function + ``map``. In particular, the following two expressions are + equivalent: + + >>> from nltk.collections import LazyMap + >>> function = str + >>> sequence = [1,2,3] + >>> map(function, sequence) # doctest: +SKIP + ['1', '2', '3'] + >>> list(LazyMap(function, sequence)) + ['1', '2', '3'] + + Like the Python ``map`` primitive, if the source lists do not have + equal size, then the value None will be supplied for the + 'missing' elements. + + Lazy maps can be useful for conserving memory, in cases where + individual values take up a lot of space. This is especially true + if the underlying list's values are constructed lazily, as is the + case with many corpus readers. + + A typical example of a use case for this class is performing + feature detection on the tokens in a corpus. Since featuresets + are encoded as dictionaries, which can take up a lot of memory, + using a ``LazyMap`` can significantly reduce memory usage when + training and running classifiers. + """ + + def __init__(self, function, *lists, **config): + """ + :param function: The function that should be applied to + elements of ``lists``. It should take as many arguments + as there are ``lists``. + :param lists: The underlying lists. + :param cache_size: Determines the size of the cache used + by this lazy map. (default=5) + """ + if not lists: + raise TypeError("LazyMap requires at least two args") + + self._lists = lists + self._func = function + self._cache_size = config.get("cache_size", 5) + self._cache = {} if self._cache_size > 0 else None + + # If you just take bool() of sum() here _all_lazy will be true just + # in case n >= 1 list is an AbstractLazySequence. Presumably this + # isn't what's intended. + self._all_lazy = sum( + isinstance(lst, AbstractLazySequence) for lst in lists + ) == len(lists) + + def iterate_from(self, index): + # Special case: one lazy sublist + if len(self._lists) == 1 and self._all_lazy: + for value in self._lists[0].iterate_from(index): + yield self._func(value) + return + + # Special case: one non-lazy sublist + elif len(self._lists) == 1: + while True: + try: + yield self._func(self._lists[0][index]) + except IndexError: + return + index += 1 + + # Special case: n lazy sublists + elif self._all_lazy: + iterators = [lst.iterate_from(index) for lst in self._lists] + while True: + elements = [] + for iterator in iterators: + try: + elements.append(next(iterator)) + except: # FIXME: What is this except really catching? StopIteration? + elements.append(None) + if elements == [None] * len(self._lists): + return + yield self._func(*elements) + index += 1 + + # general case + else: + while True: + try: + elements = [lst[index] for lst in self._lists] + except IndexError: + elements = [None] * len(self._lists) + for i, lst in enumerate(self._lists): + try: + elements[i] = lst[index] + except IndexError: + pass + if elements == [None] * len(self._lists): + return + yield self._func(*elements) + index += 1 + + def __getitem__(self, index): + if isinstance(index, slice): + sliced_lists = [lst[index] for lst in self._lists] + return LazyMap(self._func, *sliced_lists) + else: + # Handle negative indices + if index < 0: + index += len(self) + if index < 0: + raise IndexError("index out of range") + # Check the cache + if self._cache is not None and index in self._cache: + return self._cache[index] + # Calculate the value + try: + val = next(self.iterate_from(index)) + except StopIteration as e: + raise IndexError("index out of range") from e + # Update the cache + if self._cache is not None: + if len(self._cache) > self._cache_size: + self._cache.popitem() # discard random entry + self._cache[index] = val + # Return the value + return val + + def __len__(self): + return max(len(lst) for lst in self._lists) + + +class LazyZip(LazyMap): + """ + A lazy sequence whose elements are tuples, each containing the i-th + element from each of the argument sequences. The returned list is + truncated in length to the length of the shortest argument sequence. The + tuples are constructed lazily -- i.e., when you read a value from the + list, ``LazyZip`` will calculate that value by forming a tuple from + the i-th element of each of the argument sequences. + + ``LazyZip`` is essentially a lazy version of the Python primitive function + ``zip``. In particular, an evaluated LazyZip is equivalent to a zip: + + >>> from nltk.collections import LazyZip + >>> sequence1, sequence2 = [1, 2, 3], ['a', 'b', 'c'] + >>> zip(sequence1, sequence2) # doctest: +SKIP + [(1, 'a'), (2, 'b'), (3, 'c')] + >>> list(LazyZip(sequence1, sequence2)) + [(1, 'a'), (2, 'b'), (3, 'c')] + >>> sequences = [sequence1, sequence2, [6,7,8,9]] + >>> list(zip(*sequences)) == list(LazyZip(*sequences)) + True + + Lazy zips can be useful for conserving memory in cases where the argument + sequences are particularly long. + + A typical example of a use case for this class is combining long sequences + of gold standard and predicted values in a classification or tagging task + in order to calculate accuracy. By constructing tuples lazily and + avoiding the creation of an additional long sequence, memory usage can be + significantly reduced. + """ + + def __init__(self, *lists): + """ + :param lists: the underlying lists + :type lists: list(list) + """ + LazyMap.__init__(self, lambda *elts: elts, *lists) + + def iterate_from(self, index): + iterator = LazyMap.iterate_from(self, index) + while index < len(self): + yield next(iterator) + index += 1 + return + + def __len__(self): + return min(len(lst) for lst in self._lists) + + +class LazyEnumerate(LazyZip): + """ + A lazy sequence whose elements are tuples, each containing a count (from + zero) and a value yielded by underlying sequence. ``LazyEnumerate`` is + useful for obtaining an indexed list. The tuples are constructed lazily + -- i.e., when you read a value from the list, ``LazyEnumerate`` will + calculate that value by forming a tuple from the count of the i-th + element and the i-th element of the underlying sequence. + + ``LazyEnumerate`` is essentially a lazy version of the Python primitive + function ``enumerate``. In particular, the following two expressions are + equivalent: + + >>> from nltk.collections import LazyEnumerate + >>> sequence = ['first', 'second', 'third'] + >>> list(enumerate(sequence)) + [(0, 'first'), (1, 'second'), (2, 'third')] + >>> list(LazyEnumerate(sequence)) + [(0, 'first'), (1, 'second'), (2, 'third')] + + Lazy enumerations can be useful for conserving memory in cases where the + argument sequences are particularly long. + + A typical example of a use case for this class is obtaining an indexed + list for a long sequence of values. By constructing tuples lazily and + avoiding the creation of an additional long sequence, memory usage can be + significantly reduced. + """ + + def __init__(self, lst): + """ + :param lst: the underlying list + :type lst: list + """ + LazyZip.__init__(self, range(len(lst)), lst) + + +class LazyIteratorList(AbstractLazySequence): + """ + Wraps an iterator, loading its elements on demand + and making them subscriptable. + __repr__ displays only the first few elements. + """ + + def __init__(self, it, known_len=None): + self._it = it + self._len = known_len + self._cache = [] + + def __len__(self): + if self._len: + return self._len + for _ in self.iterate_from(len(self._cache)): + pass + self._len = len(self._cache) + return self._len + + def iterate_from(self, start): + """Create a new iterator over this list starting at the given offset.""" + while len(self._cache) < start: + v = next(self._it) + self._cache.append(v) + i = start + while i < len(self._cache): + yield self._cache[i] + i += 1 + try: + while True: + v = next(self._it) + self._cache.append(v) + yield v + except StopIteration: + pass + + def __add__(self, other): + """Return a list concatenating self with other.""" + return type(self)(chain(self, other)) + + def __radd__(self, other): + """Return a list concatenating other with self.""" + return type(self)(chain(other, self)) + + +###################################################################### +# Trie Implementation +###################################################################### +class Trie(dict): + """A Trie implementation for strings""" + + LEAF = True + + def __init__(self, strings=None): + """Builds a Trie object, which is built around a ``dict`` + + If ``strings`` is provided, it will add the ``strings``, which + consist of a ``list`` of ``strings``, to the Trie. + Otherwise, it'll construct an empty Trie. + + :param strings: List of strings to insert into the trie + (Default is ``None``) + :type strings: list(str) + + """ + super().__init__() + if strings: + for string in strings: + self.insert(string) + + def insert(self, string): + """Inserts ``string`` into the Trie + + :param string: String to insert into the trie + :type string: str + + :Example: + + >>> from nltk.collections import Trie + >>> trie = Trie(["abc", "def"]) + >>> expected = {'a': {'b': {'c': {True: None}}}, \ + 'd': {'e': {'f': {True: None}}}} + >>> trie == expected + True + + """ + if len(string): + self[string[0]].insert(string[1:]) + else: + # mark the string is complete + self[Trie.LEAF] = None + + def __missing__(self, key): + self[key] = Trie() + return self[key] diff --git a/llmeval-env/lib/python3.10/site-packages/nltk/collocations.py b/llmeval-env/lib/python3.10/site-packages/nltk/collocations.py new file mode 100644 index 0000000000000000000000000000000000000000..2a1fd83ad38e861f0e8db96c24871d40c4ee185e --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/nltk/collocations.py @@ -0,0 +1,412 @@ +# Natural Language Toolkit: Collocations and Association Measures +# +# Copyright (C) 2001-2023 NLTK Project +# Author: Joel Nothman +# URL: +# For license information, see LICENSE.TXT +# +""" +Tools to identify collocations --- words that often appear consecutively +--- within corpora. They may also be used to find other associations between +word occurrences. +See Manning and Schutze ch. 5 at https://nlp.stanford.edu/fsnlp/promo/colloc.pdf +and the Text::NSP Perl package at http://ngram.sourceforge.net + +Finding collocations requires first calculating the frequencies of words and +their appearance in the context of other words. Often the collection of words +will then requiring filtering to only retain useful content terms. Each ngram +of words may then be scored according to some association measure, in order +to determine the relative likelihood of each ngram being a collocation. + +The ``BigramCollocationFinder`` and ``TrigramCollocationFinder`` classes provide +these functionalities, dependent on being provided a function which scores a +ngram given appropriate frequency counts. A number of standard association +measures are provided in bigram_measures and trigram_measures. +""" + +# Possible TODOs: +# - consider the distinction between f(x,_) and f(x) and whether our +# approximation is good enough for fragmented data, and mention it +# - add a n-gram collocation finder with measures which only utilise n-gram +# and unigram counts (raw_freq, pmi, student_t) + +import itertools as _itertools + +# these two unused imports are referenced in collocations.doctest +from nltk.metrics import ( + BigramAssocMeasures, + ContingencyMeasures, + QuadgramAssocMeasures, + TrigramAssocMeasures, +) +from nltk.metrics.spearman import ranks_from_scores, spearman_correlation +from nltk.probability import FreqDist +from nltk.util import ngrams + + +class AbstractCollocationFinder: + """ + An abstract base class for collocation finders whose purpose is to + collect collocation candidate frequencies, filter and rank them. + + As a minimum, collocation finders require the frequencies of each + word in a corpus, and the joint frequency of word tuples. This data + should be provided through nltk.probability.FreqDist objects or an + identical interface. + """ + + def __init__(self, word_fd, ngram_fd): + self.word_fd = word_fd + self.N = word_fd.N() + self.ngram_fd = ngram_fd + + @classmethod + def _build_new_documents( + cls, documents, window_size, pad_left=False, pad_right=False, pad_symbol=None + ): + """ + Pad the document with the place holder according to the window_size + """ + padding = (pad_symbol,) * (window_size - 1) + if pad_right: + return _itertools.chain.from_iterable( + _itertools.chain(doc, padding) for doc in documents + ) + if pad_left: + return _itertools.chain.from_iterable( + _itertools.chain(padding, doc) for doc in documents + ) + + @classmethod + def from_documents(cls, documents): + """Constructs a collocation finder given a collection of documents, + each of which is a list (or iterable) of tokens. + """ + # return cls.from_words(_itertools.chain(*documents)) + return cls.from_words( + cls._build_new_documents(documents, cls.default_ws, pad_right=True) + ) + + @staticmethod + def _ngram_freqdist(words, n): + return FreqDist(tuple(words[i : i + n]) for i in range(len(words) - 1)) + + def _apply_filter(self, fn=lambda ngram, freq: False): + """Generic filter removes ngrams from the frequency distribution + if the function returns True when passed an ngram tuple. + """ + tmp_ngram = FreqDist() + for ngram, freq in self.ngram_fd.items(): + if not fn(ngram, freq): + tmp_ngram[ngram] = freq + self.ngram_fd = tmp_ngram + + def apply_freq_filter(self, min_freq): + """Removes candidate ngrams which have frequency less than min_freq.""" + self._apply_filter(lambda ng, freq: freq < min_freq) + + def apply_ngram_filter(self, fn): + """Removes candidate ngrams (w1, w2, ...) where fn(w1, w2, ...) + evaluates to True. + """ + self._apply_filter(lambda ng, f: fn(*ng)) + + def apply_word_filter(self, fn): + """Removes candidate ngrams (w1, w2, ...) where any of (fn(w1), fn(w2), + ...) evaluates to True. + """ + self._apply_filter(lambda ng, f: any(fn(w) for w in ng)) + + def _score_ngrams(self, score_fn): + """Generates of (ngram, score) pairs as determined by the scoring + function provided. + """ + for tup in self.ngram_fd: + score = self.score_ngram(score_fn, *tup) + if score is not None: + yield tup, score + + def score_ngrams(self, score_fn): + """Returns a sequence of (ngram, score) pairs ordered from highest to + lowest score, as determined by the scoring function provided. + """ + return sorted(self._score_ngrams(score_fn), key=lambda t: (-t[1], t[0])) + + def nbest(self, score_fn, n): + """Returns the top n ngrams when scored by the given function.""" + return [p for p, s in self.score_ngrams(score_fn)[:n]] + + def above_score(self, score_fn, min_score): + """Returns a sequence of ngrams, ordered by decreasing score, whose + scores each exceed the given minimum score. + """ + for ngram, score in self.score_ngrams(score_fn): + if score > min_score: + yield ngram + else: + break + + +class BigramCollocationFinder(AbstractCollocationFinder): + """A tool for the finding and ranking of bigram collocations or other + association measures. It is often useful to use from_words() rather than + constructing an instance directly. + """ + + default_ws = 2 + + def __init__(self, word_fd, bigram_fd, window_size=2): + """Construct a BigramCollocationFinder, given FreqDists for + appearances of words and (possibly non-contiguous) bigrams. + """ + AbstractCollocationFinder.__init__(self, word_fd, bigram_fd) + self.window_size = window_size + + @classmethod + def from_words(cls, words, window_size=2): + """Construct a BigramCollocationFinder for all bigrams in the given + sequence. When window_size > 2, count non-contiguous bigrams, in the + style of Church and Hanks's (1990) association ratio. + """ + wfd = FreqDist() + bfd = FreqDist() + + if window_size < 2: + raise ValueError("Specify window_size at least 2") + + for window in ngrams(words, window_size, pad_right=True): + w1 = window[0] + if w1 is None: + continue + wfd[w1] += 1 + for w2 in window[1:]: + if w2 is not None: + bfd[(w1, w2)] += 1 + return cls(wfd, bfd, window_size=window_size) + + def score_ngram(self, score_fn, w1, w2): + """Returns the score for a given bigram using the given scoring + function. Following Church and Hanks (1990), counts are scaled by + a factor of 1/(window_size - 1). + """ + n_all = self.N + n_ii = self.ngram_fd[(w1, w2)] / (self.window_size - 1.0) + if not n_ii: + return + n_ix = self.word_fd[w1] + n_xi = self.word_fd[w2] + return score_fn(n_ii, (n_ix, n_xi), n_all) + + +class TrigramCollocationFinder(AbstractCollocationFinder): + """A tool for the finding and ranking of trigram collocations or other + association measures. It is often useful to use from_words() rather than + constructing an instance directly. + """ + + default_ws = 3 + + def __init__(self, word_fd, bigram_fd, wildcard_fd, trigram_fd): + """Construct a TrigramCollocationFinder, given FreqDists for + appearances of words, bigrams, two words with any word between them, + and trigrams. + """ + AbstractCollocationFinder.__init__(self, word_fd, trigram_fd) + self.wildcard_fd = wildcard_fd + self.bigram_fd = bigram_fd + + @classmethod + def from_words(cls, words, window_size=3): + """Construct a TrigramCollocationFinder for all trigrams in the given + sequence. + """ + if window_size < 3: + raise ValueError("Specify window_size at least 3") + + wfd = FreqDist() + wildfd = FreqDist() + bfd = FreqDist() + tfd = FreqDist() + for window in ngrams(words, window_size, pad_right=True): + w1 = window[0] + if w1 is None: + continue + for w2, w3 in _itertools.combinations(window[1:], 2): + wfd[w1] += 1 + if w2 is None: + continue + bfd[(w1, w2)] += 1 + if w3 is None: + continue + wildfd[(w1, w3)] += 1 + tfd[(w1, w2, w3)] += 1 + return cls(wfd, bfd, wildfd, tfd) + + def bigram_finder(self): + """Constructs a bigram collocation finder with the bigram and unigram + data from this finder. Note that this does not include any filtering + applied to this finder. + """ + return BigramCollocationFinder(self.word_fd, self.bigram_fd) + + def score_ngram(self, score_fn, w1, w2, w3): + """Returns the score for a given trigram using the given scoring + function. + """ + n_all = self.N + n_iii = self.ngram_fd[(w1, w2, w3)] + if not n_iii: + return + n_iix = self.bigram_fd[(w1, w2)] + n_ixi = self.wildcard_fd[(w1, w3)] + n_xii = self.bigram_fd[(w2, w3)] + n_ixx = self.word_fd[w1] + n_xix = self.word_fd[w2] + n_xxi = self.word_fd[w3] + return score_fn(n_iii, (n_iix, n_ixi, n_xii), (n_ixx, n_xix, n_xxi), n_all) + + +class QuadgramCollocationFinder(AbstractCollocationFinder): + """A tool for the finding and ranking of quadgram collocations or other association measures. + It is often useful to use from_words() rather than constructing an instance directly. + """ + + default_ws = 4 + + def __init__(self, word_fd, quadgram_fd, ii, iii, ixi, ixxi, iixi, ixii): + """Construct a QuadgramCollocationFinder, given FreqDists for appearances of words, + bigrams, trigrams, two words with one word and two words between them, three words + with a word between them in both variations. + """ + AbstractCollocationFinder.__init__(self, word_fd, quadgram_fd) + self.iii = iii + self.ii = ii + self.ixi = ixi + self.ixxi = ixxi + self.iixi = iixi + self.ixii = ixii + + @classmethod + def from_words(cls, words, window_size=4): + if window_size < 4: + raise ValueError("Specify window_size at least 4") + ixxx = FreqDist() + iiii = FreqDist() + ii = FreqDist() + iii = FreqDist() + ixi = FreqDist() + ixxi = FreqDist() + iixi = FreqDist() + ixii = FreqDist() + + for window in ngrams(words, window_size, pad_right=True): + w1 = window[0] + if w1 is None: + continue + for w2, w3, w4 in _itertools.combinations(window[1:], 3): + ixxx[w1] += 1 + if w2 is None: + continue + ii[(w1, w2)] += 1 + if w3 is None: + continue + iii[(w1, w2, w3)] += 1 + ixi[(w1, w3)] += 1 + if w4 is None: + continue + iiii[(w1, w2, w3, w4)] += 1 + ixxi[(w1, w4)] += 1 + ixii[(w1, w3, w4)] += 1 + iixi[(w1, w2, w4)] += 1 + + return cls(ixxx, iiii, ii, iii, ixi, ixxi, iixi, ixii) + + def score_ngram(self, score_fn, w1, w2, w3, w4): + n_all = self.N + n_iiii = self.ngram_fd[(w1, w2, w3, w4)] + if not n_iiii: + return + n_iiix = self.iii[(w1, w2, w3)] + n_xiii = self.iii[(w2, w3, w4)] + n_iixi = self.iixi[(w1, w2, w4)] + n_ixii = self.ixii[(w1, w3, w4)] + + n_iixx = self.ii[(w1, w2)] + n_xxii = self.ii[(w3, w4)] + n_xiix = self.ii[(w2, w3)] + n_ixix = self.ixi[(w1, w3)] + n_ixxi = self.ixxi[(w1, w4)] + n_xixi = self.ixi[(w2, w4)] + + n_ixxx = self.word_fd[w1] + n_xixx = self.word_fd[w2] + n_xxix = self.word_fd[w3] + n_xxxi = self.word_fd[w4] + return score_fn( + n_iiii, + (n_iiix, n_iixi, n_ixii, n_xiii), + (n_iixx, n_ixix, n_ixxi, n_xixi, n_xxii, n_xiix), + (n_ixxx, n_xixx, n_xxix, n_xxxi), + n_all, + ) + + +def demo(scorer=None, compare_scorer=None): + """Finds bigram collocations in the files of the WebText corpus.""" + from nltk.metrics import ( + BigramAssocMeasures, + ranks_from_scores, + spearman_correlation, + ) + + if scorer is None: + scorer = BigramAssocMeasures.likelihood_ratio + if compare_scorer is None: + compare_scorer = BigramAssocMeasures.raw_freq + + from nltk.corpus import stopwords, webtext + + ignored_words = stopwords.words("english") + word_filter = lambda w: len(w) < 3 or w.lower() in ignored_words + + for file in webtext.fileids(): + words = [word.lower() for word in webtext.words(file)] + + cf = BigramCollocationFinder.from_words(words) + cf.apply_freq_filter(3) + cf.apply_word_filter(word_filter) + + corr = spearman_correlation( + ranks_from_scores(cf.score_ngrams(scorer)), + ranks_from_scores(cf.score_ngrams(compare_scorer)), + ) + print(file) + print("\t", [" ".join(tup) for tup in cf.nbest(scorer, 15)]) + print(f"\t Correlation to {compare_scorer.__name__}: {corr:0.4f}") + + +# Slows down loading too much +# bigram_measures = BigramAssocMeasures() +# trigram_measures = TrigramAssocMeasures() + +if __name__ == "__main__": + import sys + + from nltk.metrics import BigramAssocMeasures + + try: + scorer = eval("BigramAssocMeasures." + sys.argv[1]) + except IndexError: + scorer = None + try: + compare_scorer = eval("BigramAssocMeasures." + sys.argv[2]) + except IndexError: + compare_scorer = None + + demo(scorer, compare_scorer) + +__all__ = [ + "BigramCollocationFinder", + "TrigramCollocationFinder", + "QuadgramCollocationFinder", +] diff --git a/llmeval-env/lib/python3.10/site-packages/nltk/compat.py b/llmeval-env/lib/python3.10/site-packages/nltk/compat.py new file mode 100644 index 0000000000000000000000000000000000000000..ceedc3992530e4e523dc9d479c26fbb43c918280 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/nltk/compat.py @@ -0,0 +1,43 @@ +# Natural Language Toolkit: Compatibility +# +# Copyright (C) 2001-2023 NLTK Project +# +# URL: +# For license information, see LICENSE.TXT + +import os +from functools import wraps + +# ======= Compatibility for datasets that care about Python versions ======== + +# The following datasets have a /PY3 subdirectory containing +# a full copy of the data which has been re-encoded or repickled. +DATA_UPDATES = [ + ("chunkers", "maxent_ne_chunker"), + ("help", "tagsets"), + ("taggers", "maxent_treebank_pos_tagger"), + ("tokenizers", "punkt"), +] + +_PY3_DATA_UPDATES = [os.path.join(*path_list) for path_list in DATA_UPDATES] + + +def add_py3_data(path): + for item in _PY3_DATA_UPDATES: + if item in str(path) and "/PY3" not in str(path): + pos = path.index(item) + len(item) + if path[pos : pos + 4] == ".zip": + pos += 4 + path = path[:pos] + "/PY3" + path[pos:] + break + return path + + +# for use in adding /PY3 to the second (filename) argument +# of the file pointers in data.py +def py3_data(init_func): + def _decorator(*args, **kwargs): + args = (args[0], add_py3_data(args[1])) + args[2:] + return init_func(*args, **kwargs) + + return wraps(init_func)(_decorator) diff --git a/llmeval-env/lib/python3.10/site-packages/nltk/data.py b/llmeval-env/lib/python3.10/site-packages/nltk/data.py new file mode 100644 index 0000000000000000000000000000000000000000..fed75d2bfbf2953a2ecc61d1d5a24244f5749be6 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/nltk/data.py @@ -0,0 +1,1441 @@ +# Natural Language Toolkit: Utility functions +# +# Copyright (C) 2001-2023 NLTK Project +# Author: Edward Loper +# URL: +# For license information, see LICENSE.TXT + +""" +Functions to find and load NLTK resource files, such as corpora, +grammars, and saved processing objects. Resource files are identified +using URLs, such as ``nltk:corpora/abc/rural.txt`` or +``https://raw.githubusercontent.com/nltk/nltk/develop/nltk/test/toy.cfg``. +The following URL protocols are supported: + + - ``file:path``: Specifies the file whose path is *path*. + Both relative and absolute paths may be used. + + - ``https://host/path``: Specifies the file stored on the web + server *host* at path *path*. + + - ``nltk:path``: Specifies the file stored in the NLTK data + package at *path*. NLTK will search for these files in the + directories specified by ``nltk.data.path``. + +If no protocol is specified, then the default protocol ``nltk:`` will +be used. + +This module provides to functions that can be used to access a +resource file, given its URL: ``load()`` loads a given resource, and +adds it to a resource cache; and ``retrieve()`` copies a given resource +to a local file. +""" + +import codecs +import functools +import os +import pickle +import re +import sys +import textwrap +import zipfile +from abc import ABCMeta, abstractmethod +from gzip import WRITE as GZ_WRITE +from gzip import GzipFile +from io import BytesIO, TextIOWrapper +from urllib.request import url2pathname, urlopen + +try: + from zlib import Z_SYNC_FLUSH as FLUSH +except ImportError: + from zlib import Z_FINISH as FLUSH + +from nltk import grammar, sem +from nltk.compat import add_py3_data, py3_data +from nltk.internals import deprecated + +textwrap_indent = functools.partial(textwrap.indent, prefix=" ") + +###################################################################### +# Search Path +###################################################################### + +path = [] +"""A list of directories where the NLTK data package might reside. + These directories will be checked in order when looking for a + resource in the data package. Note that this allows users to + substitute in their own versions of resources, if they have them + (e.g., in their home directory under ~/nltk_data).""" + +# User-specified locations: +_paths_from_env = os.environ.get("NLTK_DATA", "").split(os.pathsep) +path += [d for d in _paths_from_env if d] +if "APPENGINE_RUNTIME" not in os.environ and os.path.expanduser("~/") != "~/": + path.append(os.path.expanduser("~/nltk_data")) + +if sys.platform.startswith("win"): + # Common locations on Windows: + path += [ + os.path.join(sys.prefix, "nltk_data"), + os.path.join(sys.prefix, "share", "nltk_data"), + os.path.join(sys.prefix, "lib", "nltk_data"), + os.path.join(os.environ.get("APPDATA", "C:\\"), "nltk_data"), + r"C:\nltk_data", + r"D:\nltk_data", + r"E:\nltk_data", + ] +else: + # Common locations on UNIX & OS X: + path += [ + os.path.join(sys.prefix, "nltk_data"), + os.path.join(sys.prefix, "share", "nltk_data"), + os.path.join(sys.prefix, "lib", "nltk_data"), + "/usr/share/nltk_data", + "/usr/local/share/nltk_data", + "/usr/lib/nltk_data", + "/usr/local/lib/nltk_data", + ] + + +###################################################################### +# Util Functions +###################################################################### + + +def gzip_open_unicode( + filename, + mode="rb", + compresslevel=9, + encoding="utf-8", + fileobj=None, + errors=None, + newline=None, +): + if fileobj is None: + fileobj = GzipFile(filename, mode, compresslevel, fileobj) + return TextIOWrapper(fileobj, encoding, errors, newline) + + +def split_resource_url(resource_url): + """ + Splits a resource url into ":". + + >>> windows = sys.platform.startswith('win') + >>> split_resource_url('nltk:home/nltk') + ('nltk', 'home/nltk') + >>> split_resource_url('nltk:/home/nltk') + ('nltk', '/home/nltk') + >>> split_resource_url('file:/home/nltk') + ('file', '/home/nltk') + >>> split_resource_url('file:///home/nltk') + ('file', '/home/nltk') + >>> split_resource_url('file:///C:/home/nltk') + ('file', '/C:/home/nltk') + """ + protocol, path_ = resource_url.split(":", 1) + if protocol == "nltk": + pass + elif protocol == "file": + if path_.startswith("/"): + path_ = "/" + path_.lstrip("/") + else: + path_ = re.sub(r"^/{0,2}", "", path_) + return protocol, path_ + + +def normalize_resource_url(resource_url): + r""" + Normalizes a resource url + + >>> windows = sys.platform.startswith('win') + >>> os.path.normpath(split_resource_url(normalize_resource_url('file:grammar.fcfg'))[1]) == \ + ... ('\\' if windows else '') + os.path.abspath(os.path.join(os.curdir, 'grammar.fcfg')) + True + >>> not windows or normalize_resource_url('file:C:/dir/file') == 'file:///C:/dir/file' + True + >>> not windows or normalize_resource_url('file:C:\\dir\\file') == 'file:///C:/dir/file' + True + >>> not windows or normalize_resource_url('file:C:\\dir/file') == 'file:///C:/dir/file' + True + >>> not windows or normalize_resource_url('file://C:/dir/file') == 'file:///C:/dir/file' + True + >>> not windows or normalize_resource_url('file:////C:/dir/file') == 'file:///C:/dir/file' + True + >>> not windows or normalize_resource_url('nltk:C:/dir/file') == 'file:///C:/dir/file' + True + >>> not windows or normalize_resource_url('nltk:C:\\dir\\file') == 'file:///C:/dir/file' + True + >>> windows or normalize_resource_url('file:/dir/file/toy.cfg') == 'file:///dir/file/toy.cfg' + True + >>> normalize_resource_url('nltk:home/nltk') + 'nltk:home/nltk' + >>> windows or normalize_resource_url('nltk:/home/nltk') == 'file:///home/nltk' + True + >>> normalize_resource_url('https://example.com/dir/file') + 'https://example.com/dir/file' + >>> normalize_resource_url('dir/file') + 'nltk:dir/file' + """ + try: + protocol, name = split_resource_url(resource_url) + except ValueError: + # the resource url has no protocol, use the nltk protocol by default + protocol = "nltk" + name = resource_url + # use file protocol if the path is an absolute path + if protocol == "nltk" and os.path.isabs(name): + protocol = "file://" + name = normalize_resource_name(name, False, None) + elif protocol == "file": + protocol = "file://" + # name is absolute + name = normalize_resource_name(name, False, None) + elif protocol == "nltk": + protocol = "nltk:" + name = normalize_resource_name(name, True) + else: + # handled by urllib + protocol += "://" + return "".join([protocol, name]) + + +def normalize_resource_name(resource_name, allow_relative=True, relative_path=None): + """ + :type resource_name: str or unicode + :param resource_name: The name of the resource to search for. + Resource names are posix-style relative path names, such as + ``corpora/brown``. Directory names will automatically + be converted to a platform-appropriate path separator. + Directory trailing slashes are preserved + + >>> windows = sys.platform.startswith('win') + >>> normalize_resource_name('.', True) + './' + >>> normalize_resource_name('./', True) + './' + >>> windows or normalize_resource_name('dir/file', False, '/') == '/dir/file' + True + >>> not windows or normalize_resource_name('C:/file', False, '/') == '/C:/file' + True + >>> windows or normalize_resource_name('/dir/file', False, '/') == '/dir/file' + True + >>> windows or normalize_resource_name('../dir/file', False, '/') == '/dir/file' + True + >>> not windows or normalize_resource_name('/dir/file', True, '/') == 'dir/file' + True + >>> windows or normalize_resource_name('/dir/file', True, '/') == '/dir/file' + True + """ + is_dir = bool(re.search(r"[\\/.]$", resource_name)) or resource_name.endswith( + os.path.sep + ) + if sys.platform.startswith("win"): + resource_name = resource_name.lstrip("/") + else: + resource_name = re.sub(r"^/+", "/", resource_name) + if allow_relative: + resource_name = os.path.normpath(resource_name) + else: + if relative_path is None: + relative_path = os.curdir + resource_name = os.path.abspath(os.path.join(relative_path, resource_name)) + resource_name = resource_name.replace("\\", "/").replace(os.path.sep, "/") + if sys.platform.startswith("win") and os.path.isabs(resource_name): + resource_name = "/" + resource_name + if is_dir and not resource_name.endswith("/"): + resource_name += "/" + return resource_name + + +###################################################################### +# Path Pointers +###################################################################### + + +class PathPointer(metaclass=ABCMeta): + """ + An abstract base class for 'path pointers,' used by NLTK's data + package to identify specific paths. Two subclasses exist: + ``FileSystemPathPointer`` identifies a file that can be accessed + directly via a given absolute path. ``ZipFilePathPointer`` + identifies a file contained within a zipfile, that can be accessed + by reading that zipfile. + """ + + @abstractmethod + def open(self, encoding=None): + """ + Return a seekable read-only stream that can be used to read + the contents of the file identified by this path pointer. + + :raise IOError: If the path specified by this pointer does + not contain a readable file. + """ + + @abstractmethod + def file_size(self): + """ + Return the size of the file pointed to by this path pointer, + in bytes. + + :raise IOError: If the path specified by this pointer does + not contain a readable file. + """ + + @abstractmethod + def join(self, fileid): + """ + Return a new path pointer formed by starting at the path + identified by this pointer, and then following the relative + path given by ``fileid``. The path components of ``fileid`` + should be separated by forward slashes, regardless of + the underlying file system's path separator character. + """ + + +class FileSystemPathPointer(PathPointer, str): + """ + A path pointer that identifies a file which can be accessed + directly via a given absolute path. + """ + + @py3_data + def __init__(self, _path): + """ + Create a new path pointer for the given absolute path. + + :raise IOError: If the given path does not exist. + """ + + _path = os.path.abspath(_path) + if not os.path.exists(_path): + raise OSError("No such file or directory: %r" % _path) + self._path = _path + + # There's no need to call str.__init__(), since it's a no-op; + # str does all of its setup work in __new__. + + @property + def path(self): + """The absolute path identified by this path pointer.""" + return self._path + + def open(self, encoding=None): + stream = open(self._path, "rb") + if encoding is not None: + stream = SeekableUnicodeStreamReader(stream, encoding) + return stream + + def file_size(self): + return os.stat(self._path).st_size + + def join(self, fileid): + _path = os.path.join(self._path, fileid) + return FileSystemPathPointer(_path) + + def __repr__(self): + return "FileSystemPathPointer(%r)" % self._path + + def __str__(self): + return self._path + + +@deprecated("Use gzip.GzipFile instead as it also uses a buffer.") +class BufferedGzipFile(GzipFile): + """A ``GzipFile`` subclass for compatibility with older nltk releases. + + Use ``GzipFile`` directly as it also buffers in all supported + Python versions. + """ + + @py3_data + def __init__( + self, filename=None, mode=None, compresslevel=9, fileobj=None, **kwargs + ): + """Return a buffered gzip file object.""" + GzipFile.__init__(self, filename, mode, compresslevel, fileobj) + + def write(self, data): + # This is identical to GzipFile.write but does not return + # the bytes written to retain compatibility. + super().write(data) + + +class GzipFileSystemPathPointer(FileSystemPathPointer): + """ + A subclass of ``FileSystemPathPointer`` that identifies a gzip-compressed + file located at a given absolute path. ``GzipFileSystemPathPointer`` is + appropriate for loading large gzip-compressed pickle objects efficiently. + """ + + def open(self, encoding=None): + stream = GzipFile(self._path, "rb") + if encoding: + stream = SeekableUnicodeStreamReader(stream, encoding) + return stream + + +class ZipFilePathPointer(PathPointer): + """ + A path pointer that identifies a file contained within a zipfile, + which can be accessed by reading that zipfile. + """ + + @py3_data + def __init__(self, zipfile, entry=""): + """ + Create a new path pointer pointing at the specified entry + in the given zipfile. + + :raise IOError: If the given zipfile does not exist, or if it + does not contain the specified entry. + """ + if isinstance(zipfile, str): + zipfile = OpenOnDemandZipFile(os.path.abspath(zipfile)) + + # Check that the entry exists: + if entry: + + # Normalize the entry string, it should be relative: + entry = normalize_resource_name(entry, True, "/").lstrip("/") + + try: + zipfile.getinfo(entry) + except Exception as e: + # Sometimes directories aren't explicitly listed in + # the zip file. So if `entry` is a directory name, + # then check if the zipfile contains any files that + # are under the given directory. + if entry.endswith("/") and [ + n for n in zipfile.namelist() if n.startswith(entry) + ]: + pass # zipfile contains a file in that directory. + else: + # Otherwise, complain. + raise OSError( + f"Zipfile {zipfile.filename!r} does not contain {entry!r}" + ) from e + self._zipfile = zipfile + self._entry = entry + + @property + def zipfile(self): + """ + The zipfile.ZipFile object used to access the zip file + containing the entry identified by this path pointer. + """ + return self._zipfile + + @property + def entry(self): + """ + The name of the file within zipfile that this path + pointer points to. + """ + return self._entry + + def open(self, encoding=None): + data = self._zipfile.read(self._entry) + stream = BytesIO(data) + if self._entry.endswith(".gz"): + stream = GzipFile(self._entry, fileobj=stream) + elif encoding is not None: + stream = SeekableUnicodeStreamReader(stream, encoding) + return stream + + def file_size(self): + return self._zipfile.getinfo(self._entry).file_size + + def join(self, fileid): + entry = f"{self._entry}/{fileid}" + return ZipFilePathPointer(self._zipfile, entry) + + def __repr__(self): + return f"ZipFilePathPointer({self._zipfile.filename!r}, {self._entry!r})" + + def __str__(self): + return os.path.normpath(os.path.join(self._zipfile.filename, self._entry)) + + +###################################################################### +# Access Functions +###################################################################### + +# Don't use a weak dictionary, because in the common case this +# causes a lot more reloading that necessary. +_resource_cache = {} +"""A dictionary used to cache resources so that they won't + need to be loaded more than once.""" + + +def find(resource_name, paths=None): + """ + Find the given resource by searching through the directories and + zip files in paths, where a None or empty string specifies an absolute path. + Returns a corresponding path name. If the given resource is not + found, raise a ``LookupError``, whose message gives a pointer to + the installation instructions for the NLTK downloader. + + Zip File Handling: + + - If ``resource_name`` contains a component with a ``.zip`` + extension, then it is assumed to be a zipfile; and the + remaining path components are used to look inside the zipfile. + + - If any element of ``nltk.data.path`` has a ``.zip`` extension, + then it is assumed to be a zipfile. + + - If a given resource name that does not contain any zipfile + component is not found initially, then ``find()`` will make a + second attempt to find that resource, by replacing each + component *p* in the path with *p.zip/p*. For example, this + allows ``find()`` to map the resource name + ``corpora/chat80/cities.pl`` to a zip file path pointer to + ``corpora/chat80.zip/chat80/cities.pl``. + + - When using ``find()`` to locate a directory contained in a + zipfile, the resource name must end with the forward slash + character. Otherwise, ``find()`` will not locate the + directory. + + :type resource_name: str or unicode + :param resource_name: The name of the resource to search for. + Resource names are posix-style relative path names, such as + ``corpora/brown``. Directory names will be + automatically converted to a platform-appropriate path separator. + :rtype: str + """ + resource_name = normalize_resource_name(resource_name, True) + + # Resolve default paths at runtime in-case the user overrides + # nltk.data.path + if paths is None: + paths = path + + # Check if the resource name includes a zipfile name + m = re.match(r"(.*\.zip)/?(.*)$|", resource_name) + zipfile, zipentry = m.groups() + + # Check each item in our path + for path_ in paths: + # Is the path item a zipfile? + if path_ and (os.path.isfile(path_) and path_.endswith(".zip")): + try: + return ZipFilePathPointer(path_, resource_name) + except OSError: + # resource not in zipfile + continue + + # Is the path item a directory or is resource_name an absolute path? + elif not path_ or os.path.isdir(path_): + if zipfile is None: + p = os.path.join(path_, url2pathname(resource_name)) + if os.path.exists(p): + if p.endswith(".gz"): + return GzipFileSystemPathPointer(p) + else: + return FileSystemPathPointer(p) + else: + p = os.path.join(path_, url2pathname(zipfile)) + if os.path.exists(p): + try: + return ZipFilePathPointer(p, zipentry) + except OSError: + # resource not in zipfile + continue + + # Fallback: if the path doesn't include a zip file, then try + # again, assuming that one of the path components is inside a + # zipfile of the same name. + if zipfile is None: + pieces = resource_name.split("/") + for i in range(len(pieces)): + modified_name = "/".join(pieces[:i] + [pieces[i] + ".zip"] + pieces[i:]) + try: + return find(modified_name, paths) + except LookupError: + pass + + # Identify the package (i.e. the .zip file) to download. + resource_zipname = resource_name.split("/")[1] + if resource_zipname.endswith(".zip"): + resource_zipname = resource_zipname.rpartition(".")[0] + # Display a friendly error message if the resource wasn't found: + msg = str( + "Resource \33[93m{resource}\033[0m not found.\n" + "Please use the NLTK Downloader to obtain the resource:\n\n" + "\33[31m" # To display red text in terminal. + ">>> import nltk\n" + ">>> nltk.download('{resource}')\n" + "\033[0m" + ).format(resource=resource_zipname) + msg = textwrap_indent(msg) + + msg += "\n For more information see: https://www.nltk.org/data.html\n" + + msg += "\n Attempted to load \33[93m{resource_name}\033[0m\n".format( + resource_name=resource_name + ) + + msg += "\n Searched in:" + "".join("\n - %r" % d for d in paths) + sep = "*" * 70 + resource_not_found = f"\n{sep}\n{msg}\n{sep}\n" + raise LookupError(resource_not_found) + + +def retrieve(resource_url, filename=None, verbose=True): + """ + Copy the given resource to a local file. If no filename is + specified, then use the URL's filename. If there is already a + file named ``filename``, then raise a ``ValueError``. + + :type resource_url: str + :param resource_url: A URL specifying where the resource should be + loaded from. The default protocol is "nltk:", which searches + for the file in the the NLTK data package. + """ + resource_url = normalize_resource_url(resource_url) + if filename is None: + if resource_url.startswith("file:"): + filename = os.path.split(resource_url)[-1] + else: + filename = re.sub(r"(^\w+:)?.*/", "", resource_url) + if os.path.exists(filename): + filename = os.path.abspath(filename) + raise ValueError("File %r already exists!" % filename) + + if verbose: + print(f"Retrieving {resource_url!r}, saving to {filename!r}") + + # Open the input & output streams. + infile = _open(resource_url) + + # Copy infile -> outfile, using 64k blocks. + with open(filename, "wb") as outfile: + while True: + s = infile.read(1024 * 64) # 64k blocks. + outfile.write(s) + if not s: + break + + infile.close() + + +#: A dictionary describing the formats that are supported by NLTK's +#: load() method. Keys are format names, and values are format +#: descriptions. +FORMATS = { + "pickle": "A serialized python object, stored using the pickle module.", + "json": "A serialized python object, stored using the json module.", + "yaml": "A serialized python object, stored using the yaml module.", + "cfg": "A context free grammar.", + "pcfg": "A probabilistic CFG.", + "fcfg": "A feature CFG.", + "fol": "A list of first order logic expressions, parsed with " + "nltk.sem.logic.Expression.fromstring.", + "logic": "A list of first order logic expressions, parsed with " + "nltk.sem.logic.LogicParser. Requires an additional logic_parser " + "parameter", + "val": "A semantic valuation, parsed by nltk.sem.Valuation.fromstring.", + "raw": "The raw (byte string) contents of a file.", + "text": "The raw (unicode string) contents of a file. ", +} + +#: A dictionary mapping from file extensions to format names, used +#: by load() when format="auto" to decide the format for a +#: given resource url. +AUTO_FORMATS = { + "pickle": "pickle", + "json": "json", + "yaml": "yaml", + "cfg": "cfg", + "pcfg": "pcfg", + "fcfg": "fcfg", + "fol": "fol", + "logic": "logic", + "val": "val", + "txt": "text", + "text": "text", +} + + +def load( + resource_url, + format="auto", + cache=True, + verbose=False, + logic_parser=None, + fstruct_reader=None, + encoding=None, +): + """ + Load a given resource from the NLTK data package. The following + resource formats are currently supported: + + - ``pickle`` + - ``json`` + - ``yaml`` + - ``cfg`` (context free grammars) + - ``pcfg`` (probabilistic CFGs) + - ``fcfg`` (feature-based CFGs) + - ``fol`` (formulas of First Order Logic) + - ``logic`` (Logical formulas to be parsed by the given logic_parser) + - ``val`` (valuation of First Order Logic model) + - ``text`` (the file contents as a unicode string) + - ``raw`` (the raw file contents as a byte string) + + If no format is specified, ``load()`` will attempt to determine a + format based on the resource name's file extension. If that + fails, ``load()`` will raise a ``ValueError`` exception. + + For all text formats (everything except ``pickle``, ``json``, ``yaml`` and ``raw``), + it tries to decode the raw contents using UTF-8, and if that doesn't + work, it tries with ISO-8859-1 (Latin-1), unless the ``encoding`` + is specified. + + :type resource_url: str + :param resource_url: A URL specifying where the resource should be + loaded from. The default protocol is "nltk:", which searches + for the file in the the NLTK data package. + :type cache: bool + :param cache: If true, add this resource to a cache. If load() + finds a resource in its cache, then it will return it from the + cache rather than loading it. + :type verbose: bool + :param verbose: If true, print a message when loading a resource. + Messages are not displayed when a resource is retrieved from + the cache. + :type logic_parser: LogicParser + :param logic_parser: The parser that will be used to parse logical + expressions. + :type fstruct_reader: FeatStructReader + :param fstruct_reader: The parser that will be used to parse the + feature structure of an fcfg. + :type encoding: str + :param encoding: the encoding of the input; only used for text formats. + """ + resource_url = normalize_resource_url(resource_url) + resource_url = add_py3_data(resource_url) + + # Determine the format of the resource. + if format == "auto": + resource_url_parts = resource_url.split(".") + ext = resource_url_parts[-1] + if ext == "gz": + ext = resource_url_parts[-2] + format = AUTO_FORMATS.get(ext) + if format is None: + raise ValueError( + "Could not determine format for %s based " + 'on its file\nextension; use the "format" ' + "argument to specify the format explicitly." % resource_url + ) + + if format not in FORMATS: + raise ValueError(f"Unknown format type: {format}!") + + # If we've cached the resource, then just return it. + if cache: + resource_val = _resource_cache.get((resource_url, format)) + if resource_val is not None: + if verbose: + print(f"<>") + return resource_val + + # Let the user know what's going on. + if verbose: + print(f"<>") + + # Load the resource. + opened_resource = _open(resource_url) + + if format == "raw": + resource_val = opened_resource.read() + elif format == "pickle": + resource_val = pickle.load(opened_resource) + elif format == "json": + import json + + from nltk.jsontags import json_tags + + resource_val = json.load(opened_resource) + tag = None + if len(resource_val) != 1: + tag = next(resource_val.keys()) + if tag not in json_tags: + raise ValueError("Unknown json tag.") + elif format == "yaml": + import yaml + + resource_val = yaml.safe_load(opened_resource) + else: + # The resource is a text format. + binary_data = opened_resource.read() + if encoding is not None: + string_data = binary_data.decode(encoding) + else: + try: + string_data = binary_data.decode("utf-8") + except UnicodeDecodeError: + string_data = binary_data.decode("latin-1") + if format == "text": + resource_val = string_data + elif format == "cfg": + resource_val = grammar.CFG.fromstring(string_data, encoding=encoding) + elif format == "pcfg": + resource_val = grammar.PCFG.fromstring(string_data, encoding=encoding) + elif format == "fcfg": + resource_val = grammar.FeatureGrammar.fromstring( + string_data, + logic_parser=logic_parser, + fstruct_reader=fstruct_reader, + encoding=encoding, + ) + elif format == "fol": + resource_val = sem.read_logic( + string_data, + logic_parser=sem.logic.LogicParser(), + encoding=encoding, + ) + elif format == "logic": + resource_val = sem.read_logic( + string_data, logic_parser=logic_parser, encoding=encoding + ) + elif format == "val": + resource_val = sem.read_valuation(string_data, encoding=encoding) + else: + raise AssertionError( + "Internal NLTK error: Format %s isn't " + "handled by nltk.data.load()" % (format,) + ) + + opened_resource.close() + + # If requested, add it to the cache. + if cache: + try: + _resource_cache[(resource_url, format)] = resource_val + # TODO: add this line + # print('<>' % (resource_url,)) + except TypeError: + # We can't create weak references to some object types, like + # strings and tuples. For now, just don't cache them. + pass + + return resource_val + + +def show_cfg(resource_url, escape="##"): + """ + Write out a grammar file, ignoring escaped and empty lines. + + :type resource_url: str + :param resource_url: A URL specifying where the resource should be + loaded from. The default protocol is "nltk:", which searches + for the file in the the NLTK data package. + :type escape: str + :param escape: Prepended string that signals lines to be ignored + """ + resource_url = normalize_resource_url(resource_url) + resource_val = load(resource_url, format="text", cache=False) + lines = resource_val.splitlines() + for l in lines: + if l.startswith(escape): + continue + if re.match("^$", l): + continue + print(l) + + +def clear_cache(): + """ + Remove all objects from the resource cache. + :see: load() + """ + _resource_cache.clear() + + +def _open(resource_url): + """ + Helper function that returns an open file object for a resource, + given its resource URL. If the given resource URL uses the "nltk:" + protocol, or uses no protocol, then use ``nltk.data.find`` to find + its path, and open it with the given mode; if the resource URL + uses the 'file' protocol, then open the file with the given mode; + otherwise, delegate to ``urllib2.urlopen``. + + :type resource_url: str + :param resource_url: A URL specifying where the resource should be + loaded from. The default protocol is "nltk:", which searches + for the file in the the NLTK data package. + """ + resource_url = normalize_resource_url(resource_url) + protocol, path_ = split_resource_url(resource_url) + + if protocol is None or protocol.lower() == "nltk": + return find(path_, path + [""]).open() + elif protocol.lower() == "file": + # urllib might not use mode='rb', so handle this one ourselves: + return find(path_, [""]).open() + else: + return urlopen(resource_url) + + +###################################################################### +# Lazy Resource Loader +###################################################################### + + +class LazyLoader: + @py3_data + def __init__(self, _path): + self._path = _path + + def __load(self): + resource = load(self._path) + # This is where the magic happens! Transform ourselves into + # the object by modifying our own __dict__ and __class__ to + # match that of `resource`. + self.__dict__ = resource.__dict__ + self.__class__ = resource.__class__ + + def __getattr__(self, attr): + self.__load() + # This looks circular, but its not, since __load() changes our + # __class__ to something new: + return getattr(self, attr) + + def __repr__(self): + self.__load() + # This looks circular, but its not, since __load() changes our + # __class__ to something new: + return repr(self) + + +###################################################################### +# Open-On-Demand ZipFile +###################################################################### + + +class OpenOnDemandZipFile(zipfile.ZipFile): + """ + A subclass of ``zipfile.ZipFile`` that closes its file pointer + whenever it is not using it; and re-opens it when it needs to read + data from the zipfile. This is useful for reducing the number of + open file handles when many zip files are being accessed at once. + ``OpenOnDemandZipFile`` must be constructed from a filename, not a + file-like object (to allow re-opening). ``OpenOnDemandZipFile`` is + read-only (i.e. ``write()`` and ``writestr()`` are disabled. + """ + + @py3_data + def __init__(self, filename): + if not isinstance(filename, str): + raise TypeError("ReopenableZipFile filename must be a string") + zipfile.ZipFile.__init__(self, filename) + assert self.filename == filename + self.close() + # After closing a ZipFile object, the _fileRefCnt needs to be cleared + # for Python2and3 compatible code. + self._fileRefCnt = 0 + + def read(self, name): + assert self.fp is None + self.fp = open(self.filename, "rb") + value = zipfile.ZipFile.read(self, name) + # Ensure that _fileRefCnt needs to be set for Python2and3 compatible code. + # Since we only opened one file here, we add 1. + self._fileRefCnt += 1 + self.close() + return value + + def write(self, *args, **kwargs): + """:raise NotImplementedError: OpenOnDemandZipfile is read-only""" + raise NotImplementedError("OpenOnDemandZipfile is read-only") + + def writestr(self, *args, **kwargs): + """:raise NotImplementedError: OpenOnDemandZipfile is read-only""" + raise NotImplementedError("OpenOnDemandZipfile is read-only") + + def __repr__(self): + return repr("OpenOnDemandZipFile(%r)" % self.filename) + + +###################################################################### +# Seekable Unicode Stream Reader +###################################################################### + + +class SeekableUnicodeStreamReader: + """ + A stream reader that automatically encodes the source byte stream + into unicode (like ``codecs.StreamReader``); but still supports the + ``seek()`` and ``tell()`` operations correctly. This is in contrast + to ``codecs.StreamReader``, which provide *broken* ``seek()`` and + ``tell()`` methods. + + This class was motivated by ``StreamBackedCorpusView``, which + makes extensive use of ``seek()`` and ``tell()``, and needs to be + able to handle unicode-encoded files. + + Note: this class requires stateless decoders. To my knowledge, + this shouldn't cause a problem with any of python's builtin + unicode encodings. + """ + + DEBUG = True # : If true, then perform extra sanity checks. + + @py3_data + def __init__(self, stream, encoding, errors="strict"): + # Rewind the stream to its beginning. + stream.seek(0) + + self.stream = stream + """The underlying stream.""" + + self.encoding = encoding + """The name of the encoding that should be used to encode the + underlying stream.""" + + self.errors = errors + """The error mode that should be used when decoding data from + the underlying stream. Can be 'strict', 'ignore', or + 'replace'.""" + + self.decode = codecs.getdecoder(encoding) + """The function that is used to decode byte strings into + unicode strings.""" + + self.bytebuffer = b"" + """A buffer to use bytes that have been read but have not yet + been decoded. This is only used when the final bytes from + a read do not form a complete encoding for a character.""" + + self.linebuffer = None + """A buffer used by ``readline()`` to hold characters that have + been read, but have not yet been returned by ``read()`` or + ``readline()``. This buffer consists of a list of unicode + strings, where each string corresponds to a single line. + The final element of the list may or may not be a complete + line. Note that the existence of a linebuffer makes the + ``tell()`` operation more complex, because it must backtrack + to the beginning of the buffer to determine the correct + file position in the underlying byte stream.""" + + self._rewind_checkpoint = 0 + """The file position at which the most recent read on the + underlying stream began. This is used, together with + ``_rewind_numchars``, to backtrack to the beginning of + ``linebuffer`` (which is required by ``tell()``).""" + + self._rewind_numchars = None + """The number of characters that have been returned since the + read that started at ``_rewind_checkpoint``. This is used, + together with ``_rewind_checkpoint``, to backtrack to the + beginning of ``linebuffer`` (which is required by ``tell()``).""" + + self._bom = self._check_bom() + """The length of the byte order marker at the beginning of + the stream (or None for no byte order marker).""" + + # ///////////////////////////////////////////////////////////////// + # Read methods + # ///////////////////////////////////////////////////////////////// + + def read(self, size=None): + """ + Read up to ``size`` bytes, decode them using this reader's + encoding, and return the resulting unicode string. + + :param size: The maximum number of bytes to read. If not + specified, then read as many bytes as possible. + :type size: int + :rtype: unicode + """ + chars = self._read(size) + + # If linebuffer is not empty, then include it in the result + if self.linebuffer: + chars = "".join(self.linebuffer) + chars + self.linebuffer = None + self._rewind_numchars = None + + return chars + + def discard_line(self): + if self.linebuffer and len(self.linebuffer) > 1: + line = self.linebuffer.pop(0) + self._rewind_numchars += len(line) + else: + self.stream.readline() + + def readline(self, size=None): + """ + Read a line of text, decode it using this reader's encoding, + and return the resulting unicode string. + + :param size: The maximum number of bytes to read. If no + newline is encountered before ``size`` bytes have been read, + then the returned value may not be a complete line of text. + :type size: int + """ + # If we have a non-empty linebuffer, then return the first + # line from it. (Note that the last element of linebuffer may + # not be a complete line; so let _read() deal with it.) + if self.linebuffer and len(self.linebuffer) > 1: + line = self.linebuffer.pop(0) + self._rewind_numchars += len(line) + return line + + readsize = size or 72 + chars = "" + + # If there's a remaining incomplete line in the buffer, add it. + if self.linebuffer: + chars += self.linebuffer.pop() + self.linebuffer = None + + while True: + startpos = self.stream.tell() - len(self.bytebuffer) + new_chars = self._read(readsize) + + # If we're at a '\r', then read one extra character, since + # it might be a '\n', to get the proper line ending. + if new_chars and new_chars.endswith("\r"): + new_chars += self._read(1) + + chars += new_chars + lines = chars.splitlines(True) + if len(lines) > 1: + line = lines[0] + self.linebuffer = lines[1:] + self._rewind_numchars = len(new_chars) - (len(chars) - len(line)) + self._rewind_checkpoint = startpos + break + elif len(lines) == 1: + line0withend = lines[0] + line0withoutend = lines[0].splitlines(False)[0] + if line0withend != line0withoutend: # complete line + line = line0withend + break + + if not new_chars or size is not None: + line = chars + break + + # Read successively larger blocks of text. + if readsize < 8000: + readsize *= 2 + + return line + + def readlines(self, sizehint=None, keepends=True): + """ + Read this file's contents, decode them using this reader's + encoding, and return it as a list of unicode lines. + + :rtype: list(unicode) + :param sizehint: Ignored. + :param keepends: If false, then strip newlines. + """ + return self.read().splitlines(keepends) + + def next(self): + """Return the next decoded line from the underlying stream.""" + line = self.readline() + if line: + return line + else: + raise StopIteration + + def __next__(self): + return self.next() + + def __iter__(self): + """Return self""" + return self + + def __del__(self): + # let garbage collector deal with still opened streams + if not self.closed: + self.close() + + def __enter__(self): + return self + + def __exit__(self, type, value, traceback): + self.close() + + def xreadlines(self): + """Return self""" + return self + + # ///////////////////////////////////////////////////////////////// + # Pass-through methods & properties + # ///////////////////////////////////////////////////////////////// + + @property + def closed(self): + """True if the underlying stream is closed.""" + return self.stream.closed + + @property + def name(self): + """The name of the underlying stream.""" + return self.stream.name + + @property + def mode(self): + """The mode of the underlying stream.""" + return self.stream.mode + + def close(self): + """ + Close the underlying stream. + """ + self.stream.close() + + # ///////////////////////////////////////////////////////////////// + # Seek and tell + # ///////////////////////////////////////////////////////////////// + + def seek(self, offset, whence=0): + """ + Move the stream to a new file position. If the reader is + maintaining any buffers, then they will be cleared. + + :param offset: A byte count offset. + :param whence: If 0, then the offset is from the start of the file + (offset should be positive), if 1, then the offset is from the + current position (offset may be positive or negative); and if 2, + then the offset is from the end of the file (offset should + typically be negative). + """ + if whence == 1: + raise ValueError( + "Relative seek is not supported for " + "SeekableUnicodeStreamReader -- consider " + "using char_seek_forward() instead." + ) + self.stream.seek(offset, whence) + self.linebuffer = None + self.bytebuffer = b"" + self._rewind_numchars = None + self._rewind_checkpoint = self.stream.tell() + + def char_seek_forward(self, offset): + """ + Move the read pointer forward by ``offset`` characters. + """ + if offset < 0: + raise ValueError("Negative offsets are not supported") + # Clear all buffers. + self.seek(self.tell()) + # Perform the seek operation. + self._char_seek_forward(offset) + + def _char_seek_forward(self, offset, est_bytes=None): + """ + Move the file position forward by ``offset`` characters, + ignoring all buffers. + + :param est_bytes: A hint, giving an estimate of the number of + bytes that will be needed to move forward by ``offset`` chars. + Defaults to ``offset``. + """ + if est_bytes is None: + est_bytes = offset + bytes = b"" + + while True: + # Read in a block of bytes. + newbytes = self.stream.read(est_bytes - len(bytes)) + bytes += newbytes + + # Decode the bytes to characters. + chars, bytes_decoded = self._incr_decode(bytes) + + # If we got the right number of characters, then seek + # backwards over any truncated characters, and return. + if len(chars) == offset: + self.stream.seek(-len(bytes) + bytes_decoded, 1) + return + + # If we went too far, then we can back-up until we get it + # right, using the bytes we've already read. + if len(chars) > offset: + while len(chars) > offset: + # Assume at least one byte/char. + est_bytes += offset - len(chars) + chars, bytes_decoded = self._incr_decode(bytes[:est_bytes]) + self.stream.seek(-len(bytes) + bytes_decoded, 1) + return + + # Otherwise, we haven't read enough bytes yet; loop again. + est_bytes += offset - len(chars) + + def tell(self): + """ + Return the current file position on the underlying byte + stream. If this reader is maintaining any buffers, then the + returned file position will be the position of the beginning + of those buffers. + """ + # If nothing's buffered, then just return our current filepos: + if self.linebuffer is None: + return self.stream.tell() - len(self.bytebuffer) + + # Otherwise, we'll need to backtrack the filepos until we + # reach the beginning of the buffer. + + # Store our original file position, so we can return here. + orig_filepos = self.stream.tell() + + # Calculate an estimate of where we think the newline is. + bytes_read = (orig_filepos - len(self.bytebuffer)) - self._rewind_checkpoint + buf_size = sum(len(line) for line in self.linebuffer) + est_bytes = int( + bytes_read * self._rewind_numchars / (self._rewind_numchars + buf_size) + ) + + self.stream.seek(self._rewind_checkpoint) + self._char_seek_forward(self._rewind_numchars, est_bytes) + filepos = self.stream.tell() + + # Sanity check + if self.DEBUG: + self.stream.seek(filepos) + check1 = self._incr_decode(self.stream.read(50))[0] + check2 = "".join(self.linebuffer) + assert check1.startswith(check2) or check2.startswith(check1) + + # Return to our original filepos (so we don't have to throw + # out our buffer.) + self.stream.seek(orig_filepos) + + # Return the calculated filepos + return filepos + + # ///////////////////////////////////////////////////////////////// + # Helper methods + # ///////////////////////////////////////////////////////////////// + + def _read(self, size=None): + """ + Read up to ``size`` bytes from the underlying stream, decode + them using this reader's encoding, and return the resulting + unicode string. ``linebuffer`` is not included in the result. + """ + if size == 0: + return "" + + # Skip past the byte order marker, if present. + if self._bom and self.stream.tell() == 0: + self.stream.read(self._bom) + + # Read the requested number of bytes. + if size is None: + new_bytes = self.stream.read() + else: + new_bytes = self.stream.read(size) + bytes = self.bytebuffer + new_bytes + + # Decode the bytes into unicode characters + chars, bytes_decoded = self._incr_decode(bytes) + + # If we got bytes but couldn't decode any, then read further. + if (size is not None) and (not chars) and (len(new_bytes) > 0): + while not chars: + new_bytes = self.stream.read(1) + if not new_bytes: + break # end of file. + bytes += new_bytes + chars, bytes_decoded = self._incr_decode(bytes) + + # Record any bytes we didn't consume. + self.bytebuffer = bytes[bytes_decoded:] + + # Return the result + return chars + + def _incr_decode(self, bytes): + """ + Decode the given byte string into a unicode string, using this + reader's encoding. If an exception is encountered that + appears to be caused by a truncation error, then just decode + the byte string without the bytes that cause the trunctaion + error. + + Return a tuple ``(chars, num_consumed)``, where ``chars`` is + the decoded unicode string, and ``num_consumed`` is the + number of bytes that were consumed. + """ + while True: + try: + return self.decode(bytes, "strict") + except UnicodeDecodeError as exc: + # If the exception occurs at the end of the string, + # then assume that it's a truncation error. + if exc.end == len(bytes): + return self.decode(bytes[: exc.start], self.errors) + + # Otherwise, if we're being strict, then raise it. + elif self.errors == "strict": + raise + + # If we're not strict, then re-process it with our + # errors setting. This *may* raise an exception. + else: + return self.decode(bytes, self.errors) + + _BOM_TABLE = { + "utf8": [(codecs.BOM_UTF8, None)], + "utf16": [(codecs.BOM_UTF16_LE, "utf16-le"), (codecs.BOM_UTF16_BE, "utf16-be")], + "utf16le": [(codecs.BOM_UTF16_LE, None)], + "utf16be": [(codecs.BOM_UTF16_BE, None)], + "utf32": [(codecs.BOM_UTF32_LE, "utf32-le"), (codecs.BOM_UTF32_BE, "utf32-be")], + "utf32le": [(codecs.BOM_UTF32_LE, None)], + "utf32be": [(codecs.BOM_UTF32_BE, None)], + } + + def _check_bom(self): + # Normalize our encoding name + enc = re.sub("[ -]", "", self.encoding.lower()) + + # Look up our encoding in the BOM table. + bom_info = self._BOM_TABLE.get(enc) + + if bom_info: + # Read a prefix, to check against the BOM(s) + bytes = self.stream.read(16) + self.stream.seek(0) + + # Check for each possible BOM. + for (bom, new_encoding) in bom_info: + if bytes.startswith(bom): + if new_encoding: + self.encoding = new_encoding + return len(bom) + + return None + + +__all__ = [ + "path", + "PathPointer", + "FileSystemPathPointer", + "BufferedGzipFile", + "GzipFileSystemPathPointer", + "GzipFileSystemPathPointer", + "find", + "retrieve", + "FORMATS", + "AUTO_FORMATS", + "load", + "show_cfg", + "clear_cache", + "LazyLoader", + "OpenOnDemandZipFile", + "GzipFileSystemPathPointer", + "SeekableUnicodeStreamReader", +] diff --git a/llmeval-env/lib/python3.10/site-packages/nltk/decorators.py b/llmeval-env/lib/python3.10/site-packages/nltk/decorators.py new file mode 100644 index 0000000000000000000000000000000000000000..3a0fae1852afd47a2290b41ce94843aca36aa05f --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/nltk/decorators.py @@ -0,0 +1,251 @@ +""" +Decorator module by Michele Simionato +Copyright Michele Simionato, distributed under the terms of the BSD License (see below). +http://www.phyast.pitt.edu/~micheles/python/documentation.html + +Included in NLTK for its support of a nice memoization decorator. +""" + +__docformat__ = "restructuredtext en" + +## The basic trick is to generate the source code for the decorated function +## with the right signature and to evaluate it. +## Uncomment the statement 'print >> sys.stderr, func_src' in _decorator +## to understand what is going on. + +__all__ = ["decorator", "new_wrapper", "getinfo"] + +import sys + +# Hack to keep NLTK's "tokenize" module from colliding with the "tokenize" in +# the Python standard library. +OLD_SYS_PATH = sys.path[:] +sys.path = [p for p in sys.path if p and "nltk" not in str(p)] +import inspect + +sys.path = OLD_SYS_PATH + + +def __legacysignature(signature): + """ + For retrocompatibility reasons, we don't use a standard Signature. + Instead, we use the string generated by this method. + Basically, from a Signature we create a string and remove the default values. + """ + listsignature = str(signature)[1:-1].split(",") + for counter, param in enumerate(listsignature): + if param.count("=") > 0: + listsignature[counter] = param[0 : param.index("=")].strip() + else: + listsignature[counter] = param.strip() + return ", ".join(listsignature) + + +def getinfo(func): + """ + Returns an info dictionary containing: + - name (the name of the function : str) + - argnames (the names of the arguments : list) + - defaults (the values of the default arguments : tuple) + - signature (the signature : str) + - fullsignature (the full signature : Signature) + - doc (the docstring : str) + - module (the module name : str) + - dict (the function __dict__ : str) + + >>> def f(self, x=1, y=2, *args, **kw): pass + + >>> info = getinfo(f) + + >>> info["name"] + 'f' + >>> info["argnames"] + ['self', 'x', 'y', 'args', 'kw'] + + >>> info["defaults"] + (1, 2) + + >>> info["signature"] + 'self, x, y, *args, **kw' + + >>> info["fullsignature"] + + """ + assert inspect.ismethod(func) or inspect.isfunction(func) + argspec = inspect.getfullargspec(func) + regargs, varargs, varkwargs = argspec[:3] + argnames = list(regargs) + if varargs: + argnames.append(varargs) + if varkwargs: + argnames.append(varkwargs) + fullsignature = inspect.signature(func) + # Convert Signature to str + signature = __legacysignature(fullsignature) + + # pypy compatibility + if hasattr(func, "__closure__"): + _closure = func.__closure__ + _globals = func.__globals__ + else: + _closure = func.func_closure + _globals = func.func_globals + + return dict( + name=func.__name__, + argnames=argnames, + signature=signature, + fullsignature=fullsignature, + defaults=func.__defaults__, + doc=func.__doc__, + module=func.__module__, + dict=func.__dict__, + globals=_globals, + closure=_closure, + ) + + +def update_wrapper(wrapper, model, infodict=None): + "akin to functools.update_wrapper" + infodict = infodict or getinfo(model) + wrapper.__name__ = infodict["name"] + wrapper.__doc__ = infodict["doc"] + wrapper.__module__ = infodict["module"] + wrapper.__dict__.update(infodict["dict"]) + wrapper.__defaults__ = infodict["defaults"] + wrapper.undecorated = model + return wrapper + + +def new_wrapper(wrapper, model): + """ + An improvement over functools.update_wrapper. The wrapper is a generic + callable object. It works by generating a copy of the wrapper with the + right signature and by updating the copy, not the original. + Moreovoer, 'model' can be a dictionary with keys 'name', 'doc', 'module', + 'dict', 'defaults'. + """ + if isinstance(model, dict): + infodict = model + else: # assume model is a function + infodict = getinfo(model) + assert ( + not "_wrapper_" in infodict["argnames"] + ), '"_wrapper_" is a reserved argument name!' + src = "lambda %(signature)s: _wrapper_(%(signature)s)" % infodict + funcopy = eval(src, dict(_wrapper_=wrapper)) + return update_wrapper(funcopy, model, infodict) + + +# helper used in decorator_factory +def __call__(self, func): + return new_wrapper(lambda *a, **k: self.call(func, *a, **k), func) + + +def decorator_factory(cls): + """ + Take a class with a ``.caller`` method and return a callable decorator + object. It works by adding a suitable __call__ method to the class; + it raises a TypeError if the class already has a nontrivial __call__ + method. + """ + attrs = set(dir(cls)) + if "__call__" in attrs: + raise TypeError( + "You cannot decorate a class with a nontrivial " "__call__ method" + ) + if "call" not in attrs: + raise TypeError("You cannot decorate a class without a " ".call method") + cls.__call__ = __call__ + return cls + + +def decorator(caller): + """ + General purpose decorator factory: takes a caller function as + input and returns a decorator with the same attributes. + A caller function is any function like this:: + + def caller(func, *args, **kw): + # do something + return func(*args, **kw) + + Here is an example of usage: + + >>> @decorator + ... def chatty(f, *args, **kw): + ... print("Calling %r" % f.__name__) + ... return f(*args, **kw) + + >>> chatty.__name__ + 'chatty' + + >>> @chatty + ... def f(): pass + ... + >>> f() + Calling 'f' + + decorator can also take in input a class with a .caller method; in this + case it converts the class into a factory of callable decorator objects. + See the documentation for an example. + """ + if inspect.isclass(caller): + return decorator_factory(caller) + + def _decorator(func): # the real meat is here + infodict = getinfo(func) + argnames = infodict["argnames"] + assert not ( + "_call_" in argnames or "_func_" in argnames + ), "You cannot use _call_ or _func_ as argument names!" + src = "lambda %(signature)s: _call_(_func_, %(signature)s)" % infodict + # import sys; print >> sys.stderr, src # for debugging purposes + dec_func = eval(src, dict(_func_=func, _call_=caller)) + return update_wrapper(dec_func, func, infodict) + + return update_wrapper(_decorator, caller) + + +def getattr_(obj, name, default_thunk): + "Similar to .setdefault in dictionaries." + try: + return getattr(obj, name) + except AttributeError: + default = default_thunk() + setattr(obj, name, default) + return default + + +@decorator +def memoize(func, *args): + dic = getattr_(func, "memoize_dic", dict) + # memoize_dic is created at the first call + if args in dic: + return dic[args] + result = func(*args) + dic[args] = result + return result + + +########################## LEGALESE ############################### + +## Redistributions of source code must retain the above copyright +## notice, this list of conditions and the following disclaimer. +## Redistributions in bytecode form must reproduce the above copyright +## notice, this list of conditions and the following disclaimer in +## the documentation and/or other materials provided with the +## distribution. + +## THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS +## "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT +## LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR +## A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT +## HOLDERS OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, +## INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, +## BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS +## OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND +## ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR +## TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE +## USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH +## DAMAGE. diff --git a/llmeval-env/lib/python3.10/site-packages/nltk/downloader.py b/llmeval-env/lib/python3.10/site-packages/nltk/downloader.py new file mode 100644 index 0000000000000000000000000000000000000000..71519238755062c698a1d82ffa0984b3ccb5ba92 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/nltk/downloader.py @@ -0,0 +1,2559 @@ +# Natural Language Toolkit: Corpus & Model Downloader +# +# Copyright (C) 2001-2023 NLTK Project +# Author: Edward Loper +# URL: +# For license information, see LICENSE.TXT + +""" +The NLTK corpus and module downloader. This module defines several +interfaces which can be used to download corpora, models, and other +data packages that can be used with NLTK. + +Downloading Packages +==================== +If called with no arguments, ``download()`` will display an interactive +interface which can be used to download and install new packages. +If Tkinter is available, then a graphical interface will be shown, +otherwise a simple text interface will be provided. + +Individual packages can be downloaded by calling the ``download()`` +function with a single argument, giving the package identifier for the +package that should be downloaded: + + >>> download('treebank') # doctest: +SKIP + [nltk_data] Downloading package 'treebank'... + [nltk_data] Unzipping corpora/treebank.zip. + +NLTK also provides a number of \"package collections\", consisting of +a group of related packages. To download all packages in a +colleciton, simply call ``download()`` with the collection's +identifier: + + >>> download('all-corpora') # doctest: +SKIP + [nltk_data] Downloading package 'abc'... + [nltk_data] Unzipping corpora/abc.zip. + [nltk_data] Downloading package 'alpino'... + [nltk_data] Unzipping corpora/alpino.zip. + ... + [nltk_data] Downloading package 'words'... + [nltk_data] Unzipping corpora/words.zip. + +Download Directory +================== +By default, packages are installed in either a system-wide directory +(if Python has sufficient access to write to it); or in the current +user's home directory. However, the ``download_dir`` argument may be +used to specify a different installation target, if desired. + +See ``Downloader.default_download_dir()`` for more a detailed +description of how the default download directory is chosen. + +NLTK Download Server +==================== +Before downloading any packages, the corpus and module downloader +contacts the NLTK download server, to retrieve an index file +describing the available packages. By default, this index file is +loaded from ``https://raw.githubusercontent.com/nltk/nltk_data/gh-pages/index.xml``. +If necessary, it is possible to create a new ``Downloader`` object, +specifying a different URL for the package index file. + +Usage:: + + python nltk/downloader.py [-d DATADIR] [-q] [-f] [-k] PACKAGE_IDS + +or:: + + python -m nltk.downloader [-d DATADIR] [-q] [-f] [-k] PACKAGE_IDS +""" +# ---------------------------------------------------------------------- + +""" + + 0 1 2 3 +[label][----][label][----] +[column ][column ] + +Notes +===== +Handling data files.. Some questions: + +* Should the data files be kept zipped or unzipped? I say zipped. + +* Should the data files be kept in svn at all? Advantages: history; + automatic version numbers; 'svn up' could be used rather than the + downloader to update the corpora. Disadvantages: they're big, + which makes working from svn a bit of a pain. And we're planning + to potentially make them much bigger. I don't think we want + people to have to download 400MB corpora just to use nltk from svn. + +* Compromise: keep the data files in trunk/data rather than in + trunk/nltk. That way you can check them out in svn if you want + to; but you don't need to, and you can use the downloader instead. + +* Also: keep models in mind. When we change the code, we'd + potentially like the models to get updated. This could require a + little thought. + +* So.. let's assume we have a trunk/data directory, containing a bunch + of packages. The packages should be kept as zip files, because we + really shouldn't be editing them much (well -- we may edit models + more, but they tend to be binary-ish files anyway, where diffs + aren't that helpful). So we'll have trunk/data, with a bunch of + files like abc.zip and treebank.zip and propbank.zip. For each + package we could also have eg treebank.xml and propbank.xml, + describing the contents of the package (name, copyright, license, + etc). Collections would also have .xml files. Finally, we would + pull all these together to form a single index.xml file. Some + directory structure wouldn't hurt. So how about:: + + /trunk/data/ ....................... root of data svn + index.xml ........................ main index file + src/ ............................. python scripts + packages/ ........................ dir for packages + corpora/ ....................... zip & xml files for corpora + grammars/ ...................... zip & xml files for grammars + taggers/ ....................... zip & xml files for taggers + tokenizers/ .................... zip & xml files for tokenizers + etc. + collections/ ..................... xml files for collections + + Where the root (/trunk/data) would contain a makefile; and src/ + would contain a script to update the info.xml file. It could also + contain scripts to rebuild some of the various model files. The + script that builds index.xml should probably check that each zip + file expands entirely into a single subdir, whose name matches the + package's uid. + +Changes I need to make: + - in index: change "size" to "filesize" or "compressed-size" + - in index: add "unzipped-size" + - when checking status: check both compressed & uncompressed size. + uncompressed size is important to make sure we detect a problem + if something got partially unzipped. define new status values + to differentiate stale vs corrupt vs corruptly-uncompressed?? + (we shouldn't need to re-download the file if the zip file is ok + but it didn't get uncompressed fully.) + - add other fields to the index: author, license, copyright, contact, + etc. + +the current grammars/ package would become a single new package (eg +toy-grammars or book-grammars). + +xml file should have: + - authorship info + - license info + - copyright info + - contact info + - info about what type of data/annotation it contains? + - recommended corpus reader? + +collections can contain other collections. they can also contain +multiple package types (corpora & models). Have a single 'basics' +package that includes everything we talk about in the book? + +n.b.: there will have to be a fallback to the punkt tokenizer, in case +they didn't download that model. + +default: unzip or not? + +""" +import functools +import itertools +import os +import shutil +import subprocess +import sys +import textwrap +import threading +import time +import warnings +import zipfile +from hashlib import md5 +from xml.etree import ElementTree + +try: + TKINTER = True + from tkinter import Button, Canvas, Entry, Frame, IntVar, Label, Menu, TclError, Tk + from tkinter.messagebox import showerror + + from nltk.draw.table import Table + from nltk.draw.util import ShowText +except ImportError: + TKINTER = False + TclError = ValueError + +from urllib.error import HTTPError, URLError +from urllib.request import urlopen + +import nltk + +# urllib2 = nltk.internals.import_from_stdlib('urllib2') + + +###################################################################### +# Directory entry objects (from the data server's index file) +###################################################################### + + +class Package: + """ + A directory entry for a downloadable package. These entries are + extracted from the XML index file that is downloaded by + ``Downloader``. Each package consists of a single file; but if + that file is a zip file, then it can be automatically decompressed + when the package is installed. + """ + + def __init__( + self, + id, + url, + name=None, + subdir="", + size=None, + unzipped_size=None, + checksum=None, + svn_revision=None, + copyright="Unknown", + contact="Unknown", + license="Unknown", + author="Unknown", + unzip=True, + **kw, + ): + self.id = id + """A unique identifier for this package.""" + + self.name = name or id + """A string name for this package.""" + + self.subdir = subdir + """The subdirectory where this package should be installed. + E.g., ``'corpora'`` or ``'taggers'``.""" + + self.url = url + """A URL that can be used to download this package's file.""" + + self.size = int(size) + """The filesize (in bytes) of the package file.""" + + self.unzipped_size = int(unzipped_size) + """The total filesize of the files contained in the package's + zipfile.""" + + self.checksum = checksum + """The MD-5 checksum of the package file.""" + + self.svn_revision = svn_revision + """A subversion revision number for this package.""" + + self.copyright = copyright + """Copyright holder for this package.""" + + self.contact = contact + """Name & email of the person who should be contacted with + questions about this package.""" + + self.license = license + """License information for this package.""" + + self.author = author + """Author of this package.""" + + ext = os.path.splitext(url.split("/")[-1])[1] + self.filename = os.path.join(subdir, id + ext) + """The filename that should be used for this package's file. It + is formed by joining ``self.subdir`` with ``self.id``, and + using the same extension as ``url``.""" + + self.unzip = bool(int(unzip)) # '0' or '1' + """A flag indicating whether this corpus should be unzipped by + default.""" + + # Include any other attributes provided by the XML file. + self.__dict__.update(kw) + + @staticmethod + def fromxml(xml): + if isinstance(xml, str): + xml = ElementTree.parse(xml) + for key in xml.attrib: + xml.attrib[key] = str(xml.attrib[key]) + return Package(**xml.attrib) + + def __lt__(self, other): + return self.id < other.id + + def __repr__(self): + return "" % self.id + + +class Collection: + """ + A directory entry for a collection of downloadable packages. + These entries are extracted from the XML index file that is + downloaded by ``Downloader``. + """ + + def __init__(self, id, children, name=None, **kw): + self.id = id + """A unique identifier for this collection.""" + + self.name = name or id + """A string name for this collection.""" + + self.children = children + """A list of the ``Collections`` or ``Packages`` directly + contained by this collection.""" + + self.packages = None + """A list of ``Packages`` contained by this collection or any + collections it recursively contains.""" + + # Include any other attributes provided by the XML file. + self.__dict__.update(kw) + + @staticmethod + def fromxml(xml): + if isinstance(xml, str): + xml = ElementTree.parse(xml) + for key in xml.attrib: + xml.attrib[key] = str(xml.attrib[key]) + children = [child.get("ref") for child in xml.findall("item")] + return Collection(children=children, **xml.attrib) + + def __lt__(self, other): + return self.id < other.id + + def __repr__(self): + return "" % self.id + + +###################################################################### +# Message Passing Objects +###################################################################### + + +class DownloaderMessage: + """A status message object, used by ``incr_download`` to + communicate its progress.""" + + +class StartCollectionMessage(DownloaderMessage): + """Data server has started working on a collection of packages.""" + + def __init__(self, collection): + self.collection = collection + + +class FinishCollectionMessage(DownloaderMessage): + """Data server has finished working on a collection of packages.""" + + def __init__(self, collection): + self.collection = collection + + +class StartPackageMessage(DownloaderMessage): + """Data server has started working on a package.""" + + def __init__(self, package): + self.package = package + + +class FinishPackageMessage(DownloaderMessage): + """Data server has finished working on a package.""" + + def __init__(self, package): + self.package = package + + +class StartDownloadMessage(DownloaderMessage): + """Data server has started downloading a package.""" + + def __init__(self, package): + self.package = package + + +class FinishDownloadMessage(DownloaderMessage): + """Data server has finished downloading a package.""" + + def __init__(self, package): + self.package = package + + +class StartUnzipMessage(DownloaderMessage): + """Data server has started unzipping a package.""" + + def __init__(self, package): + self.package = package + + +class FinishUnzipMessage(DownloaderMessage): + """Data server has finished unzipping a package.""" + + def __init__(self, package): + self.package = package + + +class UpToDateMessage(DownloaderMessage): + """The package download file is already up-to-date""" + + def __init__(self, package): + self.package = package + + +class StaleMessage(DownloaderMessage): + """The package download file is out-of-date or corrupt""" + + def __init__(self, package): + self.package = package + + +class ErrorMessage(DownloaderMessage): + """Data server encountered an error""" + + def __init__(self, package, message): + self.package = package + if isinstance(message, Exception): + self.message = str(message) + else: + self.message = message + + +class ProgressMessage(DownloaderMessage): + """Indicates how much progress the data server has made""" + + def __init__(self, progress): + self.progress = progress + + +class SelectDownloadDirMessage(DownloaderMessage): + """Indicates what download directory the data server is using""" + + def __init__(self, download_dir): + self.download_dir = download_dir + + +###################################################################### +# NLTK Data Server +###################################################################### + + +class Downloader: + """ + A class used to access the NLTK data server, which can be used to + download corpora and other data packages. + """ + + # ///////////////////////////////////////////////////////////////// + # Configuration + # ///////////////////////////////////////////////////////////////// + + INDEX_TIMEOUT = 60 * 60 # 1 hour + """The amount of time after which the cached copy of the data + server index will be considered 'stale,' and will be + re-downloaded.""" + + DEFAULT_URL = "https://raw.githubusercontent.com/nltk/nltk_data/gh-pages/index.xml" + """The default URL for the NLTK data server's index. An + alternative URL can be specified when creating a new + ``Downloader`` object.""" + + # ///////////////////////////////////////////////////////////////// + # Status Constants + # ///////////////////////////////////////////////////////////////// + + INSTALLED = "installed" + """A status string indicating that a package or collection is + installed and up-to-date.""" + NOT_INSTALLED = "not installed" + """A status string indicating that a package or collection is + not installed.""" + STALE = "out of date" + """A status string indicating that a package or collection is + corrupt or out-of-date.""" + PARTIAL = "partial" + """A status string indicating that a collection is partially + installed (i.e., only some of its packages are installed.)""" + + # ///////////////////////////////////////////////////////////////// + # Constructor + # ///////////////////////////////////////////////////////////////// + + def __init__(self, server_index_url=None, download_dir=None): + self._url = server_index_url or self.DEFAULT_URL + """The URL for the data server's index file.""" + + self._collections = {} + """Dictionary from collection identifier to ``Collection``""" + + self._packages = {} + """Dictionary from package identifier to ``Package``""" + + self._download_dir = download_dir + """The default directory to which packages will be downloaded.""" + + self._index = None + """The XML index file downloaded from the data server""" + + self._index_timestamp = None + """Time at which ``self._index`` was downloaded. If it is more + than ``INDEX_TIMEOUT`` seconds old, it will be re-downloaded.""" + + self._status_cache = {} + """Dictionary from package/collection identifier to status + string (``INSTALLED``, ``NOT_INSTALLED``, ``STALE``, or + ``PARTIAL``). Cache is used for packages only, not + collections.""" + + self._errors = None + """Flag for telling if all packages got successfully downloaded or not.""" + + # decide where we're going to save things to. + if self._download_dir is None: + self._download_dir = self.default_download_dir() + + # ///////////////////////////////////////////////////////////////// + # Information + # ///////////////////////////////////////////////////////////////// + + def list( + self, + download_dir=None, + show_packages=True, + show_collections=True, + header=True, + more_prompt=False, + skip_installed=False, + ): + lines = 0 # for more_prompt + if download_dir is None: + download_dir = self._download_dir + print("Using default data directory (%s)" % download_dir) + if header: + print("=" * (26 + len(self._url))) + print(" Data server index for <%s>" % self._url) + print("=" * (26 + len(self._url))) + lines += 3 # for more_prompt + stale = partial = False + + categories = [] + if show_packages: + categories.append("packages") + if show_collections: + categories.append("collections") + for category in categories: + print("%s:" % category.capitalize()) + lines += 1 # for more_prompt + for info in sorted(getattr(self, category)(), key=str): + status = self.status(info, download_dir) + if status == self.INSTALLED and skip_installed: + continue + if status == self.STALE: + stale = True + if status == self.PARTIAL: + partial = True + prefix = { + self.INSTALLED: "*", + self.STALE: "-", + self.PARTIAL: "P", + self.NOT_INSTALLED: " ", + }[status] + name = textwrap.fill( + "-" * 27 + (info.name or info.id), 75, subsequent_indent=27 * " " + )[27:] + print(" [{}] {} {}".format(prefix, info.id.ljust(20, "."), name)) + lines += len(name.split("\n")) # for more_prompt + if more_prompt and lines > 20: + user_input = input("Hit Enter to continue: ") + if user_input.lower() in ("x", "q"): + return + lines = 0 + print() + msg = "([*] marks installed packages" + if stale: + msg += "; [-] marks out-of-date or corrupt packages" + if partial: + msg += "; [P] marks partially installed collections" + print(textwrap.fill(msg + ")", subsequent_indent=" ", width=76)) + + def packages(self): + self._update_index() + return self._packages.values() + + def corpora(self): + self._update_index() + return [pkg for (id, pkg) in self._packages.items() if pkg.subdir == "corpora"] + + def models(self): + self._update_index() + return [pkg for (id, pkg) in self._packages.items() if pkg.subdir != "corpora"] + + def collections(self): + self._update_index() + return self._collections.values() + + # ///////////////////////////////////////////////////////////////// + # Downloading + # ///////////////////////////////////////////////////////////////// + + def _info_or_id(self, info_or_id): + if isinstance(info_or_id, str): + return self.info(info_or_id) + else: + return info_or_id + + # [xx] When during downloading is it 'safe' to abort? Only unsafe + # time is *during* an unzip -- we don't want to leave a + # partially-unzipped corpus in place because we wouldn't notice + # it. But if we had the exact total size of the unzipped corpus, + # then that would be fine. Then we could abort anytime we want! + # So this is really what we should do. That way the threaded + # downloader in the gui can just kill the download thread anytime + # it wants. + + def incr_download(self, info_or_id, download_dir=None, force=False): + # If they didn't specify a download_dir, then use the default one. + if download_dir is None: + download_dir = self._download_dir + yield SelectDownloadDirMessage(download_dir) + + # If they gave us a list of ids, then download each one. + if isinstance(info_or_id, (list, tuple)): + yield from self._download_list(info_or_id, download_dir, force) + return + + # Look up the requested collection or package. + try: + info = self._info_or_id(info_or_id) + except (OSError, ValueError) as e: + yield ErrorMessage(None, f"Error loading {info_or_id}: {e}") + return + + # Handle collections. + if isinstance(info, Collection): + yield StartCollectionMessage(info) + yield from self.incr_download(info.children, download_dir, force) + yield FinishCollectionMessage(info) + + # Handle Packages (delegate to a helper function). + else: + yield from self._download_package(info, download_dir, force) + + def _num_packages(self, item): + if isinstance(item, Package): + return 1 + else: + return len(item.packages) + + def _download_list(self, items, download_dir, force): + # Look up the requested items. + for i in range(len(items)): + try: + items[i] = self._info_or_id(items[i]) + except (OSError, ValueError) as e: + yield ErrorMessage(items[i], e) + return + + # Download each item, re-scaling their progress. + num_packages = sum(self._num_packages(item) for item in items) + progress = 0 + for i, item in enumerate(items): + if isinstance(item, Package): + delta = 1.0 / num_packages + else: + delta = len(item.packages) / num_packages + for msg in self.incr_download(item, download_dir, force): + if isinstance(msg, ProgressMessage): + yield ProgressMessage(progress + msg.progress * delta) + else: + yield msg + + progress += 100 * delta + + def _download_package(self, info, download_dir, force): + yield StartPackageMessage(info) + yield ProgressMessage(0) + + # Do we already have the current version? + status = self.status(info, download_dir) + if not force and status == self.INSTALLED: + yield UpToDateMessage(info) + yield ProgressMessage(100) + yield FinishPackageMessage(info) + return + + # Remove the package from our status cache + self._status_cache.pop(info.id, None) + + # Check for (and remove) any old/stale version. + filepath = os.path.join(download_dir, info.filename) + if os.path.exists(filepath): + if status == self.STALE: + yield StaleMessage(info) + os.remove(filepath) + + # Ensure the download_dir exists + if not os.path.exists(download_dir): + os.makedirs(download_dir) + if not os.path.exists(os.path.join(download_dir, info.subdir)): + os.makedirs(os.path.join(download_dir, info.subdir)) + + # Download the file. This will raise an IOError if the url + # is not found. + yield StartDownloadMessage(info) + yield ProgressMessage(5) + try: + infile = urlopen(info.url) + with open(filepath, "wb") as outfile: + num_blocks = max(1, info.size / (1024 * 16)) + for block in itertools.count(): + s = infile.read(1024 * 16) # 16k blocks. + outfile.write(s) + if not s: + break + if block % 2 == 0: # how often? + yield ProgressMessage(min(80, 5 + 75 * (block / num_blocks))) + infile.close() + except OSError as e: + yield ErrorMessage( + info, + "Error downloading %r from <%s>:" "\n %s" % (info.id, info.url, e), + ) + return + yield FinishDownloadMessage(info) + yield ProgressMessage(80) + + # If it's a zipfile, uncompress it. + if info.filename.endswith(".zip"): + zipdir = os.path.join(download_dir, info.subdir) + # Unzip if we're unzipping by default; *or* if it's already + # been unzipped (presumably a previous version). + if info.unzip or os.path.exists(os.path.join(zipdir, info.id)): + yield StartUnzipMessage(info) + for msg in _unzip_iter(filepath, zipdir, verbose=False): + # Somewhat of a hack, but we need a proper package reference + msg.package = info + yield msg + yield FinishUnzipMessage(info) + + yield FinishPackageMessage(info) + + def download( + self, + info_or_id=None, + download_dir=None, + quiet=False, + force=False, + prefix="[nltk_data] ", + halt_on_error=True, + raise_on_error=False, + print_error_to=sys.stderr, + ): + + print_to = functools.partial(print, file=print_error_to) + # If no info or id is given, then use the interactive shell. + if info_or_id is None: + # [xx] hmm -- changing self._download_dir here seems like + # the wrong thing to do. Maybe the _interactive_download + # function should make a new copy of self to use? + if download_dir is not None: + self._download_dir = download_dir + self._interactive_download() + return True + + else: + # Define a helper function for displaying output: + def show(s, prefix2=""): + print_to( + textwrap.fill( + s, + initial_indent=prefix + prefix2, + subsequent_indent=prefix + prefix2 + " " * 4, + ) + ) + + for msg in self.incr_download(info_or_id, download_dir, force): + # Error messages + if isinstance(msg, ErrorMessage): + show(msg.message) + if raise_on_error: + raise ValueError(msg.message) + if halt_on_error: + return False + self._errors = True + if not quiet: + print_to("Error installing package. Retry? [n/y/e]") + choice = input().strip() + if choice in ["y", "Y"]: + if not self.download( + msg.package.id, + download_dir, + quiet, + force, + prefix, + halt_on_error, + raise_on_error, + ): + return False + elif choice in ["e", "E"]: + return False + + # All other messages + if not quiet: + # Collection downloading messages: + if isinstance(msg, StartCollectionMessage): + show("Downloading collection %r" % msg.collection.id) + prefix += " | " + print_to(prefix) + elif isinstance(msg, FinishCollectionMessage): + print_to(prefix) + prefix = prefix[:-4] + if self._errors: + show( + "Downloaded collection %r with errors" + % msg.collection.id + ) + else: + show("Done downloading collection %s" % msg.collection.id) + + # Package downloading messages: + elif isinstance(msg, StartPackageMessage): + show( + "Downloading package %s to %s..." + % (msg.package.id, download_dir) + ) + elif isinstance(msg, UpToDateMessage): + show("Package %s is already up-to-date!" % msg.package.id, " ") + # elif isinstance(msg, StaleMessage): + # show('Package %s is out-of-date or corrupt' % + # msg.package.id, ' ') + elif isinstance(msg, StartUnzipMessage): + show("Unzipping %s." % msg.package.filename, " ") + + # Data directory message: + elif isinstance(msg, SelectDownloadDirMessage): + download_dir = msg.download_dir + return True + + def is_stale(self, info_or_id, download_dir=None): + return self.status(info_or_id, download_dir) == self.STALE + + def is_installed(self, info_or_id, download_dir=None): + return self.status(info_or_id, download_dir) == self.INSTALLED + + def clear_status_cache(self, id=None): + if id is None: + self._status_cache.clear() + else: + self._status_cache.pop(id, None) + + def status(self, info_or_id, download_dir=None): + """ + Return a constant describing the status of the given package + or collection. Status can be one of ``INSTALLED``, + ``NOT_INSTALLED``, ``STALE``, or ``PARTIAL``. + """ + if download_dir is None: + download_dir = self._download_dir + info = self._info_or_id(info_or_id) + + # Handle collections: + if isinstance(info, Collection): + pkg_status = [self.status(pkg.id) for pkg in info.packages] + if self.STALE in pkg_status: + return self.STALE + elif self.PARTIAL in pkg_status: + return self.PARTIAL + elif self.INSTALLED in pkg_status and self.NOT_INSTALLED in pkg_status: + return self.PARTIAL + elif self.NOT_INSTALLED in pkg_status: + return self.NOT_INSTALLED + else: + return self.INSTALLED + + # Handle packages: + else: + filepath = os.path.join(download_dir, info.filename) + if download_dir != self._download_dir: + return self._pkg_status(info, filepath) + else: + if info.id not in self._status_cache: + self._status_cache[info.id] = self._pkg_status(info, filepath) + return self._status_cache[info.id] + + def _pkg_status(self, info, filepath): + if not os.path.exists(filepath): + return self.NOT_INSTALLED + + # Check if the file has the correct size. + try: + filestat = os.stat(filepath) + except OSError: + return self.NOT_INSTALLED + if filestat.st_size != int(info.size): + return self.STALE + + # Check if the file's checksum matches + if md5_hexdigest(filepath) != info.checksum: + return self.STALE + + # If it's a zipfile, and it's been at least partially + # unzipped, then check if it's been fully unzipped. + if filepath.endswith(".zip"): + unzipdir = filepath[:-4] + if not os.path.exists(unzipdir): + return self.INSTALLED # but not unzipped -- ok! + if not os.path.isdir(unzipdir): + return self.STALE + + unzipped_size = sum( + os.stat(os.path.join(d, f)).st_size + for d, _, files in os.walk(unzipdir) + for f in files + ) + if unzipped_size != info.unzipped_size: + return self.STALE + + # Otherwise, everything looks good. + return self.INSTALLED + + def update(self, quiet=False, prefix="[nltk_data] "): + """ + Re-download any packages whose status is STALE. + """ + self.clear_status_cache() + for pkg in self.packages(): + if self.status(pkg) == self.STALE: + self.download(pkg, quiet=quiet, prefix=prefix) + + # ///////////////////////////////////////////////////////////////// + # Index + # ///////////////////////////////////////////////////////////////// + + def _update_index(self, url=None): + """A helper function that ensures that self._index is + up-to-date. If the index is older than self.INDEX_TIMEOUT, + then download it again.""" + # Check if the index is already up-to-date. If so, do nothing. + if not ( + self._index is None + or url is not None + or time.time() - self._index_timestamp > self.INDEX_TIMEOUT + ): + return + + # If a URL was specified, then update our URL. + self._url = url or self._url + + # Download the index file. + self._index = nltk.internals.ElementWrapper( + ElementTree.parse(urlopen(self._url)).getroot() + ) + self._index_timestamp = time.time() + + # Build a dictionary of packages. + packages = [Package.fromxml(p) for p in self._index.findall("packages/package")] + self._packages = {p.id: p for p in packages} + + # Build a dictionary of collections. + collections = [ + Collection.fromxml(c) for c in self._index.findall("collections/collection") + ] + self._collections = {c.id: c for c in collections} + + # Replace identifiers with actual children in collection.children. + for collection in self._collections.values(): + for i, child_id in enumerate(collection.children): + if child_id in self._packages: + collection.children[i] = self._packages[child_id] + elif child_id in self._collections: + collection.children[i] = self._collections[child_id] + else: + print( + "removing collection member with no package: {}".format( + child_id + ) + ) + del collection.children[i] + + # Fill in collection.packages for each collection. + for collection in self._collections.values(): + packages = {} + queue = [collection] + for child in queue: + if isinstance(child, Collection): + queue.extend(child.children) + elif isinstance(child, Package): + packages[child.id] = child + else: + pass + collection.packages = packages.values() + + # Flush the status cache + self._status_cache.clear() + + def index(self): + """ + Return the XML index describing the packages available from + the data server. If necessary, this index will be downloaded + from the data server. + """ + self._update_index() + return self._index + + def info(self, id): + """Return the ``Package`` or ``Collection`` record for the + given item.""" + self._update_index() + if id in self._packages: + return self._packages[id] + if id in self._collections: + return self._collections[id] + raise ValueError("Package %r not found in index" % id) + + def xmlinfo(self, id): + """Return the XML info record for the given item""" + self._update_index() + for package in self._index.findall("packages/package"): + if package.get("id") == id: + return package + for collection in self._index.findall("collections/collection"): + if collection.get("id") == id: + return collection + raise ValueError("Package %r not found in index" % id) + + # ///////////////////////////////////////////////////////////////// + # URL & Data Directory + # ///////////////////////////////////////////////////////////////// + + def _get_url(self): + """The URL for the data server's index file.""" + return self._url + + def _set_url(self, url): + """ + Set a new URL for the data server. If we're unable to contact + the given url, then the original url is kept. + """ + original_url = self._url + try: + self._update_index(url) + except: + self._url = original_url + raise + + url = property(_get_url, _set_url) + + def default_download_dir(self): + """ + Return the directory to which packages will be downloaded by + default. This value can be overridden using the constructor, + or on a case-by-case basis using the ``download_dir`` argument when + calling ``download()``. + + On Windows, the default download directory is + ``PYTHONHOME/lib/nltk``, where *PYTHONHOME* is the + directory containing Python, e.g. ``C:\\Python25``. + + On all other platforms, the default directory is the first of + the following which exists or which can be created with write + permission: ``/usr/share/nltk_data``, ``/usr/local/share/nltk_data``, + ``/usr/lib/nltk_data``, ``/usr/local/lib/nltk_data``, ``~/nltk_data``. + """ + # Check if we are on GAE where we cannot write into filesystem. + if "APPENGINE_RUNTIME" in os.environ: + return + + # Check if we have sufficient permissions to install in a + # variety of system-wide locations. + for nltkdir in nltk.data.path: + if os.path.exists(nltkdir) and nltk.internals.is_writable(nltkdir): + return nltkdir + + # On Windows, use %APPDATA% + if sys.platform == "win32" and "APPDATA" in os.environ: + homedir = os.environ["APPDATA"] + + # Otherwise, install in the user's home directory. + else: + homedir = os.path.expanduser("~/") + if homedir == "~/": + raise ValueError("Could not find a default download directory") + + # append "nltk_data" to the home directory + return os.path.join(homedir, "nltk_data") + + def _get_download_dir(self): + """ + The default directory to which packages will be downloaded. + This defaults to the value returned by ``default_download_dir()``. + To override this default on a case-by-case basis, use the + ``download_dir`` argument when calling ``download()``. + """ + return self._download_dir + + def _set_download_dir(self, download_dir): + self._download_dir = download_dir + # Clear the status cache. + self._status_cache.clear() + + download_dir = property(_get_download_dir, _set_download_dir) + + # ///////////////////////////////////////////////////////////////// + # Interactive Shell + # ///////////////////////////////////////////////////////////////// + + def _interactive_download(self): + # Try the GUI first; if that doesn't work, try the simple + # interactive shell. + if TKINTER: + try: + DownloaderGUI(self).mainloop() + except TclError: + DownloaderShell(self).run() + else: + DownloaderShell(self).run() + + +class DownloaderShell: + def __init__(self, dataserver): + self._ds = dataserver + + def _simple_interactive_menu(self, *options): + print("-" * 75) + spc = (68 - sum(len(o) for o in options)) // (len(options) - 1) * " " + print(" " + spc.join(options)) + print("-" * 75) + + def run(self): + print("NLTK Downloader") + while True: + self._simple_interactive_menu( + "d) Download", + "l) List", + " u) Update", + "c) Config", + "h) Help", + "q) Quit", + ) + user_input = input("Downloader> ").strip() + if not user_input: + print() + continue + command = user_input.lower().split()[0] + args = user_input.split()[1:] + try: + if command == "l": + print() + self._ds.list(self._ds.download_dir, header=False, more_prompt=True) + elif command == "h": + self._simple_interactive_help() + elif command == "c": + self._simple_interactive_config() + elif command in ("q", "x"): + return + elif command == "d": + self._simple_interactive_download(args) + elif command == "u": + self._simple_interactive_update() + else: + print("Command %r unrecognized" % user_input) + except HTTPError as e: + print("Error reading from server: %s" % e) + except URLError as e: + print("Error connecting to server: %s" % e.reason) + # try checking if user_input is a package name, & + # downloading it? + print() + + def _simple_interactive_download(self, args): + if args: + for arg in args: + try: + self._ds.download(arg, prefix=" ") + except (OSError, ValueError) as e: + print(e) + else: + while True: + print() + print("Download which package (l=list; x=cancel)?") + user_input = input(" Identifier> ") + if user_input.lower() == "l": + self._ds.list( + self._ds.download_dir, + header=False, + more_prompt=True, + skip_installed=True, + ) + continue + elif user_input.lower() in ("x", "q", ""): + return + elif user_input: + for id in user_input.split(): + try: + self._ds.download(id, prefix=" ") + except (OSError, ValueError) as e: + print(e) + break + + def _simple_interactive_update(self): + while True: + stale_packages = [] + stale = partial = False + for info in sorted(getattr(self._ds, "packages")(), key=str): + if self._ds.status(info) == self._ds.STALE: + stale_packages.append((info.id, info.name)) + + print() + if stale_packages: + print("Will update following packages (o=ok; x=cancel)") + for pid, pname in stale_packages: + name = textwrap.fill( + "-" * 27 + (pname), 75, subsequent_indent=27 * " " + )[27:] + print(" [ ] {} {}".format(pid.ljust(20, "."), name)) + print() + + user_input = input(" Identifier> ") + if user_input.lower() == "o": + for pid, pname in stale_packages: + try: + self._ds.download(pid, prefix=" ") + except (OSError, ValueError) as e: + print(e) + break + elif user_input.lower() in ("x", "q", ""): + return + else: + print("Nothing to update.") + return + + def _simple_interactive_help(self): + print() + print("Commands:") + print( + " d) Download a package or collection u) Update out of date packages" + ) + print(" l) List packages & collections h) Help") + print(" c) View & Modify Configuration q) Quit") + + def _show_config(self): + print() + print("Data Server:") + print(" - URL: <%s>" % self._ds.url) + print(" - %d Package Collections Available" % len(self._ds.collections())) + print(" - %d Individual Packages Available" % len(self._ds.packages())) + print() + print("Local Machine:") + print(" - Data directory: %s" % self._ds.download_dir) + + def _simple_interactive_config(self): + self._show_config() + while True: + print() + self._simple_interactive_menu( + "s) Show Config", "u) Set Server URL", "d) Set Data Dir", "m) Main Menu" + ) + user_input = input("Config> ").strip().lower() + if user_input == "s": + self._show_config() + elif user_input == "d": + new_dl_dir = input(" New Directory> ").strip() + if new_dl_dir in ("", "x", "q", "X", "Q"): + print(" Cancelled!") + elif os.path.isdir(new_dl_dir): + self._ds.download_dir = new_dl_dir + else: + print("Directory %r not found! Create it first." % new_dl_dir) + elif user_input == "u": + new_url = input(" New URL> ").strip() + if new_url in ("", "x", "q", "X", "Q"): + print(" Cancelled!") + else: + if not new_url.startswith(("http://", "https://")): + new_url = "http://" + new_url + try: + self._ds.url = new_url + except Exception as e: + print(f"Error reading <{new_url!r}>:\n {e}") + elif user_input == "m": + break + + +class DownloaderGUI: + """ + Graphical interface for downloading packages from the NLTK data + server. + """ + + # ///////////////////////////////////////////////////////////////// + # Column Configuration + # ///////////////////////////////////////////////////////////////// + + COLUMNS = [ + "", + "Identifier", + "Name", + "Size", + "Status", + "Unzipped Size", + "Copyright", + "Contact", + "License", + "Author", + "Subdir", + "Checksum", + ] + """A list of the names of columns. This controls the order in + which the columns will appear. If this is edited, then + ``_package_to_columns()`` may need to be edited to match.""" + + COLUMN_WEIGHTS = {"": 0, "Name": 5, "Size": 0, "Status": 0} + """A dictionary specifying how columns should be resized when the + table is resized. Columns with weight 0 will not be resized at + all; and columns with high weight will be resized more. + Default weight (for columns not explicitly listed) is 1.""" + + COLUMN_WIDTHS = { + "": 1, + "Identifier": 20, + "Name": 45, + "Size": 10, + "Unzipped Size": 10, + "Status": 12, + } + """A dictionary specifying how wide each column should be, in + characters. The default width (for columns not explicitly + listed) is specified by ``DEFAULT_COLUMN_WIDTH``.""" + + DEFAULT_COLUMN_WIDTH = 30 + """The default width for columns that are not explicitly listed + in ``COLUMN_WIDTHS``.""" + + INITIAL_COLUMNS = ["", "Identifier", "Name", "Size", "Status"] + """The set of columns that should be displayed by default.""" + + # Perform a few import-time sanity checks to make sure that the + # column configuration variables are defined consistently: + for c in COLUMN_WEIGHTS: + assert c in COLUMNS + for c in COLUMN_WIDTHS: + assert c in COLUMNS + for c in INITIAL_COLUMNS: + assert c in COLUMNS + + # ///////////////////////////////////////////////////////////////// + # Color Configuration + # ///////////////////////////////////////////////////////////////// + + _BACKDROP_COLOR = ("#000", "#ccc") + + _ROW_COLOR = { + Downloader.INSTALLED: ("#afa", "#080"), + Downloader.PARTIAL: ("#ffa", "#880"), + Downloader.STALE: ("#faa", "#800"), + Downloader.NOT_INSTALLED: ("#fff", "#888"), + } + + _MARK_COLOR = ("#000", "#ccc") + + # _FRONT_TAB_COLOR = ('#ccf', '#008') + # _BACK_TAB_COLOR = ('#88a', '#448') + _FRONT_TAB_COLOR = ("#fff", "#45c") + _BACK_TAB_COLOR = ("#aaa", "#67a") + + _PROGRESS_COLOR = ("#f00", "#aaa") + + _TAB_FONT = "helvetica -16 bold" + + # ///////////////////////////////////////////////////////////////// + # Constructor + # ///////////////////////////////////////////////////////////////// + + def __init__(self, dataserver, use_threads=True): + self._ds = dataserver + self._use_threads = use_threads + + # For the threaded downloader: + self._download_lock = threading.Lock() + self._download_msg_queue = [] + self._download_abort_queue = [] + self._downloading = False + + # For tkinter after callbacks: + self._afterid = {} + + # A message log. + self._log_messages = [] + self._log_indent = 0 + self._log("NLTK Downloader Started!") + + # Create the main window. + top = self.top = Tk() + top.geometry("+50+50") + top.title("NLTK Downloader") + top.configure(background=self._BACKDROP_COLOR[1]) + + # Set up some bindings now, in case anything goes wrong. + top.bind("", self.destroy) + top.bind("", self.destroy) + self._destroyed = False + + self._column_vars = {} + + # Initialize the GUI. + self._init_widgets() + self._init_menu() + try: + self._fill_table() + except HTTPError as e: + showerror("Error reading from server", e) + except URLError as e: + showerror("Error connecting to server", e.reason) + + self._show_info() + self._select_columns() + self._table.select(0) + + # Make sure we get notified when we're destroyed, so we can + # cancel any download in progress. + self._table.bind("", self._destroy) + + def _log(self, msg): + self._log_messages.append( + "{} {}{}".format(time.ctime(), " | " * self._log_indent, msg) + ) + + # ///////////////////////////////////////////////////////////////// + # Internals + # ///////////////////////////////////////////////////////////////// + + def _init_widgets(self): + # Create the top-level frame structures + f1 = Frame(self.top, relief="raised", border=2, padx=8, pady=0) + f1.pack(sid="top", expand=True, fill="both") + f1.grid_rowconfigure(2, weight=1) + f1.grid_columnconfigure(0, weight=1) + Frame(f1, height=8).grid(column=0, row=0) # spacer + tabframe = Frame(f1) + tabframe.grid(column=0, row=1, sticky="news") + tableframe = Frame(f1) + tableframe.grid(column=0, row=2, sticky="news") + buttonframe = Frame(f1) + buttonframe.grid(column=0, row=3, sticky="news") + Frame(f1, height=8).grid(column=0, row=4) # spacer + infoframe = Frame(f1) + infoframe.grid(column=0, row=5, sticky="news") + Frame(f1, height=8).grid(column=0, row=6) # spacer + progressframe = Frame( + self.top, padx=3, pady=3, background=self._BACKDROP_COLOR[1] + ) + progressframe.pack(side="bottom", fill="x") + self.top["border"] = 0 + self.top["highlightthickness"] = 0 + + # Create the tabs + self._tab_names = ["Collections", "Corpora", "Models", "All Packages"] + self._tabs = {} + for i, tab in enumerate(self._tab_names): + label = Label(tabframe, text=tab, font=self._TAB_FONT) + label.pack(side="left", padx=((i + 1) % 2) * 10) + label.bind("", self._select_tab) + self._tabs[tab.lower()] = label + + # Create the table. + column_weights = [self.COLUMN_WEIGHTS.get(column, 1) for column in self.COLUMNS] + self._table = Table( + tableframe, + self.COLUMNS, + column_weights=column_weights, + highlightthickness=0, + listbox_height=16, + reprfunc=self._table_reprfunc, + ) + self._table.columnconfig(0, foreground=self._MARK_COLOR[0]) # marked + for i, column in enumerate(self.COLUMNS): + width = self.COLUMN_WIDTHS.get(column, self.DEFAULT_COLUMN_WIDTH) + self._table.columnconfig(i, width=width) + self._table.pack(expand=True, fill="both") + self._table.focus() + self._table.bind_to_listboxes("", self._download) + self._table.bind("", self._table_mark) + self._table.bind("", self._download) + self._table.bind("", self._prev_tab) + self._table.bind("", self._next_tab) + self._table.bind("", self._mark_all) + + # Create entry boxes for URL & download_dir + infoframe.grid_columnconfigure(1, weight=1) + + info = [ + ("url", "Server Index:", self._set_url), + ("download_dir", "Download Directory:", self._set_download_dir), + ] + self._info = {} + for (i, (key, label, callback)) in enumerate(info): + Label(infoframe, text=label).grid(column=0, row=i, sticky="e") + entry = Entry( + infoframe, + font="courier", + relief="groove", + disabledforeground="#007aff", + foreground="#007aff", + ) + self._info[key] = (entry, callback) + entry.bind("", self._info_save) + entry.bind("", lambda e, key=key: self._info_edit(key)) + entry.grid(column=1, row=i, sticky="ew") + + # If the user edits url or download_dir, and then clicks outside + # the entry box, then save their results. + self.top.bind("", self._info_save) + + # Create Download & Refresh buttons. + self._download_button = Button( + buttonframe, text="Download", command=self._download, width=8 + ) + self._download_button.pack(side="left") + self._refresh_button = Button( + buttonframe, text="Refresh", command=self._refresh, width=8 + ) + self._refresh_button.pack(side="right") + + # Create Progress bar + self._progresslabel = Label( + progressframe, + text="", + foreground=self._BACKDROP_COLOR[0], + background=self._BACKDROP_COLOR[1], + ) + self._progressbar = Canvas( + progressframe, + width=200, + height=16, + background=self._PROGRESS_COLOR[1], + relief="sunken", + border=1, + ) + self._init_progressbar() + self._progressbar.pack(side="right") + self._progresslabel.pack(side="left") + + def _init_menu(self): + menubar = Menu(self.top) + + filemenu = Menu(menubar, tearoff=0) + filemenu.add_command( + label="Download", underline=0, command=self._download, accelerator="Return" + ) + filemenu.add_separator() + filemenu.add_command( + label="Change Server Index", + underline=7, + command=lambda: self._info_edit("url"), + ) + filemenu.add_command( + label="Change Download Directory", + underline=0, + command=lambda: self._info_edit("download_dir"), + ) + filemenu.add_separator() + filemenu.add_command(label="Show Log", underline=5, command=self._show_log) + filemenu.add_separator() + filemenu.add_command( + label="Exit", underline=1, command=self.destroy, accelerator="Ctrl-x" + ) + menubar.add_cascade(label="File", underline=0, menu=filemenu) + + # Create a menu to control which columns of the table are + # shown. n.b.: we never hide the first two columns (mark and + # identifier). + viewmenu = Menu(menubar, tearoff=0) + for column in self._table.column_names[2:]: + var = IntVar(self.top) + assert column not in self._column_vars + self._column_vars[column] = var + if column in self.INITIAL_COLUMNS: + var.set(1) + viewmenu.add_checkbutton( + label=column, underline=0, variable=var, command=self._select_columns + ) + menubar.add_cascade(label="View", underline=0, menu=viewmenu) + + # Create a sort menu + # [xx] this should be selectbuttons; and it should include + # reversed sorts as options. + sortmenu = Menu(menubar, tearoff=0) + for column in self._table.column_names[1:]: + sortmenu.add_command( + label="Sort by %s" % column, + command=(lambda c=column: self._table.sort_by(c, "ascending")), + ) + sortmenu.add_separator() + # sortmenu.add_command(label='Descending Sort:') + for column in self._table.column_names[1:]: + sortmenu.add_command( + label="Reverse sort by %s" % column, + command=(lambda c=column: self._table.sort_by(c, "descending")), + ) + menubar.add_cascade(label="Sort", underline=0, menu=sortmenu) + + helpmenu = Menu(menubar, tearoff=0) + helpmenu.add_command(label="About", underline=0, command=self.about) + helpmenu.add_command( + label="Instructions", underline=0, command=self.help, accelerator="F1" + ) + menubar.add_cascade(label="Help", underline=0, menu=helpmenu) + self.top.bind("", self.help) + + self.top.config(menu=menubar) + + def _select_columns(self): + for (column, var) in self._column_vars.items(): + if var.get(): + self._table.show_column(column) + else: + self._table.hide_column(column) + + def _refresh(self): + self._ds.clear_status_cache() + try: + self._fill_table() + except HTTPError as e: + showerror("Error reading from server", e) + except URLError as e: + showerror("Error connecting to server", e.reason) + self._table.select(0) + + def _info_edit(self, info_key): + self._info_save() # just in case. + (entry, callback) = self._info[info_key] + entry["state"] = "normal" + entry["relief"] = "sunken" + entry.focus() + + def _info_save(self, e=None): + focus = self._table + for entry, callback in self._info.values(): + if entry["state"] == "disabled": + continue + if e is not None and e.widget is entry and e.keysym != "Return": + focus = entry + else: + entry["state"] = "disabled" + entry["relief"] = "groove" + callback(entry.get()) + focus.focus() + + def _table_reprfunc(self, row, col, val): + if self._table.column_names[col].endswith("Size"): + if isinstance(val, str): + return " %s" % val + elif val < 1024**2: + return " %.1f KB" % (val / 1024.0**1) + elif val < 1024**3: + return " %.1f MB" % (val / 1024.0**2) + else: + return " %.1f GB" % (val / 1024.0**3) + + if col in (0, ""): + return str(val) + else: + return " %s" % val + + def _set_url(self, url): + if url == self._ds.url: + return + try: + self._ds.url = url + self._fill_table() + except OSError as e: + showerror("Error Setting Server Index", str(e)) + self._show_info() + + def _set_download_dir(self, download_dir): + if self._ds.download_dir == download_dir: + return + # check if the dir exists, and if not, ask if we should create it? + + # Clear our status cache, & re-check what's installed + self._ds.download_dir = download_dir + try: + self._fill_table() + except HTTPError as e: + showerror("Error reading from server", e) + except URLError as e: + showerror("Error connecting to server", e.reason) + self._show_info() + + def _show_info(self): + print("showing info", self._ds.url) + for entry, cb in self._info.values(): + entry["state"] = "normal" + entry.delete(0, "end") + self._info["url"][0].insert(0, self._ds.url) + self._info["download_dir"][0].insert(0, self._ds.download_dir) + for entry, cb in self._info.values(): + entry["state"] = "disabled" + + def _prev_tab(self, *e): + for i, tab in enumerate(self._tab_names): + if tab.lower() == self._tab and i > 0: + self._tab = self._tab_names[i - 1].lower() + try: + return self._fill_table() + except HTTPError as e: + showerror("Error reading from server", e) + except URLError as e: + showerror("Error connecting to server", e.reason) + + def _next_tab(self, *e): + for i, tab in enumerate(self._tab_names): + if tab.lower() == self._tab and i < (len(self._tabs) - 1): + self._tab = self._tab_names[i + 1].lower() + try: + return self._fill_table() + except HTTPError as e: + showerror("Error reading from server", e) + except URLError as e: + showerror("Error connecting to server", e.reason) + + def _select_tab(self, event): + self._tab = event.widget["text"].lower() + try: + self._fill_table() + except HTTPError as e: + showerror("Error reading from server", e) + except URLError as e: + showerror("Error connecting to server", e.reason) + + _tab = "collections" + # _tab = 'corpora' + _rows = None + + def _fill_table(self): + selected_row = self._table.selected_row() + self._table.clear() + if self._tab == "all packages": + items = self._ds.packages() + elif self._tab == "corpora": + items = self._ds.corpora() + elif self._tab == "models": + items = self._ds.models() + elif self._tab == "collections": + items = self._ds.collections() + else: + assert 0, "bad tab value %r" % self._tab + rows = [self._package_to_columns(item) for item in items] + self._table.extend(rows) + + # Highlight the active tab. + for tab, label in self._tabs.items(): + if tab == self._tab: + label.configure( + foreground=self._FRONT_TAB_COLOR[0], + background=self._FRONT_TAB_COLOR[1], + ) + else: + label.configure( + foreground=self._BACK_TAB_COLOR[0], + background=self._BACK_TAB_COLOR[1], + ) + + self._table.sort_by("Identifier", order="ascending") + self._color_table() + self._table.select(selected_row) + + # This is a hack, because the scrollbar isn't updating its + # position right -- I'm not sure what the underlying cause is + # though. (This is on OS X w/ python 2.5) The length of + # delay that's necessary seems to depend on how fast the + # comptuer is. :-/ + self.top.after(150, self._table._scrollbar.set, *self._table._mlb.yview()) + self.top.after(300, self._table._scrollbar.set, *self._table._mlb.yview()) + + def _update_table_status(self): + for row_num in range(len(self._table)): + status = self._ds.status(self._table[row_num, "Identifier"]) + self._table[row_num, "Status"] = status + self._color_table() + + def _download(self, *e): + # If we're using threads, then delegate to the threaded + # downloader instead. + if self._use_threads: + return self._download_threaded(*e) + + marked = [ + self._table[row, "Identifier"] + for row in range(len(self._table)) + if self._table[row, 0] != "" + ] + selection = self._table.selected_row() + if not marked and selection is not None: + marked = [self._table[selection, "Identifier"]] + + download_iter = self._ds.incr_download(marked, self._ds.download_dir) + self._log_indent = 0 + self._download_cb(download_iter, marked) + + _DL_DELAY = 10 + + def _download_cb(self, download_iter, ids): + try: + msg = next(download_iter) + except StopIteration: + # self._fill_table(sort=False) + self._update_table_status() + afterid = self.top.after(10, self._show_progress, 0) + self._afterid["_download_cb"] = afterid + return + + def show(s): + self._progresslabel["text"] = s + self._log(s) + + if isinstance(msg, ProgressMessage): + self._show_progress(msg.progress) + elif isinstance(msg, ErrorMessage): + show(msg.message) + if msg.package is not None: + self._select(msg.package.id) + self._show_progress(None) + return # halt progress. + elif isinstance(msg, StartCollectionMessage): + show("Downloading collection %s" % msg.collection.id) + self._log_indent += 1 + elif isinstance(msg, StartPackageMessage): + show("Downloading package %s" % msg.package.id) + elif isinstance(msg, UpToDateMessage): + show("Package %s is up-to-date!" % msg.package.id) + # elif isinstance(msg, StaleMessage): + # show('Package %s is out-of-date or corrupt' % msg.package.id) + elif isinstance(msg, FinishDownloadMessage): + show("Finished downloading %r." % msg.package.id) + elif isinstance(msg, StartUnzipMessage): + show("Unzipping %s" % msg.package.filename) + elif isinstance(msg, FinishCollectionMessage): + self._log_indent -= 1 + show("Finished downloading collection %r." % msg.collection.id) + self._clear_mark(msg.collection.id) + elif isinstance(msg, FinishPackageMessage): + self._clear_mark(msg.package.id) + afterid = self.top.after(self._DL_DELAY, self._download_cb, download_iter, ids) + self._afterid["_download_cb"] = afterid + + def _select(self, id): + for row in range(len(self._table)): + if self._table[row, "Identifier"] == id: + self._table.select(row) + return + + def _color_table(self): + # Color rows according to status. + for row in range(len(self._table)): + bg, sbg = self._ROW_COLOR[self._table[row, "Status"]] + fg, sfg = ("black", "white") + self._table.rowconfig( + row, + foreground=fg, + selectforeground=sfg, + background=bg, + selectbackground=sbg, + ) + # Color the marked column + self._table.itemconfigure( + row, 0, foreground=self._MARK_COLOR[0], background=self._MARK_COLOR[1] + ) + + def _clear_mark(self, id): + for row in range(len(self._table)): + if self._table[row, "Identifier"] == id: + self._table[row, 0] = "" + + def _mark_all(self, *e): + for row in range(len(self._table)): + self._table[row, 0] = "X" + + def _table_mark(self, *e): + selection = self._table.selected_row() + if selection >= 0: + if self._table[selection][0] != "": + self._table[selection, 0] = "" + else: + self._table[selection, 0] = "X" + self._table.select(delta=1) + + def _show_log(self): + text = "\n".join(self._log_messages) + ShowText(self.top, "NLTK Downloader Log", text) + + def _package_to_columns(self, pkg): + """ + Given a package, return a list of values describing that + package, one for each column in ``self.COLUMNS``. + """ + row = [] + for column_index, column_name in enumerate(self.COLUMNS): + if column_index == 0: # Mark: + row.append("") + elif column_name == "Identifier": + row.append(pkg.id) + elif column_name == "Status": + row.append(self._ds.status(pkg)) + else: + attr = column_name.lower().replace(" ", "_") + row.append(getattr(pkg, attr, "n/a")) + return row + + # ///////////////////////////////////////////////////////////////// + # External Interface + # ///////////////////////////////////////////////////////////////// + + def destroy(self, *e): + if self._destroyed: + return + self.top.destroy() + self._destroyed = True + + def _destroy(self, *e): + if self.top is not None: + for afterid in self._afterid.values(): + self.top.after_cancel(afterid) + + # Abort any download in progress. + if self._downloading and self._use_threads: + self._abort_download() + + # Make sure the garbage collector destroys these now; + # otherwise, they may get destroyed when we're not in the main + # thread, which would make Tkinter unhappy. + self._column_vars.clear() + + def mainloop(self, *args, **kwargs): + self.top.mainloop(*args, **kwargs) + + # ///////////////////////////////////////////////////////////////// + # HELP + # ///////////////////////////////////////////////////////////////// + + HELP = textwrap.dedent( + """\ + This tool can be used to download a variety of corpora and models + that can be used with NLTK. Each corpus or model is distributed + in a single zip file, known as a \"package file.\" You can + download packages individually, or you can download pre-defined + collections of packages. + + When you download a package, it will be saved to the \"download + directory.\" A default download directory is chosen when you run + + the downloader; but you may also select a different download + directory. On Windows, the default download directory is + + + \"package.\" + + The NLTK downloader can be used to download a variety of corpora, + models, and other data packages. + + Keyboard shortcuts:: + [return]\t Download + [up]\t Select previous package + [down]\t Select next package + [left]\t Select previous tab + [right]\t Select next tab + """ + ) + + def help(self, *e): + # The default font's not very legible; try using 'fixed' instead. + try: + ShowText( + self.top, + "Help: NLTK Downloader", + self.HELP.strip(), + width=75, + font="fixed", + ) + except: + ShowText(self.top, "Help: NLTK Downloader", self.HELP.strip(), width=75) + + def about(self, *e): + ABOUT = "NLTK Downloader\n" + "Written by Edward Loper" + TITLE = "About: NLTK Downloader" + try: + from tkinter.messagebox import Message + + Message(message=ABOUT, title=TITLE).show() + except ImportError: + ShowText(self.top, TITLE, ABOUT) + + # ///////////////////////////////////////////////////////////////// + # Progress Bar + # ///////////////////////////////////////////////////////////////// + + _gradient_width = 5 + + def _init_progressbar(self): + c = self._progressbar + width, height = int(c["width"]), int(c["height"]) + for i in range(0, (int(c["width"]) * 2) // self._gradient_width): + c.create_line( + i * self._gradient_width + 20, + -20, + i * self._gradient_width - height - 20, + height + 20, + width=self._gradient_width, + fill="#%02x0000" % (80 + abs(i % 6 - 3) * 12), + ) + c.addtag_all("gradient") + c.itemconfig("gradient", state="hidden") + + # This is used to display progress + c.addtag_withtag( + "redbox", c.create_rectangle(0, 0, 0, 0, fill=self._PROGRESS_COLOR[0]) + ) + + def _show_progress(self, percent): + c = self._progressbar + if percent is None: + c.coords("redbox", 0, 0, 0, 0) + c.itemconfig("gradient", state="hidden") + else: + width, height = int(c["width"]), int(c["height"]) + x = percent * int(width) // 100 + 1 + c.coords("redbox", 0, 0, x, height + 1) + + def _progress_alive(self): + c = self._progressbar + if not self._downloading: + c.itemconfig("gradient", state="hidden") + else: + c.itemconfig("gradient", state="normal") + x1, y1, x2, y2 = c.bbox("gradient") + if x1 <= -100: + c.move("gradient", (self._gradient_width * 6) - 4, 0) + else: + c.move("gradient", -4, 0) + afterid = self.top.after(200, self._progress_alive) + self._afterid["_progress_alive"] = afterid + + # ///////////////////////////////////////////////////////////////// + # Threaded downloader + # ///////////////////////////////////////////////////////////////// + + def _download_threaded(self, *e): + # If the user tries to start a new download while we're already + # downloading something, then abort the current download instead. + if self._downloading: + self._abort_download() + return + + # Change the 'download' button to an 'abort' button. + self._download_button["text"] = "Cancel" + + marked = [ + self._table[row, "Identifier"] + for row in range(len(self._table)) + if self._table[row, 0] != "" + ] + selection = self._table.selected_row() + if not marked and selection is not None: + marked = [self._table[selection, "Identifier"]] + + # Create a new data server object for the download operation, + # just in case the user modifies our data server during the + # download (e.g., clicking 'refresh' or editing the index url). + ds = Downloader(self._ds.url, self._ds.download_dir) + + # Start downloading in a separate thread. + assert self._download_msg_queue == [] + assert self._download_abort_queue == [] + self._DownloadThread( + ds, + marked, + self._download_lock, + self._download_msg_queue, + self._download_abort_queue, + ).start() + + # Monitor the download message queue & display its progress. + self._log_indent = 0 + self._downloading = True + self._monitor_message_queue() + + # Display an indication that we're still alive and well by + # cycling the progress bar. + self._progress_alive() + + def _abort_download(self): + if self._downloading: + self._download_lock.acquire() + self._download_abort_queue.append("abort") + self._download_lock.release() + + class _DownloadThread(threading.Thread): + def __init__(self, data_server, items, lock, message_queue, abort): + self.data_server = data_server + self.items = items + self.lock = lock + self.message_queue = message_queue + self.abort = abort + threading.Thread.__init__(self) + + def run(self): + for msg in self.data_server.incr_download(self.items): + self.lock.acquire() + self.message_queue.append(msg) + # Check if we've been told to kill ourselves: + if self.abort: + self.message_queue.append("aborted") + self.lock.release() + return + self.lock.release() + self.lock.acquire() + self.message_queue.append("finished") + self.lock.release() + + _MONITOR_QUEUE_DELAY = 100 + + def _monitor_message_queue(self): + def show(s): + self._progresslabel["text"] = s + self._log(s) + + # Try to acquire the lock; if it's busy, then just try again later. + if not self._download_lock.acquire(): + return + for msg in self._download_msg_queue: + + # Done downloading? + if msg == "finished" or msg == "aborted": + # self._fill_table(sort=False) + self._update_table_status() + self._downloading = False + self._download_button["text"] = "Download" + del self._download_msg_queue[:] + del self._download_abort_queue[:] + self._download_lock.release() + if msg == "aborted": + show("Download aborted!") + self._show_progress(None) + else: + afterid = self.top.after(100, self._show_progress, None) + self._afterid["_monitor_message_queue"] = afterid + return + + # All other messages + elif isinstance(msg, ProgressMessage): + self._show_progress(msg.progress) + elif isinstance(msg, ErrorMessage): + show(msg.message) + if msg.package is not None: + self._select(msg.package.id) + self._show_progress(None) + self._downloading = False + return # halt progress. + elif isinstance(msg, StartCollectionMessage): + show("Downloading collection %r" % msg.collection.id) + self._log_indent += 1 + elif isinstance(msg, StartPackageMessage): + self._ds.clear_status_cache(msg.package.id) + show("Downloading package %r" % msg.package.id) + elif isinstance(msg, UpToDateMessage): + show("Package %s is up-to-date!" % msg.package.id) + # elif isinstance(msg, StaleMessage): + # show('Package %s is out-of-date or corrupt; updating it' % + # msg.package.id) + elif isinstance(msg, FinishDownloadMessage): + show("Finished downloading %r." % msg.package.id) + elif isinstance(msg, StartUnzipMessage): + show("Unzipping %s" % msg.package.filename) + elif isinstance(msg, FinishUnzipMessage): + show("Finished installing %s" % msg.package.id) + elif isinstance(msg, FinishCollectionMessage): + self._log_indent -= 1 + show("Finished downloading collection %r." % msg.collection.id) + self._clear_mark(msg.collection.id) + elif isinstance(msg, FinishPackageMessage): + self._update_table_status() + self._clear_mark(msg.package.id) + + # Let the user know when we're aborting a download (but + # waiting for a good point to abort it, so we don't end up + # with a partially unzipped package or anything like that). + if self._download_abort_queue: + self._progresslabel["text"] = "Aborting download..." + + # Clear the message queue and then release the lock + del self._download_msg_queue[:] + self._download_lock.release() + + # Check the queue again after MONITOR_QUEUE_DELAY msec. + afterid = self.top.after(self._MONITOR_QUEUE_DELAY, self._monitor_message_queue) + self._afterid["_monitor_message_queue"] = afterid + + +###################################################################### +# Helper Functions +###################################################################### +# [xx] It may make sense to move these to nltk.internals. + + +def md5_hexdigest(file): + """ + Calculate and return the MD5 checksum for a given file. + ``file`` may either be a filename or an open stream. + """ + if isinstance(file, str): + with open(file, "rb") as infile: + return _md5_hexdigest(infile) + return _md5_hexdigest(file) + + +def _md5_hexdigest(fp): + md5_digest = md5() + while True: + block = fp.read(1024 * 16) # 16k blocks + if not block: + break + md5_digest.update(block) + return md5_digest.hexdigest() + + +# change this to periodically yield progress messages? +# [xx] get rid of topdir parameter -- we should be checking +# this when we build the index, anyway. +def unzip(filename, root, verbose=True): + """ + Extract the contents of the zip file ``filename`` into the + directory ``root``. + """ + for message in _unzip_iter(filename, root, verbose): + if isinstance(message, ErrorMessage): + raise Exception(message) + + +def _unzip_iter(filename, root, verbose=True): + if verbose: + sys.stdout.write("Unzipping %s" % os.path.split(filename)[1]) + sys.stdout.flush() + + try: + zf = zipfile.ZipFile(filename) + except zipfile.error as e: + yield ErrorMessage(filename, "Error with downloaded zip file") + return + except Exception as e: + yield ErrorMessage(filename, e) + return + + zf.extractall(root) + + if verbose: + print() + + +###################################################################### +# Index Builder +###################################################################### +# This may move to a different file sometime. + + +def build_index(root, base_url): + """ + Create a new data.xml index file, by combining the xml description + files for various packages and collections. ``root`` should be the + path to a directory containing the package xml and zip files; and + the collection xml files. The ``root`` directory is expected to + have the following subdirectories:: + + root/ + packages/ .................. subdirectory for packages + corpora/ ................. zip & xml files for corpora + grammars/ ................ zip & xml files for grammars + taggers/ ................. zip & xml files for taggers + tokenizers/ .............. zip & xml files for tokenizers + etc. + collections/ ............... xml files for collections + + For each package, there should be two files: ``package.zip`` + (where *package* is the package name) + which contains the package itself as a compressed zip file; and + ``package.xml``, which is an xml description of the package. The + zipfile ``package.zip`` should expand to a single subdirectory + named ``package/``. The base filename ``package`` must match + the identifier given in the package's xml file. + + For each collection, there should be a single file ``collection.zip`` + describing the collection, where *collection* is the name of the collection. + + All identifiers (for both packages and collections) must be unique. + """ + # Find all packages. + packages = [] + for pkg_xml, zf, subdir in _find_packages(os.path.join(root, "packages")): + zipstat = os.stat(zf.filename) + url = f"{base_url}/{subdir}/{os.path.split(zf.filename)[1]}" + unzipped_size = sum(zf_info.file_size for zf_info in zf.infolist()) + + # Fill in several fields of the package xml with calculated values. + pkg_xml.set("unzipped_size", "%s" % unzipped_size) + pkg_xml.set("size", "%s" % zipstat.st_size) + pkg_xml.set("checksum", "%s" % md5_hexdigest(zf.filename)) + pkg_xml.set("subdir", subdir) + # pkg_xml.set('svn_revision', _svn_revision(zf.filename)) + if not pkg_xml.get("url"): + pkg_xml.set("url", url) + + # Record the package. + packages.append(pkg_xml) + + # Find all collections + collections = list(_find_collections(os.path.join(root, "collections"))) + + # Check that all UIDs are unique + uids = set() + for item in packages + collections: + if item.get("id") in uids: + raise ValueError("Duplicate UID: %s" % item.get("id")) + uids.add(item.get("id")) + + # Put it all together + top_elt = ElementTree.Element("nltk_data") + top_elt.append(ElementTree.Element("packages")) + top_elt[0].extend(sorted(packages, key=lambda package: package.get("id"))) + top_elt.append(ElementTree.Element("collections")) + top_elt[1].extend(sorted(collections, key=lambda collection: collection.get("id"))) + + _indent_xml(top_elt) + return top_elt + + +def _indent_xml(xml, prefix=""): + """ + Helper for ``build_index()``: Given an XML ``ElementTree``, modify it + (and its descendents) ``text`` and ``tail`` attributes to generate + an indented tree, where each nested element is indented by 2 + spaces with respect to its parent. + """ + if len(xml) > 0: + xml.text = (xml.text or "").strip() + "\n" + prefix + " " + for child in xml: + _indent_xml(child, prefix + " ") + for child in xml[:-1]: + child.tail = (child.tail or "").strip() + "\n" + prefix + " " + xml[-1].tail = (xml[-1].tail or "").strip() + "\n" + prefix + + +def _check_package(pkg_xml, zipfilename, zf): + """ + Helper for ``build_index()``: Perform some checks to make sure that + the given package is consistent. + """ + # The filename must patch the id given in the XML file. + uid = os.path.splitext(os.path.split(zipfilename)[1])[0] + if pkg_xml.get("id") != uid: + raise ValueError( + "package identifier mismatch ({} vs {})".format(pkg_xml.get("id"), uid) + ) + + # Zip file must expand to a subdir whose name matches uid. + if sum((name != uid and not name.startswith(uid + "/")) for name in zf.namelist()): + raise ValueError( + "Zipfile %s.zip does not expand to a single " + "subdirectory %s/" % (uid, uid) + ) + + +# update for git? +def _svn_revision(filename): + """ + Helper for ``build_index()``: Calculate the subversion revision + number for a given file (by using ``subprocess`` to run ``svn``). + """ + p = subprocess.Popen( + ["svn", "status", "-v", filename], + stdout=subprocess.PIPE, + stderr=subprocess.PIPE, + ) + (stdout, stderr) = p.communicate() + if p.returncode != 0 or stderr or not stdout: + raise ValueError( + "Error determining svn_revision for %s: %s" + % (os.path.split(filename)[1], textwrap.fill(stderr)) + ) + return stdout.split()[2] + + +def _find_collections(root): + """ + Helper for ``build_index()``: Yield a list of ElementTree.Element + objects, each holding the xml for a single package collection. + """ + for dirname, _subdirs, files in os.walk(root): + for filename in files: + if filename.endswith(".xml"): + xmlfile = os.path.join(dirname, filename) + yield ElementTree.parse(xmlfile).getroot() + + +def _find_packages(root): + """ + Helper for ``build_index()``: Yield a list of tuples + ``(pkg_xml, zf, subdir)``, where: + - ``pkg_xml`` is an ``ElementTree.Element`` holding the xml for a + package + - ``zf`` is a ``zipfile.ZipFile`` for the package's contents. + - ``subdir`` is the subdirectory (relative to ``root``) where + the package was found (e.g. 'corpora' or 'grammars'). + """ + from nltk.corpus.reader.util import _path_from + + # Find all packages. + packages = [] + for dirname, subdirs, files in os.walk(root): + relpath = "/".join(_path_from(root, dirname)) + for filename in files: + if filename.endswith(".xml"): + xmlfilename = os.path.join(dirname, filename) + zipfilename = xmlfilename[:-4] + ".zip" + try: + zf = zipfile.ZipFile(zipfilename) + except Exception as e: + raise ValueError(f"Error reading file {zipfilename!r}!\n{e}") from e + try: + pkg_xml = ElementTree.parse(xmlfilename).getroot() + except Exception as e: + raise ValueError(f"Error reading file {xmlfilename!r}!\n{e}") from e + + # Check that the UID matches the filename + uid = os.path.split(xmlfilename[:-4])[1] + if pkg_xml.get("id") != uid: + raise ValueError( + "package identifier mismatch (%s " + "vs %s)" % (pkg_xml.get("id"), uid) + ) + + # Check that the zipfile expands to a subdir whose + # name matches the uid. + if sum( + (name != uid and not name.startswith(uid + "/")) + for name in zf.namelist() + ): + raise ValueError( + "Zipfile %s.zip does not expand to a " + "single subdirectory %s/" % (uid, uid) + ) + + yield pkg_xml, zf, relpath + + elif filename.endswith(".zip"): + # Warn user in case a .xml does not exist for a .zip + resourcename = os.path.splitext(filename)[0] + xmlfilename = os.path.join(dirname, resourcename + ".xml") + if not os.path.exists(xmlfilename): + warnings.warn( + f"{filename} exists, but {resourcename + '.xml'} cannot be found! " + f"This could mean that {resourcename} can not be downloaded.", + stacklevel=2, + ) + + # Don't recurse into svn subdirectories: + try: + subdirs.remove(".svn") + except ValueError: + pass + + +###################################################################### +# Main: +###################################################################### + +# There should be a command-line interface + +# Aliases +_downloader = Downloader() +download = _downloader.download + + +def download_shell(): + DownloaderShell(_downloader).run() + + +def download_gui(): + DownloaderGUI(_downloader).mainloop() + + +def update(): + _downloader.update() + + +if __name__ == "__main__": + from optparse import OptionParser + + parser = OptionParser() + parser.add_option( + "-d", + "--dir", + dest="dir", + help="download package to directory DIR", + metavar="DIR", + ) + parser.add_option( + "-q", + "--quiet", + dest="quiet", + action="store_true", + default=False, + help="work quietly", + ) + parser.add_option( + "-f", + "--force", + dest="force", + action="store_true", + default=False, + help="download even if already installed", + ) + parser.add_option( + "-e", + "--exit-on-error", + dest="halt_on_error", + action="store_true", + default=False, + help="exit if an error occurs", + ) + parser.add_option( + "-u", + "--url", + dest="server_index_url", + default=os.environ.get("NLTK_DOWNLOAD_URL"), + help="download server index url", + ) + + (options, args) = parser.parse_args() + + downloader = Downloader(server_index_url=options.server_index_url) + + if args: + for pkg_id in args: + rv = downloader.download( + info_or_id=pkg_id, + download_dir=options.dir, + quiet=options.quiet, + force=options.force, + halt_on_error=options.halt_on_error, + ) + if rv == False and options.halt_on_error: + break + else: + downloader.download( + download_dir=options.dir, + quiet=options.quiet, + force=options.force, + halt_on_error=options.halt_on_error, + ) diff --git a/llmeval-env/lib/python3.10/site-packages/nltk/featstruct.py b/llmeval-env/lib/python3.10/site-packages/nltk/featstruct.py new file mode 100644 index 0000000000000000000000000000000000000000..5684f06f51e76070ca6e606722aa1583332429e3 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/nltk/featstruct.py @@ -0,0 +1,2779 @@ +# Natural Language Toolkit: Feature Structures +# +# Copyright (C) 2001-2023 NLTK Project +# Author: Edward Loper , +# Rob Speer, +# Steven Bird +# URL: +# For license information, see LICENSE.TXT + +""" +Basic data classes for representing feature structures, and for +performing basic operations on those feature structures. A feature +structure is a mapping from feature identifiers to feature values, +where each feature value is either a basic value (such as a string or +an integer), or a nested feature structure. There are two types of +feature structure, implemented by two subclasses of ``FeatStruct``: + + - feature dictionaries, implemented by ``FeatDict``, act like + Python dictionaries. Feature identifiers may be strings or + instances of the ``Feature`` class. + - feature lists, implemented by ``FeatList``, act like Python + lists. Feature identifiers are integers. + +Feature structures are typically used to represent partial information +about objects. A feature identifier that is not mapped to a value +stands for a feature whose value is unknown (*not* a feature without +a value). Two feature structures that represent (potentially +overlapping) information about the same object can be combined by +unification. When two inconsistent feature structures are unified, +the unification fails and returns None. + +Features can be specified using "feature paths", or tuples of feature +identifiers that specify path through the nested feature structures to +a value. Feature structures may contain reentrant feature values. A +"reentrant feature value" is a single feature value that can be +accessed via multiple feature paths. Unification preserves the +reentrance relations imposed by both of the unified feature +structures. In the feature structure resulting from unification, any +modifications to a reentrant feature value will be visible using any +of its feature paths. + +Feature structure variables are encoded using the ``nltk.sem.Variable`` +class. The variables' values are tracked using a bindings +dictionary, which maps variables to their values. When two feature +structures are unified, a fresh bindings dictionary is created to +track their values; and before unification completes, all bound +variables are replaced by their values. Thus, the bindings +dictionaries are usually strictly internal to the unification process. +However, it is possible to track the bindings of variables if you +choose to, by supplying your own initial bindings dictionary to the +``unify()`` function. + +When unbound variables are unified with one another, they become +aliased. This is encoded by binding one variable to the other. + +Lightweight Feature Structures +============================== +Many of the functions defined by ``nltk.featstruct`` can be applied +directly to simple Python dictionaries and lists, rather than to +full-fledged ``FeatDict`` and ``FeatList`` objects. In other words, +Python ``dicts`` and ``lists`` can be used as "light-weight" feature +structures. + + >>> from nltk.featstruct import unify + >>> unify(dict(x=1, y=dict()), dict(a='a', y=dict(b='b'))) # doctest: +SKIP + {'y': {'b': 'b'}, 'x': 1, 'a': 'a'} + +However, you should keep in mind the following caveats: + + - Python dictionaries & lists ignore reentrance when checking for + equality between values. But two FeatStructs with different + reentrances are considered nonequal, even if all their base + values are equal. + + - FeatStructs can be easily frozen, allowing them to be used as + keys in hash tables. Python dictionaries and lists can not. + + - FeatStructs display reentrance in their string representations; + Python dictionaries and lists do not. + + - FeatStructs may *not* be mixed with Python dictionaries and lists + (e.g., when performing unification). + + - FeatStructs provide a number of useful methods, such as ``walk()`` + and ``cyclic()``, which are not available for Python dicts and lists. + +In general, if your feature structures will contain any reentrances, +or if you plan to use them as dictionary keys, it is strongly +recommended that you use full-fledged ``FeatStruct`` objects. +""" + +import copy +import re +from functools import total_ordering + +from nltk.internals import raise_unorderable_types, read_str +from nltk.sem.logic import ( + Expression, + LogicalExpressionException, + LogicParser, + SubstituteBindingsI, + Variable, +) + +###################################################################### +# Feature Structure +###################################################################### + + +@total_ordering +class FeatStruct(SubstituteBindingsI): + """ + A mapping from feature identifiers to feature values, where each + feature value is either a basic value (such as a string or an + integer), or a nested feature structure. There are two types of + feature structure: + + - feature dictionaries, implemented by ``FeatDict``, act like + Python dictionaries. Feature identifiers may be strings or + instances of the ``Feature`` class. + - feature lists, implemented by ``FeatList``, act like Python + lists. Feature identifiers are integers. + + Feature structures may be indexed using either simple feature + identifiers or 'feature paths.' A feature path is a sequence + of feature identifiers that stand for a corresponding sequence of + indexing operations. In particular, ``fstruct[(f1,f2,...,fn)]`` is + equivalent to ``fstruct[f1][f2]...[fn]``. + + Feature structures may contain reentrant feature structures. A + "reentrant feature structure" is a single feature structure + object that can be accessed via multiple feature paths. Feature + structures may also be cyclic. A feature structure is "cyclic" + if there is any feature path from the feature structure to itself. + + Two feature structures are considered equal if they assign the + same values to all features, and have the same reentrancies. + + By default, feature structures are mutable. They may be made + immutable with the ``freeze()`` method. Once they have been + frozen, they may be hashed, and thus used as dictionary keys. + """ + + _frozen = False + """:ivar: A flag indicating whether this feature structure is + frozen or not. Once this flag is set, it should never be + un-set; and no further modification should be made to this + feature structure.""" + + ##//////////////////////////////////////////////////////////// + # { Constructor + ##//////////////////////////////////////////////////////////// + + def __new__(cls, features=None, **morefeatures): + """ + Construct and return a new feature structure. If this + constructor is called directly, then the returned feature + structure will be an instance of either the ``FeatDict`` class + or the ``FeatList`` class. + + :param features: The initial feature values for this feature + structure: + + - FeatStruct(string) -> FeatStructReader().read(string) + - FeatStruct(mapping) -> FeatDict(mapping) + - FeatStruct(sequence) -> FeatList(sequence) + - FeatStruct() -> FeatDict() + :param morefeatures: If ``features`` is a mapping or None, + then ``morefeatures`` provides additional features for the + ``FeatDict`` constructor. + """ + # If the FeatStruct constructor is called directly, then decide + # whether to create a FeatDict or a FeatList, based on the + # contents of the `features` argument. + if cls is FeatStruct: + if features is None: + return FeatDict.__new__(FeatDict, **morefeatures) + elif _is_mapping(features): + return FeatDict.__new__(FeatDict, features, **morefeatures) + elif morefeatures: + raise TypeError( + "Keyword arguments may only be specified " + "if features is None or is a mapping." + ) + if isinstance(features, str): + if FeatStructReader._START_FDICT_RE.match(features): + return FeatDict.__new__(FeatDict, features, **morefeatures) + else: + return FeatList.__new__(FeatList, features, **morefeatures) + elif _is_sequence(features): + return FeatList.__new__(FeatList, features) + else: + raise TypeError("Expected string or mapping or sequence") + + # Otherwise, construct the object as normal. + else: + return super().__new__(cls, features, **morefeatures) + + ##//////////////////////////////////////////////////////////// + # { Uniform Accessor Methods + ##//////////////////////////////////////////////////////////// + # These helper functions allow the methods defined by FeatStruct + # to treat all feature structures as mappings, even if they're + # really lists. (Lists are treated as mappings from ints to vals) + + def _keys(self): + """Return an iterable of the feature identifiers used by this + FeatStruct.""" + raise NotImplementedError() # Implemented by subclasses. + + def _values(self): + """Return an iterable of the feature values directly defined + by this FeatStruct.""" + raise NotImplementedError() # Implemented by subclasses. + + def _items(self): + """Return an iterable of (fid,fval) pairs, where fid is a + feature identifier and fval is the corresponding feature + value, for all features defined by this FeatStruct.""" + raise NotImplementedError() # Implemented by subclasses. + + ##//////////////////////////////////////////////////////////// + # { Equality & Hashing + ##//////////////////////////////////////////////////////////// + + def equal_values(self, other, check_reentrance=False): + """ + Return True if ``self`` and ``other`` assign the same value to + to every feature. In particular, return true if + ``self[p]==other[p]`` for every feature path *p* such + that ``self[p]`` or ``other[p]`` is a base value (i.e., + not a nested feature structure). + + :param check_reentrance: If True, then also return False if + there is any difference between the reentrances of ``self`` + and ``other``. + :note: the ``==`` is equivalent to ``equal_values()`` with + ``check_reentrance=True``. + """ + return self._equal(other, check_reentrance, set(), set(), set()) + + def __eq__(self, other): + """ + Return true if ``self`` and ``other`` are both feature structures, + assign the same values to all features, and contain the same + reentrances. I.e., return + ``self.equal_values(other, check_reentrance=True)``. + + :see: ``equal_values()`` + """ + return self._equal(other, True, set(), set(), set()) + + def __ne__(self, other): + return not self == other + + def __lt__(self, other): + if not isinstance(other, FeatStruct): + # raise_unorderable_types("<", self, other) + # Sometimes feature values can be pure strings, + # so we need to be able to compare with non-featstructs: + return self.__class__.__name__ < other.__class__.__name__ + else: + return len(self) < len(other) + + def __hash__(self): + """ + If this feature structure is frozen, return its hash value; + otherwise, raise ``TypeError``. + """ + if not self._frozen: + raise TypeError("FeatStructs must be frozen before they " "can be hashed.") + try: + return self._hash + except AttributeError: + self._hash = self._calculate_hashvalue(set()) + return self._hash + + def _equal( + self, other, check_reentrance, visited_self, visited_other, visited_pairs + ): + """ + Return True iff self and other have equal values. + + :param visited_self: A set containing the ids of all ``self`` + feature structures we've already visited. + :param visited_other: A set containing the ids of all ``other`` + feature structures we've already visited. + :param visited_pairs: A set containing ``(selfid, otherid)`` pairs + for all pairs of feature structures we've already visited. + """ + # If we're the same object, then we're equal. + if self is other: + return True + + # If we have different classes, we're definitely not equal. + if self.__class__ != other.__class__: + return False + + # If we define different features, we're definitely not equal. + # (Perform len test first because it's faster -- we should + # do profiling to see if this actually helps) + if len(self) != len(other): + return False + if set(self._keys()) != set(other._keys()): + return False + + # If we're checking reentrance, then any time we revisit a + # structure, make sure that it was paired with the same + # feature structure that it is now. Note: if check_reentrance, + # then visited_pairs will never contain two pairs whose first + # values are equal, or two pairs whose second values are equal. + if check_reentrance: + if id(self) in visited_self or id(other) in visited_other: + return (id(self), id(other)) in visited_pairs + + # If we're not checking reentrance, then we still need to deal + # with cycles. If we encounter the same (self, other) pair a + # second time, then we won't learn anything more by examining + # their children a second time, so just return true. + else: + if (id(self), id(other)) in visited_pairs: + return True + + # Keep track of which nodes we've visited. + visited_self.add(id(self)) + visited_other.add(id(other)) + visited_pairs.add((id(self), id(other))) + + # Now we have to check all values. If any of them don't match, + # then return false. + for (fname, self_fval) in self._items(): + other_fval = other[fname] + if isinstance(self_fval, FeatStruct): + if not self_fval._equal( + other_fval, + check_reentrance, + visited_self, + visited_other, + visited_pairs, + ): + return False + else: + if self_fval != other_fval: + return False + + # Everything matched up; return true. + return True + + def _calculate_hashvalue(self, visited): + """ + Return a hash value for this feature structure. + + :require: ``self`` must be frozen. + :param visited: A set containing the ids of all feature + structures we've already visited while hashing. + """ + if id(self) in visited: + return 1 + visited.add(id(self)) + + hashval = 5831 + for (fname, fval) in sorted(self._items()): + hashval *= 37 + hashval += hash(fname) + hashval *= 37 + if isinstance(fval, FeatStruct): + hashval += fval._calculate_hashvalue(visited) + else: + hashval += hash(fval) + # Convert to a 32 bit int. + hashval = int(hashval & 0x7FFFFFFF) + return hashval + + ##//////////////////////////////////////////////////////////// + # { Freezing + ##//////////////////////////////////////////////////////////// + + #: Error message used by mutating methods when called on a frozen + #: feature structure. + _FROZEN_ERROR = "Frozen FeatStructs may not be modified." + + def freeze(self): + """ + Make this feature structure, and any feature structures it + contains, immutable. Note: this method does not attempt to + 'freeze' any feature value that is not a ``FeatStruct``; it + is recommended that you use only immutable feature values. + """ + if self._frozen: + return + self._freeze(set()) + + def frozen(self): + """ + Return True if this feature structure is immutable. Feature + structures can be made immutable with the ``freeze()`` method. + Immutable feature structures may not be made mutable again, + but new mutable copies can be produced with the ``copy()`` method. + """ + return self._frozen + + def _freeze(self, visited): + """ + Make this feature structure, and any feature structure it + contains, immutable. + + :param visited: A set containing the ids of all feature + structures we've already visited while freezing. + """ + if id(self) in visited: + return + visited.add(id(self)) + self._frozen = True + for (fname, fval) in sorted(self._items()): + if isinstance(fval, FeatStruct): + fval._freeze(visited) + + ##//////////////////////////////////////////////////////////// + # { Copying + ##//////////////////////////////////////////////////////////// + + def copy(self, deep=True): + """ + Return a new copy of ``self``. The new copy will not be frozen. + + :param deep: If true, create a deep copy; if false, create + a shallow copy. + """ + if deep: + return copy.deepcopy(self) + else: + return self.__class__(self) + + # Subclasses should define __deepcopy__ to ensure that the new + # copy will not be frozen. + def __deepcopy__(self, memo): + raise NotImplementedError() # Implemented by subclasses. + + ##//////////////////////////////////////////////////////////// + # { Structural Information + ##//////////////////////////////////////////////////////////// + + def cyclic(self): + """ + Return True if this feature structure contains itself. + """ + return self._find_reentrances({})[id(self)] + + def walk(self): + """ + Return an iterator that generates this feature structure, and + each feature structure it contains. Each feature structure will + be generated exactly once. + """ + return self._walk(set()) + + def _walk(self, visited): + """ + Return an iterator that generates this feature structure, and + each feature structure it contains. + + :param visited: A set containing the ids of all feature + structures we've already visited while freezing. + """ + raise NotImplementedError() # Implemented by subclasses. + + def _walk(self, visited): + if id(self) in visited: + return + visited.add(id(self)) + yield self + for fval in self._values(): + if isinstance(fval, FeatStruct): + yield from fval._walk(visited) + + # Walk through the feature tree. The first time we see a feature + # value, map it to False (not reentrant). If we see a feature + # value more than once, then map it to True (reentrant). + def _find_reentrances(self, reentrances): + """ + Return a dictionary that maps from the ``id`` of each feature + structure contained in ``self`` (including ``self``) to a + boolean value, indicating whether it is reentrant or not. + """ + if id(self) in reentrances: + # We've seen it more than once. + reentrances[id(self)] = True + else: + # This is the first time we've seen it. + reentrances[id(self)] = False + + # Recurse to contained feature structures. + for fval in self._values(): + if isinstance(fval, FeatStruct): + fval._find_reentrances(reentrances) + + return reentrances + + ##//////////////////////////////////////////////////////////// + # { Variables & Bindings + ##//////////////////////////////////////////////////////////// + + def substitute_bindings(self, bindings): + """:see: ``nltk.featstruct.substitute_bindings()``""" + return substitute_bindings(self, bindings) + + def retract_bindings(self, bindings): + """:see: ``nltk.featstruct.retract_bindings()``""" + return retract_bindings(self, bindings) + + def variables(self): + """:see: ``nltk.featstruct.find_variables()``""" + return find_variables(self) + + def rename_variables(self, vars=None, used_vars=(), new_vars=None): + """:see: ``nltk.featstruct.rename_variables()``""" + return rename_variables(self, vars, used_vars, new_vars) + + def remove_variables(self): + """ + Return the feature structure that is obtained by deleting + any feature whose value is a ``Variable``. + + :rtype: FeatStruct + """ + return remove_variables(self) + + ##//////////////////////////////////////////////////////////// + # { Unification + ##//////////////////////////////////////////////////////////// + + def unify(self, other, bindings=None, trace=False, fail=None, rename_vars=True): + return unify(self, other, bindings, trace, fail, rename_vars) + + def subsumes(self, other): + """ + Return True if ``self`` subsumes ``other``. I.e., return true + If unifying ``self`` with ``other`` would result in a feature + structure equal to ``other``. + """ + return subsumes(self, other) + + ##//////////////////////////////////////////////////////////// + # { String Representations + ##//////////////////////////////////////////////////////////// + + def __repr__(self): + """ + Display a single-line representation of this feature structure, + suitable for embedding in other representations. + """ + return self._repr(self._find_reentrances({}), {}) + + def _repr(self, reentrances, reentrance_ids): + """ + Return a string representation of this feature structure. + + :param reentrances: A dictionary that maps from the ``id`` of + each feature value in self, indicating whether that value + is reentrant or not. + :param reentrance_ids: A dictionary mapping from each ``id`` + of a feature value to a unique identifier. This is modified + by ``repr``: the first time a reentrant feature value is + displayed, an identifier is added to ``reentrance_ids`` for it. + """ + raise NotImplementedError() + + +# Mutation: disable if frozen. +_FROZEN_ERROR = "Frozen FeatStructs may not be modified." +_FROZEN_NOTICE = "\n%sIf self is frozen, raise ValueError." + + +def _check_frozen(method, indent=""): + """ + Given a method function, return a new method function that first + checks if ``self._frozen`` is true; and if so, raises ``ValueError`` + with an appropriate message. Otherwise, call the method and return + its result. + """ + + def wrapped(self, *args, **kwargs): + if self._frozen: + raise ValueError(_FROZEN_ERROR) + else: + return method(self, *args, **kwargs) + + wrapped.__name__ = method.__name__ + wrapped.__doc__ = (method.__doc__ or "") + (_FROZEN_NOTICE % indent) + return wrapped + + +###################################################################### +# Feature Dictionary +###################################################################### + + +class FeatDict(FeatStruct, dict): + """ + A feature structure that acts like a Python dictionary. I.e., a + mapping from feature identifiers to feature values, where a feature + identifier can be a string or a ``Feature``; and where a feature value + can be either a basic value (such as a string or an integer), or a nested + feature structure. A feature identifiers for a ``FeatDict`` is + sometimes called a "feature name". + + Two feature dicts are considered equal if they assign the same + values to all features, and have the same reentrances. + + :see: ``FeatStruct`` for information about feature paths, reentrance, + cyclic feature structures, mutability, freezing, and hashing. + """ + + def __init__(self, features=None, **morefeatures): + """ + Create a new feature dictionary, with the specified features. + + :param features: The initial value for this feature + dictionary. If ``features`` is a ``FeatStruct``, then its + features are copied (shallow copy). If ``features`` is a + dict, then a feature is created for each item, mapping its + key to its value. If ``features`` is a string, then it is + processed using ``FeatStructReader``. If ``features`` is a list of + tuples ``(name, val)``, then a feature is created for each tuple. + :param morefeatures: Additional features for the new feature + dictionary. If a feature is listed under both ``features`` and + ``morefeatures``, then the value from ``morefeatures`` will be + used. + """ + if isinstance(features, str): + FeatStructReader().fromstring(features, self) + self.update(**morefeatures) + else: + # update() checks the types of features. + self.update(features, **morefeatures) + + # //////////////////////////////////////////////////////////// + # { Dict methods + # //////////////////////////////////////////////////////////// + _INDEX_ERROR = "Expected feature name or path. Got %r." + + def __getitem__(self, name_or_path): + """If the feature with the given name or path exists, return + its value; otherwise, raise ``KeyError``.""" + if isinstance(name_or_path, (str, Feature)): + return dict.__getitem__(self, name_or_path) + elif isinstance(name_or_path, tuple): + try: + val = self + for fid in name_or_path: + if not isinstance(val, FeatStruct): + raise KeyError # path contains base value + val = val[fid] + return val + except (KeyError, IndexError) as e: + raise KeyError(name_or_path) from e + else: + raise TypeError(self._INDEX_ERROR % name_or_path) + + def get(self, name_or_path, default=None): + """If the feature with the given name or path exists, return its + value; otherwise, return ``default``.""" + try: + return self[name_or_path] + except KeyError: + return default + + def __contains__(self, name_or_path): + """Return true if a feature with the given name or path exists.""" + try: + self[name_or_path] + return True + except KeyError: + return False + + def has_key(self, name_or_path): + """Return true if a feature with the given name or path exists.""" + return name_or_path in self + + def __delitem__(self, name_or_path): + """If the feature with the given name or path exists, delete + its value; otherwise, raise ``KeyError``.""" + if self._frozen: + raise ValueError(_FROZEN_ERROR) + if isinstance(name_or_path, (str, Feature)): + return dict.__delitem__(self, name_or_path) + elif isinstance(name_or_path, tuple): + if len(name_or_path) == 0: + raise ValueError("The path () can not be set") + else: + parent = self[name_or_path[:-1]] + if not isinstance(parent, FeatStruct): + raise KeyError(name_or_path) # path contains base value + del parent[name_or_path[-1]] + else: + raise TypeError(self._INDEX_ERROR % name_or_path) + + def __setitem__(self, name_or_path, value): + """Set the value for the feature with the given name or path + to ``value``. If ``name_or_path`` is an invalid path, raise + ``KeyError``.""" + if self._frozen: + raise ValueError(_FROZEN_ERROR) + if isinstance(name_or_path, (str, Feature)): + return dict.__setitem__(self, name_or_path, value) + elif isinstance(name_or_path, tuple): + if len(name_or_path) == 0: + raise ValueError("The path () can not be set") + else: + parent = self[name_or_path[:-1]] + if not isinstance(parent, FeatStruct): + raise KeyError(name_or_path) # path contains base value + parent[name_or_path[-1]] = value + else: + raise TypeError(self._INDEX_ERROR % name_or_path) + + clear = _check_frozen(dict.clear) + pop = _check_frozen(dict.pop) + popitem = _check_frozen(dict.popitem) + setdefault = _check_frozen(dict.setdefault) + + def update(self, features=None, **morefeatures): + if self._frozen: + raise ValueError(_FROZEN_ERROR) + if features is None: + items = () + elif hasattr(features, "items") and callable(features.items): + items = features.items() + elif hasattr(features, "__iter__"): + items = features + else: + raise ValueError("Expected mapping or list of tuples") + + for key, val in items: + if not isinstance(key, (str, Feature)): + raise TypeError("Feature names must be strings") + self[key] = val + for key, val in morefeatures.items(): + if not isinstance(key, (str, Feature)): + raise TypeError("Feature names must be strings") + self[key] = val + + ##//////////////////////////////////////////////////////////// + # { Copying + ##//////////////////////////////////////////////////////////// + + def __deepcopy__(self, memo): + memo[id(self)] = selfcopy = self.__class__() + for (key, val) in self._items(): + selfcopy[copy.deepcopy(key, memo)] = copy.deepcopy(val, memo) + return selfcopy + + ##//////////////////////////////////////////////////////////// + # { Uniform Accessor Methods + ##//////////////////////////////////////////////////////////// + + def _keys(self): + return self.keys() + + def _values(self): + return self.values() + + def _items(self): + return self.items() + + ##//////////////////////////////////////////////////////////// + # { String Representations + ##//////////////////////////////////////////////////////////// + + def __str__(self): + """ + Display a multi-line representation of this feature dictionary + as an FVM (feature value matrix). + """ + return "\n".join(self._str(self._find_reentrances({}), {})) + + def _repr(self, reentrances, reentrance_ids): + segments = [] + prefix = "" + suffix = "" + + # If this is the first time we've seen a reentrant structure, + # then assign it a unique identifier. + if reentrances[id(self)]: + assert id(self) not in reentrance_ids + reentrance_ids[id(self)] = repr(len(reentrance_ids) + 1) + + # sorting note: keys are unique strings, so we'll never fall + # through to comparing values. + for (fname, fval) in sorted(self.items()): + display = getattr(fname, "display", None) + if id(fval) in reentrance_ids: + segments.append(f"{fname}->({reentrance_ids[id(fval)]})") + elif ( + display == "prefix" and not prefix and isinstance(fval, (Variable, str)) + ): + prefix = "%s" % fval + elif display == "slash" and not suffix: + if isinstance(fval, Variable): + suffix = "/%s" % fval.name + else: + suffix = "/%s" % repr(fval) + elif isinstance(fval, Variable): + segments.append(f"{fname}={fval.name}") + elif fval is True: + segments.append("+%s" % fname) + elif fval is False: + segments.append("-%s" % fname) + elif isinstance(fval, Expression): + segments.append(f"{fname}=<{fval}>") + elif not isinstance(fval, FeatStruct): + segments.append(f"{fname}={repr(fval)}") + else: + fval_repr = fval._repr(reentrances, reentrance_ids) + segments.append(f"{fname}={fval_repr}") + # If it's reentrant, then add on an identifier tag. + if reentrances[id(self)]: + prefix = f"({reentrance_ids[id(self)]}){prefix}" + return "{}[{}]{}".format(prefix, ", ".join(segments), suffix) + + def _str(self, reentrances, reentrance_ids): + """ + :return: A list of lines composing a string representation of + this feature dictionary. + :param reentrances: A dictionary that maps from the ``id`` of + each feature value in self, indicating whether that value + is reentrant or not. + :param reentrance_ids: A dictionary mapping from each ``id`` + of a feature value to a unique identifier. This is modified + by ``repr``: the first time a reentrant feature value is + displayed, an identifier is added to ``reentrance_ids`` for + it. + """ + # If this is the first time we've seen a reentrant structure, + # then tack on an id string. + if reentrances[id(self)]: + assert id(self) not in reentrance_ids + reentrance_ids[id(self)] = repr(len(reentrance_ids) + 1) + + # Special case: empty feature dict. + if len(self) == 0: + if reentrances[id(self)]: + return ["(%s) []" % reentrance_ids[id(self)]] + else: + return ["[]"] + + # What's the longest feature name? Use this to align names. + maxfnamelen = max(len("%s" % k) for k in self.keys()) + + lines = [] + # sorting note: keys are unique strings, so we'll never fall + # through to comparing values. + for (fname, fval) in sorted(self.items()): + fname = ("%s" % fname).ljust(maxfnamelen) + if isinstance(fval, Variable): + lines.append(f"{fname} = {fval.name}") + + elif isinstance(fval, Expression): + lines.append(f"{fname} = <{fval}>") + + elif isinstance(fval, FeatList): + fval_repr = fval._repr(reentrances, reentrance_ids) + lines.append(f"{fname} = {repr(fval_repr)}") + + elif not isinstance(fval, FeatDict): + # It's not a nested feature structure -- just print it. + lines.append(f"{fname} = {repr(fval)}") + + elif id(fval) in reentrance_ids: + # It's a feature structure we've seen before -- print + # the reentrance id. + lines.append(f"{fname} -> ({reentrance_ids[id(fval)]})") + + else: + # It's a new feature structure. Separate it from + # other values by a blank line. + if lines and lines[-1] != "": + lines.append("") + + # Recursively print the feature's value (fval). + fval_lines = fval._str(reentrances, reentrance_ids) + + # Indent each line to make room for fname. + fval_lines = [(" " * (maxfnamelen + 3)) + l for l in fval_lines] + + # Pick which line we'll display fname on, & splice it in. + nameline = (len(fval_lines) - 1) // 2 + fval_lines[nameline] = ( + fname + " =" + fval_lines[nameline][maxfnamelen + 2 :] + ) + + # Add the feature structure to the output. + lines += fval_lines + + # Separate FeatStructs by a blank line. + lines.append("") + + # Get rid of any excess blank lines. + if lines[-1] == "": + lines.pop() + + # Add brackets around everything. + maxlen = max(len(line) for line in lines) + lines = ["[ {}{} ]".format(line, " " * (maxlen - len(line))) for line in lines] + + # If it's reentrant, then add on an identifier tag. + if reentrances[id(self)]: + idstr = "(%s) " % reentrance_ids[id(self)] + lines = [(" " * len(idstr)) + l for l in lines] + idline = (len(lines) - 1) // 2 + lines[idline] = idstr + lines[idline][len(idstr) :] + + return lines + + +###################################################################### +# Feature List +###################################################################### + + +class FeatList(FeatStruct, list): + """ + A list of feature values, where each feature value is either a + basic value (such as a string or an integer), or a nested feature + structure. + + Feature lists may contain reentrant feature values. A "reentrant + feature value" is a single feature value that can be accessed via + multiple feature paths. Feature lists may also be cyclic. + + Two feature lists are considered equal if they assign the same + values to all features, and have the same reentrances. + + :see: ``FeatStruct`` for information about feature paths, reentrance, + cyclic feature structures, mutability, freezing, and hashing. + """ + + def __init__(self, features=()): + """ + Create a new feature list, with the specified features. + + :param features: The initial list of features for this feature + list. If ``features`` is a string, then it is paresd using + ``FeatStructReader``. Otherwise, it should be a sequence + of basic values and nested feature structures. + """ + if isinstance(features, str): + FeatStructReader().fromstring(features, self) + else: + list.__init__(self, features) + + # //////////////////////////////////////////////////////////// + # { List methods + # //////////////////////////////////////////////////////////// + _INDEX_ERROR = "Expected int or feature path. Got %r." + + def __getitem__(self, name_or_path): + if isinstance(name_or_path, int): + return list.__getitem__(self, name_or_path) + elif isinstance(name_or_path, tuple): + try: + val = self + for fid in name_or_path: + if not isinstance(val, FeatStruct): + raise KeyError # path contains base value + val = val[fid] + return val + except (KeyError, IndexError) as e: + raise KeyError(name_or_path) from e + else: + raise TypeError(self._INDEX_ERROR % name_or_path) + + def __delitem__(self, name_or_path): + """If the feature with the given name or path exists, delete + its value; otherwise, raise ``KeyError``.""" + if self._frozen: + raise ValueError(_FROZEN_ERROR) + if isinstance(name_or_path, (int, slice)): + return list.__delitem__(self, name_or_path) + elif isinstance(name_or_path, tuple): + if len(name_or_path) == 0: + raise ValueError("The path () can not be set") + else: + parent = self[name_or_path[:-1]] + if not isinstance(parent, FeatStruct): + raise KeyError(name_or_path) # path contains base value + del parent[name_or_path[-1]] + else: + raise TypeError(self._INDEX_ERROR % name_or_path) + + def __setitem__(self, name_or_path, value): + """Set the value for the feature with the given name or path + to ``value``. If ``name_or_path`` is an invalid path, raise + ``KeyError``.""" + if self._frozen: + raise ValueError(_FROZEN_ERROR) + if isinstance(name_or_path, (int, slice)): + return list.__setitem__(self, name_or_path, value) + elif isinstance(name_or_path, tuple): + if len(name_or_path) == 0: + raise ValueError("The path () can not be set") + else: + parent = self[name_or_path[:-1]] + if not isinstance(parent, FeatStruct): + raise KeyError(name_or_path) # path contains base value + parent[name_or_path[-1]] = value + else: + raise TypeError(self._INDEX_ERROR % name_or_path) + + # __delslice__ = _check_frozen(list.__delslice__, ' ') + # __setslice__ = _check_frozen(list.__setslice__, ' ') + __iadd__ = _check_frozen(list.__iadd__) + __imul__ = _check_frozen(list.__imul__) + append = _check_frozen(list.append) + extend = _check_frozen(list.extend) + insert = _check_frozen(list.insert) + pop = _check_frozen(list.pop) + remove = _check_frozen(list.remove) + reverse = _check_frozen(list.reverse) + sort = _check_frozen(list.sort) + + ##//////////////////////////////////////////////////////////// + # { Copying + ##//////////////////////////////////////////////////////////// + + def __deepcopy__(self, memo): + memo[id(self)] = selfcopy = self.__class__() + selfcopy.extend(copy.deepcopy(fval, memo) for fval in self) + return selfcopy + + ##//////////////////////////////////////////////////////////// + # { Uniform Accessor Methods + ##//////////////////////////////////////////////////////////// + + def _keys(self): + return list(range(len(self))) + + def _values(self): + return self + + def _items(self): + return enumerate(self) + + ##//////////////////////////////////////////////////////////// + # { String Representations + ##//////////////////////////////////////////////////////////// + + # Special handling for: reentrances, variables, expressions. + def _repr(self, reentrances, reentrance_ids): + # If this is the first time we've seen a reentrant structure, + # then assign it a unique identifier. + if reentrances[id(self)]: + assert id(self) not in reentrance_ids + reentrance_ids[id(self)] = repr(len(reentrance_ids) + 1) + prefix = "(%s)" % reentrance_ids[id(self)] + else: + prefix = "" + + segments = [] + for fval in self: + if id(fval) in reentrance_ids: + segments.append("->(%s)" % reentrance_ids[id(fval)]) + elif isinstance(fval, Variable): + segments.append(fval.name) + elif isinstance(fval, Expression): + segments.append("%s" % fval) + elif isinstance(fval, FeatStruct): + segments.append(fval._repr(reentrances, reentrance_ids)) + else: + segments.append("%s" % repr(fval)) + + return "{}[{}]".format(prefix, ", ".join(segments)) + + +###################################################################### +# Variables & Bindings +###################################################################### + + +def substitute_bindings(fstruct, bindings, fs_class="default"): + """ + Return the feature structure that is obtained by replacing each + variable bound by ``bindings`` with its binding. If a variable is + aliased to a bound variable, then it will be replaced by that + variable's value. If a variable is aliased to an unbound + variable, then it will be replaced by that variable. + + :type bindings: dict(Variable -> any) + :param bindings: A dictionary mapping from variables to values. + """ + if fs_class == "default": + fs_class = _default_fs_class(fstruct) + fstruct = copy.deepcopy(fstruct) + _substitute_bindings(fstruct, bindings, fs_class, set()) + return fstruct + + +def _substitute_bindings(fstruct, bindings, fs_class, visited): + # Visit each node only once: + if id(fstruct) in visited: + return + visited.add(id(fstruct)) + + if _is_mapping(fstruct): + items = fstruct.items() + elif _is_sequence(fstruct): + items = enumerate(fstruct) + else: + raise ValueError("Expected mapping or sequence") + for (fname, fval) in items: + while isinstance(fval, Variable) and fval in bindings: + fval = fstruct[fname] = bindings[fval] + if isinstance(fval, fs_class): + _substitute_bindings(fval, bindings, fs_class, visited) + elif isinstance(fval, SubstituteBindingsI): + fstruct[fname] = fval.substitute_bindings(bindings) + + +def retract_bindings(fstruct, bindings, fs_class="default"): + """ + Return the feature structure that is obtained by replacing each + feature structure value that is bound by ``bindings`` with the + variable that binds it. A feature structure value must be + identical to a bound value (i.e., have equal id) to be replaced. + + ``bindings`` is modified to point to this new feature structure, + rather than the original feature structure. Feature structure + values in ``bindings`` may be modified if they are contained in + ``fstruct``. + """ + if fs_class == "default": + fs_class = _default_fs_class(fstruct) + (fstruct, new_bindings) = copy.deepcopy((fstruct, bindings)) + bindings.update(new_bindings) + inv_bindings = {id(val): var for (var, val) in bindings.items()} + _retract_bindings(fstruct, inv_bindings, fs_class, set()) + return fstruct + + +def _retract_bindings(fstruct, inv_bindings, fs_class, visited): + # Visit each node only once: + if id(fstruct) in visited: + return + visited.add(id(fstruct)) + + if _is_mapping(fstruct): + items = fstruct.items() + elif _is_sequence(fstruct): + items = enumerate(fstruct) + else: + raise ValueError("Expected mapping or sequence") + for (fname, fval) in items: + if isinstance(fval, fs_class): + if id(fval) in inv_bindings: + fstruct[fname] = inv_bindings[id(fval)] + _retract_bindings(fval, inv_bindings, fs_class, visited) + + +def find_variables(fstruct, fs_class="default"): + """ + :return: The set of variables used by this feature structure. + :rtype: set(Variable) + """ + if fs_class == "default": + fs_class = _default_fs_class(fstruct) + return _variables(fstruct, set(), fs_class, set()) + + +def _variables(fstruct, vars, fs_class, visited): + # Visit each node only once: + if id(fstruct) in visited: + return + visited.add(id(fstruct)) + if _is_mapping(fstruct): + items = fstruct.items() + elif _is_sequence(fstruct): + items = enumerate(fstruct) + else: + raise ValueError("Expected mapping or sequence") + for (fname, fval) in items: + if isinstance(fval, Variable): + vars.add(fval) + elif isinstance(fval, fs_class): + _variables(fval, vars, fs_class, visited) + elif isinstance(fval, SubstituteBindingsI): + vars.update(fval.variables()) + return vars + + +def rename_variables( + fstruct, vars=None, used_vars=(), new_vars=None, fs_class="default" +): + """ + Return the feature structure that is obtained by replacing + any of this feature structure's variables that are in ``vars`` + with new variables. The names for these new variables will be + names that are not used by any variable in ``vars``, or in + ``used_vars``, or in this feature structure. + + :type vars: set + :param vars: The set of variables that should be renamed. + If not specified, ``find_variables(fstruct)`` is used; i.e., all + variables will be given new names. + :type used_vars: set + :param used_vars: A set of variables whose names should not be + used by the new variables. + :type new_vars: dict(Variable -> Variable) + :param new_vars: A dictionary that is used to hold the mapping + from old variables to new variables. For each variable *v* + in this feature structure: + + - If ``new_vars`` maps *v* to *v'*, then *v* will be + replaced by *v'*. + - If ``new_vars`` does not contain *v*, but ``vars`` + does contain *v*, then a new entry will be added to + ``new_vars``, mapping *v* to the new variable that is used + to replace it. + + To consistently rename the variables in a set of feature + structures, simply apply rename_variables to each one, using + the same dictionary: + + >>> from nltk.featstruct import FeatStruct + >>> fstruct1 = FeatStruct('[subj=[agr=[gender=?y]], obj=[agr=[gender=?y]]]') + >>> fstruct2 = FeatStruct('[subj=[agr=[number=?z,gender=?y]], obj=[agr=[number=?z,gender=?y]]]') + >>> new_vars = {} # Maps old vars to alpha-renamed vars + >>> fstruct1.rename_variables(new_vars=new_vars) + [obj=[agr=[gender=?y2]], subj=[agr=[gender=?y2]]] + >>> fstruct2.rename_variables(new_vars=new_vars) + [obj=[agr=[gender=?y2, number=?z2]], subj=[agr=[gender=?y2, number=?z2]]] + + If new_vars is not specified, then an empty dictionary is used. + """ + if fs_class == "default": + fs_class = _default_fs_class(fstruct) + + # Default values: + if new_vars is None: + new_vars = {} + if vars is None: + vars = find_variables(fstruct, fs_class) + else: + vars = set(vars) + + # Add our own variables to used_vars. + used_vars = find_variables(fstruct, fs_class).union(used_vars) + + # Copy ourselves, and rename variables in the copy. + return _rename_variables( + copy.deepcopy(fstruct), vars, used_vars, new_vars, fs_class, set() + ) + + +def _rename_variables(fstruct, vars, used_vars, new_vars, fs_class, visited): + if id(fstruct) in visited: + return + visited.add(id(fstruct)) + if _is_mapping(fstruct): + items = fstruct.items() + elif _is_sequence(fstruct): + items = enumerate(fstruct) + else: + raise ValueError("Expected mapping or sequence") + for (fname, fval) in items: + if isinstance(fval, Variable): + # If it's in new_vars, then rebind it. + if fval in new_vars: + fstruct[fname] = new_vars[fval] + # If it's in vars, pick a new name for it. + elif fval in vars: + new_vars[fval] = _rename_variable(fval, used_vars) + fstruct[fname] = new_vars[fval] + used_vars.add(new_vars[fval]) + elif isinstance(fval, fs_class): + _rename_variables(fval, vars, used_vars, new_vars, fs_class, visited) + elif isinstance(fval, SubstituteBindingsI): + # Pick new names for any variables in `vars` + for var in fval.variables(): + if var in vars and var not in new_vars: + new_vars[var] = _rename_variable(var, used_vars) + used_vars.add(new_vars[var]) + # Replace all variables in `new_vars`. + fstruct[fname] = fval.substitute_bindings(new_vars) + return fstruct + + +def _rename_variable(var, used_vars): + name, n = re.sub(r"\d+$", "", var.name), 2 + if not name: + name = "?" + while Variable(f"{name}{n}") in used_vars: + n += 1 + return Variable(f"{name}{n}") + + +def remove_variables(fstruct, fs_class="default"): + """ + :rtype: FeatStruct + :return: The feature structure that is obtained by deleting + all features whose values are ``Variables``. + """ + if fs_class == "default": + fs_class = _default_fs_class(fstruct) + return _remove_variables(copy.deepcopy(fstruct), fs_class, set()) + + +def _remove_variables(fstruct, fs_class, visited): + if id(fstruct) in visited: + return + visited.add(id(fstruct)) + + if _is_mapping(fstruct): + items = list(fstruct.items()) + elif _is_sequence(fstruct): + items = list(enumerate(fstruct)) + else: + raise ValueError("Expected mapping or sequence") + + for (fname, fval) in items: + if isinstance(fval, Variable): + del fstruct[fname] + elif isinstance(fval, fs_class): + _remove_variables(fval, fs_class, visited) + return fstruct + + +###################################################################### +# Unification +###################################################################### + + +class _UnificationFailure: + def __repr__(self): + return "nltk.featstruct.UnificationFailure" + + +UnificationFailure = _UnificationFailure() +"""A unique value used to indicate unification failure. It can be + returned by ``Feature.unify_base_values()`` or by custom ``fail()`` + functions to indicate that unificaiton should fail.""" + + +# The basic unification algorithm: +# 1. Make copies of self and other (preserving reentrance) +# 2. Destructively unify self and other +# 3. Apply forward pointers, to preserve reentrance. +# 4. Replace bound variables with their values. +def unify( + fstruct1, + fstruct2, + bindings=None, + trace=False, + fail=None, + rename_vars=True, + fs_class="default", +): + """ + Unify ``fstruct1`` with ``fstruct2``, and return the resulting feature + structure. This unified feature structure is the minimal + feature structure that contains all feature value assignments from both + ``fstruct1`` and ``fstruct2``, and that preserves all reentrancies. + + If no such feature structure exists (because ``fstruct1`` and + ``fstruct2`` specify incompatible values for some feature), then + unification fails, and ``unify`` returns None. + + Bound variables are replaced by their values. Aliased + variables are replaced by their representative variable + (if unbound) or the value of their representative variable + (if bound). I.e., if variable *v* is in ``bindings``, + then *v* is replaced by ``bindings[v]``. This will + be repeated until the variable is replaced by an unbound + variable or a non-variable value. + + Unbound variables are bound when they are unified with + values; and aliased when they are unified with variables. + I.e., if variable *v* is not in ``bindings``, and is + unified with a variable or value *x*, then + ``bindings[v]`` is set to *x*. + + If ``bindings`` is unspecified, then all variables are + assumed to be unbound. I.e., ``bindings`` defaults to an + empty dict. + + >>> from nltk.featstruct import FeatStruct + >>> FeatStruct('[a=?x]').unify(FeatStruct('[b=?x]')) + [a=?x, b=?x2] + + :type bindings: dict(Variable -> any) + :param bindings: A set of variable bindings to be used and + updated during unification. + :type trace: bool + :param trace: If true, generate trace output. + :type rename_vars: bool + :param rename_vars: If True, then rename any variables in + ``fstruct2`` that are also used in ``fstruct1``, in order to + avoid collisions on variable names. + """ + # Decide which class(es) will be treated as feature structures, + # for the purposes of unification. + if fs_class == "default": + fs_class = _default_fs_class(fstruct1) + if _default_fs_class(fstruct2) != fs_class: + raise ValueError( + "Mixing FeatStruct objects with Python " + "dicts and lists is not supported." + ) + assert isinstance(fstruct1, fs_class) + assert isinstance(fstruct2, fs_class) + + # If bindings are unspecified, use an empty set of bindings. + user_bindings = bindings is not None + if bindings is None: + bindings = {} + + # Make copies of fstruct1 and fstruct2 (since the unification + # algorithm is destructive). Do it all at once, to preserve + # reentrance links between fstruct1 and fstruct2. Copy bindings + # as well, in case there are any bound vars that contain parts + # of fstruct1 or fstruct2. + (fstruct1copy, fstruct2copy, bindings_copy) = copy.deepcopy( + (fstruct1, fstruct2, bindings) + ) + + # Copy the bindings back to the original bindings dict. + bindings.update(bindings_copy) + + if rename_vars: + vars1 = find_variables(fstruct1copy, fs_class) + vars2 = find_variables(fstruct2copy, fs_class) + _rename_variables(fstruct2copy, vars1, vars2, {}, fs_class, set()) + + # Do the actual unification. If it fails, return None. + forward = {} + if trace: + _trace_unify_start((), fstruct1copy, fstruct2copy) + try: + result = _destructively_unify( + fstruct1copy, fstruct2copy, bindings, forward, trace, fail, fs_class, () + ) + except _UnificationFailureError: + return None + + # _destructively_unify might return UnificationFailure, e.g. if we + # tried to unify a mapping with a sequence. + if result is UnificationFailure: + if fail is None: + return None + else: + return fail(fstruct1copy, fstruct2copy, ()) + + # Replace any feature structure that has a forward pointer + # with the target of its forward pointer. + result = _apply_forwards(result, forward, fs_class, set()) + if user_bindings: + _apply_forwards_to_bindings(forward, bindings) + + # Replace bound vars with values. + _resolve_aliases(bindings) + _substitute_bindings(result, bindings, fs_class, set()) + + # Return the result. + if trace: + _trace_unify_succeed((), result) + if trace: + _trace_bindings((), bindings) + return result + + +class _UnificationFailureError(Exception): + """An exception that is used by ``_destructively_unify`` to abort + unification when a failure is encountered.""" + + +def _destructively_unify( + fstruct1, fstruct2, bindings, forward, trace, fail, fs_class, path +): + """ + Attempt to unify ``fstruct1`` and ``fstruct2`` by modifying them + in-place. If the unification succeeds, then ``fstruct1`` will + contain the unified value, the value of ``fstruct2`` is undefined, + and forward[id(fstruct2)] is set to fstruct1. If the unification + fails, then a _UnificationFailureError is raised, and the + values of ``fstruct1`` and ``fstruct2`` are undefined. + + :param bindings: A dictionary mapping variables to values. + :param forward: A dictionary mapping feature structures ids + to replacement structures. When two feature structures + are merged, a mapping from one to the other will be added + to the forward dictionary; and changes will be made only + to the target of the forward dictionary. + ``_destructively_unify`` will always 'follow' any links + in the forward dictionary for fstruct1 and fstruct2 before + actually unifying them. + :param trace: If true, generate trace output + :param path: The feature path that led us to this unification + step. Used for trace output. + """ + # If fstruct1 is already identical to fstruct2, we're done. + # Note: this, together with the forward pointers, ensures + # that unification will terminate even for cyclic structures. + if fstruct1 is fstruct2: + if trace: + _trace_unify_identity(path, fstruct1) + return fstruct1 + + # Set fstruct2's forward pointer to point to fstruct1; this makes + # fstruct1 the canonical copy for fstruct2. Note that we need to + # do this before we recurse into any child structures, in case + # they're cyclic. + forward[id(fstruct2)] = fstruct1 + + # Unifying two mappings: + if _is_mapping(fstruct1) and _is_mapping(fstruct2): + for fname in fstruct1: + if getattr(fname, "default", None) is not None: + fstruct2.setdefault(fname, fname.default) + for fname in fstruct2: + if getattr(fname, "default", None) is not None: + fstruct1.setdefault(fname, fname.default) + + # Unify any values that are defined in both fstruct1 and + # fstruct2. Copy any values that are defined in fstruct2 but + # not in fstruct1 to fstruct1. Note: sorting fstruct2's + # features isn't actually necessary; but we do it to give + # deterministic behavior, e.g. for tracing. + for fname, fval2 in sorted(fstruct2.items()): + if fname in fstruct1: + fstruct1[fname] = _unify_feature_values( + fname, + fstruct1[fname], + fval2, + bindings, + forward, + trace, + fail, + fs_class, + path + (fname,), + ) + else: + fstruct1[fname] = fval2 + + return fstruct1 # Contains the unified value. + + # Unifying two sequences: + elif _is_sequence(fstruct1) and _is_sequence(fstruct2): + # If the lengths don't match, fail. + if len(fstruct1) != len(fstruct2): + return UnificationFailure + + # Unify corresponding values in fstruct1 and fstruct2. + for findex in range(len(fstruct1)): + fstruct1[findex] = _unify_feature_values( + findex, + fstruct1[findex], + fstruct2[findex], + bindings, + forward, + trace, + fail, + fs_class, + path + (findex,), + ) + + return fstruct1 # Contains the unified value. + + # Unifying sequence & mapping: fail. The failure function + # doesn't get a chance to recover in this case. + elif (_is_sequence(fstruct1) or _is_mapping(fstruct1)) and ( + _is_sequence(fstruct2) or _is_mapping(fstruct2) + ): + return UnificationFailure + + # Unifying anything else: not allowed! + raise TypeError("Expected mappings or sequences") + + +def _unify_feature_values( + fname, fval1, fval2, bindings, forward, trace, fail, fs_class, fpath +): + """ + Attempt to unify ``fval1`` and and ``fval2``, and return the + resulting unified value. The method of unification will depend on + the types of ``fval1`` and ``fval2``: + + 1. If they're both feature structures, then destructively + unify them (see ``_destructively_unify()``. + 2. If they're both unbound variables, then alias one variable + to the other (by setting bindings[v2]=v1). + 3. If one is an unbound variable, and the other is a value, + then bind the unbound variable to the value. + 4. If one is a feature structure, and the other is a base value, + then fail. + 5. If they're both base values, then unify them. By default, + this will succeed if they are equal, and fail otherwise. + """ + if trace: + _trace_unify_start(fpath, fval1, fval2) + + # Look up the "canonical" copy of fval1 and fval2 + while id(fval1) in forward: + fval1 = forward[id(fval1)] + while id(fval2) in forward: + fval2 = forward[id(fval2)] + + # If fval1 or fval2 is a bound variable, then + # replace it by the variable's bound value. This + # includes aliased variables, which are encoded as + # variables bound to other variables. + fvar1 = fvar2 = None + while isinstance(fval1, Variable) and fval1 in bindings: + fvar1 = fval1 + fval1 = bindings[fval1] + while isinstance(fval2, Variable) and fval2 in bindings: + fvar2 = fval2 + fval2 = bindings[fval2] + + # Case 1: Two feature structures (recursive case) + if isinstance(fval1, fs_class) and isinstance(fval2, fs_class): + result = _destructively_unify( + fval1, fval2, bindings, forward, trace, fail, fs_class, fpath + ) + + # Case 2: Two unbound variables (create alias) + elif isinstance(fval1, Variable) and isinstance(fval2, Variable): + if fval1 != fval2: + bindings[fval2] = fval1 + result = fval1 + + # Case 3: An unbound variable and a value (bind) + elif isinstance(fval1, Variable): + bindings[fval1] = fval2 + result = fval1 + elif isinstance(fval2, Variable): + bindings[fval2] = fval1 + result = fval2 + + # Case 4: A feature structure & a base value (fail) + elif isinstance(fval1, fs_class) or isinstance(fval2, fs_class): + result = UnificationFailure + + # Case 5: Two base values + else: + # Case 5a: Feature defines a custom unification method for base values + if isinstance(fname, Feature): + result = fname.unify_base_values(fval1, fval2, bindings) + # Case 5b: Feature value defines custom unification method + elif isinstance(fval1, CustomFeatureValue): + result = fval1.unify(fval2) + # Sanity check: unify value should be symmetric + if isinstance(fval2, CustomFeatureValue) and result != fval2.unify(fval1): + raise AssertionError( + "CustomFeatureValue objects %r and %r disagree " + "about unification value: %r vs. %r" + % (fval1, fval2, result, fval2.unify(fval1)) + ) + elif isinstance(fval2, CustomFeatureValue): + result = fval2.unify(fval1) + # Case 5c: Simple values -- check if they're equal. + else: + if fval1 == fval2: + result = fval1 + else: + result = UnificationFailure + + # If either value was a bound variable, then update the + # bindings. (This is really only necessary if fname is a + # Feature or if either value is a CustomFeatureValue.) + if result is not UnificationFailure: + if fvar1 is not None: + bindings[fvar1] = result + result = fvar1 + if fvar2 is not None and fvar2 != fvar1: + bindings[fvar2] = result + result = fvar2 + + # If we unification failed, call the failure function; it + # might decide to continue anyway. + if result is UnificationFailure: + if fail is not None: + result = fail(fval1, fval2, fpath) + if trace: + _trace_unify_fail(fpath[:-1], result) + if result is UnificationFailure: + raise _UnificationFailureError + + # Normalize the result. + if isinstance(result, fs_class): + result = _apply_forwards(result, forward, fs_class, set()) + + if trace: + _trace_unify_succeed(fpath, result) + if trace and isinstance(result, fs_class): + _trace_bindings(fpath, bindings) + + return result + + +def _apply_forwards_to_bindings(forward, bindings): + """ + Replace any feature structure that has a forward pointer with + the target of its forward pointer (to preserve reentrancy). + """ + for (var, value) in bindings.items(): + while id(value) in forward: + value = forward[id(value)] + bindings[var] = value + + +def _apply_forwards(fstruct, forward, fs_class, visited): + """ + Replace any feature structure that has a forward pointer with + the target of its forward pointer (to preserve reentrancy). + """ + # Follow our own forwards pointers (if any) + while id(fstruct) in forward: + fstruct = forward[id(fstruct)] + + # Visit each node only once: + if id(fstruct) in visited: + return + visited.add(id(fstruct)) + + if _is_mapping(fstruct): + items = fstruct.items() + elif _is_sequence(fstruct): + items = enumerate(fstruct) + else: + raise ValueError("Expected mapping or sequence") + for fname, fval in items: + if isinstance(fval, fs_class): + # Replace w/ forwarded value. + while id(fval) in forward: + fval = forward[id(fval)] + fstruct[fname] = fval + # Recurse to child. + _apply_forwards(fval, forward, fs_class, visited) + + return fstruct + + +def _resolve_aliases(bindings): + """ + Replace any bound aliased vars with their binding; and replace + any unbound aliased vars with their representative var. + """ + for (var, value) in bindings.items(): + while isinstance(value, Variable) and value in bindings: + value = bindings[var] = bindings[value] + + +def _trace_unify_start(path, fval1, fval2): + if path == (): + print("\nUnification trace:") + else: + fullname = ".".join("%s" % n for n in path) + print(" " + "| " * (len(path) - 1) + "|") + print(" " + "| " * (len(path) - 1) + "| Unify feature: %s" % fullname) + print(" " + "| " * len(path) + " / " + _trace_valrepr(fval1)) + print(" " + "| " * len(path) + "|\\ " + _trace_valrepr(fval2)) + + +def _trace_unify_identity(path, fval1): + print(" " + "| " * len(path) + "|") + print(" " + "| " * len(path) + "| (identical objects)") + print(" " + "| " * len(path) + "|") + print(" " + "| " * len(path) + "+-->" + repr(fval1)) + + +def _trace_unify_fail(path, result): + if result is UnificationFailure: + resume = "" + else: + resume = " (nonfatal)" + print(" " + "| " * len(path) + "| |") + print(" " + "X " * len(path) + "X X <-- FAIL" + resume) + + +def _trace_unify_succeed(path, fval1): + # Print the result. + print(" " + "| " * len(path) + "|") + print(" " + "| " * len(path) + "+-->" + repr(fval1)) + + +def _trace_bindings(path, bindings): + # Print the bindings (if any). + if len(bindings) > 0: + binditems = sorted(bindings.items(), key=lambda v: v[0].name) + bindstr = "{%s}" % ", ".join( + f"{var}: {_trace_valrepr(val)}" for (var, val) in binditems + ) + print(" " + "| " * len(path) + " Bindings: " + bindstr) + + +def _trace_valrepr(val): + if isinstance(val, Variable): + return "%s" % val + else: + return "%s" % repr(val) + + +def subsumes(fstruct1, fstruct2): + """ + Return True if ``fstruct1`` subsumes ``fstruct2``. I.e., return + true if unifying ``fstruct1`` with ``fstruct2`` would result in a + feature structure equal to ``fstruct2.`` + + :rtype: bool + """ + return fstruct2 == unify(fstruct1, fstruct2) + + +def conflicts(fstruct1, fstruct2, trace=0): + """ + Return a list of the feature paths of all features which are + assigned incompatible values by ``fstruct1`` and ``fstruct2``. + + :rtype: list(tuple) + """ + conflict_list = [] + + def add_conflict(fval1, fval2, path): + conflict_list.append(path) + return fval1 + + unify(fstruct1, fstruct2, fail=add_conflict, trace=trace) + return conflict_list + + +###################################################################### +# Helper Functions +###################################################################### + + +def _is_mapping(v): + return hasattr(v, "__contains__") and hasattr(v, "keys") + + +def _is_sequence(v): + return hasattr(v, "__iter__") and hasattr(v, "__len__") and not isinstance(v, str) + + +def _default_fs_class(obj): + if isinstance(obj, FeatStruct): + return FeatStruct + if isinstance(obj, (dict, list)): + return (dict, list) + else: + raise ValueError( + "To unify objects of type %s, you must specify " + "fs_class explicitly." % obj.__class__.__name__ + ) + + +###################################################################### +# FeatureValueSet & FeatureValueTuple +###################################################################### + + +class SubstituteBindingsSequence(SubstituteBindingsI): + """ + A mixin class for sequence classes that distributes variables() and + substitute_bindings() over the object's elements. + """ + + def variables(self): + return [elt for elt in self if isinstance(elt, Variable)] + sum( + ( + list(elt.variables()) + for elt in self + if isinstance(elt, SubstituteBindingsI) + ), + [], + ) + + def substitute_bindings(self, bindings): + return self.__class__([self.subst(v, bindings) for v in self]) + + def subst(self, v, bindings): + if isinstance(v, SubstituteBindingsI): + return v.substitute_bindings(bindings) + else: + return bindings.get(v, v) + + +class FeatureValueTuple(SubstituteBindingsSequence, tuple): + """ + A base feature value that is a tuple of other base feature values. + FeatureValueTuple implements ``SubstituteBindingsI``, so it any + variable substitutions will be propagated to the elements + contained by the set. A ``FeatureValueTuple`` is immutable. + """ + + def __repr__(self): # [xx] really use %s here? + if len(self) == 0: + return "()" + return "(%s)" % ", ".join(f"{b}" for b in self) + + +class FeatureValueSet(SubstituteBindingsSequence, frozenset): + """ + A base feature value that is a set of other base feature values. + FeatureValueSet implements ``SubstituteBindingsI``, so it any + variable substitutions will be propagated to the elements + contained by the set. A ``FeatureValueSet`` is immutable. + """ + + def __repr__(self): # [xx] really use %s here? + if len(self) == 0: + return "{/}" # distinguish from dict. + # n.b., we sort the string reprs of our elements, to ensure + # that our own repr is deterministic. + return "{%s}" % ", ".join(sorted(f"{b}" for b in self)) + + __str__ = __repr__ + + +class FeatureValueUnion(SubstituteBindingsSequence, frozenset): + """ + A base feature value that represents the union of two or more + ``FeatureValueSet`` or ``Variable``. + """ + + def __new__(cls, values): + # If values contains FeatureValueUnions, then collapse them. + values = _flatten(values, FeatureValueUnion) + + # If the resulting list contains no variables, then + # use a simple FeatureValueSet instead. + if sum(isinstance(v, Variable) for v in values) == 0: + values = _flatten(values, FeatureValueSet) + return FeatureValueSet(values) + + # If we contain a single variable, return that variable. + if len(values) == 1: + return list(values)[0] + + # Otherwise, build the FeatureValueUnion. + return frozenset.__new__(cls, values) + + def __repr__(self): + # n.b., we sort the string reprs of our elements, to ensure + # that our own repr is deterministic. also, note that len(self) + # is guaranteed to be 2 or more. + return "{%s}" % "+".join(sorted(f"{b}" for b in self)) + + +class FeatureValueConcat(SubstituteBindingsSequence, tuple): + """ + A base feature value that represents the concatenation of two or + more ``FeatureValueTuple`` or ``Variable``. + """ + + def __new__(cls, values): + # If values contains FeatureValueConcats, then collapse them. + values = _flatten(values, FeatureValueConcat) + + # If the resulting list contains no variables, then + # use a simple FeatureValueTuple instead. + if sum(isinstance(v, Variable) for v in values) == 0: + values = _flatten(values, FeatureValueTuple) + return FeatureValueTuple(values) + + # If we contain a single variable, return that variable. + if len(values) == 1: + return list(values)[0] + + # Otherwise, build the FeatureValueConcat. + return tuple.__new__(cls, values) + + def __repr__(self): + # n.b.: len(self) is guaranteed to be 2 or more. + return "(%s)" % "+".join(f"{b}" for b in self) + + +def _flatten(lst, cls): + """ + Helper function -- return a copy of list, with all elements of + type ``cls`` spliced in rather than appended in. + """ + result = [] + for elt in lst: + if isinstance(elt, cls): + result.extend(elt) + else: + result.append(elt) + return result + + +###################################################################### +# Specialized Features +###################################################################### + + +@total_ordering +class Feature: + """ + A feature identifier that's specialized to put additional + constraints, default values, etc. + """ + + def __init__(self, name, default=None, display=None): + assert display in (None, "prefix", "slash") + + self._name = name # [xx] rename to .identifier? + self._default = default # [xx] not implemented yet. + self._display = display + + if self._display == "prefix": + self._sortkey = (-1, self._name) + elif self._display == "slash": + self._sortkey = (1, self._name) + else: + self._sortkey = (0, self._name) + + @property + def name(self): + """The name of this feature.""" + return self._name + + @property + def default(self): + """Default value for this feature.""" + return self._default + + @property + def display(self): + """Custom display location: can be prefix, or slash.""" + return self._display + + def __repr__(self): + return "*%s*" % self.name + + def __lt__(self, other): + if isinstance(other, str): + return True + if not isinstance(other, Feature): + raise_unorderable_types("<", self, other) + return self._sortkey < other._sortkey + + def __eq__(self, other): + return type(self) == type(other) and self._name == other._name + + def __ne__(self, other): + return not self == other + + def __hash__(self): + return hash(self._name) + + # //////////////////////////////////////////////////////////// + # These can be overridden by subclasses: + # //////////////////////////////////////////////////////////// + + def read_value(self, s, position, reentrances, parser): + return parser.read_value(s, position, reentrances) + + def unify_base_values(self, fval1, fval2, bindings): + """ + If possible, return a single value.. If not, return + the value ``UnificationFailure``. + """ + if fval1 == fval2: + return fval1 + else: + return UnificationFailure + + +class SlashFeature(Feature): + def read_value(self, s, position, reentrances, parser): + return parser.read_partial(s, position, reentrances) + + +class RangeFeature(Feature): + RANGE_RE = re.compile(r"(-?\d+):(-?\d+)") + + def read_value(self, s, position, reentrances, parser): + m = self.RANGE_RE.match(s, position) + if not m: + raise ValueError("range", position) + return (int(m.group(1)), int(m.group(2))), m.end() + + def unify_base_values(self, fval1, fval2, bindings): + if fval1 is None: + return fval2 + if fval2 is None: + return fval1 + rng = max(fval1[0], fval2[0]), min(fval1[1], fval2[1]) + if rng[1] < rng[0]: + return UnificationFailure + return rng + + +SLASH = SlashFeature("slash", default=False, display="slash") +TYPE = Feature("type", display="prefix") + + +###################################################################### +# Specialized Feature Values +###################################################################### + + +@total_ordering +class CustomFeatureValue: + """ + An abstract base class for base values that define a custom + unification method. The custom unification method of + ``CustomFeatureValue`` will be used during unification if: + + - The ``CustomFeatureValue`` is unified with another base value. + - The ``CustomFeatureValue`` is not the value of a customized + ``Feature`` (which defines its own unification method). + + If two ``CustomFeatureValue`` objects are unified with one another + during feature structure unification, then the unified base values + they return *must* be equal; otherwise, an ``AssertionError`` will + be raised. + + Subclasses must define ``unify()``, ``__eq__()`` and ``__lt__()``. + Subclasses may also wish to define ``__hash__()``. + """ + + def unify(self, other): + """ + If this base value unifies with ``other``, then return the + unified value. Otherwise, return ``UnificationFailure``. + """ + raise NotImplementedError("abstract base class") + + def __eq__(self, other): + return NotImplemented + + def __ne__(self, other): + return not self == other + + def __lt__(self, other): + return NotImplemented + + def __hash__(self): + raise TypeError("%s objects or unhashable" % self.__class__.__name__) + + +###################################################################### +# Feature Structure Reader +###################################################################### + + +class FeatStructReader: + def __init__( + self, + features=(SLASH, TYPE), + fdict_class=FeatStruct, + flist_class=FeatList, + logic_parser=None, + ): + self._features = {f.name: f for f in features} + self._fdict_class = fdict_class + self._flist_class = flist_class + self._prefix_feature = None + self._slash_feature = None + for feature in features: + if feature.display == "slash": + if self._slash_feature: + raise ValueError("Multiple features w/ display=slash") + self._slash_feature = feature + if feature.display == "prefix": + if self._prefix_feature: + raise ValueError("Multiple features w/ display=prefix") + self._prefix_feature = feature + self._features_with_defaults = [ + feature for feature in features if feature.default is not None + ] + if logic_parser is None: + logic_parser = LogicParser() + self._logic_parser = logic_parser + + def fromstring(self, s, fstruct=None): + """ + Convert a string representation of a feature structure (as + displayed by repr) into a ``FeatStruct``. This process + imposes the following restrictions on the string + representation: + + - Feature names cannot contain any of the following: + whitespace, parentheses, quote marks, equals signs, + dashes, commas, and square brackets. Feature names may + not begin with plus signs or minus signs. + - Only the following basic feature value are supported: + strings, integers, variables, None, and unquoted + alphanumeric strings. + - For reentrant values, the first mention must specify + a reentrance identifier and a value; and any subsequent + mentions must use arrows (``'->'``) to reference the + reentrance identifier. + """ + s = s.strip() + value, position = self.read_partial(s, 0, {}, fstruct) + if position != len(s): + self._error(s, "end of string", position) + return value + + _START_FSTRUCT_RE = re.compile(r"\s*(?:\((\d+)\)\s*)?(\??[\w-]+)?(\[)") + _END_FSTRUCT_RE = re.compile(r"\s*]\s*") + _SLASH_RE = re.compile(r"/") + _FEATURE_NAME_RE = re.compile(r'\s*([+-]?)([^\s\(\)<>"\'\-=\[\],]+)\s*') + _REENTRANCE_RE = re.compile(r"\s*->\s*") + _TARGET_RE = re.compile(r"\s*\((\d+)\)\s*") + _ASSIGN_RE = re.compile(r"\s*=\s*") + _COMMA_RE = re.compile(r"\s*,\s*") + _BARE_PREFIX_RE = re.compile(r"\s*(?:\((\d+)\)\s*)?(\??[\w-]+\s*)()") + # This one is used to distinguish fdicts from flists: + _START_FDICT_RE = re.compile( + r"(%s)|(%s\s*(%s\s*(=|->)|[+-]%s|\]))" + % ( + _BARE_PREFIX_RE.pattern, + _START_FSTRUCT_RE.pattern, + _FEATURE_NAME_RE.pattern, + _FEATURE_NAME_RE.pattern, + ) + ) + + def read_partial(self, s, position=0, reentrances=None, fstruct=None): + """ + Helper function that reads in a feature structure. + + :param s: The string to read. + :param position: The position in the string to start parsing. + :param reentrances: A dictionary from reentrance ids to values. + Defaults to an empty dictionary. + :return: A tuple (val, pos) of the feature structure created by + parsing and the position where the parsed feature structure ends. + :rtype: bool + """ + if reentrances is None: + reentrances = {} + try: + return self._read_partial(s, position, reentrances, fstruct) + except ValueError as e: + if len(e.args) != 2: + raise + self._error(s, *e.args) + + def _read_partial(self, s, position, reentrances, fstruct=None): + # Create the new feature structure + if fstruct is None: + if self._START_FDICT_RE.match(s, position): + fstruct = self._fdict_class() + else: + fstruct = self._flist_class() + + # Read up to the open bracket. + match = self._START_FSTRUCT_RE.match(s, position) + if not match: + match = self._BARE_PREFIX_RE.match(s, position) + if not match: + raise ValueError("open bracket or identifier", position) + position = match.end() + + # If there as an identifier, record it. + if match.group(1): + identifier = match.group(1) + if identifier in reentrances: + raise ValueError("new identifier", match.start(1)) + reentrances[identifier] = fstruct + + if isinstance(fstruct, FeatDict): + fstruct.clear() + return self._read_partial_featdict(s, position, match, reentrances, fstruct) + else: + del fstruct[:] + return self._read_partial_featlist(s, position, match, reentrances, fstruct) + + def _read_partial_featlist(self, s, position, match, reentrances, fstruct): + # Prefix features are not allowed: + if match.group(2): + raise ValueError("open bracket") + # Bare prefixes are not allowed: + if not match.group(3): + raise ValueError("open bracket") + + # Build a list of the features defined by the structure. + while position < len(s): + # Check for the close bracket. + match = self._END_FSTRUCT_RE.match(s, position) + if match is not None: + return fstruct, match.end() + + # Reentances have the form "-> (target)" + match = self._REENTRANCE_RE.match(s, position) + if match: + position = match.end() + match = self._TARGET_RE.match(s, position) + if not match: + raise ValueError("identifier", position) + target = match.group(1) + if target not in reentrances: + raise ValueError("bound identifier", position) + position = match.end() + fstruct.append(reentrances[target]) + + # Anything else is a value. + else: + value, position = self._read_value(0, s, position, reentrances) + fstruct.append(value) + + # If there's a close bracket, handle it at the top of the loop. + if self._END_FSTRUCT_RE.match(s, position): + continue + + # Otherwise, there should be a comma + match = self._COMMA_RE.match(s, position) + if match is None: + raise ValueError("comma", position) + position = match.end() + + # We never saw a close bracket. + raise ValueError("close bracket", position) + + def _read_partial_featdict(self, s, position, match, reentrances, fstruct): + # If there was a prefix feature, record it. + if match.group(2): + if self._prefix_feature is None: + raise ValueError("open bracket or identifier", match.start(2)) + prefixval = match.group(2).strip() + if prefixval.startswith("?"): + prefixval = Variable(prefixval) + fstruct[self._prefix_feature] = prefixval + + # If group 3 is empty, then we just have a bare prefix, so + # we're done. + if not match.group(3): + return self._finalize(s, match.end(), reentrances, fstruct) + + # Build a list of the features defined by the structure. + # Each feature has one of the three following forms: + # name = value + # name -> (target) + # +name + # -name + while position < len(s): + # Use these variables to hold info about each feature: + name = value = None + + # Check for the close bracket. + match = self._END_FSTRUCT_RE.match(s, position) + if match is not None: + return self._finalize(s, match.end(), reentrances, fstruct) + + # Get the feature name's name + match = self._FEATURE_NAME_RE.match(s, position) + if match is None: + raise ValueError("feature name", position) + name = match.group(2) + position = match.end() + + # Check if it's a special feature. + if name[0] == "*" and name[-1] == "*": + name = self._features.get(name[1:-1]) + if name is None: + raise ValueError("known special feature", match.start(2)) + + # Check if this feature has a value already. + if name in fstruct: + raise ValueError("new name", match.start(2)) + + # Boolean value ("+name" or "-name") + if match.group(1) == "+": + value = True + if match.group(1) == "-": + value = False + + # Reentrance link ("-> (target)") + if value is None: + match = self._REENTRANCE_RE.match(s, position) + if match is not None: + position = match.end() + match = self._TARGET_RE.match(s, position) + if not match: + raise ValueError("identifier", position) + target = match.group(1) + if target not in reentrances: + raise ValueError("bound identifier", position) + position = match.end() + value = reentrances[target] + + # Assignment ("= value"). + if value is None: + match = self._ASSIGN_RE.match(s, position) + if match: + position = match.end() + value, position = self._read_value(name, s, position, reentrances) + # None of the above: error. + else: + raise ValueError("equals sign", position) + + # Store the value. + fstruct[name] = value + + # If there's a close bracket, handle it at the top of the loop. + if self._END_FSTRUCT_RE.match(s, position): + continue + + # Otherwise, there should be a comma + match = self._COMMA_RE.match(s, position) + if match is None: + raise ValueError("comma", position) + position = match.end() + + # We never saw a close bracket. + raise ValueError("close bracket", position) + + def _finalize(self, s, pos, reentrances, fstruct): + """ + Called when we see the close brace -- checks for a slash feature, + and adds in default values. + """ + # Add the slash feature (if any) + match = self._SLASH_RE.match(s, pos) + if match: + name = self._slash_feature + v, pos = self._read_value(name, s, match.end(), reentrances) + fstruct[name] = v + ## Add any default features. -- handle in unficiation instead? + # for feature in self._features_with_defaults: + # fstruct.setdefault(feature, feature.default) + # Return the value. + return fstruct, pos + + def _read_value(self, name, s, position, reentrances): + if isinstance(name, Feature): + return name.read_value(s, position, reentrances, self) + else: + return self.read_value(s, position, reentrances) + + def read_value(self, s, position, reentrances): + for (handler, regexp) in self.VALUE_HANDLERS: + match = regexp.match(s, position) + if match: + handler_func = getattr(self, handler) + return handler_func(s, position, reentrances, match) + raise ValueError("value", position) + + def _error(self, s, expected, position): + lines = s.split("\n") + while position > len(lines[0]): + position -= len(lines.pop(0)) + 1 # +1 for the newline. + estr = ( + "Error parsing feature structure\n " + + lines[0] + + "\n " + + " " * position + + "^ " + + "Expected %s" % expected + ) + raise ValueError(estr) + + # //////////////////////////////////////////////////////////// + # { Value Readers + # //////////////////////////////////////////////////////////// + + #: A table indicating how feature values should be processed. Each + #: entry in the table is a pair (handler, regexp). The first entry + #: with a matching regexp will have its handler called. Handlers + #: should have the following signature:: + #: + #: def handler(s, position, reentrances, match): ... + #: + #: and should return a tuple (value, position), where position is + #: the string position where the value ended. (n.b.: order is + #: important here!) + VALUE_HANDLERS = [ + ("read_fstruct_value", _START_FSTRUCT_RE), + ("read_var_value", re.compile(r"\?[a-zA-Z_][a-zA-Z0-9_]*")), + ("read_str_value", re.compile("[uU]?[rR]?(['\"])")), + ("read_int_value", re.compile(r"-?\d+")), + ("read_sym_value", re.compile(r"[a-zA-Z_][a-zA-Z0-9_]*")), + ( + "read_app_value", + re.compile(r"<(app)\((\?[a-z][a-z]*)\s*," r"\s*(\?[a-z][a-z]*)\)>"), + ), + # ('read_logic_value', re.compile(r'<([^>]*)>')), + # lazily match any character after '<' until we hit a '>' not preceded by '-' + ("read_logic_value", re.compile(r"<(.*?)(?")), + ("read_set_value", re.compile(r"{")), + ("read_tuple_value", re.compile(r"\(")), + ] + + def read_fstruct_value(self, s, position, reentrances, match): + return self.read_partial(s, position, reentrances) + + def read_str_value(self, s, position, reentrances, match): + return read_str(s, position) + + def read_int_value(self, s, position, reentrances, match): + return int(match.group()), match.end() + + # Note: the '?' is included in the variable name. + def read_var_value(self, s, position, reentrances, match): + return Variable(match.group()), match.end() + + _SYM_CONSTS = {"None": None, "True": True, "False": False} + + def read_sym_value(self, s, position, reentrances, match): + val, end = match.group(), match.end() + return self._SYM_CONSTS.get(val, val), end + + def read_app_value(self, s, position, reentrances, match): + """Mainly included for backwards compat.""" + return self._logic_parser.parse("%s(%s)" % match.group(2, 3)), match.end() + + def read_logic_value(self, s, position, reentrances, match): + try: + try: + expr = self._logic_parser.parse(match.group(1)) + except LogicalExpressionException as e: + raise ValueError from e + return expr, match.end() + except ValueError as e: + raise ValueError("logic expression", match.start(1)) from e + + def read_tuple_value(self, s, position, reentrances, match): + return self._read_seq_value( + s, position, reentrances, match, ")", FeatureValueTuple, FeatureValueConcat + ) + + def read_set_value(self, s, position, reentrances, match): + return self._read_seq_value( + s, position, reentrances, match, "}", FeatureValueSet, FeatureValueUnion + ) + + def _read_seq_value( + self, s, position, reentrances, match, close_paren, seq_class, plus_class + ): + """ + Helper function used by read_tuple_value and read_set_value. + """ + cp = re.escape(close_paren) + position = match.end() + # Special syntax of empty tuples: + m = re.compile(r"\s*/?\s*%s" % cp).match(s, position) + if m: + return seq_class(), m.end() + # Read values: + values = [] + seen_plus = False + while True: + # Close paren: return value. + m = re.compile(r"\s*%s" % cp).match(s, position) + if m: + if seen_plus: + return plus_class(values), m.end() + else: + return seq_class(values), m.end() + + # Read the next value. + val, position = self.read_value(s, position, reentrances) + values.append(val) + + # Comma or looking at close paren + m = re.compile(r"\s*(,|\+|(?=%s))\s*" % cp).match(s, position) + if not m: + raise ValueError("',' or '+' or '%s'" % cp, position) + if m.group(1) == "+": + seen_plus = True + position = m.end() + + +###################################################################### +# { Demo +###################################################################### + + +def display_unification(fs1, fs2, indent=" "): + # Print the two input feature structures, side by side. + fs1_lines = ("%s" % fs1).split("\n") + fs2_lines = ("%s" % fs2).split("\n") + if len(fs1_lines) > len(fs2_lines): + blankline = "[" + " " * (len(fs2_lines[0]) - 2) + "]" + fs2_lines += [blankline] * len(fs1_lines) + else: + blankline = "[" + " " * (len(fs1_lines[0]) - 2) + "]" + fs1_lines += [blankline] * len(fs2_lines) + for (fs1_line, fs2_line) in zip(fs1_lines, fs2_lines): + print(indent + fs1_line + " " + fs2_line) + print(indent + "-" * len(fs1_lines[0]) + " " + "-" * len(fs2_lines[0])) + + linelen = len(fs1_lines[0]) * 2 + 3 + print(indent + "| |".center(linelen)) + print(indent + "+-----UNIFY-----+".center(linelen)) + print(indent + "|".center(linelen)) + print(indent + "V".center(linelen)) + + bindings = {} + + result = fs1.unify(fs2, bindings) + if result is None: + print(indent + "(FAILED)".center(linelen)) + else: + print( + "\n".join(indent + l.center(linelen) for l in ("%s" % result).split("\n")) + ) + if bindings and len(bindings.bound_variables()) > 0: + print(repr(bindings).center(linelen)) + return result + + +def interactive_demo(trace=False): + import random + import sys + + HELP = """ + 1-%d: Select the corresponding feature structure + q: Quit + t: Turn tracing on or off + l: List all feature structures + ?: Help + """ + + print( + """ + This demo will repeatedly present you with a list of feature + structures, and ask you to choose two for unification. Whenever a + new feature structure is generated, it is added to the list of + choices that you can pick from. However, since this can be a + large number of feature structures, the demo will only print out a + random subset for you to choose between at a given time. If you + want to see the complete lists, type "l". For a list of valid + commands, type "?". + """ + ) + print('Press "Enter" to continue...') + sys.stdin.readline() + + fstruct_strings = [ + "[agr=[number=sing, gender=masc]]", + "[agr=[gender=masc, person=3]]", + "[agr=[gender=fem, person=3]]", + "[subj=[agr=(1)[]], agr->(1)]", + "[obj=?x]", + "[subj=?x]", + "[/=None]", + "[/=NP]", + "[cat=NP]", + "[cat=VP]", + "[cat=PP]", + "[subj=[agr=[gender=?y]], obj=[agr=[gender=?y]]]", + "[gender=masc, agr=?C]", + "[gender=?S, agr=[gender=?S,person=3]]", + ] + + all_fstructs = [ + (i, FeatStruct(fstruct_strings[i])) for i in range(len(fstruct_strings)) + ] + + def list_fstructs(fstructs): + for i, fstruct in fstructs: + print() + lines = ("%s" % fstruct).split("\n") + print("%3d: %s" % (i + 1, lines[0])) + for line in lines[1:]: + print(" " + line) + print() + + while True: + # Pick 5 feature structures at random from the master list. + MAX_CHOICES = 5 + if len(all_fstructs) > MAX_CHOICES: + fstructs = sorted(random.sample(all_fstructs, MAX_CHOICES)) + else: + fstructs = all_fstructs + + print("_" * 75) + + print("Choose two feature structures to unify:") + list_fstructs(fstructs) + + selected = [None, None] + for (nth, i) in (("First", 0), ("Second", 1)): + while selected[i] is None: + print( + ( + "%s feature structure (1-%d,q,t,l,?): " + % (nth, len(all_fstructs)) + ), + end=" ", + ) + try: + input = sys.stdin.readline().strip() + if input in ("q", "Q", "x", "X"): + return + if input in ("t", "T"): + trace = not trace + print(" Trace = %s" % trace) + continue + if input in ("h", "H", "?"): + print(HELP % len(fstructs)) + continue + if input in ("l", "L"): + list_fstructs(all_fstructs) + continue + num = int(input) - 1 + selected[i] = all_fstructs[num][1] + print() + except: + print("Bad sentence number") + continue + + if trace: + result = selected[0].unify(selected[1], trace=1) + else: + result = display_unification(selected[0], selected[1]) + if result is not None: + for i, fstruct in all_fstructs: + if repr(result) == repr(fstruct): + break + else: + all_fstructs.append((len(all_fstructs), result)) + + print('\nType "Enter" to continue unifying; or "q" to quit.') + input = sys.stdin.readline().strip() + if input in ("q", "Q", "x", "X"): + return + + +def demo(trace=False): + """ + Just for testing + """ + # import random + + # processor breaks with values like '3rd' + fstruct_strings = [ + "[agr=[number=sing, gender=masc]]", + "[agr=[gender=masc, person=3]]", + "[agr=[gender=fem, person=3]]", + "[subj=[agr=(1)[]], agr->(1)]", + "[obj=?x]", + "[subj=?x]", + "[/=None]", + "[/=NP]", + "[cat=NP]", + "[cat=VP]", + "[cat=PP]", + "[subj=[agr=[gender=?y]], obj=[agr=[gender=?y]]]", + "[gender=masc, agr=?C]", + "[gender=?S, agr=[gender=?S,person=3]]", + ] + all_fstructs = [FeatStruct(fss) for fss in fstruct_strings] + # MAX_CHOICES = 5 + # if len(all_fstructs) > MAX_CHOICES: + # fstructs = random.sample(all_fstructs, MAX_CHOICES) + # fstructs.sort() + # else: + # fstructs = all_fstructs + + for fs1 in all_fstructs: + for fs2 in all_fstructs: + print( + "\n*******************\nfs1 is:\n%s\n\nfs2 is:\n%s\n\nresult is:\n%s" + % (fs1, fs2, unify(fs1, fs2)) + ) + + +if __name__ == "__main__": + demo() + +__all__ = [ + "FeatStruct", + "FeatDict", + "FeatList", + "unify", + "subsumes", + "conflicts", + "Feature", + "SlashFeature", + "RangeFeature", + "SLASH", + "TYPE", + "FeatStructReader", +] diff --git a/llmeval-env/lib/python3.10/site-packages/nltk/grammar.py b/llmeval-env/lib/python3.10/site-packages/nltk/grammar.py new file mode 100644 index 0000000000000000000000000000000000000000..c0f1fe736a4a84e0982780e514108a6812f6876b --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/nltk/grammar.py @@ -0,0 +1,1708 @@ +# Natural Language Toolkit: Context Free Grammars +# +# Copyright (C) 2001-2023 NLTK Project +# Author: Steven Bird +# Edward Loper +# Jason Narad +# Peter Ljunglöf +# Tom Aarsen <> +# URL: +# For license information, see LICENSE.TXT +# + +""" +Basic data classes for representing context free grammars. A +"grammar" specifies which trees can represent the structure of a +given text. Each of these trees is called a "parse tree" for the +text (or simply a "parse"). In a "context free" grammar, the set of +parse trees for any piece of a text can depend only on that piece, and +not on the rest of the text (i.e., the piece's context). Context free +grammars are often used to find possible syntactic structures for +sentences. In this context, the leaves of a parse tree are word +tokens; and the node values are phrasal categories, such as ``NP`` +and ``VP``. + +The ``CFG`` class is used to encode context free grammars. Each +``CFG`` consists of a start symbol and a set of productions. +The "start symbol" specifies the root node value for parse trees. For example, +the start symbol for syntactic parsing is usually ``S``. Start +symbols are encoded using the ``Nonterminal`` class, which is discussed +below. + +A Grammar's "productions" specify what parent-child relationships a parse +tree can contain. Each production specifies that a particular +node can be the parent of a particular set of children. For example, +the production `` -> `` specifies that an ``S`` node can +be the parent of an ``NP`` node and a ``VP`` node. + +Grammar productions are implemented by the ``Production`` class. +Each ``Production`` consists of a left hand side and a right hand +side. The "left hand side" is a ``Nonterminal`` that specifies the +node type for a potential parent; and the "right hand side" is a list +that specifies allowable children for that parent. This lists +consists of ``Nonterminals`` and text types: each ``Nonterminal`` +indicates that the corresponding child may be a ``TreeToken`` with the +specified node type; and each text type indicates that the +corresponding child may be a ``Token`` with the with that type. + +The ``Nonterminal`` class is used to distinguish node values from leaf +values. This prevents the grammar from accidentally using a leaf +value (such as the English word "A") as the node of a subtree. Within +a ``CFG``, all node values are wrapped in the ``Nonterminal`` +class. Note, however, that the trees that are specified by the grammar do +*not* include these ``Nonterminal`` wrappers. + +Grammars can also be given a more procedural interpretation. According to +this interpretation, a Grammar specifies any tree structure *tree* that +can be produced by the following procedure: + +| Set tree to the start symbol +| Repeat until tree contains no more nonterminal leaves: +| Choose a production prod with whose left hand side +| lhs is a nonterminal leaf of tree. +| Replace the nonterminal leaf with a subtree, whose node +| value is the value wrapped by the nonterminal lhs, and +| whose children are the right hand side of prod. + +The operation of replacing the left hand side (*lhs*) of a production +with the right hand side (*rhs*) in a tree (*tree*) is known as +"expanding" *lhs* to *rhs* in *tree*. +""" +import re +from functools import total_ordering + +from nltk.featstruct import SLASH, TYPE, FeatDict, FeatStruct, FeatStructReader +from nltk.internals import raise_unorderable_types +from nltk.probability import ImmutableProbabilisticMixIn +from nltk.util import invert_graph, transitive_closure + +################################################################# +# Nonterminal +################################################################# + + +@total_ordering +class Nonterminal: + """ + A non-terminal symbol for a context free grammar. ``Nonterminal`` + is a wrapper class for node values; it is used by ``Production`` + objects to distinguish node values from leaf values. + The node value that is wrapped by a ``Nonterminal`` is known as its + "symbol". Symbols are typically strings representing phrasal + categories (such as ``"NP"`` or ``"VP"``). However, more complex + symbol types are sometimes used (e.g., for lexicalized grammars). + Since symbols are node values, they must be immutable and + hashable. Two ``Nonterminals`` are considered equal if their + symbols are equal. + + :see: ``CFG``, ``Production`` + :type _symbol: any + :ivar _symbol: The node value corresponding to this + ``Nonterminal``. This value must be immutable and hashable. + """ + + def __init__(self, symbol): + """ + Construct a new non-terminal from the given symbol. + + :type symbol: any + :param symbol: The node value corresponding to this + ``Nonterminal``. This value must be immutable and + hashable. + """ + self._symbol = symbol + + def symbol(self): + """ + Return the node value corresponding to this ``Nonterminal``. + + :rtype: (any) + """ + return self._symbol + + def __eq__(self, other): + """ + Return True if this non-terminal is equal to ``other``. In + particular, return True if ``other`` is a ``Nonterminal`` + and this non-terminal's symbol is equal to ``other`` 's symbol. + + :rtype: bool + """ + return type(self) == type(other) and self._symbol == other._symbol + + def __ne__(self, other): + return not self == other + + def __lt__(self, other): + if not isinstance(other, Nonterminal): + raise_unorderable_types("<", self, other) + return self._symbol < other._symbol + + def __hash__(self): + return hash(self._symbol) + + def __repr__(self): + """ + Return a string representation for this ``Nonterminal``. + + :rtype: str + """ + if isinstance(self._symbol, str): + return "%s" % self._symbol + else: + return "%s" % repr(self._symbol) + + def __str__(self): + """ + Return a string representation for this ``Nonterminal``. + + :rtype: str + """ + if isinstance(self._symbol, str): + return "%s" % self._symbol + else: + return "%s" % repr(self._symbol) + + def __div__(self, rhs): + """ + Return a new nonterminal whose symbol is ``A/B``, where ``A`` is + the symbol for this nonterminal, and ``B`` is the symbol for rhs. + + :param rhs: The nonterminal used to form the right hand side + of the new nonterminal. + :type rhs: Nonterminal + :rtype: Nonterminal + """ + return Nonterminal(f"{self._symbol}/{rhs._symbol}") + + def __truediv__(self, rhs): + """ + Return a new nonterminal whose symbol is ``A/B``, where ``A`` is + the symbol for this nonterminal, and ``B`` is the symbol for rhs. + This function allows use of the slash ``/`` operator with + the future import of division. + + :param rhs: The nonterminal used to form the right hand side + of the new nonterminal. + :type rhs: Nonterminal + :rtype: Nonterminal + """ + return self.__div__(rhs) + + +def nonterminals(symbols): + """ + Given a string containing a list of symbol names, return a list of + ``Nonterminals`` constructed from those symbols. + + :param symbols: The symbol name string. This string can be + delimited by either spaces or commas. + :type symbols: str + :return: A list of ``Nonterminals`` constructed from the symbol + names given in ``symbols``. The ``Nonterminals`` are sorted + in the same order as the symbols names. + :rtype: list(Nonterminal) + """ + if "," in symbols: + symbol_list = symbols.split(",") + else: + symbol_list = symbols.split() + return [Nonterminal(s.strip()) for s in symbol_list] + + +class FeatStructNonterminal(FeatDict, Nonterminal): + """A feature structure that's also a nonterminal. It acts as its + own symbol, and automatically freezes itself when hashed.""" + + def __hash__(self): + self.freeze() + return FeatStruct.__hash__(self) + + def symbol(self): + return self + + +def is_nonterminal(item): + """ + :return: True if the item is a ``Nonterminal``. + :rtype: bool + """ + return isinstance(item, Nonterminal) + + +################################################################# +# Terminals +################################################################# + + +def is_terminal(item): + """ + Return True if the item is a terminal, which currently is + if it is hashable and not a ``Nonterminal``. + + :rtype: bool + """ + return hasattr(item, "__hash__") and not isinstance(item, Nonterminal) + + +################################################################# +# Productions +################################################################# + + +@total_ordering +class Production: + """ + A grammar production. Each production maps a single symbol + on the "left-hand side" to a sequence of symbols on the + "right-hand side". (In the case of context-free productions, + the left-hand side must be a ``Nonterminal``, and the right-hand + side is a sequence of terminals and ``Nonterminals``.) + "terminals" can be any immutable hashable object that is + not a ``Nonterminal``. Typically, terminals are strings + representing words, such as ``"dog"`` or ``"under"``. + + :see: ``CFG`` + :see: ``DependencyGrammar`` + :see: ``Nonterminal`` + :type _lhs: Nonterminal + :ivar _lhs: The left-hand side of the production. + :type _rhs: tuple(Nonterminal, terminal) + :ivar _rhs: The right-hand side of the production. + """ + + def __init__(self, lhs, rhs): + """ + Construct a new ``Production``. + + :param lhs: The left-hand side of the new ``Production``. + :type lhs: Nonterminal + :param rhs: The right-hand side of the new ``Production``. + :type rhs: sequence(Nonterminal and terminal) + """ + if isinstance(rhs, str): + raise TypeError( + "production right hand side should be a list, " "not a string" + ) + self._lhs = lhs + self._rhs = tuple(rhs) + + def lhs(self): + """ + Return the left-hand side of this ``Production``. + + :rtype: Nonterminal + """ + return self._lhs + + def rhs(self): + """ + Return the right-hand side of this ``Production``. + + :rtype: sequence(Nonterminal and terminal) + """ + return self._rhs + + def __len__(self): + """ + Return the length of the right-hand side. + + :rtype: int + """ + return len(self._rhs) + + def is_nonlexical(self): + """ + Return True if the right-hand side only contains ``Nonterminals`` + + :rtype: bool + """ + return all(is_nonterminal(n) for n in self._rhs) + + def is_lexical(self): + """ + Return True if the right-hand contain at least one terminal token. + + :rtype: bool + """ + return not self.is_nonlexical() + + def __str__(self): + """ + Return a verbose string representation of the ``Production``. + + :rtype: str + """ + result = "%s -> " % repr(self._lhs) + result += " ".join(repr(el) for el in self._rhs) + return result + + def __repr__(self): + """ + Return a concise string representation of the ``Production``. + + :rtype: str + """ + return "%s" % self + + def __eq__(self, other): + """ + Return True if this ``Production`` is equal to ``other``. + + :rtype: bool + """ + return ( + type(self) == type(other) + and self._lhs == other._lhs + and self._rhs == other._rhs + ) + + def __ne__(self, other): + return not self == other + + def __lt__(self, other): + if not isinstance(other, Production): + raise_unorderable_types("<", self, other) + return (self._lhs, self._rhs) < (other._lhs, other._rhs) + + def __hash__(self): + """ + Return a hash value for the ``Production``. + + :rtype: int + """ + return hash((self._lhs, self._rhs)) + + +class DependencyProduction(Production): + """ + A dependency grammar production. Each production maps a single + head word to an unordered list of one or more modifier words. + """ + + def __str__(self): + """ + Return a verbose string representation of the ``DependencyProduction``. + + :rtype: str + """ + result = f"'{self._lhs}' ->" + for elt in self._rhs: + result += f" '{elt}'" + return result + + +class ProbabilisticProduction(Production, ImmutableProbabilisticMixIn): + """ + A probabilistic context free grammar production. + A PCFG ``ProbabilisticProduction`` is essentially just a ``Production`` that + has an associated probability, which represents how likely it is that + this production will be used. In particular, the probability of a + ``ProbabilisticProduction`` records the likelihood that its right-hand side is + the correct instantiation for any given occurrence of its left-hand side. + + :see: ``Production`` + """ + + def __init__(self, lhs, rhs, **prob): + """ + Construct a new ``ProbabilisticProduction``. + + :param lhs: The left-hand side of the new ``ProbabilisticProduction``. + :type lhs: Nonterminal + :param rhs: The right-hand side of the new ``ProbabilisticProduction``. + :type rhs: sequence(Nonterminal and terminal) + :param prob: Probability parameters of the new ``ProbabilisticProduction``. + """ + ImmutableProbabilisticMixIn.__init__(self, **prob) + Production.__init__(self, lhs, rhs) + + def __str__(self): + return super().__str__() + ( + " [1.0]" if (self.prob() == 1.0) else " [%g]" % self.prob() + ) + + def __eq__(self, other): + return ( + type(self) == type(other) + and self._lhs == other._lhs + and self._rhs == other._rhs + and self.prob() == other.prob() + ) + + def __ne__(self, other): + return not self == other + + def __hash__(self): + return hash((self._lhs, self._rhs, self.prob())) + + +################################################################# +# Grammars +################################################################# + + +class CFG: + """ + A context-free grammar. A grammar consists of a start state and + a set of productions. The set of terminals and nonterminals is + implicitly specified by the productions. + + If you need efficient key-based access to productions, you + can use a subclass to implement it. + """ + + def __init__(self, start, productions, calculate_leftcorners=True): + """ + Create a new context-free grammar, from the given start state + and set of ``Production`` instances. + + :param start: The start symbol + :type start: Nonterminal + :param productions: The list of productions that defines the grammar + :type productions: list(Production) + :param calculate_leftcorners: False if we don't want to calculate the + leftcorner relation. In that case, some optimized chart parsers won't work. + :type calculate_leftcorners: bool + """ + if not is_nonterminal(start): + raise TypeError( + "start should be a Nonterminal object," + " not a %s" % type(start).__name__ + ) + + self._start = start + self._productions = productions + self._categories = {prod.lhs() for prod in productions} + self._calculate_indexes() + self._calculate_grammar_forms() + if calculate_leftcorners: + self._calculate_leftcorners() + + def _calculate_indexes(self): + self._lhs_index = {} + self._rhs_index = {} + self._empty_index = {} + self._lexical_index = {} + for prod in self._productions: + # Left hand side. + lhs = prod._lhs + if lhs not in self._lhs_index: + self._lhs_index[lhs] = [] + self._lhs_index[lhs].append(prod) + if prod._rhs: + # First item in right hand side. + rhs0 = prod._rhs[0] + if rhs0 not in self._rhs_index: + self._rhs_index[rhs0] = [] + self._rhs_index[rhs0].append(prod) + else: + # The right hand side is empty. + self._empty_index[prod.lhs()] = prod + # Lexical tokens in the right hand side. + for token in prod._rhs: + if is_terminal(token): + self._lexical_index.setdefault(token, set()).add(prod) + + def _calculate_leftcorners(self): + # Calculate leftcorner relations, for use in optimized parsing. + self._immediate_leftcorner_categories = {cat: {cat} for cat in self._categories} + self._immediate_leftcorner_words = {cat: set() for cat in self._categories} + for prod in self.productions(): + if len(prod) > 0: + cat, left = prod.lhs(), prod.rhs()[0] + if is_nonterminal(left): + self._immediate_leftcorner_categories[cat].add(left) + else: + self._immediate_leftcorner_words[cat].add(left) + + lc = transitive_closure(self._immediate_leftcorner_categories, reflexive=True) + self._leftcorners = lc + self._leftcorner_parents = invert_graph(lc) + + nr_leftcorner_categories = sum( + map(len, self._immediate_leftcorner_categories.values()) + ) + nr_leftcorner_words = sum(map(len, self._immediate_leftcorner_words.values())) + if nr_leftcorner_words > nr_leftcorner_categories > 10000: + # If the grammar is big, the leftcorner-word dictionary will be too large. + # In that case it is better to calculate the relation on demand. + self._leftcorner_words = None + return + + self._leftcorner_words = {} + for cat in self._leftcorners: + lefts = self._leftcorners[cat] + lc = self._leftcorner_words[cat] = set() + for left in lefts: + lc.update(self._immediate_leftcorner_words.get(left, set())) + + @classmethod + def fromstring(cls, input, encoding=None): + """ + Return the grammar instance corresponding to the input string(s). + + :param input: a grammar, either in the form of a string or as a list of strings. + """ + start, productions = read_grammar( + input, standard_nonterm_parser, encoding=encoding + ) + return cls(start, productions) + + def start(self): + """ + Return the start symbol of the grammar + + :rtype: Nonterminal + """ + return self._start + + # tricky to balance readability and efficiency here! + # can't use set operations as they don't preserve ordering + def productions(self, lhs=None, rhs=None, empty=False): + """ + Return the grammar productions, filtered by the left-hand side + or the first item in the right-hand side. + + :param lhs: Only return productions with the given left-hand side. + :param rhs: Only return productions with the given first item + in the right-hand side. + :param empty: Only return productions with an empty right-hand side. + :return: A list of productions matching the given constraints. + :rtype: list(Production) + """ + if rhs and empty: + raise ValueError( + "You cannot select empty and non-empty " "productions at the same time." + ) + + # no constraints so return everything + if not lhs and not rhs: + if not empty: + return self._productions + else: + return self._empty_index.values() + + # only lhs specified so look up its index + elif lhs and not rhs: + if not empty: + return self._lhs_index.get(lhs, []) + elif lhs in self._empty_index: + return [self._empty_index[lhs]] + else: + return [] + + # only rhs specified so look up its index + elif rhs and not lhs: + return self._rhs_index.get(rhs, []) + + # intersect + else: + return [ + prod + for prod in self._lhs_index.get(lhs, []) + if prod in self._rhs_index.get(rhs, []) + ] + + def leftcorners(self, cat): + """ + Return the set of all nonterminals that the given nonterminal + can start with, including itself. + + This is the reflexive, transitive closure of the immediate + leftcorner relation: (A > B) iff (A -> B beta) + + :param cat: the parent of the leftcorners + :type cat: Nonterminal + :return: the set of all leftcorners + :rtype: set(Nonterminal) + """ + return self._leftcorners.get(cat, {cat}) + + def is_leftcorner(self, cat, left): + """ + True if left is a leftcorner of cat, where left can be a + terminal or a nonterminal. + + :param cat: the parent of the leftcorner + :type cat: Nonterminal + :param left: the suggested leftcorner + :type left: Terminal or Nonterminal + :rtype: bool + """ + if is_nonterminal(left): + return left in self.leftcorners(cat) + elif self._leftcorner_words: + return left in self._leftcorner_words.get(cat, set()) + else: + return any( + left in self._immediate_leftcorner_words.get(parent, set()) + for parent in self.leftcorners(cat) + ) + + def leftcorner_parents(self, cat): + """ + Return the set of all nonterminals for which the given category + is a left corner. This is the inverse of the leftcorner relation. + + :param cat: the suggested leftcorner + :type cat: Nonterminal + :return: the set of all parents to the leftcorner + :rtype: set(Nonterminal) + """ + return self._leftcorner_parents.get(cat, {cat}) + + def check_coverage(self, tokens): + """ + Check whether the grammar rules cover the given list of tokens. + If not, then raise an exception. + + :type tokens: list(str) + """ + missing = [tok for tok in tokens if not self._lexical_index.get(tok)] + if missing: + missing = ", ".join(f"{w!r}" for w in missing) + raise ValueError( + "Grammar does not cover some of the " "input words: %r." % missing + ) + + def _calculate_grammar_forms(self): + """ + Pre-calculate of which form(s) the grammar is. + """ + prods = self._productions + self._is_lexical = all(p.is_lexical() for p in prods) + self._is_nonlexical = all(p.is_nonlexical() for p in prods if len(p) != 1) + self._min_len = min(len(p) for p in prods) + self._max_len = max(len(p) for p in prods) + self._all_unary_are_lexical = all(p.is_lexical() for p in prods if len(p) == 1) + + def is_lexical(self): + """ + Return True if all productions are lexicalised. + """ + return self._is_lexical + + def is_nonlexical(self): + """ + Return True if all lexical rules are "preterminals", that is, + unary rules which can be separated in a preprocessing step. + + This means that all productions are of the forms + A -> B1 ... Bn (n>=0), or A -> "s". + + Note: is_lexical() and is_nonlexical() are not opposites. + There are grammars which are neither, and grammars which are both. + """ + return self._is_nonlexical + + def min_len(self): + """ + Return the right-hand side length of the shortest grammar production. + """ + return self._min_len + + def max_len(self): + """ + Return the right-hand side length of the longest grammar production. + """ + return self._max_len + + def is_nonempty(self): + """ + Return True if there are no empty productions. + """ + return self._min_len > 0 + + def is_binarised(self): + """ + Return True if all productions are at most binary. + Note that there can still be empty and unary productions. + """ + return self._max_len <= 2 + + def is_flexible_chomsky_normal_form(self): + """ + Return True if all productions are of the forms + A -> B C, A -> B, or A -> "s". + """ + return self.is_nonempty() and self.is_nonlexical() and self.is_binarised() + + def is_chomsky_normal_form(self): + """ + Return True if the grammar is of Chomsky Normal Form, i.e. all productions + are of the form A -> B C, or A -> "s". + """ + return self.is_flexible_chomsky_normal_form() and self._all_unary_are_lexical + + def chomsky_normal_form(self, new_token_padding="@$@", flexible=False): + """ + Returns a new Grammar that is in chomsky normal + + :param: new_token_padding + Customise new rule formation during binarisation + """ + if self.is_chomsky_normal_form(): + return self + if self.productions(empty=True): + raise ValueError( + "Grammar has Empty rules. " "Cannot deal with them at the moment" + ) + + # check for mixed rules + for rule in self.productions(): + if rule.is_lexical() and len(rule.rhs()) > 1: + raise ValueError( + f"Cannot handled mixed rule {rule.lhs()} => {rule.rhs()}" + ) + + step1 = CFG.eliminate_start(self) + step2 = CFG.binarize(step1, new_token_padding) + if flexible: + return step2 + step3 = CFG.remove_unitary_rules(step2) + step4 = CFG(step3.start(), list(set(step3.productions()))) + return step4 + + @classmethod + def remove_unitary_rules(cls, grammar): + """ + Remove nonlexical unitary rules and convert them to + lexical + """ + result = [] + unitary = [] + for rule in grammar.productions(): + if len(rule) == 1 and rule.is_nonlexical(): + unitary.append(rule) + else: + result.append(rule) + + while unitary: + rule = unitary.pop(0) + for item in grammar.productions(lhs=rule.rhs()[0]): + new_rule = Production(rule.lhs(), item.rhs()) + if len(new_rule) != 1 or new_rule.is_lexical(): + result.append(new_rule) + else: + unitary.append(new_rule) + + n_grammar = CFG(grammar.start(), result) + return n_grammar + + @classmethod + def binarize(cls, grammar, padding="@$@"): + """ + Convert all non-binary rules into binary by introducing + new tokens. + Example:: + + Original: + A => B C D + After Conversion: + A => B A@$@B + A@$@B => C D + """ + result = [] + + for rule in grammar.productions(): + if len(rule.rhs()) > 2: + # this rule needs to be broken down + left_side = rule.lhs() + for k in range(0, len(rule.rhs()) - 2): + tsym = rule.rhs()[k] + new_sym = Nonterminal(left_side.symbol() + padding + tsym.symbol()) + new_production = Production(left_side, (tsym, new_sym)) + left_side = new_sym + result.append(new_production) + last_prd = Production(left_side, rule.rhs()[-2:]) + result.append(last_prd) + else: + result.append(rule) + + n_grammar = CFG(grammar.start(), result) + return n_grammar + + @classmethod + def eliminate_start(cls, grammar): + """ + Eliminate start rule in case it appears on RHS + Example: S -> S0 S1 and S0 -> S1 S + Then another rule S0_Sigma -> S is added + """ + start = grammar.start() + result = [] + need_to_add = None + for rule in grammar.productions(): + if start in rule.rhs(): + need_to_add = True + result.append(rule) + if need_to_add: + start = Nonterminal("S0_SIGMA") + result.append(Production(start, [grammar.start()])) + n_grammar = CFG(start, result) + return n_grammar + return grammar + + def __repr__(self): + return "" % len(self._productions) + + def __str__(self): + result = "Grammar with %d productions" % len(self._productions) + result += " (start state = %r)" % self._start + for production in self._productions: + result += "\n %s" % production + return result + + +class FeatureGrammar(CFG): + """ + A feature-based grammar. This is equivalent to a + ``CFG`` whose nonterminals are all + ``FeatStructNonterminal``. + + A grammar consists of a start state and a set of + productions. The set of terminals and nonterminals + is implicitly specified by the productions. + """ + + def __init__(self, start, productions): + """ + Create a new feature-based grammar, from the given start + state and set of ``Productions``. + + :param start: The start symbol + :type start: FeatStructNonterminal + :param productions: The list of productions that defines the grammar + :type productions: list(Production) + """ + CFG.__init__(self, start, productions) + + # The difference with CFG is that the productions are + # indexed on the TYPE feature of the nonterminals. + # This is calculated by the method _get_type_if_possible(). + + def _calculate_indexes(self): + self._lhs_index = {} + self._rhs_index = {} + self._empty_index = {} + self._empty_productions = [] + self._lexical_index = {} + for prod in self._productions: + # Left hand side. + lhs = self._get_type_if_possible(prod._lhs) + if lhs not in self._lhs_index: + self._lhs_index[lhs] = [] + self._lhs_index[lhs].append(prod) + if prod._rhs: + # First item in right hand side. + rhs0 = self._get_type_if_possible(prod._rhs[0]) + if rhs0 not in self._rhs_index: + self._rhs_index[rhs0] = [] + self._rhs_index[rhs0].append(prod) + else: + # The right hand side is empty. + if lhs not in self._empty_index: + self._empty_index[lhs] = [] + self._empty_index[lhs].append(prod) + self._empty_productions.append(prod) + # Lexical tokens in the right hand side. + for token in prod._rhs: + if is_terminal(token): + self._lexical_index.setdefault(token, set()).add(prod) + + @classmethod + def fromstring( + cls, input, features=None, logic_parser=None, fstruct_reader=None, encoding=None + ): + """ + Return a feature structure based grammar. + + :param input: a grammar, either in the form of a string or else + as a list of strings. + :param features: a tuple of features (default: SLASH, TYPE) + :param logic_parser: a parser for lambda-expressions, + by default, ``LogicParser()`` + :param fstruct_reader: a feature structure parser + (only if features and logic_parser is None) + """ + if features is None: + features = (SLASH, TYPE) + + if fstruct_reader is None: + fstruct_reader = FeatStructReader( + features, FeatStructNonterminal, logic_parser=logic_parser + ) + elif logic_parser is not None: + raise Exception( + "'logic_parser' and 'fstruct_reader' must " "not both be set" + ) + + start, productions = read_grammar( + input, fstruct_reader.read_partial, encoding=encoding + ) + return cls(start, productions) + + def productions(self, lhs=None, rhs=None, empty=False): + """ + Return the grammar productions, filtered by the left-hand side + or the first item in the right-hand side. + + :param lhs: Only return productions with the given left-hand side. + :param rhs: Only return productions with the given first item + in the right-hand side. + :param empty: Only return productions with an empty right-hand side. + :rtype: list(Production) + """ + if rhs and empty: + raise ValueError( + "You cannot select empty and non-empty " "productions at the same time." + ) + + # no constraints so return everything + if not lhs and not rhs: + if empty: + return self._empty_productions + else: + return self._productions + + # only lhs specified so look up its index + elif lhs and not rhs: + if empty: + return self._empty_index.get(self._get_type_if_possible(lhs), []) + else: + return self._lhs_index.get(self._get_type_if_possible(lhs), []) + + # only rhs specified so look up its index + elif rhs and not lhs: + return self._rhs_index.get(self._get_type_if_possible(rhs), []) + + # intersect + else: + return [ + prod + for prod in self._lhs_index.get(self._get_type_if_possible(lhs), []) + if prod in self._rhs_index.get(self._get_type_if_possible(rhs), []) + ] + + def leftcorners(self, cat): + """ + Return the set of all words that the given category can start with. + Also called the "first set" in compiler construction. + """ + raise NotImplementedError("Not implemented yet") + + def leftcorner_parents(self, cat): + """ + Return the set of all categories for which the given category + is a left corner. + """ + raise NotImplementedError("Not implemented yet") + + def _get_type_if_possible(self, item): + """ + Helper function which returns the ``TYPE`` feature of the ``item``, + if it exists, otherwise it returns the ``item`` itself + """ + if isinstance(item, dict) and TYPE in item: + return FeatureValueType(item[TYPE]) + else: + return item + + +@total_ordering +class FeatureValueType: + """ + A helper class for ``FeatureGrammars``, designed to be different + from ordinary strings. This is to stop the ``FeatStruct`` + ``FOO[]`` from being compare equal to the terminal "FOO". + """ + + def __init__(self, value): + self._value = value + + def __repr__(self): + return "<%s>" % self._value + + def __eq__(self, other): + return type(self) == type(other) and self._value == other._value + + def __ne__(self, other): + return not self == other + + def __lt__(self, other): + if not isinstance(other, FeatureValueType): + raise_unorderable_types("<", self, other) + return self._value < other._value + + def __hash__(self): + return hash(self._value) + + +class DependencyGrammar: + """ + A dependency grammar. A DependencyGrammar consists of a set of + productions. Each production specifies a head/modifier relationship + between a pair of words. + """ + + def __init__(self, productions): + """ + Create a new dependency grammar, from the set of ``Productions``. + + :param productions: The list of productions that defines the grammar + :type productions: list(Production) + """ + self._productions = productions + + @classmethod + def fromstring(cls, input): + productions = [] + for linenum, line in enumerate(input.split("\n")): + line = line.strip() + if line.startswith("#") or line == "": + continue + try: + productions += _read_dependency_production(line) + except ValueError as e: + raise ValueError(f"Unable to parse line {linenum}: {line}") from e + if len(productions) == 0: + raise ValueError("No productions found!") + return cls(productions) + + def contains(self, head, mod): + """ + :param head: A head word. + :type head: str + :param mod: A mod word, to test as a modifier of 'head'. + :type mod: str + + :return: true if this ``DependencyGrammar`` contains a + ``DependencyProduction`` mapping 'head' to 'mod'. + :rtype: bool + """ + for production in self._productions: + for possibleMod in production._rhs: + if production._lhs == head and possibleMod == mod: + return True + return False + + def __contains__(self, head_mod): + """ + Return True if this ``DependencyGrammar`` contains a + ``DependencyProduction`` mapping 'head' to 'mod'. + + :param head_mod: A tuple of a head word and a mod word, + to test as a modifier of 'head'. + :type head: Tuple[str, str] + :rtype: bool + """ + try: + head, mod = head_mod + except ValueError as e: + raise ValueError( + "Must use a tuple of strings, e.g. `('price', 'of') in grammar`" + ) from e + return self.contains(head, mod) + + # # should be rewritten, the set comp won't work in all comparisons + # def contains_exactly(self, head, modlist): + # for production in self._productions: + # if(len(production._rhs) == len(modlist)): + # if(production._lhs == head): + # set1 = Set(production._rhs) + # set2 = Set(modlist) + # if(set1 == set2): + # return True + # return False + + def __str__(self): + """ + Return a verbose string representation of the ``DependencyGrammar`` + + :rtype: str + """ + str = "Dependency grammar with %d productions" % len(self._productions) + for production in self._productions: + str += "\n %s" % production + return str + + def __repr__(self): + """ + Return a concise string representation of the ``DependencyGrammar`` + """ + return "Dependency grammar with %d productions" % len(self._productions) + + +class ProbabilisticDependencyGrammar: + """ """ + + def __init__(self, productions, events, tags): + self._productions = productions + self._events = events + self._tags = tags + + def contains(self, head, mod): + """ + Return True if this ``DependencyGrammar`` contains a + ``DependencyProduction`` mapping 'head' to 'mod'. + + :param head: A head word. + :type head: str + :param mod: A mod word, to test as a modifier of 'head'. + :type mod: str + :rtype: bool + """ + for production in self._productions: + for possibleMod in production._rhs: + if production._lhs == head and possibleMod == mod: + return True + return False + + def __str__(self): + """ + Return a verbose string representation of the ``ProbabilisticDependencyGrammar`` + + :rtype: str + """ + str = "Statistical dependency grammar with %d productions" % len( + self._productions + ) + for production in self._productions: + str += "\n %s" % production + str += "\nEvents:" + for event in self._events: + str += "\n %d:%s" % (self._events[event], event) + str += "\nTags:" + for tag_word in self._tags: + str += f"\n {tag_word}:\t({self._tags[tag_word]})" + return str + + def __repr__(self): + """ + Return a concise string representation of the ``ProbabilisticDependencyGrammar`` + """ + return "Statistical Dependency grammar with %d productions" % len( + self._productions + ) + + +class PCFG(CFG): + """ + A probabilistic context-free grammar. A PCFG consists of a + start state and a set of productions with probabilities. The set of + terminals and nonterminals is implicitly specified by the productions. + + PCFG productions use the ``ProbabilisticProduction`` class. + ``PCFGs`` impose the constraint that the set of productions with + any given left-hand-side must have probabilities that sum to 1 + (allowing for a small margin of error). + + If you need efficient key-based access to productions, you can use + a subclass to implement it. + + :type EPSILON: float + :cvar EPSILON: The acceptable margin of error for checking that + productions with a given left-hand side have probabilities + that sum to 1. + """ + + EPSILON = 0.01 + + def __init__(self, start, productions, calculate_leftcorners=True): + """ + Create a new context-free grammar, from the given start state + and set of ``ProbabilisticProductions``. + + :param start: The start symbol + :type start: Nonterminal + :param productions: The list of productions that defines the grammar + :type productions: list(Production) + :raise ValueError: if the set of productions with any left-hand-side + do not have probabilities that sum to a value within + EPSILON of 1. + :param calculate_leftcorners: False if we don't want to calculate the + leftcorner relation. In that case, some optimized chart parsers won't work. + :type calculate_leftcorners: bool + """ + CFG.__init__(self, start, productions, calculate_leftcorners) + + # Make sure that the probabilities sum to one. + probs = {} + for production in productions: + probs[production.lhs()] = probs.get(production.lhs(), 0) + production.prob() + for (lhs, p) in probs.items(): + if not ((1 - PCFG.EPSILON) < p < (1 + PCFG.EPSILON)): + raise ValueError("Productions for %r do not sum to 1" % lhs) + + @classmethod + def fromstring(cls, input, encoding=None): + """ + Return a probabilistic context-free grammar corresponding to the + input string(s). + + :param input: a grammar, either in the form of a string or else + as a list of strings. + """ + start, productions = read_grammar( + input, standard_nonterm_parser, probabilistic=True, encoding=encoding + ) + return cls(start, productions) + + +################################################################# +# Inducing Grammars +################################################################# + +# Contributed by Nathan Bodenstab + + +def induce_pcfg(start, productions): + r""" + Induce a PCFG grammar from a list of productions. + + The probability of a production A -> B C in a PCFG is: + + | count(A -> B C) + | P(B, C | A) = --------------- where \* is any right hand side + | count(A -> \*) + + :param start: The start symbol + :type start: Nonterminal + :param productions: The list of productions that defines the grammar + :type productions: list(Production) + """ + # Production count: the number of times a given production occurs + pcount = {} + + # LHS-count: counts the number of times a given lhs occurs + lcount = {} + + for prod in productions: + lcount[prod.lhs()] = lcount.get(prod.lhs(), 0) + 1 + pcount[prod] = pcount.get(prod, 0) + 1 + + prods = [ + ProbabilisticProduction(p.lhs(), p.rhs(), prob=pcount[p] / lcount[p.lhs()]) + for p in pcount + ] + return PCFG(start, prods) + + +################################################################# +# Helper functions for reading productions +################################################################# + + +def _read_cfg_production(input): + """ + Return a list of context-free ``Productions``. + """ + return _read_production(input, standard_nonterm_parser) + + +def _read_pcfg_production(input): + """ + Return a list of PCFG ``ProbabilisticProductions``. + """ + return _read_production(input, standard_nonterm_parser, probabilistic=True) + + +def _read_fcfg_production(input, fstruct_reader): + """ + Return a list of feature-based ``Productions``. + """ + return _read_production(input, fstruct_reader) + + +# Parsing generic grammars + +_ARROW_RE = re.compile(r"\s* -> \s*", re.VERBOSE) +_PROBABILITY_RE = re.compile(r"( \[ [\d\.]+ \] ) \s*", re.VERBOSE) +_TERMINAL_RE = re.compile(r'( "[^"]*" | \'[^\']*\' ) \s*', re.VERBOSE) +_DISJUNCTION_RE = re.compile(r"\| \s*", re.VERBOSE) + + +def _read_production(line, nonterm_parser, probabilistic=False): + """ + Parse a grammar rule, given as a string, and return + a list of productions. + """ + pos = 0 + + # Parse the left-hand side. + lhs, pos = nonterm_parser(line, pos) + + # Skip over the arrow. + m = _ARROW_RE.match(line, pos) + if not m: + raise ValueError("Expected an arrow") + pos = m.end() + + # Parse the right hand side. + probabilities = [0.0] + rhsides = [[]] + while pos < len(line): + # Probability. + m = _PROBABILITY_RE.match(line, pos) + if probabilistic and m: + pos = m.end() + probabilities[-1] = float(m.group(1)[1:-1]) + if probabilities[-1] > 1.0: + raise ValueError( + "Production probability %f, " + "should not be greater than 1.0" % (probabilities[-1],) + ) + + # String -- add terminal. + elif line[pos] in "'\"": + m = _TERMINAL_RE.match(line, pos) + if not m: + raise ValueError("Unterminated string") + rhsides[-1].append(m.group(1)[1:-1]) + pos = m.end() + + # Vertical bar -- start new rhside. + elif line[pos] == "|": + m = _DISJUNCTION_RE.match(line, pos) + probabilities.append(0.0) + rhsides.append([]) + pos = m.end() + + # Anything else -- nonterminal. + else: + nonterm, pos = nonterm_parser(line, pos) + rhsides[-1].append(nonterm) + + if probabilistic: + return [ + ProbabilisticProduction(lhs, rhs, prob=probability) + for (rhs, probability) in zip(rhsides, probabilities) + ] + else: + return [Production(lhs, rhs) for rhs in rhsides] + + +################################################################# +# Reading Phrase Structure Grammars +################################################################# + + +def read_grammar(input, nonterm_parser, probabilistic=False, encoding=None): + """ + Return a pair consisting of a starting category and a list of + ``Productions``. + + :param input: a grammar, either in the form of a string or else + as a list of strings. + :param nonterm_parser: a function for parsing nonterminals. + It should take a ``(string, position)`` as argument and + return a ``(nonterminal, position)`` as result. + :param probabilistic: are the grammar rules probabilistic? + :type probabilistic: bool + :param encoding: the encoding of the grammar, if it is a binary string + :type encoding: str + """ + if encoding is not None: + input = input.decode(encoding) + if isinstance(input, str): + lines = input.split("\n") + else: + lines = input + + start = None + productions = [] + continue_line = "" + for linenum, line in enumerate(lines): + line = continue_line + line.strip() + if line.startswith("#") or line == "": + continue + if line.endswith("\\"): + continue_line = line[:-1].rstrip() + " " + continue + continue_line = "" + try: + if line[0] == "%": + directive, args = line[1:].split(None, 1) + if directive == "start": + start, pos = nonterm_parser(args, 0) + if pos != len(args): + raise ValueError("Bad argument to start directive") + else: + raise ValueError("Bad directive") + else: + # expand out the disjunctions on the RHS + productions += _read_production(line, nonterm_parser, probabilistic) + except ValueError as e: + raise ValueError(f"Unable to parse line {linenum + 1}: {line}\n{e}") from e + + if not productions: + raise ValueError("No productions found!") + if not start: + start = productions[0].lhs() + return (start, productions) + + +_STANDARD_NONTERM_RE = re.compile(r"( [\w/][\w/^<>-]* ) \s*", re.VERBOSE) + + +def standard_nonterm_parser(string, pos): + m = _STANDARD_NONTERM_RE.match(string, pos) + if not m: + raise ValueError("Expected a nonterminal, found: " + string[pos:]) + return (Nonterminal(m.group(1)), m.end()) + + +################################################################# +# Reading Dependency Grammars +################################################################# + +_READ_DG_RE = re.compile( + r"""^\s* # leading whitespace + ('[^']+')\s* # single-quoted lhs + (?:[-=]+>)\s* # arrow + (?:( # rhs: + "[^"]+" # doubled-quoted terminal + | '[^']+' # single-quoted terminal + | \| # disjunction + ) + \s*) # trailing space + *$""", # zero or more copies + re.VERBOSE, +) +_SPLIT_DG_RE = re.compile(r"""('[^']'|[-=]+>|"[^"]+"|'[^']+'|\|)""") + + +def _read_dependency_production(s): + if not _READ_DG_RE.match(s): + raise ValueError("Bad production string") + pieces = _SPLIT_DG_RE.split(s) + pieces = [p for i, p in enumerate(pieces) if i % 2 == 1] + lhside = pieces[0].strip("'\"") + rhsides = [[]] + for piece in pieces[2:]: + if piece == "|": + rhsides.append([]) + else: + rhsides[-1].append(piece.strip("'\"")) + return [DependencyProduction(lhside, rhside) for rhside in rhsides] + + +################################################################# +# Demonstration +################################################################# + + +def cfg_demo(): + """ + A demonstration showing how ``CFGs`` can be created and used. + """ + + from nltk import CFG, Production, nonterminals + + # Create some nonterminals + S, NP, VP, PP = nonterminals("S, NP, VP, PP") + N, V, P, Det = nonterminals("N, V, P, Det") + VP_slash_NP = VP / NP + + print("Some nonterminals:", [S, NP, VP, PP, N, V, P, Det, VP / NP]) + print(" S.symbol() =>", repr(S.symbol())) + print() + + print(Production(S, [NP])) + + # Create some Grammar Productions + grammar = CFG.fromstring( + """ + S -> NP VP + PP -> P NP + NP -> Det N | NP PP + VP -> V NP | VP PP + Det -> 'a' | 'the' + N -> 'dog' | 'cat' + V -> 'chased' | 'sat' + P -> 'on' | 'in' + """ + ) + + print("A Grammar:", repr(grammar)) + print(" grammar.start() =>", repr(grammar.start())) + print(" grammar.productions() =>", end=" ") + # Use string.replace(...) is to line-wrap the output. + print(repr(grammar.productions()).replace(",", ",\n" + " " * 25)) + print() + + +def pcfg_demo(): + """ + A demonstration showing how a ``PCFG`` can be created and used. + """ + + from nltk import induce_pcfg, treetransforms + from nltk.corpus import treebank + from nltk.parse import pchart + + toy_pcfg1 = PCFG.fromstring( + """ + S -> NP VP [1.0] + NP -> Det N [0.5] | NP PP [0.25] | 'John' [0.1] | 'I' [0.15] + Det -> 'the' [0.8] | 'my' [0.2] + N -> 'man' [0.5] | 'telescope' [0.5] + VP -> VP PP [0.1] | V NP [0.7] | V [0.2] + V -> 'ate' [0.35] | 'saw' [0.65] + PP -> P NP [1.0] + P -> 'with' [0.61] | 'under' [0.39] + """ + ) + + toy_pcfg2 = PCFG.fromstring( + """ + S -> NP VP [1.0] + VP -> V NP [.59] + VP -> V [.40] + VP -> VP PP [.01] + NP -> Det N [.41] + NP -> Name [.28] + NP -> NP PP [.31] + PP -> P NP [1.0] + V -> 'saw' [.21] + V -> 'ate' [.51] + V -> 'ran' [.28] + N -> 'boy' [.11] + N -> 'cookie' [.12] + N -> 'table' [.13] + N -> 'telescope' [.14] + N -> 'hill' [.5] + Name -> 'Jack' [.52] + Name -> 'Bob' [.48] + P -> 'with' [.61] + P -> 'under' [.39] + Det -> 'the' [.41] + Det -> 'a' [.31] + Det -> 'my' [.28] + """ + ) + + pcfg_prods = toy_pcfg1.productions() + + pcfg_prod = pcfg_prods[2] + print("A PCFG production:", repr(pcfg_prod)) + print(" pcfg_prod.lhs() =>", repr(pcfg_prod.lhs())) + print(" pcfg_prod.rhs() =>", repr(pcfg_prod.rhs())) + print(" pcfg_prod.prob() =>", repr(pcfg_prod.prob())) + print() + + grammar = toy_pcfg2 + print("A PCFG grammar:", repr(grammar)) + print(" grammar.start() =>", repr(grammar.start())) + print(" grammar.productions() =>", end=" ") + # Use .replace(...) is to line-wrap the output. + print(repr(grammar.productions()).replace(",", ",\n" + " " * 26)) + print() + + # extract productions from three trees and induce the PCFG + print("Induce PCFG grammar from treebank data:") + + productions = [] + item = treebank._fileids[0] + for tree in treebank.parsed_sents(item)[:3]: + # perform optional tree transformations, e.g.: + tree.collapse_unary(collapsePOS=False) + tree.chomsky_normal_form(horzMarkov=2) + + productions += tree.productions() + + S = Nonterminal("S") + grammar = induce_pcfg(S, productions) + print(grammar) + print() + + print("Parse sentence using induced grammar:") + + parser = pchart.InsideChartParser(grammar) + parser.trace(3) + + # doesn't work as tokens are different: + # sent = treebank.tokenized('wsj_0001.mrg')[0] + + sent = treebank.parsed_sents(item)[0].leaves() + print(sent) + for parse in parser.parse(sent): + print(parse) + + +def fcfg_demo(): + import nltk.data + + g = nltk.data.load("grammars/book_grammars/feat0.fcfg") + print(g) + print() + + +def dg_demo(): + """ + A demonstration showing the creation and inspection of a + ``DependencyGrammar``. + """ + grammar = DependencyGrammar.fromstring( + """ + 'scratch' -> 'cats' | 'walls' + 'walls' -> 'the' + 'cats' -> 'the' + """ + ) + print(grammar) + + +def sdg_demo(): + """ + A demonstration of how to read a string representation of + a CoNLL format dependency tree. + """ + from nltk.parse import DependencyGraph + + dg = DependencyGraph( + """ + 1 Ze ze Pron Pron per|3|evofmv|nom 2 su _ _ + 2 had heb V V trans|ovt|1of2of3|ev 0 ROOT _ _ + 3 met met Prep Prep voor 8 mod _ _ + 4 haar haar Pron Pron bez|3|ev|neut|attr 5 det _ _ + 5 moeder moeder N N soort|ev|neut 3 obj1 _ _ + 6 kunnen kan V V hulp|ott|1of2of3|mv 2 vc _ _ + 7 gaan ga V V hulp|inf 6 vc _ _ + 8 winkelen winkel V V intrans|inf 11 cnj _ _ + 9 , , Punc Punc komma 8 punct _ _ + 10 zwemmen zwem V V intrans|inf 11 cnj _ _ + 11 of of Conj Conj neven 7 vc _ _ + 12 terrassen terras N N soort|mv|neut 11 cnj _ _ + 13 . . Punc Punc punt 12 punct _ _ + """ + ) + tree = dg.tree() + print(tree.pprint()) + + +def demo(): + cfg_demo() + pcfg_demo() + fcfg_demo() + dg_demo() + sdg_demo() + + +if __name__ == "__main__": + demo() + +__all__ = [ + "Nonterminal", + "nonterminals", + "CFG", + "Production", + "PCFG", + "ProbabilisticProduction", + "DependencyGrammar", + "DependencyProduction", + "ProbabilisticDependencyGrammar", + "induce_pcfg", + "read_grammar", +] diff --git a/llmeval-env/lib/python3.10/site-packages/nltk/help.py b/llmeval-env/lib/python3.10/site-packages/nltk/help.py new file mode 100644 index 0000000000000000000000000000000000000000..e0b5f7b876cda304a7fdaeecfbab9278113058df --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/nltk/help.py @@ -0,0 +1,64 @@ +# Natural Language Toolkit (NLTK) Help +# +# Copyright (C) 2001-2023 NLTK Project +# Authors: Steven Bird +# URL: +# For license information, see LICENSE.TXT + +""" +Provide structured access to documentation. +""" + +import re +from textwrap import wrap + +from nltk.data import load + + +def brown_tagset(tagpattern=None): + _format_tagset("brown_tagset", tagpattern) + + +def claws5_tagset(tagpattern=None): + _format_tagset("claws5_tagset", tagpattern) + + +def upenn_tagset(tagpattern=None): + _format_tagset("upenn_tagset", tagpattern) + + +##################################################################### +# UTILITIES +##################################################################### + + +def _print_entries(tags, tagdict): + for tag in tags: + entry = tagdict[tag] + defn = [tag + ": " + entry[0]] + examples = wrap( + entry[1], width=75, initial_indent=" ", subsequent_indent=" " + ) + print("\n".join(defn + examples)) + + +def _format_tagset(tagset, tagpattern=None): + tagdict = load("help/tagsets/" + tagset + ".pickle") + if not tagpattern: + _print_entries(sorted(tagdict), tagdict) + elif tagpattern in tagdict: + _print_entries([tagpattern], tagdict) + else: + tagpattern = re.compile(tagpattern) + tags = [tag for tag in sorted(tagdict) if tagpattern.match(tag)] + if tags: + _print_entries(tags, tagdict) + else: + print("No matching tags found.") + + +if __name__ == "__main__": + brown_tagset(r"NN.*") + upenn_tagset(r".*\$") + claws5_tagset("UNDEFINED") + brown_tagset(r"NN") diff --git a/llmeval-env/lib/python3.10/site-packages/nltk/internals.py b/llmeval-env/lib/python3.10/site-packages/nltk/internals.py new file mode 100644 index 0000000000000000000000000000000000000000..b53d77da5e976c08f2cb002759e9da1044dc9bf0 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/nltk/internals.py @@ -0,0 +1,1123 @@ +# Natural Language Toolkit: Internal utility functions +# +# Copyright (C) 2001-2023 NLTK Project +# Author: Steven Bird +# Edward Loper +# Nitin Madnani +# URL: +# For license information, see LICENSE.TXT + +import fnmatch +import locale +import os +import re +import stat +import subprocess +import sys +import textwrap +import types +import warnings +from xml.etree import ElementTree + +########################################################################## +# Java Via Command-Line +########################################################################## + +_java_bin = None +_java_options = [] +# [xx] add classpath option to config_java? +def config_java(bin=None, options=None, verbose=False): + """ + Configure nltk's java interface, by letting nltk know where it can + find the Java binary, and what extra options (if any) should be + passed to Java when it is run. + + :param bin: The full path to the Java binary. If not specified, + then nltk will search the system for a Java binary; and if + one is not found, it will raise a ``LookupError`` exception. + :type bin: str + :param options: A list of options that should be passed to the + Java binary when it is called. A common value is + ``'-Xmx512m'``, which tells Java binary to increase + the maximum heap size to 512 megabytes. If no options are + specified, then do not modify the options list. + :type options: list(str) + """ + global _java_bin, _java_options + _java_bin = find_binary( + "java", + bin, + env_vars=["JAVAHOME", "JAVA_HOME"], + verbose=verbose, + binary_names=["java.exe"], + ) + + if options is not None: + if isinstance(options, str): + options = options.split() + _java_options = list(options) + + +def java(cmd, classpath=None, stdin=None, stdout=None, stderr=None, blocking=True): + """ + Execute the given java command, by opening a subprocess that calls + Java. If java has not yet been configured, it will be configured + by calling ``config_java()`` with no arguments. + + :param cmd: The java command that should be called, formatted as + a list of strings. Typically, the first string will be the name + of the java class; and the remaining strings will be arguments + for that java class. + :type cmd: list(str) + + :param classpath: A ``':'`` separated list of directories, JAR + archives, and ZIP archives to search for class files. + :type classpath: str + + :param stdin: Specify the executed program's + standard input file handles, respectively. Valid values are ``subprocess.PIPE``, + an existing file descriptor (a positive integer), an existing + file object, 'pipe', 'stdout', 'devnull' and None. ``subprocess.PIPE`` indicates that a + new pipe to the child should be created. With None, no + redirection will occur; the child's file handles will be + inherited from the parent. Additionally, stderr can be + ``subprocess.STDOUT``, which indicates that the stderr data + from the applications should be captured into the same file + handle as for stdout. + + :param stdout: Specify the executed program's standard output file + handle. See ``stdin`` for valid values. + + :param stderr: Specify the executed program's standard error file + handle. See ``stdin`` for valid values. + + + :param blocking: If ``false``, then return immediately after + spawning the subprocess. In this case, the return value is + the ``Popen`` object, and not a ``(stdout, stderr)`` tuple. + + :return: If ``blocking=True``, then return a tuple ``(stdout, + stderr)``, containing the stdout and stderr outputs generated + by the java command if the ``stdout`` and ``stderr`` parameters + were set to ``subprocess.PIPE``; or None otherwise. If + ``blocking=False``, then return a ``subprocess.Popen`` object. + + :raise OSError: If the java command returns a nonzero return code. + """ + + subprocess_output_dict = { + "pipe": subprocess.PIPE, + "stdout": subprocess.STDOUT, + "devnull": subprocess.DEVNULL, + } + + stdin = subprocess_output_dict.get(stdin, stdin) + stdout = subprocess_output_dict.get(stdout, stdout) + stderr = subprocess_output_dict.get(stderr, stderr) + + if isinstance(cmd, str): + raise TypeError("cmd should be a list of strings") + + # Make sure we know where a java binary is. + if _java_bin is None: + config_java() + + # Set up the classpath. + if isinstance(classpath, str): + classpaths = [classpath] + else: + classpaths = list(classpath) + classpath = os.path.pathsep.join(classpaths) + + # Construct the full command string. + cmd = list(cmd) + cmd = ["-cp", classpath] + cmd + cmd = [_java_bin] + _java_options + cmd + + # Call java via a subprocess + p = subprocess.Popen(cmd, stdin=stdin, stdout=stdout, stderr=stderr) + if not blocking: + return p + (stdout, stderr) = p.communicate() + + # Check the return code. + if p.returncode != 0: + print(_decode_stdoutdata(stderr)) + raise OSError("Java command failed : " + str(cmd)) + + return (stdout, stderr) + + +###################################################################### +# Parsing +###################################################################### + + +class ReadError(ValueError): + """ + Exception raised by read_* functions when they fail. + :param position: The index in the input string where an error occurred. + :param expected: What was expected when an error occurred. + """ + + def __init__(self, expected, position): + ValueError.__init__(self, expected, position) + self.expected = expected + self.position = position + + def __str__(self): + return f"Expected {self.expected} at {self.position}" + + +_STRING_START_RE = re.compile(r"[uU]?[rR]?(\"\"\"|\'\'\'|\"|\')") + + +def read_str(s, start_position): + """ + If a Python string literal begins at the specified position in the + given string, then return a tuple ``(val, end_position)`` + containing the value of the string literal and the position where + it ends. Otherwise, raise a ``ReadError``. + + :param s: A string that will be checked to see if within which a + Python string literal exists. + :type s: str + + :param start_position: The specified beginning position of the string ``s`` + to begin regex matching. + :type start_position: int + + :return: A tuple containing the matched string literal evaluated as a + string and the end position of the string literal. + :rtype: tuple(str, int) + + :raise ReadError: If the ``_STRING_START_RE`` regex doesn't return a + match in ``s`` at ``start_position``, i.e., open quote. If the + ``_STRING_END_RE`` regex doesn't return a match in ``s`` at the + end of the first match, i.e., close quote. + :raise ValueError: If an invalid string (i.e., contains an invalid + escape sequence) is passed into the ``eval``. + + :Example: + + >>> from nltk.internals import read_str + >>> read_str('"Hello", World!', 0) + ('Hello', 7) + + """ + # Read the open quote, and any modifiers. + m = _STRING_START_RE.match(s, start_position) + if not m: + raise ReadError("open quote", start_position) + quotemark = m.group(1) + + # Find the close quote. + _STRING_END_RE = re.compile(r"\\|%s" % quotemark) + position = m.end() + while True: + match = _STRING_END_RE.search(s, position) + if not match: + raise ReadError("close quote", position) + if match.group(0) == "\\": + position = match.end() + 1 + else: + break + + # Process it, using eval. Strings with invalid escape sequences + # might raise ValueError. + try: + return eval(s[start_position : match.end()]), match.end() + except ValueError as e: + raise ReadError("valid escape sequence", start_position) from e + + +_READ_INT_RE = re.compile(r"-?\d+") + + +def read_int(s, start_position): + """ + If an integer begins at the specified position in the given + string, then return a tuple ``(val, end_position)`` containing the + value of the integer and the position where it ends. Otherwise, + raise a ``ReadError``. + + :param s: A string that will be checked to see if within which a + Python integer exists. + :type s: str + + :param start_position: The specified beginning position of the string ``s`` + to begin regex matching. + :type start_position: int + + :return: A tuple containing the matched integer casted to an int, + and the end position of the int in ``s``. + :rtype: tuple(int, int) + + :raise ReadError: If the ``_READ_INT_RE`` regex doesn't return a + match in ``s`` at ``start_position``. + + :Example: + + >>> from nltk.internals import read_int + >>> read_int('42 is the answer', 0) + (42, 2) + + """ + m = _READ_INT_RE.match(s, start_position) + if not m: + raise ReadError("integer", start_position) + return int(m.group()), m.end() + + +_READ_NUMBER_VALUE = re.compile(r"-?(\d*)([.]?\d*)?") + + +def read_number(s, start_position): + """ + If an integer or float begins at the specified position in the + given string, then return a tuple ``(val, end_position)`` + containing the value of the number and the position where it ends. + Otherwise, raise a ``ReadError``. + + :param s: A string that will be checked to see if within which a + Python number exists. + :type s: str + + :param start_position: The specified beginning position of the string ``s`` + to begin regex matching. + :type start_position: int + + :return: A tuple containing the matched number casted to a ``float``, + and the end position of the number in ``s``. + :rtype: tuple(float, int) + + :raise ReadError: If the ``_READ_NUMBER_VALUE`` regex doesn't return a + match in ``s`` at ``start_position``. + + :Example: + + >>> from nltk.internals import read_number + >>> read_number('Pi is 3.14159', 6) + (3.14159, 13) + + """ + m = _READ_NUMBER_VALUE.match(s, start_position) + if not m or not (m.group(1) or m.group(2)): + raise ReadError("number", start_position) + if m.group(2): + return float(m.group()), m.end() + else: + return int(m.group()), m.end() + + +###################################################################### +# Check if a method has been overridden +###################################################################### + + +def overridden(method): + """ + :return: True if ``method`` overrides some method with the same + name in a base class. This is typically used when defining + abstract base classes or interfaces, to allow subclasses to define + either of two related methods: + + >>> class EaterI: + ... '''Subclass must define eat() or batch_eat().''' + ... def eat(self, food): + ... if overridden(self.batch_eat): + ... return self.batch_eat([food])[0] + ... else: + ... raise NotImplementedError() + ... def batch_eat(self, foods): + ... return [self.eat(food) for food in foods] + + :type method: instance method + """ + if isinstance(method, types.MethodType) and method.__self__.__class__ is not None: + name = method.__name__ + funcs = [ + cls.__dict__[name] + for cls in _mro(method.__self__.__class__) + if name in cls.__dict__ + ] + return len(funcs) > 1 + else: + raise TypeError("Expected an instance method.") + + +def _mro(cls): + """ + Return the method resolution order for ``cls`` -- i.e., a list + containing ``cls`` and all its base classes, in the order in which + they would be checked by ``getattr``. For new-style classes, this + is just cls.__mro__. For classic classes, this can be obtained by + a depth-first left-to-right traversal of ``__bases__``. + """ + if isinstance(cls, type): + return cls.__mro__ + else: + mro = [cls] + for base in cls.__bases__: + mro.extend(_mro(base)) + return mro + + +###################################################################### +# Deprecation decorator & base class +###################################################################### +# [xx] dedent msg first if it comes from a docstring. + + +def _add_epytext_field(obj, field, message): + """Add an epytext @field to a given object's docstring.""" + indent = "" + # If we already have a docstring, then add a blank line to separate + # it from the new field, and check its indentation. + if obj.__doc__: + obj.__doc__ = obj.__doc__.rstrip() + "\n\n" + indents = re.findall(r"(?<=\n)[ ]+(?!\s)", obj.__doc__.expandtabs()) + if indents: + indent = min(indents) + # If we don't have a docstring, add an empty one. + else: + obj.__doc__ = "" + + obj.__doc__ += textwrap.fill( + f"@{field}: {message}", + initial_indent=indent, + subsequent_indent=indent + " ", + ) + + +def deprecated(message): + """ + A decorator used to mark functions as deprecated. This will cause + a warning to be printed the when the function is used. Usage: + + >>> from nltk.internals import deprecated + >>> @deprecated('Use foo() instead') + ... def bar(x): + ... print(x/10) + + """ + + def decorator(func): + msg = f"Function {func.__name__}() has been deprecated. {message}" + msg = "\n" + textwrap.fill(msg, initial_indent=" ", subsequent_indent=" ") + + def newFunc(*args, **kwargs): + warnings.warn(msg, category=DeprecationWarning, stacklevel=2) + return func(*args, **kwargs) + + # Copy the old function's name, docstring, & dict + newFunc.__dict__.update(func.__dict__) + newFunc.__name__ = func.__name__ + newFunc.__doc__ = func.__doc__ + newFunc.__deprecated__ = True + # Add a @deprecated field to the docstring. + _add_epytext_field(newFunc, "deprecated", message) + return newFunc + + return decorator + + +class Deprecated: + """ + A base class used to mark deprecated classes. A typical usage is to + alert users that the name of a class has changed: + + >>> from nltk.internals import Deprecated + >>> class NewClassName: + ... pass # All logic goes here. + ... + >>> class OldClassName(Deprecated, NewClassName): + ... "Use NewClassName instead." + + The docstring of the deprecated class will be used in the + deprecation warning message. + """ + + def __new__(cls, *args, **kwargs): + # Figure out which class is the deprecated one. + dep_cls = None + for base in _mro(cls): + if Deprecated in base.__bases__: + dep_cls = base + break + assert dep_cls, "Unable to determine which base is deprecated." + + # Construct an appropriate warning. + doc = dep_cls.__doc__ or "".strip() + # If there's a @deprecated field, strip off the field marker. + doc = re.sub(r"\A\s*@deprecated:", r"", doc) + # Strip off any indentation. + doc = re.sub(r"(?m)^\s*", "", doc) + # Construct a 'name' string. + name = "Class %s" % dep_cls.__name__ + if cls != dep_cls: + name += " (base class for %s)" % cls.__name__ + # Put it all together. + msg = f"{name} has been deprecated. {doc}" + # Wrap it. + msg = "\n" + textwrap.fill(msg, initial_indent=" ", subsequent_indent=" ") + warnings.warn(msg, category=DeprecationWarning, stacklevel=2) + # Do the actual work of __new__. + return object.__new__(cls) + + +########################################################################## +# COUNTER, FOR UNIQUE NAMING +########################################################################## + + +class Counter: + """ + A counter that auto-increments each time its value is read. + """ + + def __init__(self, initial_value=0): + self._value = initial_value + + def get(self): + self._value += 1 + return self._value + + +########################################################################## +# Search for files/binaries +########################################################################## + + +def find_file_iter( + filename, + env_vars=(), + searchpath=(), + file_names=None, + url=None, + verbose=False, + finding_dir=False, +): + """ + Search for a file to be used by nltk. + + :param filename: The name or path of the file. + :param env_vars: A list of environment variable names to check. + :param file_names: A list of alternative file names to check. + :param searchpath: List of directories to search. + :param url: URL presented to user for download help. + :param verbose: Whether or not to print path when a file is found. + """ + file_names = [filename] + (file_names or []) + assert isinstance(filename, str) + assert not isinstance(file_names, str) + assert not isinstance(searchpath, str) + if isinstance(env_vars, str): + env_vars = env_vars.split() + yielded = False + + # File exists, no magic + for alternative in file_names: + path_to_file = os.path.join(filename, alternative) + if os.path.isfile(path_to_file): + if verbose: + print(f"[Found {filename}: {path_to_file}]") + yielded = True + yield path_to_file + # Check the bare alternatives + if os.path.isfile(alternative): + if verbose: + print(f"[Found {filename}: {alternative}]") + yielded = True + yield alternative + # Check if the alternative is inside a 'file' directory + path_to_file = os.path.join(filename, "file", alternative) + if os.path.isfile(path_to_file): + if verbose: + print(f"[Found {filename}: {path_to_file}]") + yielded = True + yield path_to_file + + # Check environment variables + for env_var in env_vars: + if env_var in os.environ: + if finding_dir: # This is to file a directory instead of file + yielded = True + yield os.environ[env_var] + + for env_dir in os.environ[env_var].split(os.pathsep): + # Check if the environment variable contains a direct path to the bin + if os.path.isfile(env_dir): + if verbose: + print(f"[Found {filename}: {env_dir}]") + yielded = True + yield env_dir + # Check if the possible bin names exist inside the environment variable directories + for alternative in file_names: + path_to_file = os.path.join(env_dir, alternative) + if os.path.isfile(path_to_file): + if verbose: + print(f"[Found {filename}: {path_to_file}]") + yielded = True + yield path_to_file + # Check if the alternative is inside a 'file' directory + # path_to_file = os.path.join(env_dir, 'file', alternative) + + # Check if the alternative is inside a 'bin' directory + path_to_file = os.path.join(env_dir, "bin", alternative) + + if os.path.isfile(path_to_file): + if verbose: + print(f"[Found {filename}: {path_to_file}]") + yielded = True + yield path_to_file + + # Check the path list. + for directory in searchpath: + for alternative in file_names: + path_to_file = os.path.join(directory, alternative) + if os.path.isfile(path_to_file): + yielded = True + yield path_to_file + + # If we're on a POSIX system, then try using the 'which' command + # to find the file. + if os.name == "posix": + for alternative in file_names: + try: + p = subprocess.Popen( + ["which", alternative], + stdout=subprocess.PIPE, + stderr=subprocess.PIPE, + ) + stdout, stderr = p.communicate() + path = _decode_stdoutdata(stdout).strip() + if path.endswith(alternative) and os.path.exists(path): + if verbose: + print(f"[Found {filename}: {path}]") + yielded = True + yield path + except (KeyboardInterrupt, SystemExit, OSError): + raise + finally: + pass + + if not yielded: + msg = ( + "NLTK was unable to find the %s file!" + "\nUse software specific " + "configuration parameters" % filename + ) + if env_vars: + msg += " or set the %s environment variable" % env_vars[0] + msg += "." + if searchpath: + msg += "\n\n Searched in:" + msg += "".join("\n - %s" % d for d in searchpath) + if url: + msg += f"\n\n For more information on {filename}, see:\n <{url}>" + div = "=" * 75 + raise LookupError(f"\n\n{div}\n{msg}\n{div}") + + +def find_file( + filename, env_vars=(), searchpath=(), file_names=None, url=None, verbose=False +): + return next( + find_file_iter(filename, env_vars, searchpath, file_names, url, verbose) + ) + + +def find_dir( + filename, env_vars=(), searchpath=(), file_names=None, url=None, verbose=False +): + return next( + find_file_iter( + filename, env_vars, searchpath, file_names, url, verbose, finding_dir=True + ) + ) + + +def find_binary_iter( + name, + path_to_bin=None, + env_vars=(), + searchpath=(), + binary_names=None, + url=None, + verbose=False, +): + """ + Search for a file to be used by nltk. + + :param name: The name or path of the file. + :param path_to_bin: The user-supplied binary location (deprecated) + :param env_vars: A list of environment variable names to check. + :param file_names: A list of alternative file names to check. + :param searchpath: List of directories to search. + :param url: URL presented to user for download help. + :param verbose: Whether or not to print path when a file is found. + """ + yield from find_file_iter( + path_to_bin or name, env_vars, searchpath, binary_names, url, verbose + ) + + +def find_binary( + name, + path_to_bin=None, + env_vars=(), + searchpath=(), + binary_names=None, + url=None, + verbose=False, +): + return next( + find_binary_iter( + name, path_to_bin, env_vars, searchpath, binary_names, url, verbose + ) + ) + + +def find_jar_iter( + name_pattern, + path_to_jar=None, + env_vars=(), + searchpath=(), + url=None, + verbose=False, + is_regex=False, +): + """ + Search for a jar that is used by nltk. + + :param name_pattern: The name of the jar file + :param path_to_jar: The user-supplied jar location, or None. + :param env_vars: A list of environment variable names to check + in addition to the CLASSPATH variable which is + checked by default. + :param searchpath: List of directories to search. + :param is_regex: Whether name is a regular expression. + """ + + assert isinstance(name_pattern, str) + assert not isinstance(searchpath, str) + if isinstance(env_vars, str): + env_vars = env_vars.split() + yielded = False + + # Make sure we check the CLASSPATH first + env_vars = ["CLASSPATH"] + list(env_vars) + + # If an explicit location was given, then check it, and yield it if + # it's present; otherwise, complain. + if path_to_jar is not None: + if os.path.isfile(path_to_jar): + yielded = True + yield path_to_jar + else: + raise LookupError( + f"Could not find {name_pattern} jar file at {path_to_jar}" + ) + + # Check environment variables + for env_var in env_vars: + if env_var in os.environ: + if env_var == "CLASSPATH": + classpath = os.environ["CLASSPATH"] + for cp in classpath.split(os.path.pathsep): + cp = os.path.expanduser(cp) + if os.path.isfile(cp): + filename = os.path.basename(cp) + if ( + is_regex + and re.match(name_pattern, filename) + or (not is_regex and filename == name_pattern) + ): + if verbose: + print(f"[Found {name_pattern}: {cp}]") + yielded = True + yield cp + # The case where user put directory containing the jar file in the classpath + if os.path.isdir(cp): + if not is_regex: + if os.path.isfile(os.path.join(cp, name_pattern)): + if verbose: + print(f"[Found {name_pattern}: {cp}]") + yielded = True + yield os.path.join(cp, name_pattern) + else: + # Look for file using regular expression + for file_name in os.listdir(cp): + if re.match(name_pattern, file_name): + if verbose: + print( + "[Found %s: %s]" + % ( + name_pattern, + os.path.join(cp, file_name), + ) + ) + yielded = True + yield os.path.join(cp, file_name) + + else: + jar_env = os.path.expanduser(os.environ[env_var]) + jar_iter = ( + ( + os.path.join(jar_env, path_to_jar) + for path_to_jar in os.listdir(jar_env) + ) + if os.path.isdir(jar_env) + else (jar_env,) + ) + for path_to_jar in jar_iter: + if os.path.isfile(path_to_jar): + filename = os.path.basename(path_to_jar) + if ( + is_regex + and re.match(name_pattern, filename) + or (not is_regex and filename == name_pattern) + ): + if verbose: + print(f"[Found {name_pattern}: {path_to_jar}]") + yielded = True + yield path_to_jar + + # Check the path list. + for directory in searchpath: + if is_regex: + for filename in os.listdir(directory): + path_to_jar = os.path.join(directory, filename) + if os.path.isfile(path_to_jar): + if re.match(name_pattern, filename): + if verbose: + print(f"[Found {filename}: {path_to_jar}]") + yielded = True + yield path_to_jar + else: + path_to_jar = os.path.join(directory, name_pattern) + if os.path.isfile(path_to_jar): + if verbose: + print(f"[Found {name_pattern}: {path_to_jar}]") + yielded = True + yield path_to_jar + + if not yielded: + # If nothing was found, raise an error + msg = "NLTK was unable to find %s!" % name_pattern + if env_vars: + msg += " Set the %s environment variable" % env_vars[0] + msg = textwrap.fill(msg + ".", initial_indent=" ", subsequent_indent=" ") + if searchpath: + msg += "\n\n Searched in:" + msg += "".join("\n - %s" % d for d in searchpath) + if url: + msg += "\n\n For more information, on {}, see:\n <{}>".format( + name_pattern, + url, + ) + div = "=" * 75 + raise LookupError(f"\n\n{div}\n{msg}\n{div}") + + +def find_jar( + name_pattern, + path_to_jar=None, + env_vars=(), + searchpath=(), + url=None, + verbose=False, + is_regex=False, +): + return next( + find_jar_iter( + name_pattern, path_to_jar, env_vars, searchpath, url, verbose, is_regex + ) + ) + + +def find_jars_within_path(path_to_jars): + return [ + os.path.join(root, filename) + for root, dirnames, filenames in os.walk(path_to_jars) + for filename in fnmatch.filter(filenames, "*.jar") + ] + + +def _decode_stdoutdata(stdoutdata): + """Convert data read from stdout/stderr to unicode""" + if not isinstance(stdoutdata, bytes): + return stdoutdata + + encoding = getattr(sys.__stdout__, "encoding", locale.getpreferredencoding()) + if encoding is None: + return stdoutdata.decode() + return stdoutdata.decode(encoding) + + +########################################################################## +# Import Stdlib Module +########################################################################## + + +def import_from_stdlib(module): + """ + When python is run from within the nltk/ directory tree, the + current directory is included at the beginning of the search path. + Unfortunately, that means that modules within nltk can sometimes + shadow standard library modules. As an example, the stdlib + 'inspect' module will attempt to import the stdlib 'tokenize' + module, but will instead end up importing NLTK's 'tokenize' module + instead (causing the import to fail). + """ + old_path = sys.path + sys.path = [d for d in sys.path if d not in ("", ".")] + m = __import__(module) + sys.path = old_path + return m + + +########################################################################## +# Wrapper for ElementTree Elements +########################################################################## + + +class ElementWrapper: + """ + A wrapper around ElementTree Element objects whose main purpose is + to provide nicer __repr__ and __str__ methods. In addition, any + of the wrapped Element's methods that return other Element objects + are overridden to wrap those values before returning them. + + This makes Elements more convenient to work with in + interactive sessions and doctests, at the expense of some + efficiency. + """ + + # Prevent double-wrapping: + def __new__(cls, etree): + """ + Create and return a wrapper around a given Element object. + If ``etree`` is an ``ElementWrapper``, then ``etree`` is + returned as-is. + """ + if isinstance(etree, ElementWrapper): + return etree + else: + return object.__new__(ElementWrapper) + + def __init__(self, etree): + r""" + Initialize a new Element wrapper for ``etree``. + + If ``etree`` is a string, then it will be converted to an + Element object using ``ElementTree.fromstring()`` first: + + >>> ElementWrapper("") + \n"> + + """ + if isinstance(etree, str): + etree = ElementTree.fromstring(etree) + self.__dict__["_etree"] = etree + + def unwrap(self): + """ + Return the Element object wrapped by this wrapper. + """ + return self._etree + + ##//////////////////////////////////////////////////////////// + # { String Representation + ##//////////////////////////////////////////////////////////// + + def __repr__(self): + s = ElementTree.tostring(self._etree, encoding="utf8").decode("utf8") + if len(s) > 60: + e = s.rfind("<") + if (len(s) - e) > 30: + e = -20 + s = f"{s[:30]}...{s[e:]}" + return "" % s + + def __str__(self): + """ + :return: the result of applying ``ElementTree.tostring()`` to + the wrapped Element object. + """ + return ( + ElementTree.tostring(self._etree, encoding="utf8").decode("utf8").rstrip() + ) + + ##//////////////////////////////////////////////////////////// + # { Element interface Delegation (pass-through) + ##//////////////////////////////////////////////////////////// + + def __getattr__(self, attrib): + return getattr(self._etree, attrib) + + def __setattr__(self, attr, value): + return setattr(self._etree, attr, value) + + def __delattr__(self, attr): + return delattr(self._etree, attr) + + def __setitem__(self, index, element): + self._etree[index] = element + + def __delitem__(self, index): + del self._etree[index] + + def __setslice__(self, start, stop, elements): + self._etree[start:stop] = elements + + def __delslice__(self, start, stop): + del self._etree[start:stop] + + def __len__(self): + return len(self._etree) + + ##//////////////////////////////////////////////////////////// + # { Element interface Delegation (wrap result) + ##//////////////////////////////////////////////////////////// + + def __getitem__(self, index): + return ElementWrapper(self._etree[index]) + + def __getslice__(self, start, stop): + return [ElementWrapper(elt) for elt in self._etree[start:stop]] + + def getchildren(self): + return [ElementWrapper(elt) for elt in self._etree] + + def getiterator(self, tag=None): + return (ElementWrapper(elt) for elt in self._etree.getiterator(tag)) + + def makeelement(self, tag, attrib): + return ElementWrapper(self._etree.makeelement(tag, attrib)) + + def find(self, path): + elt = self._etree.find(path) + if elt is None: + return elt + else: + return ElementWrapper(elt) + + def findall(self, path): + return [ElementWrapper(elt) for elt in self._etree.findall(path)] + + +###################################################################### +# Helper for Handling Slicing +###################################################################### + + +def slice_bounds(sequence, slice_obj, allow_step=False): + """ + Given a slice, return the corresponding (start, stop) bounds, + taking into account None indices and negative indices. The + following guarantees are made for the returned start and stop values: + + - 0 <= start <= len(sequence) + - 0 <= stop <= len(sequence) + - start <= stop + + :raise ValueError: If ``slice_obj.step`` is not None. + :param allow_step: If true, then the slice object may have a + non-None step. If it does, then return a tuple + (start, stop, step). + """ + start, stop = (slice_obj.start, slice_obj.stop) + + # If allow_step is true, then include the step in our return + # value tuple. + if allow_step: + step = slice_obj.step + if step is None: + step = 1 + # Use a recursive call without allow_step to find the slice + # bounds. If step is negative, then the roles of start and + # stop (in terms of default values, etc), are swapped. + if step < 0: + start, stop = slice_bounds(sequence, slice(stop, start)) + else: + start, stop = slice_bounds(sequence, slice(start, stop)) + return start, stop, step + + # Otherwise, make sure that no non-default step value is used. + elif slice_obj.step not in (None, 1): + raise ValueError( + "slices with steps are not supported by %s" % sequence.__class__.__name__ + ) + + # Supply default offsets. + if start is None: + start = 0 + if stop is None: + stop = len(sequence) + + # Handle negative indices. + if start < 0: + start = max(0, len(sequence) + start) + if stop < 0: + stop = max(0, len(sequence) + stop) + + # Make sure stop doesn't go past the end of the list. Note that + # we avoid calculating len(sequence) if possible, because for lazy + # sequences, calculating the length of a sequence can be expensive. + if stop > 0: + try: + sequence[stop - 1] + except IndexError: + stop = len(sequence) + + # Make sure start isn't past stop. + start = min(start, stop) + + # That's all folks! + return start, stop + + +###################################################################### +# Permission Checking +###################################################################### + + +def is_writable(path): + # Ensure that it exists. + if not os.path.exists(path): + return False + + # If we're on a posix system, check its permissions. + if hasattr(os, "getuid"): + statdata = os.stat(path) + perm = stat.S_IMODE(statdata.st_mode) + # is it world-writable? + if perm & 0o002: + return True + # do we own it? + elif statdata.st_uid == os.getuid() and (perm & 0o200): + return True + # are we in a group that can write to it? + elif (statdata.st_gid in [os.getgid()] + os.getgroups()) and (perm & 0o020): + return True + # otherwise, we can't write to it. + else: + return False + + # Otherwise, we'll assume it's writable. + # [xx] should we do other checks on other platforms? + return True + + +###################################################################### +# NLTK Error reporting +###################################################################### + + +def raise_unorderable_types(ordering, a, b): + raise TypeError( + "unorderable types: %s() %s %s()" + % (type(a).__name__, ordering, type(b).__name__) + ) diff --git a/llmeval-env/lib/python3.10/site-packages/nltk/jsontags.py b/llmeval-env/lib/python3.10/site-packages/nltk/jsontags.py new file mode 100644 index 0000000000000000000000000000000000000000..58d73bf138d07236bc38979bd69266c5972b62b2 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/nltk/jsontags.py @@ -0,0 +1,65 @@ +# Natural Language Toolkit: JSON Encoder/Decoder Helpers +# +# Copyright (C) 2001-2023 NLTK Project +# Author: Steven Xu +# +# URL: +# For license information, see LICENSE.TXT + +""" +Register JSON tags, so the nltk data loader knows what module and class to look for. + +NLTK uses simple '!' tags to mark the types of objects, but the fully-qualified +"tag:nltk.org,2011:" prefix is also accepted in case anyone ends up +using it. +""" + +import json + +json_tags = {} + +TAG_PREFIX = "!" + + +def register_tag(cls): + """ + Decorates a class to register it's json tag. + """ + json_tags[TAG_PREFIX + getattr(cls, "json_tag")] = cls + return cls + + +class JSONTaggedEncoder(json.JSONEncoder): + def default(self, obj): + obj_tag = getattr(obj, "json_tag", None) + if obj_tag is None: + return super().default(obj) + obj_tag = TAG_PREFIX + obj_tag + obj = obj.encode_json_obj() + return {obj_tag: obj} + + +class JSONTaggedDecoder(json.JSONDecoder): + def decode(self, s): + return self.decode_obj(super().decode(s)) + + @classmethod + def decode_obj(cls, obj): + # Decode nested objects first. + if isinstance(obj, dict): + obj = {key: cls.decode_obj(val) for (key, val) in obj.items()} + elif isinstance(obj, list): + obj = list(cls.decode_obj(val) for val in obj) + # Check if we have a tagged object. + if not isinstance(obj, dict) or len(obj) != 1: + return obj + obj_tag = next(iter(obj.keys())) + if not obj_tag.startswith("!"): + return obj + if obj_tag not in json_tags: + raise ValueError("Unknown tag", obj_tag) + obj_cls = json_tags[obj_tag] + return obj_cls.decode_json_obj(obj[obj_tag]) + + +__all__ = ["register_tag", "json_tags", "JSONTaggedEncoder", "JSONTaggedDecoder"] diff --git a/llmeval-env/lib/python3.10/site-packages/nltk/langnames.py b/llmeval-env/lib/python3.10/site-packages/nltk/langnames.py new file mode 100644 index 0000000000000000000000000000000000000000..b7fa6b40a4b381b4b2c4f3ff42ee2450f3849465 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/nltk/langnames.py @@ -0,0 +1,730 @@ +# Natural Language Toolkit: Language Codes +# +# Copyright (C) 2022-2023 NLTK Project +# Author: Eric Kafe +# URL: +# For license information, see LICENSE.TXT +# +# iso639-3 language codes (C) https://iso639-3.sil.org/ + +""" +Translate between language names and language codes. + +The iso639-3 language codes were downloaded from the registration authority at +https://iso639-3.sil.org/ + +The iso639-3 codeset is evolving, so retired language codes are kept in the +"iso639retired" dictionary, which is used as fallback by the wrapper functions +"langname" and "langcode", in order to support the lookup of retired codes. + +The "langcode" function returns the current iso639-3 code if there is one, +and falls back to the retired code otherwise. As specified by BCP-47, +it returns the shortest (2-letter) code by default, but 3-letter codes +are also available: + + >>> import nltk.langnames as lgn + >>> lgn.langname('fri') #'fri' is a retired code + 'Western Frisian' + + The current code is different from the retired one: + >>> lgn.langcode('Western Frisian') + 'fy' + + >>> lgn.langcode('Western Frisian', typ = 3) + 'fry' + +""" + +import re +from warnings import warn + +from nltk.corpus import bcp47 + +codepattern = re.compile("[a-z][a-z][a-z]?") + + +def langname(tag, typ="full"): + """ + Convert a composite BCP-47 tag to a language name + + >>> from nltk.langnames import langname + >>> langname('ca-Latn-ES-valencia') + 'Catalan: Latin: Spain: Valencian' + + >>> langname('ca-Latn-ES-valencia', typ="short") + 'Catalan' + """ + tags = tag.split("-") + code = tags[0].lower() + if codepattern.fullmatch(code): + if code in iso639retired: # retired codes + return iso639retired[code] + elif code in iso639short: # 3-letter codes + code2 = iso639short[code] # convert to 2-letter code + warn(f"Shortening {code!r} to {code2!r}", stacklevel=2) + tag = "-".join([code2] + tags[1:]) + name = bcp47.name(tag) # parse according to BCP-47 + if typ == "full": + return name # include all subtags + elif name: + return name.split(":")[0] # only the language subtag + else: + warn(f"Could not find code in {code!r}", stacklevel=2) + + +def langcode(name, typ=2): + """ + Convert language name to iso639-3 language code. Returns the short 2-letter + code by default, if one is available, and the 3-letter code otherwise: + + >>> from nltk.langnames import langcode + >>> langcode('Modern Greek (1453-)') + 'el' + + Specify 'typ=3' to get the 3-letter code: + + >>> langcode('Modern Greek (1453-)', typ=3) + 'ell' + """ + if name in bcp47.langcode: + code = bcp47.langcode[name] + if typ == 3 and code in iso639long: + code = iso639long[code] # convert to 3-letter code + return code + elif name in iso639code_retired: + return iso639code_retired[name] + else: + warn(f"Could not find language in {name!r}", stacklevel=2) + + +# ======================================================================= +# Translate betwwen Wikidata Q-codes and BCP-47 codes or names +# ....................................................................... + + +def tag2q(tag): + """ + Convert BCP-47 tag to Wikidata Q-code + + >>> tag2q('nds-u-sd-demv') + 'Q4289225' + """ + return bcp47.wiki_q[tag] + + +def q2tag(qcode): + """ + Convert Wikidata Q-code to BCP-47 tag + + >>> q2tag('Q4289225') + 'nds-u-sd-demv' + """ + return wiki_bcp47[qcode] + + +def q2name(qcode, typ="full"): + """ + Convert Wikidata Q-code to BCP-47 (full or short) language name + + >>> q2name('Q4289225') + 'Low German: Mecklenburg-Vorpommern' + + >>> q2name('Q4289225', "short") + 'Low German' + """ + return langname(q2tag(qcode), typ) + + +def lang2q(name): + """ + Convert simple language name to Wikidata Q-code + + >>> lang2q('Low German') + 'Q25433' + """ + return tag2q(langcode(name)) + + +# ====================================================================== +# Data dictionaries +# ...................................................................... + + +def inverse_dict(dic): + """Return inverse mapping, but only if it is bijective""" + if len(dic.keys()) == len(set(dic.values())): + return {val: key for (key, val) in dic.items()} + else: + warn("This dictionary has no bijective inverse mapping.") + + +bcp47.load_wiki_q() # Wikidata conversion table needs to be loaded explicitly +wiki_bcp47 = inverse_dict(bcp47.wiki_q) + +iso639short = { + "aar": "aa", + "abk": "ab", + "afr": "af", + "aka": "ak", + "amh": "am", + "ara": "ar", + "arg": "an", + "asm": "as", + "ava": "av", + "ave": "ae", + "aym": "ay", + "aze": "az", + "bak": "ba", + "bam": "bm", + "bel": "be", + "ben": "bn", + "bis": "bi", + "bod": "bo", + "bos": "bs", + "bre": "br", + "bul": "bg", + "cat": "ca", + "ces": "cs", + "cha": "ch", + "che": "ce", + "chu": "cu", + "chv": "cv", + "cor": "kw", + "cos": "co", + "cre": "cr", + "cym": "cy", + "dan": "da", + "deu": "de", + "div": "dv", + "dzo": "dz", + "ell": "el", + "eng": "en", + "epo": "eo", + "est": "et", + "eus": "eu", + "ewe": "ee", + "fao": "fo", + "fas": "fa", + "fij": "fj", + "fin": "fi", + "fra": "fr", + "fry": "fy", + "ful": "ff", + "gla": "gd", + "gle": "ga", + "glg": "gl", + "glv": "gv", + "grn": "gn", + "guj": "gu", + "hat": "ht", + "hau": "ha", + "hbs": "sh", + "heb": "he", + "her": "hz", + "hin": "hi", + "hmo": "ho", + "hrv": "hr", + "hun": "hu", + "hye": "hy", + "ibo": "ig", + "ido": "io", + "iii": "ii", + "iku": "iu", + "ile": "ie", + "ina": "ia", + "ind": "id", + "ipk": "ik", + "isl": "is", + "ita": "it", + "jav": "jv", + "jpn": "ja", + "kal": "kl", + "kan": "kn", + "kas": "ks", + "kat": "ka", + "kau": "kr", + "kaz": "kk", + "khm": "km", + "kik": "ki", + "kin": "rw", + "kir": "ky", + "kom": "kv", + "kon": "kg", + "kor": "ko", + "kua": "kj", + "kur": "ku", + "lao": "lo", + "lat": "la", + "lav": "lv", + "lim": "li", + "lin": "ln", + "lit": "lt", + "ltz": "lb", + "lub": "lu", + "lug": "lg", + "mah": "mh", + "mal": "ml", + "mar": "mr", + "mkd": "mk", + "mlg": "mg", + "mlt": "mt", + "mon": "mn", + "mri": "mi", + "msa": "ms", + "mya": "my", + "nau": "na", + "nav": "nv", + "nbl": "nr", + "nde": "nd", + "ndo": "ng", + "nep": "ne", + "nld": "nl", + "nno": "nn", + "nob": "nb", + "nor": "no", + "nya": "ny", + "oci": "oc", + "oji": "oj", + "ori": "or", + "orm": "om", + "oss": "os", + "pan": "pa", + "pli": "pi", + "pol": "pl", + "por": "pt", + "pus": "ps", + "que": "qu", + "roh": "rm", + "ron": "ro", + "run": "rn", + "rus": "ru", + "sag": "sg", + "san": "sa", + "sin": "si", + "slk": "sk", + "slv": "sl", + "sme": "se", + "smo": "sm", + "sna": "sn", + "snd": "sd", + "som": "so", + "sot": "st", + "spa": "es", + "sqi": "sq", + "srd": "sc", + "srp": "sr", + "ssw": "ss", + "sun": "su", + "swa": "sw", + "swe": "sv", + "tah": "ty", + "tam": "ta", + "tat": "tt", + "tel": "te", + "tgk": "tg", + "tgl": "tl", + "tha": "th", + "tir": "ti", + "ton": "to", + "tsn": "tn", + "tso": "ts", + "tuk": "tk", + "tur": "tr", + "twi": "tw", + "uig": "ug", + "ukr": "uk", + "urd": "ur", + "uzb": "uz", + "ven": "ve", + "vie": "vi", + "vol": "vo", + "wln": "wa", + "wol": "wo", + "xho": "xh", + "yid": "yi", + "yor": "yo", + "zha": "za", + "zho": "zh", + "zul": "zu", +} + + +iso639retired = { + "fri": "Western Frisian", + "auv": "Auvergnat", + "gsc": "Gascon", + "lms": "Limousin", + "lnc": "Languedocien", + "prv": "Provençal", + "amd": "Amapá Creole", + "bgh": "Bogan", + "bnh": "Banawá", + "bvs": "Belgian Sign Language", + "ccy": "Southern Zhuang", + "cit": "Chittagonian", + "flm": "Falam Chin", + "jap": "Jaruára", + "kob": "Kohoroxitari", + "mob": "Moinba", + "mzf": "Aiku", + "nhj": "Tlalitzlipa Nahuatl", + "nhs": "Southeastern Puebla Nahuatl", + "occ": "Occidental", + "tmx": "Tomyang", + "tot": "Patla-Chicontla Totonac", + "xmi": "Miarrã", + "yib": "Yinglish", + "ztc": "Lachirioag Zapotec", + "atf": "Atuence", + "bqe": "Navarro-Labourdin Basque", + "bsz": "Souletin Basque", + "aex": "Amerax", + "ahe": "Ahe", + "aiz": "Aari", + "akn": "Amikoana", + "arf": "Arafundi", + "azr": "Adzera", + "bcx": "Pamona", + "bii": "Bisu", + "bke": "Bengkulu", + "blu": "Hmong Njua", + "boc": "Bakung Kenyah", + "bsd": "Sarawak Bisaya", + "bwv": "Bahau River Kenyah", + "bxt": "Buxinhua", + "byu": "Buyang", + "ccx": "Northern Zhuang", + "cru": "Carútana", + "dat": "Darang Deng", + "dyk": "Land Dayak", + "eni": "Enim", + "fiz": "Izere", + "gen": "Geman Deng", + "ggh": "Garreh-Ajuran", + "itu": "Itutang", + "kds": "Lahu Shi", + "knh": "Kayan River Kenyah", + "krg": "North Korowai", + "krq": "Krui", + "kxg": "Katingan", + "lmt": "Lematang", + "lnt": "Lintang", + "lod": "Berawan", + "mbg": "Northern Nambikuára", + "mdo": "Southwest Gbaya", + "mhv": "Arakanese", + "miv": "Mimi", + "mqd": "Madang", + "nky": "Khiamniungan Naga", + "nxj": "Nyadu", + "ogn": "Ogan", + "ork": "Orokaiva", + "paj": "Ipeka-Tapuia", + "pec": "Southern Pesisir", + "pen": "Penesak", + "plm": "Palembang", + "poj": "Lower Pokomo", + "pun": "Pubian", + "rae": "Ranau", + "rjb": "Rajbanshi", + "rws": "Rawas", + "sdd": "Semendo", + "sdi": "Sindang Kelingi", + "skl": "Selako", + "slb": "Kahumamahon Saluan", + "srj": "Serawai", + "suf": "Tarpia", + "suh": "Suba", + "suu": "Sungkai", + "szk": "Sizaki", + "tle": "Southern Marakwet", + "tnj": "Tanjong", + "ttx": "Tutong 1", + "ubm": "Upper Baram Kenyah", + "vky": "Kayu Agung", + "vmo": "Muko-Muko", + "wre": "Ware", + "xah": "Kahayan", + "xkm": "Mahakam Kenyah", + "xuf": "Kunfal", + "yio": "Dayao Yi", + "ymj": "Muji Yi", + "ypl": "Pula Yi", + "ypw": "Puwa Yi", + "ywm": "Wumeng Yi", + "yym": "Yuanjiang-Mojiang Yi", + "mly": "Malay (individual language)", + "muw": "Mundari", + "xst": "Silt'e", + "ope": "Old Persian", + "scc": "Serbian", + "scr": "Croatian", + "xsk": "Sakan", + "mol": "Moldavian", + "aay": "Aariya", + "acc": "Cubulco Achí", + "cbm": "Yepocapa Southwestern Cakchiquel", + "chs": "Chumash", + "ckc": "Northern Cakchiquel", + "ckd": "South Central Cakchiquel", + "cke": "Eastern Cakchiquel", + "ckf": "Southern Cakchiquel", + "cki": "Santa María De Jesús Cakchiquel", + "ckj": "Santo Domingo Xenacoj Cakchiquel", + "ckk": "Acatenango Southwestern Cakchiquel", + "ckw": "Western Cakchiquel", + "cnm": "Ixtatán Chuj", + "cti": "Tila Chol", + "cun": "Cunén Quiché", + "eml": "Emiliano-Romagnolo", + "eur": "Europanto", + "gmo": "Gamo-Gofa-Dawro", + "hsf": "Southeastern Huastec", + "hva": "San Luís Potosí Huastec", + "ixi": "Nebaj Ixil", + "ixj": "Chajul Ixil", + "jai": "Western Jacalteco", + "mms": "Southern Mam", + "mpf": "Tajumulco Mam", + "mtz": "Tacanec", + "mvc": "Central Mam", + "mvj": "Todos Santos Cuchumatán Mam", + "poa": "Eastern Pokomam", + "pob": "Western Pokomchí", + "pou": "Southern Pokomam", + "ppv": "Papavô", + "quj": "Joyabaj Quiché", + "qut": "West Central Quiché", + "quu": "Eastern Quiché", + "qxi": "San Andrés Quiché", + "sic": "Malinguat", + "stc": "Santa Cruz", + "tlz": "Toala'", + "tzb": "Bachajón Tzeltal", + "tzc": "Chamula Tzotzil", + "tze": "Chenalhó Tzotzil", + "tzs": "San Andrés Larrainzar Tzotzil", + "tzt": "Western Tzutujil", + "tzu": "Huixtán Tzotzil", + "tzz": "Zinacantán Tzotzil", + "vlr": "Vatrata", + "yus": "Chan Santa Cruz Maya", + "nfg": "Nyeng", + "nfk": "Shakara", + "agp": "Paranan", + "bhk": "Albay Bicolano", + "bkb": "Finallig", + "btb": "Beti (Cameroon)", + "cjr": "Chorotega", + "cmk": "Chimakum", + "drh": "Darkhat", + "drw": "Darwazi", + "gav": "Gabutamon", + "mof": "Mohegan-Montauk-Narragansett", + "mst": "Cataelano Mandaya", + "myt": "Sangab Mandaya", + "rmr": "Caló", + "sgl": "Sanglechi-Ishkashimi", + "sul": "Surigaonon", + "sum": "Sumo-Mayangna", + "tnf": "Tangshewi", + "wgw": "Wagawaga", + "ayx": "Ayi (China)", + "bjq": "Southern Betsimisaraka Malagasy", + "dha": "Dhanwar (India)", + "dkl": "Kolum So Dogon", + "mja": "Mahei", + "nbf": "Naxi", + "noo": "Nootka", + "tie": "Tingal", + "tkk": "Takpa", + "baz": "Tunen", + "bjd": "Bandjigali", + "ccq": "Chaungtha", + "cka": "Khumi Awa Chin", + "dap": "Nisi (India)", + "dwl": "Walo Kumbe Dogon", + "elp": "Elpaputih", + "gbc": "Garawa", + "gio": "Gelao", + "hrr": "Horuru", + "ibi": "Ibilo", + "jar": "Jarawa (Nigeria)", + "kdv": "Kado", + "kgh": "Upper Tanudan Kalinga", + "kpp": "Paku Karen", + "kzh": "Kenuzi-Dongola", + "lcq": "Luhu", + "mgx": "Omati", + "nln": "Durango Nahuatl", + "pbz": "Palu", + "pgy": "Pongyong", + "sca": "Sansu", + "tlw": "South Wemale", + "unp": "Worora", + "wiw": "Wirangu", + "ybd": "Yangbye", + "yen": "Yendang", + "yma": "Yamphe", + "daf": "Dan", + "djl": "Djiwarli", + "ggr": "Aghu Tharnggalu", + "ilw": "Talur", + "izi": "Izi-Ezaa-Ikwo-Mgbo", + "meg": "Mea", + "mld": "Malakhel", + "mnt": "Maykulan", + "mwd": "Mudbura", + "myq": "Forest Maninka", + "nbx": "Ngura", + "nlr": "Ngarla", + "pcr": "Panang", + "ppr": "Piru", + "tgg": "Tangga", + "wit": "Wintu", + "xia": "Xiandao", + "yiy": "Yir Yoront", + "yos": "Yos", + "emo": "Emok", + "ggm": "Gugu Mini", + "leg": "Lengua", + "lmm": "Lamam", + "mhh": "Maskoy Pidgin", + "puz": "Purum Naga", + "sap": "Sanapaná", + "yuu": "Yugh", + "aam": "Aramanik", + "adp": "Adap", + "aue": "ǂKxʼauǁʼein", + "bmy": "Bemba (Democratic Republic of Congo)", + "bxx": "Borna (Democratic Republic of Congo)", + "byy": "Buya", + "dzd": "Daza", + "gfx": "Mangetti Dune ǃXung", + "gti": "Gbati-ri", + "ime": "Imeraguen", + "kbf": "Kakauhua", + "koj": "Sara Dunjo", + "kwq": "Kwak", + "kxe": "Kakihum", + "lii": "Lingkhim", + "mwj": "Maligo", + "nnx": "Ngong", + "oun": "ǃOǃung", + "pmu": "Mirpur Panjabi", + "sgo": "Songa", + "thx": "The", + "tsf": "Southwestern Tamang", + "uok": "Uokha", + "xsj": "Subi", + "yds": "Yiddish Sign Language", + "ymt": "Mator-Taygi-Karagas", + "ynh": "Yangho", + "bgm": "Baga Mboteni", + "btl": "Bhatola", + "cbe": "Chipiajes", + "cbh": "Cagua", + "coy": "Coyaima", + "cqu": "Chilean Quechua", + "cum": "Cumeral", + "duj": "Dhuwal", + "ggn": "Eastern Gurung", + "ggo": "Southern Gondi", + "guv": "Gey", + "iap": "Iapama", + "ill": "Iranun", + "kgc": "Kasseng", + "kox": "Coxima", + "ktr": "Kota Marudu Tinagas", + "kvs": "Kunggara", + "kzj": "Coastal Kadazan", + "kzt": "Tambunan Dusun", + "nad": "Nijadali", + "nts": "Natagaimas", + "ome": "Omejes", + "pmc": "Palumata", + "pod": "Ponares", + "ppa": "Pao", + "pry": "Pray 3", + "rna": "Runa", + "svr": "Savara", + "tdu": "Tempasuk Dusun", + "thc": "Tai Hang Tong", + "tid": "Tidong", + "tmp": "Tai Mène", + "tne": "Tinoc Kallahan", + "toe": "Tomedes", + "xba": "Kamba (Brazil)", + "xbx": "Kabixí", + "xip": "Xipináwa", + "xkh": "Karahawyana", + "yri": "Yarí", + "jeg": "Jeng", + "kgd": "Kataang", + "krm": "Krim", + "prb": "Lua'", + "puk": "Pu Ko", + "rie": "Rien", + "rsi": "Rennellese Sign Language", + "skk": "Sok", + "snh": "Shinabo", + "lsg": "Lyons Sign Language", + "mwx": "Mediak", + "mwy": "Mosiro", + "ncp": "Ndaktup", + "ais": "Nataoran Amis", + "asd": "Asas", + "dit": "Dirari", + "dud": "Hun-Saare", + "lba": "Lui", + "llo": "Khlor", + "myd": "Maramba", + "myi": "Mina (India)", + "nns": "Ningye", + "aoh": "Arma", + "ayy": "Tayabas Ayta", + "bbz": "Babalia Creole Arabic", + "bpb": "Barbacoas", + "cca": "Cauca", + "cdg": "Chamari", + "dgu": "Degaru", + "drr": "Dororo", + "ekc": "Eastern Karnic", + "gli": "Guliguli", + "kjf": "Khalaj", + "kxl": "Nepali Kurux", + "kxu": "Kui (India)", + "lmz": "Lumbee", + "nxu": "Narau", + "plp": "Palpa", + "sdm": "Semandang", + "tbb": "Tapeba", + "xrq": "Karranga", + "xtz": "Tasmanian", + "zir": "Ziriya", + "thw": "Thudam", + "bic": "Bikaru", + "bij": "Vaghat-Ya-Bijim-Legeri", + "blg": "Balau", + "gji": "Geji", + "mvm": "Muya", + "ngo": "Ngoni", + "pat": "Papitalai", + "vki": "Ija-Zuba", + "wra": "Warapu", + "ajt": "Judeo-Tunisian Arabic", + "cug": "Chungmboko", + "lak": "Laka (Nigeria)", + "lno": "Lango (South Sudan)", + "pii": "Pini", + "smd": "Sama", + "snb": "Sebuyau", + "uun": "Kulon-Pazeh", + "wrd": "Warduji", + "wya": "Wyandot", +} + + +iso639long = inverse_dict(iso639short) + +iso639code_retired = inverse_dict(iso639retired) diff --git a/llmeval-env/lib/python3.10/site-packages/nltk/lazyimport.py b/llmeval-env/lib/python3.10/site-packages/nltk/lazyimport.py new file mode 100644 index 0000000000000000000000000000000000000000..ee0c8e4451fff3a19c3608d0d08e3422a77fd8f0 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/nltk/lazyimport.py @@ -0,0 +1,142 @@ +# This module is from mx/DateTime/LazyModule.py and is +# distributed under the terms of the eGenix.com Public License Agreement +# https://www.egenix.com/products/eGenix.com-Public-License-1.1.0.pdf + +""" Helper to enable simple lazy module import. + + 'Lazy' means the actual import is deferred until an attribute is + requested from the module's namespace. This has the advantage of + allowing all imports to be done at the top of a script (in a + prominent and visible place) without having a great impact + on startup time. + + Copyright (c) 1999-2005, Marc-Andre Lemburg; mailto:mal@lemburg.com + See the documentation for further information on copyrights, + or contact the author. All Rights Reserved. +""" + +### Constants + +_debug = 0 + +### + + +class LazyModule: + + """Lazy module class. + + Lazy modules are imported into the given namespaces whenever a + non-special attribute (there are some attributes like __doc__ + that class instances handle without calling __getattr__) is + requested. The module is then registered under the given name + in locals usually replacing the import wrapper instance. The + import itself is done using globals as global namespace. + + Example of creating a lazy load module: + + ISO = LazyModule('ISO',locals(),globals()) + + Later, requesting an attribute from ISO will load the module + automatically into the locals() namespace, overriding the + LazyModule instance: + + t = ISO.Week(1998,1,1) + + """ + + # Flag which indicates whether the LazyModule is initialized or not + __lazymodule_init = 0 + + # Name of the module to load + __lazymodule_name = "" + + # Flag which indicates whether the module was loaded or not + __lazymodule_loaded = 0 + + # Locals dictionary where to register the module + __lazymodule_locals = None + + # Globals dictionary to use for the module import + __lazymodule_globals = None + + def __init__(self, name, locals, globals=None): + + """Create a LazyModule instance wrapping module name. + + The module will later on be registered in locals under the + given module name. + + globals is optional and defaults to locals. + + """ + self.__lazymodule_locals = locals + if globals is None: + globals = locals + self.__lazymodule_globals = globals + mainname = globals.get("__name__", "") + if mainname: + self.__name__ = mainname + "." + name + self.__lazymodule_name = name + else: + self.__name__ = self.__lazymodule_name = name + self.__lazymodule_init = 1 + + def __lazymodule_import(self): + + """Import the module now.""" + # Load and register module + local_name = self.__lazymodule_name # e.g. "toolbox" + full_name = self.__name__ # e.g. "nltk.toolbox" + if self.__lazymodule_loaded: + return self.__lazymodule_locals[local_name] + if _debug: + print("LazyModule: Loading module %r" % full_name) + self.__lazymodule_locals[local_name] = module = __import__( + full_name, self.__lazymodule_locals, self.__lazymodule_globals, "*" + ) + + # Fill namespace with all symbols from original module to + # provide faster access. + self.__dict__.update(module.__dict__) + + # Set import flag + self.__dict__["__lazymodule_loaded"] = 1 + + if _debug: + print("LazyModule: Module %r loaded" % full_name) + return module + + def __getattr__(self, name): + + """Import the module on demand and get the attribute.""" + if self.__lazymodule_loaded: + raise AttributeError(name) + if _debug: + print( + "LazyModule: " + "Module load triggered by attribute %r read access" % name + ) + module = self.__lazymodule_import() + return getattr(module, name) + + def __setattr__(self, name, value): + + """Import the module on demand and set the attribute.""" + if not self.__lazymodule_init: + self.__dict__[name] = value + return + if self.__lazymodule_loaded: + self.__lazymodule_locals[self.__lazymodule_name] = value + self.__dict__[name] = value + return + if _debug: + print( + "LazyModule: " + "Module load triggered by attribute %r write access" % name + ) + module = self.__lazymodule_import() + setattr(module, name, value) + + def __repr__(self): + return "" % self.__name__ diff --git a/llmeval-env/lib/python3.10/site-packages/nltk/probability.py b/llmeval-env/lib/python3.10/site-packages/nltk/probability.py new file mode 100644 index 0000000000000000000000000000000000000000..a6de70732ac33e375c42d5e675aac124ffeafdf6 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/nltk/probability.py @@ -0,0 +1,2578 @@ +# Natural Language Toolkit: Probability and Statistics +# +# Copyright (C) 2001-2023 NLTK Project +# Author: Edward Loper +# Steven Bird (additions) +# Trevor Cohn (additions) +# Peter Ljunglöf (additions) +# Liang Dong (additions) +# Geoffrey Sampson (additions) +# Ilia Kurenkov (additions) +# +# URL: +# For license information, see LICENSE.TXT + +""" +Classes for representing and processing probabilistic information. + +The ``FreqDist`` class is used to encode "frequency distributions", +which count the number of times that each outcome of an experiment +occurs. + +The ``ProbDistI`` class defines a standard interface for "probability +distributions", which encode the probability of each outcome for an +experiment. There are two types of probability distribution: + + - "derived probability distributions" are created from frequency + distributions. They attempt to model the probability distribution + that generated the frequency distribution. + - "analytic probability distributions" are created directly from + parameters (such as variance). + +The ``ConditionalFreqDist`` class and ``ConditionalProbDistI`` interface +are used to encode conditional distributions. Conditional probability +distributions can be derived or analytic; but currently the only +implementation of the ``ConditionalProbDistI`` interface is +``ConditionalProbDist``, a derived distribution. + +""" + +import array +import math +import random +import warnings +from abc import ABCMeta, abstractmethod +from collections import Counter, defaultdict +from functools import reduce + +from nltk.internals import raise_unorderable_types + +_NINF = float("-1e300") + +##////////////////////////////////////////////////////// +## Frequency Distributions +##////////////////////////////////////////////////////// + + +class FreqDist(Counter): + """ + A frequency distribution for the outcomes of an experiment. A + frequency distribution records the number of times each outcome of + an experiment has occurred. For example, a frequency distribution + could be used to record the frequency of each word type in a + document. Formally, a frequency distribution can be defined as a + function mapping from each sample to the number of times that + sample occurred as an outcome. + + Frequency distributions are generally constructed by running a + number of experiments, and incrementing the count for a sample + every time it is an outcome of an experiment. For example, the + following code will produce a frequency distribution that encodes + how often each word occurs in a text: + + >>> from nltk.tokenize import word_tokenize + >>> from nltk.probability import FreqDist + >>> sent = 'This is an example sentence' + >>> fdist = FreqDist() + >>> for word in word_tokenize(sent): + ... fdist[word.lower()] += 1 + + An equivalent way to do this is with the initializer: + + >>> fdist = FreqDist(word.lower() for word in word_tokenize(sent)) + + """ + + def __init__(self, samples=None): + """ + Construct a new frequency distribution. If ``samples`` is + given, then the frequency distribution will be initialized + with the count of each object in ``samples``; otherwise, it + will be initialized to be empty. + + In particular, ``FreqDist()`` returns an empty frequency + distribution; and ``FreqDist(samples)`` first creates an empty + frequency distribution, and then calls ``update`` with the + list ``samples``. + + :param samples: The samples to initialize the frequency + distribution with. + :type samples: Sequence + """ + Counter.__init__(self, samples) + + # Cached number of samples in this FreqDist + self._N = None + + def N(self): + """ + Return the total number of sample outcomes that have been + recorded by this FreqDist. For the number of unique + sample values (or bins) with counts greater than zero, use + ``FreqDist.B()``. + + :rtype: int + """ + if self._N is None: + # Not already cached, or cache has been invalidated + self._N = sum(self.values()) + return self._N + + def __setitem__(self, key, val): + """ + Override ``Counter.__setitem__()`` to invalidate the cached N + """ + self._N = None + super().__setitem__(key, val) + + def __delitem__(self, key): + """ + Override ``Counter.__delitem__()`` to invalidate the cached N + """ + self._N = None + super().__delitem__(key) + + def update(self, *args, **kwargs): + """ + Override ``Counter.update()`` to invalidate the cached N + """ + self._N = None + super().update(*args, **kwargs) + + def setdefault(self, key, val): + """ + Override ``Counter.setdefault()`` to invalidate the cached N + """ + self._N = None + super().setdefault(key, val) + + def B(self): + """ + Return the total number of sample values (or "bins") that + have counts greater than zero. For the total + number of sample outcomes recorded, use ``FreqDist.N()``. + (FreqDist.B() is the same as len(FreqDist).) + + :rtype: int + """ + return len(self) + + def hapaxes(self): + """ + Return a list of all samples that occur once (hapax legomena) + + :rtype: list + """ + return [item for item in self if self[item] == 1] + + def Nr(self, r, bins=None): + return self.r_Nr(bins)[r] + + def r_Nr(self, bins=None): + """ + Return the dictionary mapping r to Nr, the number of samples with frequency r, where Nr > 0. + + :type bins: int + :param bins: The number of possible sample outcomes. ``bins`` + is used to calculate Nr(0). In particular, Nr(0) is + ``bins-self.B()``. If ``bins`` is not specified, it + defaults to ``self.B()`` (so Nr(0) will be 0). + :rtype: int + """ + + _r_Nr = defaultdict(int) + for count in self.values(): + _r_Nr[count] += 1 + + # Special case for Nr[0]: + _r_Nr[0] = bins - self.B() if bins is not None else 0 + + return _r_Nr + + def _cumulative_frequencies(self, samples): + """ + Return the cumulative frequencies of the specified samples. + If no samples are specified, all counts are returned, starting + with the largest. + + :param samples: the samples whose frequencies should be returned. + :type samples: any + :rtype: list(float) + """ + cf = 0.0 + for sample in samples: + cf += self[sample] + yield cf + + # slightly odd nomenclature freq() if FreqDist does counts and ProbDist does probs, + # here, freq() does probs + def freq(self, sample): + """ + Return the frequency of a given sample. The frequency of a + sample is defined as the count of that sample divided by the + total number of sample outcomes that have been recorded by + this FreqDist. The count of a sample is defined as the + number of times that sample outcome was recorded by this + FreqDist. Frequencies are always real numbers in the range + [0, 1]. + + :param sample: the sample whose frequency + should be returned. + :type sample: any + :rtype: float + """ + n = self.N() + if n == 0: + return 0 + return self[sample] / n + + def max(self): + """ + Return the sample with the greatest number of outcomes in this + frequency distribution. If two or more samples have the same + number of outcomes, return one of them; which sample is + returned is undefined. If no outcomes have occurred in this + frequency distribution, return None. + + :return: The sample with the maximum number of outcomes in this + frequency distribution. + :rtype: any or None + """ + if len(self) == 0: + raise ValueError( + "A FreqDist must have at least one sample before max is defined." + ) + return self.most_common(1)[0][0] + + def plot( + self, *args, title="", cumulative=False, percents=False, show=True, **kwargs + ): + """ + Plot samples from the frequency distribution + displaying the most frequent sample first. If an integer + parameter is supplied, stop after this many samples have been + plotted. For a cumulative plot, specify cumulative=True. Additional + ``**kwargs`` are passed to matplotlib's plot function. + (Requires Matplotlib to be installed.) + + :param title: The title for the graph. + :type title: str + :param cumulative: Whether the plot is cumulative. (default = False) + :type cumulative: bool + :param percents: Whether the plot uses percents instead of counts. (default = False) + :type percents: bool + :param show: Whether to show the plot, or only return the ax. + :type show: bool + """ + try: + import matplotlib.pyplot as plt + except ImportError as e: + raise ValueError( + "The plot function requires matplotlib to be installed." + "See https://matplotlib.org/" + ) from e + + if len(args) == 0: + args = [len(self)] + samples = [item for item, _ in self.most_common(*args)] + + if cumulative: + freqs = list(self._cumulative_frequencies(samples)) + ylabel = "Cumulative " + else: + freqs = [self[sample] for sample in samples] + ylabel = "" + + if percents: + freqs = [f / self.N() * 100 for f in freqs] + ylabel += "Percents" + else: + ylabel += "Counts" + + ax = plt.gca() + ax.grid(True, color="silver") + + if "linewidth" not in kwargs: + kwargs["linewidth"] = 2 + if title: + ax.set_title(title) + + ax.plot(freqs, **kwargs) + ax.set_xticks(range(len(samples))) + ax.set_xticklabels([str(s) for s in samples], rotation=90) + ax.set_xlabel("Samples") + ax.set_ylabel(ylabel) + + if show: + plt.show() + + return ax + + def tabulate(self, *args, **kwargs): + """ + Tabulate the given samples from the frequency distribution (cumulative), + displaying the most frequent sample first. If an integer + parameter is supplied, stop after this many samples have been + plotted. + + :param samples: The samples to plot (default is all samples) + :type samples: list + :param cumulative: A flag to specify whether the freqs are cumulative (default = False) + :type title: bool + """ + if len(args) == 0: + args = [len(self)] + samples = _get_kwarg( + kwargs, "samples", [item for item, _ in self.most_common(*args)] + ) + + cumulative = _get_kwarg(kwargs, "cumulative", False) + if cumulative: + freqs = list(self._cumulative_frequencies(samples)) + else: + freqs = [self[sample] for sample in samples] + # percents = [f * 100 for f in freqs] only in ProbDist? + + width = max(len(f"{s}") for s in samples) + width = max(width, max(len("%d" % f) for f in freqs)) + + for i in range(len(samples)): + print("%*s" % (width, samples[i]), end=" ") + print() + for i in range(len(samples)): + print("%*d" % (width, freqs[i]), end=" ") + print() + + def copy(self): + """ + Create a copy of this frequency distribution. + + :rtype: FreqDist + """ + return self.__class__(self) + + # Mathematical operatiors + + def __add__(self, other): + """ + Add counts from two counters. + + >>> FreqDist('abbb') + FreqDist('bcc') + FreqDist({'b': 4, 'c': 2, 'a': 1}) + + """ + return self.__class__(super().__add__(other)) + + def __sub__(self, other): + """ + Subtract count, but keep only results with positive counts. + + >>> FreqDist('abbbc') - FreqDist('bccd') + FreqDist({'b': 2, 'a': 1}) + + """ + return self.__class__(super().__sub__(other)) + + def __or__(self, other): + """ + Union is the maximum of value in either of the input counters. + + >>> FreqDist('abbb') | FreqDist('bcc') + FreqDist({'b': 3, 'c': 2, 'a': 1}) + + """ + return self.__class__(super().__or__(other)) + + def __and__(self, other): + """ + Intersection is the minimum of corresponding counts. + + >>> FreqDist('abbb') & FreqDist('bcc') + FreqDist({'b': 1}) + + """ + return self.__class__(super().__and__(other)) + + def __le__(self, other): + """ + Returns True if this frequency distribution is a subset of the other + and for no key the value exceeds the value of the same key from + the other frequency distribution. + + The <= operator forms partial order and satisfying the axioms + reflexivity, antisymmetry and transitivity. + + >>> FreqDist('a') <= FreqDist('a') + True + >>> a = FreqDist('abc') + >>> b = FreqDist('aabc') + >>> (a <= b, b <= a) + (True, False) + >>> FreqDist('a') <= FreqDist('abcd') + True + >>> FreqDist('abc') <= FreqDist('xyz') + False + >>> FreqDist('xyz') <= FreqDist('abc') + False + >>> c = FreqDist('a') + >>> d = FreqDist('aa') + >>> e = FreqDist('aaa') + >>> c <= d and d <= e and c <= e + True + """ + if not isinstance(other, FreqDist): + raise_unorderable_types("<=", self, other) + return set(self).issubset(other) and all( + self[key] <= other[key] for key in self + ) + + def __ge__(self, other): + if not isinstance(other, FreqDist): + raise_unorderable_types(">=", self, other) + return set(self).issuperset(other) and all( + self[key] >= other[key] for key in other + ) + + __lt__ = lambda self, other: self <= other and not self == other + __gt__ = lambda self, other: self >= other and not self == other + + def __repr__(self): + """ + Return a string representation of this FreqDist. + + :rtype: string + """ + return self.pformat() + + def pprint(self, maxlen=10, stream=None): + """ + Print a string representation of this FreqDist to 'stream' + + :param maxlen: The maximum number of items to print + :type maxlen: int + :param stream: The stream to print to. stdout by default + """ + print(self.pformat(maxlen=maxlen), file=stream) + + def pformat(self, maxlen=10): + """ + Return a string representation of this FreqDist. + + :param maxlen: The maximum number of items to display + :type maxlen: int + :rtype: string + """ + items = ["{!r}: {!r}".format(*item) for item in self.most_common(maxlen)] + if len(self) > maxlen: + items.append("...") + return "FreqDist({{{0}}})".format(", ".join(items)) + + def __str__(self): + """ + Return a string representation of this FreqDist. + + :rtype: string + """ + return "" % (len(self), self.N()) + + def __iter__(self): + """ + Return an iterator which yields tokens ordered by frequency. + + :rtype: iterator + """ + for token, _ in self.most_common(self.B()): + yield token + + +##////////////////////////////////////////////////////// +## Probability Distributions +##////////////////////////////////////////////////////// + + +class ProbDistI(metaclass=ABCMeta): + """ + A probability distribution for the outcomes of an experiment. A + probability distribution specifies how likely it is that an + experiment will have any given outcome. For example, a + probability distribution could be used to predict the probability + that a token in a document will have a given type. Formally, a + probability distribution can be defined as a function mapping from + samples to nonnegative real numbers, such that the sum of every + number in the function's range is 1.0. A ``ProbDist`` is often + used to model the probability distribution of the experiment used + to generate a frequency distribution. + """ + + SUM_TO_ONE = True + """True if the probabilities of the samples in this probability + distribution will always sum to one.""" + + @abstractmethod + def __init__(self): + """ + Classes inheriting from ProbDistI should implement __init__. + """ + + @abstractmethod + def prob(self, sample): + """ + Return the probability for a given sample. Probabilities + are always real numbers in the range [0, 1]. + + :param sample: The sample whose probability + should be returned. + :type sample: any + :rtype: float + """ + + def logprob(self, sample): + """ + Return the base 2 logarithm of the probability for a given sample. + + :param sample: The sample whose probability + should be returned. + :type sample: any + :rtype: float + """ + # Default definition, in terms of prob() + p = self.prob(sample) + return math.log(p, 2) if p != 0 else _NINF + + @abstractmethod + def max(self): + """ + Return the sample with the greatest probability. If two or + more samples have the same probability, return one of them; + which sample is returned is undefined. + + :rtype: any + """ + + @abstractmethod + def samples(self): + """ + Return a list of all samples that have nonzero probabilities. + Use ``prob`` to find the probability of each sample. + + :rtype: list + """ + + # cf self.SUM_TO_ONE + def discount(self): + """ + Return the ratio by which counts are discounted on average: c*/c + + :rtype: float + """ + return 0.0 + + # Subclasses should define more efficient implementations of this, + # where possible. + def generate(self): + """ + Return a randomly selected sample from this probability distribution. + The probability of returning each sample ``samp`` is equal to + ``self.prob(samp)``. + """ + p = random.random() + p_init = p + for sample in self.samples(): + p -= self.prob(sample) + if p <= 0: + return sample + # allow for some rounding error: + if p < 0.0001: + return sample + # we *should* never get here + if self.SUM_TO_ONE: + warnings.warn( + "Probability distribution %r sums to %r; generate()" + " is returning an arbitrary sample." % (self, p_init - p) + ) + return random.choice(list(self.samples())) + + +class UniformProbDist(ProbDistI): + """ + A probability distribution that assigns equal probability to each + sample in a given set; and a zero probability to all other + samples. + """ + + def __init__(self, samples): + """ + Construct a new uniform probability distribution, that assigns + equal probability to each sample in ``samples``. + + :param samples: The samples that should be given uniform + probability. + :type samples: list + :raise ValueError: If ``samples`` is empty. + """ + if len(samples) == 0: + raise ValueError( + "A Uniform probability distribution must " + "have at least one sample." + ) + self._sampleset = set(samples) + self._prob = 1.0 / len(self._sampleset) + self._samples = list(self._sampleset) + + def prob(self, sample): + return self._prob if sample in self._sampleset else 0 + + def max(self): + return self._samples[0] + + def samples(self): + return self._samples + + def __repr__(self): + return "" % len(self._sampleset) + + +class RandomProbDist(ProbDistI): + """ + Generates a random probability distribution whereby each sample + will be between 0 and 1 with equal probability (uniform random distribution. + Also called a continuous uniform distribution). + """ + + def __init__(self, samples): + if len(samples) == 0: + raise ValueError( + "A probability distribution must " + "have at least one sample." + ) + self._probs = self.unirand(samples) + self._samples = list(self._probs.keys()) + + @classmethod + def unirand(cls, samples): + """ + The key function that creates a randomized initial distribution + that still sums to 1. Set as a dictionary of prob values so that + it can still be passed to MutableProbDist and called with identical + syntax to UniformProbDist + """ + samples = set(samples) + randrow = [random.random() for i in range(len(samples))] + total = sum(randrow) + for i, x in enumerate(randrow): + randrow[i] = x / total + + total = sum(randrow) + if total != 1: + # this difference, if present, is so small (near NINF) that it + # can be subtracted from any element without risking probs not (0 1) + randrow[-1] -= total - 1 + + return {s: randrow[i] for i, s in enumerate(samples)} + + def max(self): + if not hasattr(self, "_max"): + self._max = max((p, v) for (v, p) in self._probs.items())[1] + return self._max + + def prob(self, sample): + return self._probs.get(sample, 0) + + def samples(self): + return self._samples + + def __repr__(self): + return "" % len(self._probs) + + +class DictionaryProbDist(ProbDistI): + """ + A probability distribution whose probabilities are directly + specified by a given dictionary. The given dictionary maps + samples to probabilities. + """ + + def __init__(self, prob_dict=None, log=False, normalize=False): + """ + Construct a new probability distribution from the given + dictionary, which maps values to probabilities (or to log + probabilities, if ``log`` is true). If ``normalize`` is + true, then the probability values are scaled by a constant + factor such that they sum to 1. + + If called without arguments, the resulting probability + distribution assigns zero probability to all values. + """ + + self._prob_dict = prob_dict.copy() if prob_dict is not None else {} + self._log = log + + # Normalize the distribution, if requested. + if normalize: + if len(prob_dict) == 0: + raise ValueError( + "A DictionaryProbDist must have at least one sample " + + "before it can be normalized." + ) + if log: + value_sum = sum_logs(list(self._prob_dict.values())) + if value_sum <= _NINF: + logp = math.log(1.0 / len(prob_dict), 2) + for x in prob_dict: + self._prob_dict[x] = logp + else: + for (x, p) in self._prob_dict.items(): + self._prob_dict[x] -= value_sum + else: + value_sum = sum(self._prob_dict.values()) + if value_sum == 0: + p = 1.0 / len(prob_dict) + for x in prob_dict: + self._prob_dict[x] = p + else: + norm_factor = 1.0 / value_sum + for (x, p) in self._prob_dict.items(): + self._prob_dict[x] *= norm_factor + + def prob(self, sample): + if self._log: + return 2 ** (self._prob_dict[sample]) if sample in self._prob_dict else 0 + else: + return self._prob_dict.get(sample, 0) + + def logprob(self, sample): + if self._log: + return self._prob_dict.get(sample, _NINF) + else: + if sample not in self._prob_dict: + return _NINF + elif self._prob_dict[sample] == 0: + return _NINF + else: + return math.log(self._prob_dict[sample], 2) + + def max(self): + if not hasattr(self, "_max"): + self._max = max((p, v) for (v, p) in self._prob_dict.items())[1] + return self._max + + def samples(self): + return self._prob_dict.keys() + + def __repr__(self): + return "" % len(self._prob_dict) + + +class MLEProbDist(ProbDistI): + """ + The maximum likelihood estimate for the probability distribution + of the experiment used to generate a frequency distribution. The + "maximum likelihood estimate" approximates the probability of + each sample as the frequency of that sample in the frequency + distribution. + """ + + def __init__(self, freqdist, bins=None): + """ + Use the maximum likelihood estimate to create a probability + distribution for the experiment used to generate ``freqdist``. + + :type freqdist: FreqDist + :param freqdist: The frequency distribution that the + probability estimates should be based on. + """ + self._freqdist = freqdist + + def freqdist(self): + """ + Return the frequency distribution that this probability + distribution is based on. + + :rtype: FreqDist + """ + return self._freqdist + + def prob(self, sample): + return self._freqdist.freq(sample) + + def max(self): + return self._freqdist.max() + + def samples(self): + return self._freqdist.keys() + + def __repr__(self): + """ + :rtype: str + :return: A string representation of this ``ProbDist``. + """ + return "" % self._freqdist.N() + + +class LidstoneProbDist(ProbDistI): + """ + The Lidstone estimate for the probability distribution of the + experiment used to generate a frequency distribution. The + "Lidstone estimate" is parameterized by a real number *gamma*, + which typically ranges from 0 to 1. The Lidstone estimate + approximates the probability of a sample with count *c* from an + experiment with *N* outcomes and *B* bins as + ``c+gamma)/(N+B*gamma)``. This is equivalent to adding + *gamma* to the count for each bin, and taking the maximum + likelihood estimate of the resulting frequency distribution. + """ + + SUM_TO_ONE = False + + def __init__(self, freqdist, gamma, bins=None): + """ + Use the Lidstone estimate to create a probability distribution + for the experiment used to generate ``freqdist``. + + :type freqdist: FreqDist + :param freqdist: The frequency distribution that the + probability estimates should be based on. + :type gamma: float + :param gamma: A real number used to parameterize the + estimate. The Lidstone estimate is equivalent to adding + *gamma* to the count for each bin, and taking the + maximum likelihood estimate of the resulting frequency + distribution. + :type bins: int + :param bins: The number of sample values that can be generated + by the experiment that is described by the probability + distribution. This value must be correctly set for the + probabilities of the sample values to sum to one. If + ``bins`` is not specified, it defaults to ``freqdist.B()``. + """ + if (bins == 0) or (bins is None and freqdist.N() == 0): + name = self.__class__.__name__[:-8] + raise ValueError( + "A %s probability distribution " % name + "must have at least one bin." + ) + if (bins is not None) and (bins < freqdist.B()): + name = self.__class__.__name__[:-8] + raise ValueError( + "\nThe number of bins in a %s distribution " % name + + "(%d) must be greater than or equal to\n" % bins + + "the number of bins in the FreqDist used " + + "to create it (%d)." % freqdist.B() + ) + + self._freqdist = freqdist + self._gamma = float(gamma) + self._N = self._freqdist.N() + + if bins is None: + bins = freqdist.B() + self._bins = bins + + self._divisor = self._N + bins * gamma + if self._divisor == 0.0: + # In extreme cases we force the probability to be 0, + # which it will be, since the count will be 0: + self._gamma = 0 + self._divisor = 1 + + def freqdist(self): + """ + Return the frequency distribution that this probability + distribution is based on. + + :rtype: FreqDist + """ + return self._freqdist + + def prob(self, sample): + c = self._freqdist[sample] + return (c + self._gamma) / self._divisor + + def max(self): + # For Lidstone distributions, probability is monotonic with + # frequency, so the most probable sample is the one that + # occurs most frequently. + return self._freqdist.max() + + def samples(self): + return self._freqdist.keys() + + def discount(self): + gb = self._gamma * self._bins + return gb / (self._N + gb) + + def __repr__(self): + """ + Return a string representation of this ``ProbDist``. + + :rtype: str + """ + return "" % self._freqdist.N() + + +class LaplaceProbDist(LidstoneProbDist): + """ + The Laplace estimate for the probability distribution of the + experiment used to generate a frequency distribution. The + "Laplace estimate" approximates the probability of a sample with + count *c* from an experiment with *N* outcomes and *B* bins as + *(c+1)/(N+B)*. This is equivalent to adding one to the count for + each bin, and taking the maximum likelihood estimate of the + resulting frequency distribution. + """ + + def __init__(self, freqdist, bins=None): + """ + Use the Laplace estimate to create a probability distribution + for the experiment used to generate ``freqdist``. + + :type freqdist: FreqDist + :param freqdist: The frequency distribution that the + probability estimates should be based on. + :type bins: int + :param bins: The number of sample values that can be generated + by the experiment that is described by the probability + distribution. This value must be correctly set for the + probabilities of the sample values to sum to one. If + ``bins`` is not specified, it defaults to ``freqdist.B()``. + """ + LidstoneProbDist.__init__(self, freqdist, 1, bins) + + def __repr__(self): + """ + :rtype: str + :return: A string representation of this ``ProbDist``. + """ + return "" % self._freqdist.N() + + +class ELEProbDist(LidstoneProbDist): + """ + The expected likelihood estimate for the probability distribution + of the experiment used to generate a frequency distribution. The + "expected likelihood estimate" approximates the probability of a + sample with count *c* from an experiment with *N* outcomes and + *B* bins as *(c+0.5)/(N+B/2)*. This is equivalent to adding 0.5 + to the count for each bin, and taking the maximum likelihood + estimate of the resulting frequency distribution. + """ + + def __init__(self, freqdist, bins=None): + """ + Use the expected likelihood estimate to create a probability + distribution for the experiment used to generate ``freqdist``. + + :type freqdist: FreqDist + :param freqdist: The frequency distribution that the + probability estimates should be based on. + :type bins: int + :param bins: The number of sample values that can be generated + by the experiment that is described by the probability + distribution. This value must be correctly set for the + probabilities of the sample values to sum to one. If + ``bins`` is not specified, it defaults to ``freqdist.B()``. + """ + LidstoneProbDist.__init__(self, freqdist, 0.5, bins) + + def __repr__(self): + """ + Return a string representation of this ``ProbDist``. + + :rtype: str + """ + return "" % self._freqdist.N() + + +class HeldoutProbDist(ProbDistI): + """ + The heldout estimate for the probability distribution of the + experiment used to generate two frequency distributions. These + two frequency distributions are called the "heldout frequency + distribution" and the "base frequency distribution." The + "heldout estimate" uses uses the "heldout frequency + distribution" to predict the probability of each sample, given its + frequency in the "base frequency distribution". + + In particular, the heldout estimate approximates the probability + for a sample that occurs *r* times in the base distribution as + the average frequency in the heldout distribution of all samples + that occur *r* times in the base distribution. + + This average frequency is *Tr[r]/(Nr[r].N)*, where: + + - *Tr[r]* is the total count in the heldout distribution for + all samples that occur *r* times in the base distribution. + - *Nr[r]* is the number of samples that occur *r* times in + the base distribution. + - *N* is the number of outcomes recorded by the heldout + frequency distribution. + + In order to increase the efficiency of the ``prob`` member + function, *Tr[r]/(Nr[r].N)* is precomputed for each value of *r* + when the ``HeldoutProbDist`` is created. + + :type _estimate: list(float) + :ivar _estimate: A list mapping from *r*, the number of + times that a sample occurs in the base distribution, to the + probability estimate for that sample. ``_estimate[r]`` is + calculated by finding the average frequency in the heldout + distribution of all samples that occur *r* times in the base + distribution. In particular, ``_estimate[r]`` = + *Tr[r]/(Nr[r].N)*. + :type _max_r: int + :ivar _max_r: The maximum number of times that any sample occurs + in the base distribution. ``_max_r`` is used to decide how + large ``_estimate`` must be. + """ + + SUM_TO_ONE = False + + def __init__(self, base_fdist, heldout_fdist, bins=None): + """ + Use the heldout estimate to create a probability distribution + for the experiment used to generate ``base_fdist`` and + ``heldout_fdist``. + + :type base_fdist: FreqDist + :param base_fdist: The base frequency distribution. + :type heldout_fdist: FreqDist + :param heldout_fdist: The heldout frequency distribution. + :type bins: int + :param bins: The number of sample values that can be generated + by the experiment that is described by the probability + distribution. This value must be correctly set for the + probabilities of the sample values to sum to one. If + ``bins`` is not specified, it defaults to ``freqdist.B()``. + """ + + self._base_fdist = base_fdist + self._heldout_fdist = heldout_fdist + + # The max number of times any sample occurs in base_fdist. + self._max_r = base_fdist[base_fdist.max()] + + # Calculate Tr, Nr, and N. + Tr = self._calculate_Tr() + r_Nr = base_fdist.r_Nr(bins) + Nr = [r_Nr[r] for r in range(self._max_r + 1)] + N = heldout_fdist.N() + + # Use Tr, Nr, and N to compute the probability estimate for + # each value of r. + self._estimate = self._calculate_estimate(Tr, Nr, N) + + def _calculate_Tr(self): + """ + Return the list *Tr*, where *Tr[r]* is the total count in + ``heldout_fdist`` for all samples that occur *r* + times in ``base_fdist``. + + :rtype: list(float) + """ + Tr = [0.0] * (self._max_r + 1) + for sample in self._heldout_fdist: + r = self._base_fdist[sample] + Tr[r] += self._heldout_fdist[sample] + return Tr + + def _calculate_estimate(self, Tr, Nr, N): + """ + Return the list *estimate*, where *estimate[r]* is the probability + estimate for any sample that occurs *r* times in the base frequency + distribution. In particular, *estimate[r]* is *Tr[r]/(N[r].N)*. + In the special case that *N[r]=0*, *estimate[r]* will never be used; + so we define *estimate[r]=None* for those cases. + + :rtype: list(float) + :type Tr: list(float) + :param Tr: the list *Tr*, where *Tr[r]* is the total count in + the heldout distribution for all samples that occur *r* + times in base distribution. + :type Nr: list(float) + :param Nr: The list *Nr*, where *Nr[r]* is the number of + samples that occur *r* times in the base distribution. + :type N: int + :param N: The total number of outcomes recorded by the heldout + frequency distribution. + """ + estimate = [] + for r in range(self._max_r + 1): + if Nr[r] == 0: + estimate.append(None) + else: + estimate.append(Tr[r] / (Nr[r] * N)) + return estimate + + def base_fdist(self): + """ + Return the base frequency distribution that this probability + distribution is based on. + + :rtype: FreqDist + """ + return self._base_fdist + + def heldout_fdist(self): + """ + Return the heldout frequency distribution that this + probability distribution is based on. + + :rtype: FreqDist + """ + return self._heldout_fdist + + def samples(self): + return self._base_fdist.keys() + + def prob(self, sample): + # Use our precomputed probability estimate. + r = self._base_fdist[sample] + return self._estimate[r] + + def max(self): + # Note: the Heldout estimation is *not* necessarily monotonic; + # so this implementation is currently broken. However, it + # should give the right answer *most* of the time. :) + return self._base_fdist.max() + + def discount(self): + raise NotImplementedError() + + def __repr__(self): + """ + :rtype: str + :return: A string representation of this ``ProbDist``. + """ + s = "" + return s % (self._base_fdist.N(), self._heldout_fdist.N()) + + +class CrossValidationProbDist(ProbDistI): + """ + The cross-validation estimate for the probability distribution of + the experiment used to generate a set of frequency distribution. + The "cross-validation estimate" for the probability of a sample + is found by averaging the held-out estimates for the sample in + each pair of frequency distributions. + """ + + SUM_TO_ONE = False + + def __init__(self, freqdists, bins): + """ + Use the cross-validation estimate to create a probability + distribution for the experiment used to generate + ``freqdists``. + + :type freqdists: list(FreqDist) + :param freqdists: A list of the frequency distributions + generated by the experiment. + :type bins: int + :param bins: The number of sample values that can be generated + by the experiment that is described by the probability + distribution. This value must be correctly set for the + probabilities of the sample values to sum to one. If + ``bins`` is not specified, it defaults to ``freqdist.B()``. + """ + self._freqdists = freqdists + + # Create a heldout probability distribution for each pair of + # frequency distributions in freqdists. + self._heldout_probdists = [] + for fdist1 in freqdists: + for fdist2 in freqdists: + if fdist1 is not fdist2: + probdist = HeldoutProbDist(fdist1, fdist2, bins) + self._heldout_probdists.append(probdist) + + def freqdists(self): + """ + Return the list of frequency distributions that this ``ProbDist`` is based on. + + :rtype: list(FreqDist) + """ + return self._freqdists + + def samples(self): + # [xx] nb: this is not too efficient + return set(sum((list(fd) for fd in self._freqdists), [])) + + def prob(self, sample): + # Find the average probability estimate returned by each + # heldout distribution. + prob = 0.0 + for heldout_probdist in self._heldout_probdists: + prob += heldout_probdist.prob(sample) + return prob / len(self._heldout_probdists) + + def discount(self): + raise NotImplementedError() + + def __repr__(self): + """ + Return a string representation of this ``ProbDist``. + + :rtype: str + """ + return "" % len(self._freqdists) + + +class WittenBellProbDist(ProbDistI): + """ + The Witten-Bell estimate of a probability distribution. This distribution + allocates uniform probability mass to as yet unseen events by using the + number of events that have only been seen once. The probability mass + reserved for unseen events is equal to *T / (N + T)* + where *T* is the number of observed event types and *N* is the total + number of observed events. This equates to the maximum likelihood estimate + of a new type event occurring. The remaining probability mass is discounted + such that all probability estimates sum to one, yielding: + + - *p = T / Z (N + T)*, if count = 0 + - *p = c / (N + T)*, otherwise + """ + + def __init__(self, freqdist, bins=None): + """ + Creates a distribution of Witten-Bell probability estimates. This + distribution allocates uniform probability mass to as yet unseen + events by using the number of events that have only been seen once. The + probability mass reserved for unseen events is equal to *T / (N + T)* + where *T* is the number of observed event types and *N* is the total + number of observed events. This equates to the maximum likelihood + estimate of a new type event occurring. The remaining probability mass + is discounted such that all probability estimates sum to one, + yielding: + + - *p = T / Z (N + T)*, if count = 0 + - *p = c / (N + T)*, otherwise + + The parameters *T* and *N* are taken from the ``freqdist`` parameter + (the ``B()`` and ``N()`` values). The normalizing factor *Z* is + calculated using these values along with the ``bins`` parameter. + + :param freqdist: The frequency counts upon which to base the + estimation. + :type freqdist: FreqDist + :param bins: The number of possible event types. This must be at least + as large as the number of bins in the ``freqdist``. If None, then + it's assumed to be equal to that of the ``freqdist`` + :type bins: int + """ + assert bins is None or bins >= freqdist.B(), ( + "bins parameter must not be less than %d=freqdist.B()" % freqdist.B() + ) + if bins is None: + bins = freqdist.B() + self._freqdist = freqdist + self._T = self._freqdist.B() + self._Z = bins - self._freqdist.B() + self._N = self._freqdist.N() + # self._P0 is P(0), precalculated for efficiency: + if self._N == 0: + # if freqdist is empty, we approximate P(0) by a UniformProbDist: + self._P0 = 1.0 / self._Z + else: + self._P0 = self._T / (self._Z * (self._N + self._T)) + + def prob(self, sample): + # inherit docs from ProbDistI + c = self._freqdist[sample] + return c / (self._N + self._T) if c != 0 else self._P0 + + def max(self): + return self._freqdist.max() + + def samples(self): + return self._freqdist.keys() + + def freqdist(self): + return self._freqdist + + def discount(self): + raise NotImplementedError() + + def __repr__(self): + """ + Return a string representation of this ``ProbDist``. + + :rtype: str + """ + return "" % self._freqdist.N() + + +##////////////////////////////////////////////////////// +## Good-Turing Probability Distributions +##////////////////////////////////////////////////////// + +# Good-Turing frequency estimation was contributed by Alan Turing and +# his statistical assistant I.J. Good, during their collaboration in +# the WWII. It is a statistical technique for predicting the +# probability of occurrence of objects belonging to an unknown number +# of species, given past observations of such objects and their +# species. (In drawing balls from an urn, the 'objects' would be balls +# and the 'species' would be the distinct colors of the balls (finite +# but unknown in number). +# +# Good-Turing method calculates the probability mass to assign to +# events with zero or low counts based on the number of events with +# higher counts. It does so by using the adjusted count *c\**: +# +# - *c\* = (c + 1) N(c + 1) / N(c)* for c >= 1 +# - *things with frequency zero in training* = N(1) for c == 0 +# +# where *c* is the original count, *N(i)* is the number of event types +# observed with count *i*. We can think the count of unseen as the count +# of frequency one (see Jurafsky & Martin 2nd Edition, p101). +# +# This method is problematic because the situation ``N(c+1) == 0`` +# is quite common in the original Good-Turing estimation; smoothing or +# interpolation of *N(i)* values is essential in practice. +# +# Bill Gale and Geoffrey Sampson present a simple and effective approach, +# Simple Good-Turing. As a smoothing curve they simply use a power curve: +# +# Nr = a*r^b (with b < -1 to give the appropriate hyperbolic +# relationship) +# +# They estimate a and b by simple linear regression technique on the +# logarithmic form of the equation: +# +# log Nr = a + b*log(r) +# +# However, they suggest that such a simple curve is probably only +# appropriate for high values of r. For low values of r, they use the +# measured Nr directly. (see M&S, p.213) +# +# Gale and Sampson propose to use r while the difference between r and +# r* is 1.96 greater than the standard deviation, and switch to r* if +# it is less or equal: +# +# |r - r*| > 1.96 * sqrt((r + 1)^2 (Nr+1 / Nr^2) (1 + Nr+1 / Nr)) +# +# The 1.96 coefficient correspond to a 0.05 significance criterion, +# some implementations can use a coefficient of 1.65 for a 0.1 +# significance criterion. +# + +##////////////////////////////////////////////////////// +## Simple Good-Turing Probablity Distributions +##////////////////////////////////////////////////////// + + +class SimpleGoodTuringProbDist(ProbDistI): + """ + SimpleGoodTuring ProbDist approximates from frequency to frequency of + frequency into a linear line under log space by linear regression. + Details of Simple Good-Turing algorithm can be found in: + + - Good Turing smoothing without tears" (Gale & Sampson 1995), + Journal of Quantitative Linguistics, vol. 2 pp. 217-237. + - "Speech and Language Processing (Jurafsky & Martin), + 2nd Edition, Chapter 4.5 p103 (log(Nc) = a + b*log(c)) + - https://www.grsampson.net/RGoodTur.html + + Given a set of pair (xi, yi), where the xi denotes the frequency and + yi denotes the frequency of frequency, we want to minimize their + square variation. E(x) and E(y) represent the mean of xi and yi. + + - slope: b = sigma ((xi-E(x)(yi-E(y))) / sigma ((xi-E(x))(xi-E(x))) + - intercept: a = E(y) - b.E(x) + """ + + SUM_TO_ONE = False + + def __init__(self, freqdist, bins=None): + """ + :param freqdist: The frequency counts upon which to base the + estimation. + :type freqdist: FreqDist + :param bins: The number of possible event types. This must be + larger than the number of bins in the ``freqdist``. If None, + then it's assumed to be equal to ``freqdist``.B() + 1 + :type bins: int + """ + assert ( + bins is None or bins > freqdist.B() + ), "bins parameter must not be less than %d=freqdist.B()+1" % (freqdist.B() + 1) + if bins is None: + bins = freqdist.B() + 1 + self._freqdist = freqdist + self._bins = bins + r, nr = self._r_Nr() + self.find_best_fit(r, nr) + self._switch(r, nr) + self._renormalize(r, nr) + + def _r_Nr_non_zero(self): + r_Nr = self._freqdist.r_Nr() + del r_Nr[0] + return r_Nr + + def _r_Nr(self): + """ + Split the frequency distribution in two list (r, Nr), where Nr(r) > 0 + """ + nonzero = self._r_Nr_non_zero() + + if not nonzero: + return [], [] + return zip(*sorted(nonzero.items())) + + def find_best_fit(self, r, nr): + """ + Use simple linear regression to tune parameters self._slope and + self._intercept in the log-log space based on count and Nr(count) + (Work in log space to avoid floating point underflow.) + """ + # For higher sample frequencies the data points becomes horizontal + # along line Nr=1. To create a more evident linear model in log-log + # space, we average positive Nr values with the surrounding zero + # values. (Church and Gale, 1991) + + if not r or not nr: + # Empty r or nr? + return + + zr = [] + for j in range(len(r)): + i = r[j - 1] if j > 0 else 0 + k = 2 * r[j] - i if j == len(r) - 1 else r[j + 1] + zr_ = 2.0 * nr[j] / (k - i) + zr.append(zr_) + + log_r = [math.log(i) for i in r] + log_zr = [math.log(i) for i in zr] + + xy_cov = x_var = 0.0 + x_mean = sum(log_r) / len(log_r) + y_mean = sum(log_zr) / len(log_zr) + for (x, y) in zip(log_r, log_zr): + xy_cov += (x - x_mean) * (y - y_mean) + x_var += (x - x_mean) ** 2 + self._slope = xy_cov / x_var if x_var != 0 else 0.0 + if self._slope >= -1: + warnings.warn( + "SimpleGoodTuring did not find a proper best fit " + "line for smoothing probabilities of occurrences. " + "The probability estimates are likely to be " + "unreliable." + ) + self._intercept = y_mean - self._slope * x_mean + + def _switch(self, r, nr): + """ + Calculate the r frontier where we must switch from Nr to Sr + when estimating E[Nr]. + """ + for i, r_ in enumerate(r): + if len(r) == i + 1 or r[i + 1] != r_ + 1: + # We are at the end of r, or there is a gap in r + self._switch_at = r_ + break + + Sr = self.smoothedNr + smooth_r_star = (r_ + 1) * Sr(r_ + 1) / Sr(r_) + unsmooth_r_star = (r_ + 1) * nr[i + 1] / nr[i] + + std = math.sqrt(self._variance(r_, nr[i], nr[i + 1])) + if abs(unsmooth_r_star - smooth_r_star) <= 1.96 * std: + self._switch_at = r_ + break + + def _variance(self, r, nr, nr_1): + r = float(r) + nr = float(nr) + nr_1 = float(nr_1) + return (r + 1.0) ** 2 * (nr_1 / nr**2) * (1.0 + nr_1 / nr) + + def _renormalize(self, r, nr): + """ + It is necessary to renormalize all the probability estimates to + ensure a proper probability distribution results. This can be done + by keeping the estimate of the probability mass for unseen items as + N(1)/N and renormalizing all the estimates for previously seen items + (as Gale and Sampson (1995) propose). (See M&S P.213, 1999) + """ + prob_cov = 0.0 + for r_, nr_ in zip(r, nr): + prob_cov += nr_ * self._prob_measure(r_) + if prob_cov: + self._renormal = (1 - self._prob_measure(0)) / prob_cov + + def smoothedNr(self, r): + """ + Return the number of samples with count r. + + :param r: The amount of frequency. + :type r: int + :rtype: float + """ + + # Nr = a*r^b (with b < -1 to give the appropriate hyperbolic + # relationship) + # Estimate a and b by simple linear regression technique on + # the logarithmic form of the equation: log Nr = a + b*log(r) + + return math.exp(self._intercept + self._slope * math.log(r)) + + def prob(self, sample): + """ + Return the sample's probability. + + :param sample: sample of the event + :type sample: str + :rtype: float + """ + count = self._freqdist[sample] + p = self._prob_measure(count) + if count == 0: + if self._bins == self._freqdist.B(): + p = 0.0 + else: + p = p / (self._bins - self._freqdist.B()) + else: + p = p * self._renormal + return p + + def _prob_measure(self, count): + if count == 0 and self._freqdist.N() == 0: + return 1.0 + elif count == 0 and self._freqdist.N() != 0: + return self._freqdist.Nr(1) / self._freqdist.N() + + if self._switch_at > count: + Er_1 = self._freqdist.Nr(count + 1) + Er = self._freqdist.Nr(count) + else: + Er_1 = self.smoothedNr(count + 1) + Er = self.smoothedNr(count) + + r_star = (count + 1) * Er_1 / Er + return r_star / self._freqdist.N() + + def check(self): + prob_sum = 0.0 + for i in range(0, len(self._Nr)): + prob_sum += self._Nr[i] * self._prob_measure(i) / self._renormal + print("Probability Sum:", prob_sum) + # assert prob_sum != 1.0, "probability sum should be one!" + + def discount(self): + """ + This function returns the total mass of probability transfers from the + seen samples to the unseen samples. + """ + return self.smoothedNr(1) / self._freqdist.N() + + def max(self): + return self._freqdist.max() + + def samples(self): + return self._freqdist.keys() + + def freqdist(self): + return self._freqdist + + def __repr__(self): + """ + Return a string representation of this ``ProbDist``. + + :rtype: str + """ + return "" % self._freqdist.N() + + +class MutableProbDist(ProbDistI): + """ + An mutable probdist where the probabilities may be easily modified. This + simply copies an existing probdist, storing the probability values in a + mutable dictionary and providing an update method. + """ + + def __init__(self, prob_dist, samples, store_logs=True): + """ + Creates the mutable probdist based on the given prob_dist and using + the list of samples given. These values are stored as log + probabilities if the store_logs flag is set. + + :param prob_dist: the distribution from which to garner the + probabilities + :type prob_dist: ProbDist + :param samples: the complete set of samples + :type samples: sequence of any + :param store_logs: whether to store the probabilities as logarithms + :type store_logs: bool + """ + self._samples = samples + self._sample_dict = {samples[i]: i for i in range(len(samples))} + self._data = array.array("d", [0.0]) * len(samples) + for i in range(len(samples)): + if store_logs: + self._data[i] = prob_dist.logprob(samples[i]) + else: + self._data[i] = prob_dist.prob(samples[i]) + self._logs = store_logs + + def max(self): + # inherit documentation + return max((p, v) for (v, p) in self._sample_dict.items())[1] + + def samples(self): + # inherit documentation + return self._samples + + def prob(self, sample): + # inherit documentation + i = self._sample_dict.get(sample) + if i is None: + return 0.0 + return 2 ** (self._data[i]) if self._logs else self._data[i] + + def logprob(self, sample): + # inherit documentation + i = self._sample_dict.get(sample) + if i is None: + return float("-inf") + return self._data[i] if self._logs else math.log(self._data[i], 2) + + def update(self, sample, prob, log=True): + """ + Update the probability for the given sample. This may cause the object + to stop being the valid probability distribution - the user must + ensure that they update the sample probabilities such that all samples + have probabilities between 0 and 1 and that all probabilities sum to + one. + + :param sample: the sample for which to update the probability + :type sample: any + :param prob: the new probability + :type prob: float + :param log: is the probability already logged + :type log: bool + """ + i = self._sample_dict.get(sample) + assert i is not None + if self._logs: + self._data[i] = prob if log else math.log(prob, 2) + else: + self._data[i] = 2 ** (prob) if log else prob + + +##///////////////////////////////////////////////////// +## Kneser-Ney Probability Distribution +##////////////////////////////////////////////////////// + +# This method for calculating probabilities was introduced in 1995 by Reinhard +# Kneser and Hermann Ney. It was meant to improve the accuracy of language +# models that use backing-off to deal with sparse data. The authors propose two +# ways of doing so: a marginal distribution constraint on the back-off +# distribution and a leave-one-out distribution. For a start, the first one is +# implemented as a class below. +# +# The idea behind a back-off n-gram model is that we have a series of +# frequency distributions for our n-grams so that in case we have not seen a +# given n-gram during training (and as a result have a 0 probability for it) we +# can 'back off' (hence the name!) and try testing whether we've seen the +# n-1-gram part of the n-gram in training. +# +# The novelty of Kneser and Ney's approach was that they decided to fiddle +# around with the way this latter, backed off probability was being calculated +# whereas their peers seemed to focus on the primary probability. +# +# The implementation below uses one of the techniques described in their paper +# titled "Improved backing-off for n-gram language modeling." In the same paper +# another technique is introduced to attempt to smooth the back-off +# distribution as well as the primary one. There is also a much-cited +# modification of this method proposed by Chen and Goodman. +# +# In order for the implementation of Kneser-Ney to be more efficient, some +# changes have been made to the original algorithm. Namely, the calculation of +# the normalizing function gamma has been significantly simplified and +# combined slightly differently with beta. None of these changes affect the +# nature of the algorithm, but instead aim to cut out unnecessary calculations +# and take advantage of storing and retrieving information in dictionaries +# where possible. + + +class KneserNeyProbDist(ProbDistI): + """ + Kneser-Ney estimate of a probability distribution. This is a version of + back-off that counts how likely an n-gram is provided the n-1-gram had + been seen in training. Extends the ProbDistI interface, requires a trigram + FreqDist instance to train on. Optionally, a different from default discount + value can be specified. The default discount is set to 0.75. + + """ + + def __init__(self, freqdist, bins=None, discount=0.75): + """ + :param freqdist: The trigram frequency distribution upon which to base + the estimation + :type freqdist: FreqDist + :param bins: Included for compatibility with nltk.tag.hmm + :type bins: int or float + :param discount: The discount applied when retrieving counts of + trigrams + :type discount: float (preferred, but can be set to int) + """ + + if not bins: + self._bins = freqdist.B() + else: + self._bins = bins + self._D = discount + + # cache for probability calculation + self._cache = {} + + # internal bigram and trigram frequency distributions + self._bigrams = defaultdict(int) + self._trigrams = freqdist + + # helper dictionaries used to calculate probabilities + self._wordtypes_after = defaultdict(float) + self._trigrams_contain = defaultdict(float) + self._wordtypes_before = defaultdict(float) + for w0, w1, w2 in freqdist: + self._bigrams[(w0, w1)] += freqdist[(w0, w1, w2)] + self._wordtypes_after[(w0, w1)] += 1 + self._trigrams_contain[w1] += 1 + self._wordtypes_before[(w1, w2)] += 1 + + def prob(self, trigram): + # sample must be a triple + if len(trigram) != 3: + raise ValueError("Expected an iterable with 3 members.") + trigram = tuple(trigram) + w0, w1, w2 = trigram + + if trigram in self._cache: + return self._cache[trigram] + else: + # if the sample trigram was seen during training + if trigram in self._trigrams: + prob = (self._trigrams[trigram] - self.discount()) / self._bigrams[ + (w0, w1) + ] + + # else if the 'rougher' environment was seen during training + elif (w0, w1) in self._bigrams and (w1, w2) in self._wordtypes_before: + aftr = self._wordtypes_after[(w0, w1)] + bfr = self._wordtypes_before[(w1, w2)] + + # the probability left over from alphas + leftover_prob = (aftr * self.discount()) / self._bigrams[(w0, w1)] + + # the beta (including normalization) + beta = bfr / (self._trigrams_contain[w1] - aftr) + + prob = leftover_prob * beta + + # else the sample was completely unseen during training + else: + prob = 0.0 + + self._cache[trigram] = prob + return prob + + def discount(self): + """ + Return the value by which counts are discounted. By default set to 0.75. + + :rtype: float + """ + return self._D + + def set_discount(self, discount): + """ + Set the value by which counts are discounted to the value of discount. + + :param discount: the new value to discount counts by + :type discount: float (preferred, but int possible) + :rtype: None + """ + self._D = discount + + def samples(self): + return self._trigrams.keys() + + def max(self): + return self._trigrams.max() + + def __repr__(self): + """ + Return a string representation of this ProbDist + + :rtype: str + """ + return f">> from nltk.probability import ConditionalFreqDist + >>> from nltk.tokenize import word_tokenize + >>> sent = "the the the dog dog some other words that we do not care about" + >>> cfdist = ConditionalFreqDist() + >>> for word in word_tokenize(sent): + ... condition = len(word) + ... cfdist[condition][word] += 1 + + An equivalent way to do this is with the initializer: + + >>> cfdist = ConditionalFreqDist((len(word), word) for word in word_tokenize(sent)) + + The frequency distribution for each condition is accessed using + the indexing operator: + + >>> cfdist[3] + FreqDist({'the': 3, 'dog': 2, 'not': 1}) + >>> cfdist[3].freq('the') + 0.5 + >>> cfdist[3]['dog'] + 2 + + When the indexing operator is used to access the frequency + distribution for a condition that has not been accessed before, + ``ConditionalFreqDist`` creates a new empty FreqDist for that + condition. + + """ + + def __init__(self, cond_samples=None): + """ + Construct a new empty conditional frequency distribution. In + particular, the count for every sample, under every condition, + is zero. + + :param cond_samples: The samples to initialize the conditional + frequency distribution with + :type cond_samples: Sequence of (condition, sample) tuples + """ + defaultdict.__init__(self, FreqDist) + + if cond_samples: + for (cond, sample) in cond_samples: + self[cond][sample] += 1 + + def __reduce__(self): + kv_pairs = ((cond, self[cond]) for cond in self.conditions()) + return (self.__class__, (), None, None, kv_pairs) + + def conditions(self): + """ + Return a list of the conditions that have been accessed for + this ``ConditionalFreqDist``. Use the indexing operator to + access the frequency distribution for a given condition. + Note that the frequency distributions for some conditions + may contain zero sample outcomes. + + :rtype: list + """ + return list(self.keys()) + + def N(self): + """ + Return the total number of sample outcomes that have been + recorded by this ``ConditionalFreqDist``. + + :rtype: int + """ + return sum(fdist.N() for fdist in self.values()) + + def plot( + self, + *args, + samples=None, + title="", + cumulative=False, + percents=False, + conditions=None, + show=True, + **kwargs, + ): + """ + Plot the given samples from the conditional frequency distribution. + For a cumulative plot, specify cumulative=True. Additional ``*args`` and + ``**kwargs`` are passed to matplotlib's plot function. + (Requires Matplotlib to be installed.) + + :param samples: The samples to plot + :type samples: list + :param title: The title for the graph + :type title: str + :param cumulative: Whether the plot is cumulative. (default = False) + :type cumulative: bool + :param percents: Whether the plot uses percents instead of counts. (default = False) + :type percents: bool + :param conditions: The conditions to plot (default is all) + :type conditions: list + :param show: Whether to show the plot, or only return the ax. + :type show: bool + """ + try: + import matplotlib.pyplot as plt # import statement fix + except ImportError as e: + raise ValueError( + "The plot function requires matplotlib to be installed." + "See https://matplotlib.org/" + ) from e + + if not conditions: + conditions = self.conditions() + else: + conditions = [c for c in conditions if c in self] + if not samples: + samples = sorted({v for c in conditions for v in self[c]}) + if "linewidth" not in kwargs: + kwargs["linewidth"] = 2 + ax = plt.gca() + if conditions: + freqs = [] + for condition in conditions: + if cumulative: + # freqs should be a list of list where each sub list will be a frequency of a condition + freq = list(self[condition]._cumulative_frequencies(samples)) + else: + freq = [self[condition][sample] for sample in samples] + + if percents: + freq = [f / self[condition].N() * 100 for f in freq] + + freqs.append(freq) + + if cumulative: + ylabel = "Cumulative " + legend_loc = "lower right" + else: + ylabel = "" + legend_loc = "upper right" + + if percents: + ylabel += "Percents" + else: + ylabel += "Counts" + + i = 0 + for freq in freqs: + kwargs["label"] = conditions[i] # label for each condition + i += 1 + ax.plot(freq, *args, **kwargs) + ax.legend(loc=legend_loc) + ax.grid(True, color="silver") + ax.set_xticks(range(len(samples))) + ax.set_xticklabels([str(s) for s in samples], rotation=90) + if title: + ax.set_title(title) + ax.set_xlabel("Samples") + ax.set_ylabel(ylabel) + + if show: + plt.show() + + return ax + + def tabulate(self, *args, **kwargs): + """ + Tabulate the given samples from the conditional frequency distribution. + + :param samples: The samples to plot + :type samples: list + :param conditions: The conditions to plot (default is all) + :type conditions: list + :param cumulative: A flag to specify whether the freqs are cumulative (default = False) + :type title: bool + """ + + cumulative = _get_kwarg(kwargs, "cumulative", False) + conditions = _get_kwarg(kwargs, "conditions", sorted(self.conditions())) + samples = _get_kwarg( + kwargs, + "samples", + sorted({v for c in conditions if c in self for v in self[c]}), + ) # this computation could be wasted + + width = max(len("%s" % s) for s in samples) + freqs = dict() + for c in conditions: + if cumulative: + freqs[c] = list(self[c]._cumulative_frequencies(samples)) + else: + freqs[c] = [self[c][sample] for sample in samples] + width = max(width, max(len("%d" % f) for f in freqs[c])) + + condition_size = max(len("%s" % c) for c in conditions) + print(" " * condition_size, end=" ") + for s in samples: + print("%*s" % (width, s), end=" ") + print() + for c in conditions: + print("%*s" % (condition_size, c), end=" ") + for f in freqs[c]: + print("%*d" % (width, f), end=" ") + print() + + # Mathematical operators + + def __add__(self, other): + """ + Add counts from two ConditionalFreqDists. + """ + if not isinstance(other, ConditionalFreqDist): + return NotImplemented + result = self.copy() + for cond in other.conditions(): + result[cond] += other[cond] + return result + + def __sub__(self, other): + """ + Subtract count, but keep only results with positive counts. + """ + if not isinstance(other, ConditionalFreqDist): + return NotImplemented + result = self.copy() + for cond in other.conditions(): + result[cond] -= other[cond] + if not result[cond]: + del result[cond] + return result + + def __or__(self, other): + """ + Union is the maximum of value in either of the input counters. + """ + if not isinstance(other, ConditionalFreqDist): + return NotImplemented + result = self.copy() + for cond in other.conditions(): + result[cond] |= other[cond] + return result + + def __and__(self, other): + """ + Intersection is the minimum of corresponding counts. + """ + if not isinstance(other, ConditionalFreqDist): + return NotImplemented + result = ConditionalFreqDist() + for cond in self.conditions(): + newfreqdist = self[cond] & other[cond] + if newfreqdist: + result[cond] = newfreqdist + return result + + # @total_ordering doesn't work here, since the class inherits from a builtin class + def __le__(self, other): + if not isinstance(other, ConditionalFreqDist): + raise_unorderable_types("<=", self, other) + return set(self.conditions()).issubset(other.conditions()) and all( + self[c] <= other[c] for c in self.conditions() + ) + + def __lt__(self, other): + if not isinstance(other, ConditionalFreqDist): + raise_unorderable_types("<", self, other) + return self <= other and self != other + + def __ge__(self, other): + if not isinstance(other, ConditionalFreqDist): + raise_unorderable_types(">=", self, other) + return other <= self + + def __gt__(self, other): + if not isinstance(other, ConditionalFreqDist): + raise_unorderable_types(">", self, other) + return other < self + + def deepcopy(self): + from copy import deepcopy + + return deepcopy(self) + + copy = deepcopy + + def __repr__(self): + """ + Return a string representation of this ``ConditionalFreqDist``. + + :rtype: str + """ + return "" % len(self) + + +class ConditionalProbDistI(dict, metaclass=ABCMeta): + """ + A collection of probability distributions for a single experiment + run under different conditions. Conditional probability + distributions are used to estimate the likelihood of each sample, + given the condition under which the experiment was run. For + example, a conditional probability distribution could be used to + estimate the probability of each word type in a document, given + the length of the word type. Formally, a conditional probability + distribution can be defined as a function that maps from each + condition to the ``ProbDist`` for the experiment under that + condition. + """ + + @abstractmethod + def __init__(self): + """ + Classes inheriting from ConditionalProbDistI should implement __init__. + """ + + def conditions(self): + """ + Return a list of the conditions that are represented by + this ``ConditionalProbDist``. Use the indexing operator to + access the probability distribution for a given condition. + + :rtype: list + """ + return list(self.keys()) + + def __repr__(self): + """ + Return a string representation of this ``ConditionalProbDist``. + + :rtype: str + """ + return "<%s with %d conditions>" % (type(self).__name__, len(self)) + + +class ConditionalProbDist(ConditionalProbDistI): + """ + A conditional probability distribution modeling the experiments + that were used to generate a conditional frequency distribution. + A ConditionalProbDist is constructed from a + ``ConditionalFreqDist`` and a ``ProbDist`` factory: + + - The ``ConditionalFreqDist`` specifies the frequency + distribution for each condition. + - The ``ProbDist`` factory is a function that takes a + condition's frequency distribution, and returns its + probability distribution. A ``ProbDist`` class's name (such as + ``MLEProbDist`` or ``HeldoutProbDist``) can be used to specify + that class's constructor. + + The first argument to the ``ProbDist`` factory is the frequency + distribution that it should model; and the remaining arguments are + specified by the ``factory_args`` parameter to the + ``ConditionalProbDist`` constructor. For example, the following + code constructs a ``ConditionalProbDist``, where the probability + distribution for each condition is an ``ELEProbDist`` with 10 bins: + + >>> from nltk.corpus import brown + >>> from nltk.probability import ConditionalFreqDist + >>> from nltk.probability import ConditionalProbDist, ELEProbDist + >>> cfdist = ConditionalFreqDist(brown.tagged_words()[:5000]) + >>> cpdist = ConditionalProbDist(cfdist, ELEProbDist, 10) + >>> cpdist['passed'].max() + 'VBD' + >>> cpdist['passed'].prob('VBD') #doctest: +ELLIPSIS + 0.423... + + """ + + def __init__(self, cfdist, probdist_factory, *factory_args, **factory_kw_args): + """ + Construct a new conditional probability distribution, based on + the given conditional frequency distribution and ``ProbDist`` + factory. + + :type cfdist: ConditionalFreqDist + :param cfdist: The ``ConditionalFreqDist`` specifying the + frequency distribution for each condition. + :type probdist_factory: class or function + :param probdist_factory: The function or class that maps + a condition's frequency distribution to its probability + distribution. The function is called with the frequency + distribution as its first argument, + ``factory_args`` as its remaining arguments, and + ``factory_kw_args`` as keyword arguments. + :type factory_args: (any) + :param factory_args: Extra arguments for ``probdist_factory``. + These arguments are usually used to specify extra + properties for the probability distributions of individual + conditions, such as the number of bins they contain. + :type factory_kw_args: (any) + :param factory_kw_args: Extra keyword arguments for ``probdist_factory``. + """ + self._probdist_factory = probdist_factory + self._factory_args = factory_args + self._factory_kw_args = factory_kw_args + + for condition in cfdist: + self[condition] = probdist_factory( + cfdist[condition], *factory_args, **factory_kw_args + ) + + def __missing__(self, key): + self[key] = self._probdist_factory( + FreqDist(), *self._factory_args, **self._factory_kw_args + ) + return self[key] + + +class DictionaryConditionalProbDist(ConditionalProbDistI): + """ + An alternative ConditionalProbDist that simply wraps a dictionary of + ProbDists rather than creating these from FreqDists. + """ + + def __init__(self, probdist_dict): + """ + :param probdist_dict: a dictionary containing the probdists indexed + by the conditions + :type probdist_dict: dict any -> probdist + """ + self.update(probdist_dict) + + def __missing__(self, key): + self[key] = DictionaryProbDist() + return self[key] + + +##////////////////////////////////////////////////////// +## Adding in log-space. +##////////////////////////////////////////////////////// + +# If the difference is bigger than this, then just take the bigger one: +_ADD_LOGS_MAX_DIFF = math.log(1e-30, 2) + + +def add_logs(logx, logy): + """ + Given two numbers ``logx`` = *log(x)* and ``logy`` = *log(y)*, return + *log(x+y)*. Conceptually, this is the same as returning + ``log(2**(logx)+2**(logy))``, but the actual implementation + avoids overflow errors that could result from direct computation. + """ + if logx < logy + _ADD_LOGS_MAX_DIFF: + return logy + if logy < logx + _ADD_LOGS_MAX_DIFF: + return logx + base = min(logx, logy) + return base + math.log(2 ** (logx - base) + 2 ** (logy - base), 2) + + +def sum_logs(logs): + return reduce(add_logs, logs[1:], logs[0]) if len(logs) != 0 else _NINF + + +##////////////////////////////////////////////////////// +## Probabilistic Mix-in +##////////////////////////////////////////////////////// + + +class ProbabilisticMixIn: + """ + A mix-in class to associate probabilities with other classes + (trees, rules, etc.). To use the ``ProbabilisticMixIn`` class, + define a new class that derives from an existing class and from + ProbabilisticMixIn. You will need to define a new constructor for + the new class, which explicitly calls the constructors of both its + parent classes. For example: + + >>> from nltk.probability import ProbabilisticMixIn + >>> class A: + ... def __init__(self, x, y): self.data = (x,y) + ... + >>> class ProbabilisticA(A, ProbabilisticMixIn): + ... def __init__(self, x, y, **prob_kwarg): + ... A.__init__(self, x, y) + ... ProbabilisticMixIn.__init__(self, **prob_kwarg) + + See the documentation for the ProbabilisticMixIn + ``constructor<__init__>`` for information about the arguments it + expects. + + You should generally also redefine the string representation + methods, the comparison methods, and the hashing method. + """ + + def __init__(self, **kwargs): + """ + Initialize this object's probability. This initializer should + be called by subclass constructors. ``prob`` should generally be + the first argument for those constructors. + + :param prob: The probability associated with the object. + :type prob: float + :param logprob: The log of the probability associated with + the object. + :type logprob: float + """ + if "prob" in kwargs: + if "logprob" in kwargs: + raise TypeError("Must specify either prob or logprob " "(not both)") + else: + ProbabilisticMixIn.set_prob(self, kwargs["prob"]) + elif "logprob" in kwargs: + ProbabilisticMixIn.set_logprob(self, kwargs["logprob"]) + else: + self.__prob = self.__logprob = None + + def set_prob(self, prob): + """ + Set the probability associated with this object to ``prob``. + + :param prob: The new probability + :type prob: float + """ + self.__prob = prob + self.__logprob = None + + def set_logprob(self, logprob): + """ + Set the log probability associated with this object to + ``logprob``. I.e., set the probability associated with this + object to ``2**(logprob)``. + + :param logprob: The new log probability + :type logprob: float + """ + self.__logprob = logprob + self.__prob = None + + def prob(self): + """ + Return the probability associated with this object. + + :rtype: float + """ + if self.__prob is None: + if self.__logprob is None: + return None + self.__prob = 2 ** (self.__logprob) + return self.__prob + + def logprob(self): + """ + Return ``log(p)``, where ``p`` is the probability associated + with this object. + + :rtype: float + """ + if self.__logprob is None: + if self.__prob is None: + return None + self.__logprob = math.log(self.__prob, 2) + return self.__logprob + + +class ImmutableProbabilisticMixIn(ProbabilisticMixIn): + def set_prob(self, prob): + raise ValueError("%s is immutable" % self.__class__.__name__) + + def set_logprob(self, prob): + raise ValueError("%s is immutable" % self.__class__.__name__) + + +## Helper function for processing keyword arguments + + +def _get_kwarg(kwargs, key, default): + if key in kwargs: + arg = kwargs[key] + del kwargs[key] + else: + arg = default + return arg + + +##////////////////////////////////////////////////////// +## Demonstration +##////////////////////////////////////////////////////// + + +def _create_rand_fdist(numsamples, numoutcomes): + """ + Create a new frequency distribution, with random samples. The + samples are numbers from 1 to ``numsamples``, and are generated by + summing two numbers, each of which has a uniform distribution. + """ + + fdist = FreqDist() + for x in range(numoutcomes): + y = random.randint(1, (1 + numsamples) // 2) + random.randint( + 0, numsamples // 2 + ) + fdist[y] += 1 + return fdist + + +def _create_sum_pdist(numsamples): + """ + Return the true probability distribution for the experiment + ``_create_rand_fdist(numsamples, x)``. + """ + fdist = FreqDist() + for x in range(1, (1 + numsamples) // 2 + 1): + for y in range(0, numsamples // 2 + 1): + fdist[x + y] += 1 + return MLEProbDist(fdist) + + +def demo(numsamples=6, numoutcomes=500): + """ + A demonstration of frequency distributions and probability + distributions. This demonstration creates three frequency + distributions with, and uses them to sample a random process with + ``numsamples`` samples. Each frequency distribution is sampled + ``numoutcomes`` times. These three frequency distributions are + then used to build six probability distributions. Finally, the + probability estimates of these distributions are compared to the + actual probability of each sample. + + :type numsamples: int + :param numsamples: The number of samples to use in each demo + frequency distributions. + :type numoutcomes: int + :param numoutcomes: The total number of outcomes for each + demo frequency distribution. These outcomes are divided into + ``numsamples`` bins. + :rtype: None + """ + + # Randomly sample a stochastic process three times. + fdist1 = _create_rand_fdist(numsamples, numoutcomes) + fdist2 = _create_rand_fdist(numsamples, numoutcomes) + fdist3 = _create_rand_fdist(numsamples, numoutcomes) + + # Use our samples to create probability distributions. + pdists = [ + MLEProbDist(fdist1), + LidstoneProbDist(fdist1, 0.5, numsamples), + HeldoutProbDist(fdist1, fdist2, numsamples), + HeldoutProbDist(fdist2, fdist1, numsamples), + CrossValidationProbDist([fdist1, fdist2, fdist3], numsamples), + SimpleGoodTuringProbDist(fdist1), + SimpleGoodTuringProbDist(fdist1, 7), + _create_sum_pdist(numsamples), + ] + + # Find the probability of each sample. + vals = [] + for n in range(1, numsamples + 1): + vals.append(tuple([n, fdist1.freq(n)] + [pdist.prob(n) for pdist in pdists])) + + # Print the results in a formatted table. + print( + "%d samples (1-%d); %d outcomes were sampled for each FreqDist" + % (numsamples, numsamples, numoutcomes) + ) + print("=" * 9 * (len(pdists) + 2)) + FORMATSTR = " FreqDist " + "%8s " * (len(pdists) - 1) + "| Actual" + print(FORMATSTR % tuple(repr(pdist)[1:9] for pdist in pdists[:-1])) + print("-" * 9 * (len(pdists) + 2)) + FORMATSTR = "%3d %8.6f " + "%8.6f " * (len(pdists) - 1) + "| %8.6f" + for val in vals: + print(FORMATSTR % val) + + # Print the totals for each column (should all be 1.0) + zvals = list(zip(*vals)) + sums = [sum(val) for val in zvals[1:]] + print("-" * 9 * (len(pdists) + 2)) + FORMATSTR = "Total " + "%8.6f " * (len(pdists)) + "| %8.6f" + print(FORMATSTR % tuple(sums)) + print("=" * 9 * (len(pdists) + 2)) + + # Display the distributions themselves, if they're short enough. + if len("%s" % fdist1) < 70: + print(" fdist1: %s" % fdist1) + print(" fdist2: %s" % fdist2) + print(" fdist3: %s" % fdist3) + print() + + print("Generating:") + for pdist in pdists: + fdist = FreqDist(pdist.generate() for i in range(5000)) + print("{:>20} {}".format(pdist.__class__.__name__[:20], ("%s" % fdist)[:55])) + print() + + +def gt_demo(): + from nltk import corpus + + emma_words = corpus.gutenberg.words("austen-emma.txt") + fd = FreqDist(emma_words) + sgt = SimpleGoodTuringProbDist(fd) + print("{:>18} {:>8} {:>14}".format("word", "frequency", "SimpleGoodTuring")) + fd_keys_sorted = ( + key for key, value in sorted(fd.items(), key=lambda item: item[1], reverse=True) + ) + for key in fd_keys_sorted: + print("%18s %8d %14e" % (key, fd[key], sgt.prob(key))) + + +if __name__ == "__main__": + demo(6, 10) + demo(5, 5000) + gt_demo() + +__all__ = [ + "ConditionalFreqDist", + "ConditionalProbDist", + "ConditionalProbDistI", + "CrossValidationProbDist", + "DictionaryConditionalProbDist", + "DictionaryProbDist", + "ELEProbDist", + "FreqDist", + "SimpleGoodTuringProbDist", + "HeldoutProbDist", + "ImmutableProbabilisticMixIn", + "LaplaceProbDist", + "LidstoneProbDist", + "MLEProbDist", + "MutableProbDist", + "KneserNeyProbDist", + "ProbDistI", + "ProbabilisticMixIn", + "UniformProbDist", + "WittenBellProbDist", + "add_logs", + "log_likelihood", + "sum_logs", + "entropy", +] diff --git a/llmeval-env/lib/python3.10/site-packages/nltk/stem/api.py b/llmeval-env/lib/python3.10/site-packages/nltk/stem/api.py new file mode 100644 index 0000000000000000000000000000000000000000..7a58c059a10ca2649faeb695d042a0c6cbb9ec69 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/nltk/stem/api.py @@ -0,0 +1,27 @@ +# Natural Language Toolkit: Stemmer Interface +# +# Copyright (C) 2001-2023 NLTK Project +# Author: Trevor Cohn +# Edward Loper +# Steven Bird +# URL: +# For license information, see LICENSE.TXT + +from abc import ABCMeta, abstractmethod + + +class StemmerI(metaclass=ABCMeta): + """ + A processing interface for removing morphological affixes from + words. This process is known as stemming. + + """ + + @abstractmethod + def stem(self, token): + """ + Strip affixes from the token and return the stem. + + :param token: The token that should be stemmed. + :type token: str + """ diff --git a/llmeval-env/lib/python3.10/site-packages/nltk/stem/util.py b/llmeval-env/lib/python3.10/site-packages/nltk/stem/util.py new file mode 100644 index 0000000000000000000000000000000000000000..71d3a661e582e5dd60ef0a2bdcb2674ef29d472c --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/nltk/stem/util.py @@ -0,0 +1,25 @@ +# Natural Language Toolkit: Stemmer Utilities +# +# Copyright (C) 2001-2023 NLTK Project +# Author: Helder +# URL: +# For license information, see LICENSE.TXT + + +def suffix_replace(original, old, new): + """ + Replaces the old suffix of the original string by a new suffix + """ + return original[: -len(old)] + new + + +def prefix_replace(original, old, new): + """ + Replaces the old prefix of the original string by a new suffix + + :param original: string + :param old: string + :param new: string + :return: string + """ + return new + original[len(old) :] diff --git a/llmeval-env/lib/python3.10/site-packages/nltk/text.py b/llmeval-env/lib/python3.10/site-packages/nltk/text.py new file mode 100644 index 0000000000000000000000000000000000000000..85614dbd22f6a4afd388cf96cb5f8e3520883c16 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/nltk/text.py @@ -0,0 +1,779 @@ +# Natural Language Toolkit: Texts +# +# Copyright (C) 2001-2023 NLTK Project +# Author: Steven Bird +# Edward Loper +# URL: +# For license information, see LICENSE.TXT + +""" +This module brings together a variety of NLTK functionality for +text analysis, and provides simple, interactive interfaces. +Functionality includes: concordancing, collocation discovery, +regular expression search over tokenized strings, and +distributional similarity. +""" + +import re +import sys +from collections import Counter, defaultdict, namedtuple +from functools import reduce +from math import log + +from nltk.collocations import BigramCollocationFinder +from nltk.lm import MLE +from nltk.lm.preprocessing import padded_everygram_pipeline +from nltk.metrics import BigramAssocMeasures, f_measure +from nltk.probability import ConditionalFreqDist as CFD +from nltk.probability import FreqDist +from nltk.tokenize import sent_tokenize +from nltk.util import LazyConcatenation, tokenwrap + +ConcordanceLine = namedtuple( + "ConcordanceLine", + ["left", "query", "right", "offset", "left_print", "right_print", "line"], +) + + +class ContextIndex: + """ + A bidirectional index between words and their 'contexts' in a text. + The context of a word is usually defined to be the words that occur + in a fixed window around the word; but other definitions may also + be used by providing a custom context function. + """ + + @staticmethod + def _default_context(tokens, i): + """One left token and one right token, normalized to lowercase""" + left = tokens[i - 1].lower() if i != 0 else "*START*" + right = tokens[i + 1].lower() if i != len(tokens) - 1 else "*END*" + return (left, right) + + def __init__(self, tokens, context_func=None, filter=None, key=lambda x: x): + self._key = key + self._tokens = tokens + if context_func: + self._context_func = context_func + else: + self._context_func = self._default_context + if filter: + tokens = [t for t in tokens if filter(t)] + self._word_to_contexts = CFD( + (self._key(w), self._context_func(tokens, i)) for i, w in enumerate(tokens) + ) + self._context_to_words = CFD( + (self._context_func(tokens, i), self._key(w)) for i, w in enumerate(tokens) + ) + + def tokens(self): + """ + :rtype: list(str) + :return: The document that this context index was + created from. + """ + return self._tokens + + def word_similarity_dict(self, word): + """ + Return a dictionary mapping from words to 'similarity scores,' + indicating how often these two words occur in the same + context. + """ + word = self._key(word) + word_contexts = set(self._word_to_contexts[word]) + + scores = {} + for w, w_contexts in self._word_to_contexts.items(): + scores[w] = f_measure(word_contexts, set(w_contexts)) + + return scores + + def similar_words(self, word, n=20): + scores = defaultdict(int) + for c in self._word_to_contexts[self._key(word)]: + for w in self._context_to_words[c]: + if w != word: + scores[w] += ( + self._context_to_words[c][word] * self._context_to_words[c][w] + ) + return sorted(scores, key=scores.get, reverse=True)[:n] + + def common_contexts(self, words, fail_on_unknown=False): + """ + Find contexts where the specified words can all appear; and + return a frequency distribution mapping each context to the + number of times that context was used. + + :param words: The words used to seed the similarity search + :type words: str + :param fail_on_unknown: If true, then raise a value error if + any of the given words do not occur at all in the index. + """ + words = [self._key(w) for w in words] + contexts = [set(self._word_to_contexts[w]) for w in words] + empty = [words[i] for i in range(len(words)) if not contexts[i]] + common = reduce(set.intersection, contexts) + if empty and fail_on_unknown: + raise ValueError("The following word(s) were not found:", " ".join(words)) + elif not common: + # nothing in common -- just return an empty freqdist. + return FreqDist() + else: + fd = FreqDist( + c for w in words for c in self._word_to_contexts[w] if c in common + ) + return fd + + +class ConcordanceIndex: + """ + An index that can be used to look up the offset locations at which + a given word occurs in a document. + """ + + def __init__(self, tokens, key=lambda x: x): + """ + Construct a new concordance index. + + :param tokens: The document (list of tokens) that this + concordance index was created from. This list can be used + to access the context of a given word occurrence. + :param key: A function that maps each token to a normalized + version that will be used as a key in the index. E.g., if + you use ``key=lambda s:s.lower()``, then the index will be + case-insensitive. + """ + self._tokens = tokens + """The document (list of tokens) that this concordance index + was created from.""" + + self._key = key + """Function mapping each token to an index key (or None).""" + + self._offsets = defaultdict(list) + """Dictionary mapping words (or keys) to lists of offset indices.""" + # Initialize the index (self._offsets) + for index, word in enumerate(tokens): + word = self._key(word) + self._offsets[word].append(index) + + def tokens(self): + """ + :rtype: list(str) + :return: The document that this concordance index was + created from. + """ + return self._tokens + + def offsets(self, word): + """ + :rtype: list(int) + :return: A list of the offset positions at which the given + word occurs. If a key function was specified for the + index, then given word's key will be looked up. + """ + word = self._key(word) + return self._offsets[word] + + def __repr__(self): + return "" % ( + len(self._tokens), + len(self._offsets), + ) + + def find_concordance(self, word, width=80): + """ + Find all concordance lines given the query word. + + Provided with a list of words, these will be found as a phrase. + """ + if isinstance(word, list): + phrase = word + else: + phrase = [word] + + half_width = (width - len(" ".join(phrase)) - 2) // 2 + context = width // 4 # approx number of words of context + + # Find the instances of the word to create the ConcordanceLine + concordance_list = [] + offsets = self.offsets(phrase[0]) + for i, word in enumerate(phrase[1:]): + word_offsets = {offset - i - 1 for offset in self.offsets(word)} + offsets = sorted(word_offsets.intersection(offsets)) + if offsets: + for i in offsets: + query_word = " ".join(self._tokens[i : i + len(phrase)]) + # Find the context of query word. + left_context = self._tokens[max(0, i - context) : i] + right_context = self._tokens[i + len(phrase) : i + context] + # Create the pretty lines with the query_word in the middle. + left_print = " ".join(left_context)[-half_width:] + right_print = " ".join(right_context)[:half_width] + # The WYSIWYG line of the concordance. + line_print = " ".join([left_print, query_word, right_print]) + # Create the ConcordanceLine + concordance_line = ConcordanceLine( + left_context, + query_word, + right_context, + i, + left_print, + right_print, + line_print, + ) + concordance_list.append(concordance_line) + return concordance_list + + def print_concordance(self, word, width=80, lines=25): + """ + Print concordance lines given the query word. + :param word: The target word or phrase (a list of strings) + :type word: str or list + :param lines: The number of lines to display (default=25) + :type lines: int + :param width: The width of each line, in characters (default=80) + :type width: int + :param save: The option to save the concordance. + :type save: bool + """ + concordance_list = self.find_concordance(word, width=width) + + if not concordance_list: + print("no matches") + else: + lines = min(lines, len(concordance_list)) + print(f"Displaying {lines} of {len(concordance_list)} matches:") + for i, concordance_line in enumerate(concordance_list[:lines]): + print(concordance_line.line) + + +class TokenSearcher: + """ + A class that makes it easier to use regular expressions to search + over tokenized strings. The tokenized string is converted to a + string where tokens are marked with angle brackets -- e.g., + ``''``. The regular expression + passed to the ``findall()`` method is modified to treat angle + brackets as non-capturing parentheses, in addition to matching the + token boundaries; and to have ``'.'`` not match the angle brackets. + """ + + def __init__(self, tokens): + self._raw = "".join("<" + w + ">" for w in tokens) + + def findall(self, regexp): + """ + Find instances of the regular expression in the text. + The text is a list of tokens, and a regexp pattern to match + a single token must be surrounded by angle brackets. E.g. + + >>> from nltk.text import TokenSearcher + >>> from nltk.book import text1, text5, text9 + >>> text5.findall("<.*><.*>") + you rule bro; telling you bro; u twizted bro + >>> text1.findall("(<.*>)") + monied; nervous; dangerous; white; white; white; pious; queer; good; + mature; white; Cape; great; wise; wise; butterless; white; fiendish; + pale; furious; better; certain; complete; dismasted; younger; brave; + brave; brave; brave + >>> text9.findall("{3,}") + thread through those; the thought that; that the thing; the thing + that; that that thing; through these than through; them that the; + through the thick; them that they; thought that the + + :param regexp: A regular expression + :type regexp: str + """ + # preprocess the regular expression + regexp = re.sub(r"\s", "", regexp) + regexp = re.sub(r"<", "(?:<(?:", regexp) + regexp = re.sub(r">", ")>)", regexp) + regexp = re.sub(r"(?]", regexp) + + # perform the search + hits = re.findall(regexp, self._raw) + + # Sanity check + for h in hits: + if not h.startswith("<") and h.endswith(">"): + raise ValueError("Bad regexp for TokenSearcher.findall") + + # postprocess the output + hits = [h[1:-1].split("><") for h in hits] + return hits + + +class Text: + """ + A wrapper around a sequence of simple (string) tokens, which is + intended to support initial exploration of texts (via the + interactive console). Its methods perform a variety of analyses + on the text's contexts (e.g., counting, concordancing, collocation + discovery), and display the results. If you wish to write a + program which makes use of these analyses, then you should bypass + the ``Text`` class, and use the appropriate analysis function or + class directly instead. + + A ``Text`` is typically initialized from a given document or + corpus. E.g.: + + >>> import nltk.corpus + >>> from nltk.text import Text + >>> moby = Text(nltk.corpus.gutenberg.words('melville-moby_dick.txt')) + + """ + + # This defeats lazy loading, but makes things faster. This + # *shouldn't* be necessary because the corpus view *should* be + # doing intelligent caching, but without this it's running slow. + # Look into whether the caching is working correctly. + _COPY_TOKENS = True + + def __init__(self, tokens, name=None): + """ + Create a Text object. + + :param tokens: The source text. + :type tokens: sequence of str + """ + if self._COPY_TOKENS: + tokens = list(tokens) + self.tokens = tokens + + if name: + self.name = name + elif "]" in tokens[:20]: + end = tokens[:20].index("]") + self.name = " ".join(str(tok) for tok in tokens[1:end]) + else: + self.name = " ".join(str(tok) for tok in tokens[:8]) + "..." + + # //////////////////////////////////////////////////////////// + # Support item & slice access + # //////////////////////////////////////////////////////////// + + def __getitem__(self, i): + return self.tokens[i] + + def __len__(self): + return len(self.tokens) + + # //////////////////////////////////////////////////////////// + # Interactive console methods + # //////////////////////////////////////////////////////////// + + def concordance(self, word, width=79, lines=25): + """ + Prints a concordance for ``word`` with the specified context window. + Word matching is not case-sensitive. + + :param word: The target word or phrase (a list of strings) + :type word: str or list + :param width: The width of each line, in characters (default=80) + :type width: int + :param lines: The number of lines to display (default=25) + :type lines: int + + :seealso: ``ConcordanceIndex`` + """ + if "_concordance_index" not in self.__dict__: + self._concordance_index = ConcordanceIndex( + self.tokens, key=lambda s: s.lower() + ) + + return self._concordance_index.print_concordance(word, width, lines) + + def concordance_list(self, word, width=79, lines=25): + """ + Generate a concordance for ``word`` with the specified context window. + Word matching is not case-sensitive. + + :param word: The target word or phrase (a list of strings) + :type word: str or list + :param width: The width of each line, in characters (default=80) + :type width: int + :param lines: The number of lines to display (default=25) + :type lines: int + + :seealso: ``ConcordanceIndex`` + """ + if "_concordance_index" not in self.__dict__: + self._concordance_index = ConcordanceIndex( + self.tokens, key=lambda s: s.lower() + ) + return self._concordance_index.find_concordance(word, width)[:lines] + + def collocation_list(self, num=20, window_size=2): + """ + Return collocations derived from the text, ignoring stopwords. + + >>> from nltk.book import text4 + >>> text4.collocation_list()[:2] + [('United', 'States'), ('fellow', 'citizens')] + + :param num: The maximum number of collocations to return. + :type num: int + :param window_size: The number of tokens spanned by a collocation (default=2) + :type window_size: int + :rtype: list(tuple(str, str)) + """ + if not ( + "_collocations" in self.__dict__ + and self._num == num + and self._window_size == window_size + ): + self._num = num + self._window_size = window_size + + # print("Building collocations list") + from nltk.corpus import stopwords + + ignored_words = stopwords.words("english") + finder = BigramCollocationFinder.from_words(self.tokens, window_size) + finder.apply_freq_filter(2) + finder.apply_word_filter(lambda w: len(w) < 3 or w.lower() in ignored_words) + bigram_measures = BigramAssocMeasures() + self._collocations = list( + finder.nbest(bigram_measures.likelihood_ratio, num) + ) + return self._collocations + + def collocations(self, num=20, window_size=2): + """ + Print collocations derived from the text, ignoring stopwords. + + >>> from nltk.book import text4 + >>> text4.collocations() # doctest: +NORMALIZE_WHITESPACE + United States; fellow citizens; years ago; four years; Federal + Government; General Government; American people; Vice President; God + bless; Chief Justice; one another; fellow Americans; Old World; + Almighty God; Fellow citizens; Chief Magistrate; every citizen; Indian + tribes; public debt; foreign nations + + + :param num: The maximum number of collocations to print. + :type num: int + :param window_size: The number of tokens spanned by a collocation (default=2) + :type window_size: int + """ + + collocation_strings = [ + w1 + " " + w2 for w1, w2 in self.collocation_list(num, window_size) + ] + print(tokenwrap(collocation_strings, separator="; ")) + + def count(self, word): + """ + Count the number of times this word appears in the text. + """ + return self.tokens.count(word) + + def index(self, word): + """ + Find the index of the first occurrence of the word in the text. + """ + return self.tokens.index(word) + + def readability(self, method): + # code from nltk_contrib.readability + raise NotImplementedError + + def similar(self, word, num=20): + """ + Distributional similarity: find other words which appear in the + same contexts as the specified word; list most similar words first. + + :param word: The word used to seed the similarity search + :type word: str + :param num: The number of words to generate (default=20) + :type num: int + :seealso: ContextIndex.similar_words() + """ + if "_word_context_index" not in self.__dict__: + # print('Building word-context index...') + self._word_context_index = ContextIndex( + self.tokens, filter=lambda x: x.isalpha(), key=lambda s: s.lower() + ) + + # words = self._word_context_index.similar_words(word, num) + + word = word.lower() + wci = self._word_context_index._word_to_contexts + if word in wci.conditions(): + contexts = set(wci[word]) + fd = Counter( + w + for w in wci.conditions() + for c in wci[w] + if c in contexts and not w == word + ) + words = [w for w, _ in fd.most_common(num)] + print(tokenwrap(words)) + else: + print("No matches") + + def common_contexts(self, words, num=20): + """ + Find contexts where the specified words appear; list + most frequent common contexts first. + + :param words: The words used to seed the similarity search + :type words: str + :param num: The number of words to generate (default=20) + :type num: int + :seealso: ContextIndex.common_contexts() + """ + if "_word_context_index" not in self.__dict__: + # print('Building word-context index...') + self._word_context_index = ContextIndex( + self.tokens, key=lambda s: s.lower() + ) + + try: + fd = self._word_context_index.common_contexts(words, True) + if not fd: + print("No common contexts were found") + else: + ranked_contexts = [w for w, _ in fd.most_common(num)] + print(tokenwrap(w1 + "_" + w2 for w1, w2 in ranked_contexts)) + + except ValueError as e: + print(e) + + def dispersion_plot(self, words): + """ + Produce a plot showing the distribution of the words through the text. + Requires pylab to be installed. + + :param words: The words to be plotted + :type words: list(str) + :seealso: nltk.draw.dispersion_plot() + """ + from nltk.draw import dispersion_plot + + dispersion_plot(self, words) + + def _train_default_ngram_lm(self, tokenized_sents, n=3): + train_data, padded_sents = padded_everygram_pipeline(n, tokenized_sents) + model = MLE(order=n) + model.fit(train_data, padded_sents) + return model + + def generate(self, length=100, text_seed=None, random_seed=42): + """ + Print random text, generated using a trigram language model. + See also `help(nltk.lm)`. + + :param length: The length of text to generate (default=100) + :type length: int + + :param text_seed: Generation can be conditioned on preceding context. + :type text_seed: list(str) + + :param random_seed: A random seed or an instance of `random.Random`. If provided, + makes the random sampling part of generation reproducible. (default=42) + :type random_seed: int + """ + # Create the model when using it the first time. + self._tokenized_sents = [ + sent.split(" ") for sent in sent_tokenize(" ".join(self.tokens)) + ] + if not hasattr(self, "_trigram_model"): + print("Building ngram index...", file=sys.stderr) + self._trigram_model = self._train_default_ngram_lm( + self._tokenized_sents, n=3 + ) + + generated_tokens = [] + + assert length > 0, "The `length` must be more than 0." + while len(generated_tokens) < length: + for idx, token in enumerate( + self._trigram_model.generate( + length, text_seed=text_seed, random_seed=random_seed + ) + ): + if token == "": + continue + if token == "": + break + generated_tokens.append(token) + random_seed += 1 + + prefix = " ".join(text_seed) + " " if text_seed else "" + output_str = prefix + tokenwrap(generated_tokens[:length]) + print(output_str) + return output_str + + def plot(self, *args): + """ + See documentation for FreqDist.plot() + :seealso: nltk.prob.FreqDist.plot() + """ + return self.vocab().plot(*args) + + def vocab(self): + """ + :seealso: nltk.prob.FreqDist + """ + if "_vocab" not in self.__dict__: + # print("Building vocabulary index...") + self._vocab = FreqDist(self) + return self._vocab + + def findall(self, regexp): + """ + Find instances of the regular expression in the text. + The text is a list of tokens, and a regexp pattern to match + a single token must be surrounded by angle brackets. E.g. + + >>> from nltk.book import text1, text5, text9 + >>> text5.findall("<.*><.*>") + you rule bro; telling you bro; u twizted bro + >>> text1.findall("(<.*>)") + monied; nervous; dangerous; white; white; white; pious; queer; good; + mature; white; Cape; great; wise; wise; butterless; white; fiendish; + pale; furious; better; certain; complete; dismasted; younger; brave; + brave; brave; brave + >>> text9.findall("{3,}") + thread through those; the thought that; that the thing; the thing + that; that that thing; through these than through; them that the; + through the thick; them that they; thought that the + + :param regexp: A regular expression + :type regexp: str + """ + + if "_token_searcher" not in self.__dict__: + self._token_searcher = TokenSearcher(self) + + hits = self._token_searcher.findall(regexp) + hits = [" ".join(h) for h in hits] + print(tokenwrap(hits, "; ")) + + # //////////////////////////////////////////////////////////// + # Helper Methods + # //////////////////////////////////////////////////////////// + + _CONTEXT_RE = re.compile(r"\w+|[\.\!\?]") + + def _context(self, tokens, i): + """ + One left & one right token, both case-normalized. Skip over + non-sentence-final punctuation. Used by the ``ContextIndex`` + that is created for ``similar()`` and ``common_contexts()``. + """ + # Left context + j = i - 1 + while j >= 0 and not self._CONTEXT_RE.match(tokens[j]): + j -= 1 + left = tokens[j] if j != 0 else "*START*" + + # Right context + j = i + 1 + while j < len(tokens) and not self._CONTEXT_RE.match(tokens[j]): + j += 1 + right = tokens[j] if j != len(tokens) else "*END*" + + return (left, right) + + # //////////////////////////////////////////////////////////// + # String Display + # //////////////////////////////////////////////////////////// + + def __str__(self): + return "" % self.name + + def __repr__(self): + return "" % self.name + + +# Prototype only; this approach will be slow to load +class TextCollection(Text): + """A collection of texts, which can be loaded with list of texts, or + with a corpus consisting of one or more texts, and which supports + counting, concordancing, collocation discovery, etc. Initialize a + TextCollection as follows: + + >>> import nltk.corpus + >>> from nltk.text import TextCollection + >>> from nltk.book import text1, text2, text3 + >>> gutenberg = TextCollection(nltk.corpus.gutenberg) + >>> mytexts = TextCollection([text1, text2, text3]) + + Iterating over a TextCollection produces all the tokens of all the + texts in order. + """ + + def __init__(self, source): + if hasattr(source, "words"): # bridge to the text corpus reader + source = [source.words(f) for f in source.fileids()] + + self._texts = source + Text.__init__(self, LazyConcatenation(source)) + self._idf_cache = {} + + def tf(self, term, text): + """The frequency of the term in text.""" + return text.count(term) / len(text) + + def idf(self, term): + """The number of texts in the corpus divided by the + number of texts that the term appears in. + If a term does not appear in the corpus, 0.0 is returned.""" + # idf values are cached for performance. + idf = self._idf_cache.get(term) + if idf is None: + matches = len([True for text in self._texts if term in text]) + if len(self._texts) == 0: + raise ValueError("IDF undefined for empty document collection") + idf = log(len(self._texts) / matches) if matches else 0.0 + self._idf_cache[term] = idf + return idf + + def tf_idf(self, term, text): + return self.tf(term, text) * self.idf(term) + + +def demo(): + from nltk.corpus import brown + + text = Text(brown.words(categories="news")) + print(text) + print() + print("Concordance:") + text.concordance("news") + print() + print("Distributionally similar words:") + text.similar("news") + print() + print("Collocations:") + text.collocations() + print() + # print("Automatically generated text:") + # text.generate() + # print() + print("Dispersion plot:") + text.dispersion_plot(["news", "report", "said", "announced"]) + print() + print("Vocabulary plot:") + text.plot(50) + print() + print("Indexing:") + print("text[3]:", text[3]) + print("text[3:5]:", text[3:5]) + print("text.vocab()['news']:", text.vocab()["news"]) + + +if __name__ == "__main__": + demo() + +__all__ = [ + "ContextIndex", + "ConcordanceIndex", + "TokenSearcher", + "Text", + "TextCollection", +] diff --git a/llmeval-env/lib/python3.10/site-packages/nltk/tgrep.py b/llmeval-env/lib/python3.10/site-packages/nltk/tgrep.py new file mode 100644 index 0000000000000000000000000000000000000000..45ce2ab92629296fc52931ff12720d62aab939cf --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/nltk/tgrep.py @@ -0,0 +1,1039 @@ +#!/usr/bin/env python +# +# Natural Language Toolkit: TGrep search +# +# Copyright (C) 2001-2023 NLTK Project +# Author: Will Roberts +# URL: +# For license information, see LICENSE.TXT + +""" +============================================ + TGrep search implementation for NLTK trees +============================================ + +This module supports TGrep2 syntax for matching parts of NLTK Trees. +Note that many tgrep operators require the tree passed to be a +``ParentedTree``. + +External links: + +- `Tgrep tutorial `_ +- `Tgrep2 manual `_ +- `Tgrep2 source `_ + +Usage +===== + +>>> from nltk.tree import ParentedTree +>>> from nltk.tgrep import tgrep_nodes, tgrep_positions +>>> tree = ParentedTree.fromstring('(S (NP (DT the) (JJ big) (NN dog)) (VP bit) (NP (DT a) (NN cat)))') +>>> list(tgrep_nodes('NN', [tree])) +[[ParentedTree('NN', ['dog']), ParentedTree('NN', ['cat'])]] +>>> list(tgrep_positions('NN', [tree])) +[[(0, 2), (2, 1)]] +>>> list(tgrep_nodes('DT', [tree])) +[[ParentedTree('DT', ['the']), ParentedTree('DT', ['a'])]] +>>> list(tgrep_nodes('DT $ JJ', [tree])) +[[ParentedTree('DT', ['the'])]] + +This implementation adds syntax to select nodes based on their NLTK +tree position. This syntax is ``N`` plus a Python tuple representing +the tree position. For instance, ``N()``, ``N(0,)``, ``N(0,0)`` are +valid node selectors. Example: + +>>> tree = ParentedTree.fromstring('(S (NP (DT the) (JJ big) (NN dog)) (VP bit) (NP (DT a) (NN cat)))') +>>> tree[0,0] +ParentedTree('DT', ['the']) +>>> tree[0,0].treeposition() +(0, 0) +>>> list(tgrep_nodes('N(0,0)', [tree])) +[[ParentedTree('DT', ['the'])]] + +Caveats: +======== + +- Link modifiers: "?" and "=" are not implemented. +- Tgrep compatibility: Using "@" for "!", "{" for "<", "}" for ">" are + not implemented. +- The "=" and "~" links are not implemented. + +Known Issues: +============= + +- There are some issues with link relations involving leaf nodes + (which are represented as bare strings in NLTK trees). For + instance, consider the tree:: + + (S (A x)) + + The search string ``* !>> S`` should select all nodes which are not + dominated in some way by an ``S`` node (i.e., all nodes which are + not descendants of an ``S``). Clearly, in this tree, the only node + which fulfills this criterion is the top node (since it is not + dominated by anything). However, the code here will find both the + top node and the leaf node ``x``. This is because we cannot recover + the parent of the leaf, since it is stored as a bare string. + + A possible workaround, when performing this kind of search, would be + to filter out all leaf nodes. + +Implementation notes +==================== + +This implementation is (somewhat awkwardly) based on lambda functions +which are predicates on a node. A predicate is a function which is +either True or False; using a predicate function, we can identify sets +of nodes with particular properties. A predicate function, could, for +instance, return True only if a particular node has a label matching a +particular regular expression, and has a daughter node which has no +sisters. Because tgrep2 search strings can do things statefully (such +as substituting in macros, and binding nodes with node labels), the +actual predicate function is declared with three arguments:: + + pred = lambda n, m, l: return True # some logic here + +``n`` + is a node in a tree; this argument must always be given + +``m`` + contains a dictionary, mapping macro names onto predicate functions + +``l`` + is a dictionary to map node labels onto nodes in the tree + +``m`` and ``l`` are declared to default to ``None``, and so need not be +specified in a call to a predicate. Predicates which call other +predicates must always pass the value of these arguments on. The +top-level predicate (constructed by ``_tgrep_exprs_action``) binds the +macro definitions to ``m`` and initialises ``l`` to an empty dictionary. +""" + +import functools +import re + +try: + import pyparsing +except ImportError: + print("Warning: nltk.tgrep will not work without the `pyparsing` package") + print("installed.") + +import nltk.tree + + +class TgrepException(Exception): + """Tgrep exception type.""" + + pass + + +def ancestors(node): + """ + Returns the list of all nodes dominating the given tree node. + This method will not work with leaf nodes, since there is no way + to recover the parent. + """ + results = [] + try: + current = node.parent() + except AttributeError: + # if node is a leaf, we cannot retrieve its parent + return results + while current: + results.append(current) + current = current.parent() + return results + + +def unique_ancestors(node): + """ + Returns the list of all nodes dominating the given node, where + there is only a single path of descent. + """ + results = [] + try: + current = node.parent() + except AttributeError: + # if node is a leaf, we cannot retrieve its parent + return results + while current and len(current) == 1: + results.append(current) + current = current.parent() + return results + + +def _descendants(node): + """ + Returns the list of all nodes which are descended from the given + tree node in some way. + """ + try: + treepos = node.treepositions() + except AttributeError: + return [] + return [node[x] for x in treepos[1:]] + + +def _leftmost_descendants(node): + """ + Returns the set of all nodes descended in some way through + left branches from this node. + """ + try: + treepos = node.treepositions() + except AttributeError: + return [] + return [node[x] for x in treepos[1:] if all(y == 0 for y in x)] + + +def _rightmost_descendants(node): + """ + Returns the set of all nodes descended in some way through + right branches from this node. + """ + try: + rightmost_leaf = max(node.treepositions()) + except AttributeError: + return [] + return [node[rightmost_leaf[:i]] for i in range(1, len(rightmost_leaf) + 1)] + + +def _istree(obj): + """Predicate to check whether `obj` is a nltk.tree.Tree.""" + return isinstance(obj, nltk.tree.Tree) + + +def _unique_descendants(node): + """ + Returns the list of all nodes descended from the given node, where + there is only a single path of descent. + """ + results = [] + current = node + while current and _istree(current) and len(current) == 1: + current = current[0] + results.append(current) + return results + + +def _before(node): + """ + Returns the set of all nodes that are before the given node. + """ + try: + pos = node.treeposition() + tree = node.root() + except AttributeError: + return [] + return [tree[x] for x in tree.treepositions() if x[: len(pos)] < pos[: len(x)]] + + +def _immediately_before(node): + """ + Returns the set of all nodes that are immediately before the given + node. + + Tree node A immediately precedes node B if the last terminal + symbol (word) produced by A immediately precedes the first + terminal symbol produced by B. + """ + try: + pos = node.treeposition() + tree = node.root() + except AttributeError: + return [] + # go "upwards" from pos until there is a place we can go to the left + idx = len(pos) - 1 + while 0 <= idx and pos[idx] == 0: + idx -= 1 + if idx < 0: + return [] + pos = list(pos[: idx + 1]) + pos[-1] -= 1 + before = tree[pos] + return [before] + _rightmost_descendants(before) + + +def _after(node): + """ + Returns the set of all nodes that are after the given node. + """ + try: + pos = node.treeposition() + tree = node.root() + except AttributeError: + return [] + return [tree[x] for x in tree.treepositions() if x[: len(pos)] > pos[: len(x)]] + + +def _immediately_after(node): + """ + Returns the set of all nodes that are immediately after the given + node. + + Tree node A immediately follows node B if the first terminal + symbol (word) produced by A immediately follows the last + terminal symbol produced by B. + """ + try: + pos = node.treeposition() + tree = node.root() + current = node.parent() + except AttributeError: + return [] + # go "upwards" from pos until there is a place we can go to the + # right + idx = len(pos) - 1 + while 0 <= idx and pos[idx] == len(current) - 1: + idx -= 1 + current = current.parent() + if idx < 0: + return [] + pos = list(pos[: idx + 1]) + pos[-1] += 1 + after = tree[pos] + return [after] + _leftmost_descendants(after) + + +def _tgrep_node_literal_value(node): + """ + Gets the string value of a given parse tree node, for comparison + using the tgrep node literal predicates. + """ + return node.label() if _istree(node) else str(node) + + +def _tgrep_macro_use_action(_s, _l, tokens): + """ + Builds a lambda function which looks up the macro name used. + """ + assert len(tokens) == 1 + assert tokens[0][0] == "@" + macro_name = tokens[0][1:] + + def macro_use(n, m=None, l=None): + if m is None or macro_name not in m: + raise TgrepException(f"macro {macro_name} not defined") + return m[macro_name](n, m, l) + + return macro_use + + +def _tgrep_node_action(_s, _l, tokens): + """ + Builds a lambda function representing a predicate on a tree node + depending on the name of its node. + """ + if tokens[0] == "'": + # strip initial apostrophe (tgrep2 print command) + tokens = tokens[1:] + if len(tokens) > 1: + # disjunctive definition of a node name + assert list(set(tokens[1::2])) == ["|"] + # recursively call self to interpret each node name definition + tokens = [_tgrep_node_action(None, None, [node]) for node in tokens[::2]] + # capture tokens and return the disjunction + return (lambda t: lambda n, m=None, l=None: any(f(n, m, l) for f in t))(tokens) + else: + if hasattr(tokens[0], "__call__"): + # this is a previously interpreted parenthetical node + # definition (lambda function) + return tokens[0] + elif tokens[0] == "*" or tokens[0] == "__": + return lambda n, m=None, l=None: True + elif tokens[0].startswith('"'): + assert tokens[0].endswith('"') + node_lit = tokens[0][1:-1].replace('\\"', '"').replace("\\\\", "\\") + return ( + lambda s: lambda n, m=None, l=None: _tgrep_node_literal_value(n) == s + )(node_lit) + elif tokens[0].startswith("/"): + assert tokens[0].endswith("/") + node_lit = tokens[0][1:-1] + return ( + lambda r: lambda n, m=None, l=None: r.search( + _tgrep_node_literal_value(n) + ) + )(re.compile(node_lit)) + elif tokens[0].startswith("i@"): + node_func = _tgrep_node_action(_s, _l, [tokens[0][2:].lower()]) + return ( + lambda f: lambda n, m=None, l=None: f( + _tgrep_node_literal_value(n).lower() + ) + )(node_func) + else: + return ( + lambda s: lambda n, m=None, l=None: _tgrep_node_literal_value(n) == s + )(tokens[0]) + + +def _tgrep_parens_action(_s, _l, tokens): + """ + Builds a lambda function representing a predicate on a tree node + from a parenthetical notation. + """ + assert len(tokens) == 3 + assert tokens[0] == "(" + assert tokens[2] == ")" + return tokens[1] + + +def _tgrep_nltk_tree_pos_action(_s, _l, tokens): + """ + Builds a lambda function representing a predicate on a tree node + which returns true if the node is located at a specific tree + position. + """ + # recover the tuple from the parsed string + node_tree_position = tuple(int(x) for x in tokens if x.isdigit()) + # capture the node's tree position + return ( + lambda i: lambda n, m=None, l=None: ( + hasattr(n, "treeposition") and n.treeposition() == i + ) + )(node_tree_position) + + +def _tgrep_relation_action(_s, _l, tokens): + """ + Builds a lambda function representing a predicate on a tree node + depending on its relation to other nodes in the tree. + """ + # process negation first if needed + negated = False + if tokens[0] == "!": + negated = True + tokens = tokens[1:] + if tokens[0] == "[": + # process square-bracketed relation expressions + assert len(tokens) == 3 + assert tokens[2] == "]" + retval = tokens[1] + else: + # process operator-node relation expressions + assert len(tokens) == 2 + operator, predicate = tokens + # A < B A is the parent of (immediately dominates) B. + if operator == "<": + retval = lambda n, m=None, l=None: ( + _istree(n) and any(predicate(x, m, l) for x in n) + ) + # A > B A is the child of B. + elif operator == ">": + retval = lambda n, m=None, l=None: ( + hasattr(n, "parent") + and bool(n.parent()) + and predicate(n.parent(), m, l) + ) + # A <, B Synonymous with A <1 B. + elif operator == "<," or operator == "<1": + retval = lambda n, m=None, l=None: ( + _istree(n) and bool(list(n)) and predicate(n[0], m, l) + ) + # A >, B Synonymous with A >1 B. + elif operator == ">," or operator == ">1": + retval = lambda n, m=None, l=None: ( + hasattr(n, "parent") + and bool(n.parent()) + and (n is n.parent()[0]) + and predicate(n.parent(), m, l) + ) + # A N B A is the Nth child of B (the first child is >1). + elif operator[0] == ">" and operator[1:].isdigit(): + idx = int(operator[1:]) + # capture the index parameter + retval = ( + lambda i: lambda n, m=None, l=None: ( + hasattr(n, "parent") + and bool(n.parent()) + and 0 <= i < len(n.parent()) + and (n is n.parent()[i]) + and predicate(n.parent(), m, l) + ) + )(idx - 1) + # A <' B B is the last child of A (also synonymous with A <-1 B). + # A <- B B is the last child of A (synonymous with A <-1 B). + elif operator == "<'" or operator == "<-" or operator == "<-1": + retval = lambda n, m=None, l=None: ( + _istree(n) and bool(list(n)) and predicate(n[-1], m, l) + ) + # A >' B A is the last child of B (also synonymous with A >-1 B). + # A >- B A is the last child of B (synonymous with A >-1 B). + elif operator == ">'" or operator == ">-" or operator == ">-1": + retval = lambda n, m=None, l=None: ( + hasattr(n, "parent") + and bool(n.parent()) + and (n is n.parent()[-1]) + and predicate(n.parent(), m, l) + ) + # A <-N B B is the N th-to-last child of A (the last child is <-1). + elif operator[:2] == "<-" and operator[2:].isdigit(): + idx = -int(operator[2:]) + # capture the index parameter + retval = ( + lambda i: lambda n, m=None, l=None: ( + _istree(n) + and bool(list(n)) + and 0 <= (i + len(n)) < len(n) + and predicate(n[i + len(n)], m, l) + ) + )(idx) + # A >-N B A is the N th-to-last child of B (the last child is >-1). + elif operator[:2] == ">-" and operator[2:].isdigit(): + idx = -int(operator[2:]) + # capture the index parameter + retval = ( + lambda i: lambda n, m=None, l=None: ( + hasattr(n, "parent") + and bool(n.parent()) + and 0 <= (i + len(n.parent())) < len(n.parent()) + and (n is n.parent()[i + len(n.parent())]) + and predicate(n.parent(), m, l) + ) + )(idx) + # A <: B B is the only child of A + elif operator == "<:": + retval = lambda n, m=None, l=None: ( + _istree(n) and len(n) == 1 and predicate(n[0], m, l) + ) + # A >: B A is the only child of B. + elif operator == ">:": + retval = lambda n, m=None, l=None: ( + hasattr(n, "parent") + and bool(n.parent()) + and len(n.parent()) == 1 + and predicate(n.parent(), m, l) + ) + # A << B A dominates B (A is an ancestor of B). + elif operator == "<<": + retval = lambda n, m=None, l=None: ( + _istree(n) and any(predicate(x, m, l) for x in _descendants(n)) + ) + # A >> B A is dominated by B (A is a descendant of B). + elif operator == ">>": + retval = lambda n, m=None, l=None: any( + predicate(x, m, l) for x in ancestors(n) + ) + # A <<, B B is a left-most descendant of A. + elif operator == "<<," or operator == "<<1": + retval = lambda n, m=None, l=None: ( + _istree(n) and any(predicate(x, m, l) for x in _leftmost_descendants(n)) + ) + # A >>, B A is a left-most descendant of B. + elif operator == ">>,": + retval = lambda n, m=None, l=None: any( + (predicate(x, m, l) and n in _leftmost_descendants(x)) + for x in ancestors(n) + ) + # A <<' B B is a right-most descendant of A. + elif operator == "<<'": + retval = lambda n, m=None, l=None: ( + _istree(n) + and any(predicate(x, m, l) for x in _rightmost_descendants(n)) + ) + # A >>' B A is a right-most descendant of B. + elif operator == ">>'": + retval = lambda n, m=None, l=None: any( + (predicate(x, m, l) and n in _rightmost_descendants(x)) + for x in ancestors(n) + ) + # A <<: B There is a single path of descent from A and B is on it. + elif operator == "<<:": + retval = lambda n, m=None, l=None: ( + _istree(n) and any(predicate(x, m, l) for x in _unique_descendants(n)) + ) + # A >>: B There is a single path of descent from B and A is on it. + elif operator == ">>:": + retval = lambda n, m=None, l=None: any( + predicate(x, m, l) for x in unique_ancestors(n) + ) + # A . B A immediately precedes B. + elif operator == ".": + retval = lambda n, m=None, l=None: any( + predicate(x, m, l) for x in _immediately_after(n) + ) + # A , B A immediately follows B. + elif operator == ",": + retval = lambda n, m=None, l=None: any( + predicate(x, m, l) for x in _immediately_before(n) + ) + # A .. B A precedes B. + elif operator == "..": + retval = lambda n, m=None, l=None: any( + predicate(x, m, l) for x in _after(n) + ) + # A ,, B A follows B. + elif operator == ",,": + retval = lambda n, m=None, l=None: any( + predicate(x, m, l) for x in _before(n) + ) + # A $ B A is a sister of B (and A != B). + elif operator == "$" or operator == "%": + retval = lambda n, m=None, l=None: ( + hasattr(n, "parent") + and bool(n.parent()) + and any(predicate(x, m, l) for x in n.parent() if x is not n) + ) + # A $. B A is a sister of and immediately precedes B. + elif operator == "$." or operator == "%.": + retval = lambda n, m=None, l=None: ( + hasattr(n, "right_sibling") + and bool(n.right_sibling()) + and predicate(n.right_sibling(), m, l) + ) + # A $, B A is a sister of and immediately follows B. + elif operator == "$," or operator == "%,": + retval = lambda n, m=None, l=None: ( + hasattr(n, "left_sibling") + and bool(n.left_sibling()) + and predicate(n.left_sibling(), m, l) + ) + # A $.. B A is a sister of and precedes B. + elif operator == "$.." or operator == "%..": + retval = lambda n, m=None, l=None: ( + hasattr(n, "parent") + and hasattr(n, "parent_index") + and bool(n.parent()) + and any(predicate(x, m, l) for x in n.parent()[n.parent_index() + 1 :]) + ) + # A $,, B A is a sister of and follows B. + elif operator == "$,," or operator == "%,,": + retval = lambda n, m=None, l=None: ( + hasattr(n, "parent") + and hasattr(n, "parent_index") + and bool(n.parent()) + and any(predicate(x, m, l) for x in n.parent()[: n.parent_index()]) + ) + else: + raise TgrepException(f'cannot interpret tgrep operator "{operator}"') + # now return the built function + if negated: + return (lambda r: (lambda n, m=None, l=None: not r(n, m, l)))(retval) + else: + return retval + + +def _tgrep_conjunction_action(_s, _l, tokens, join_char="&"): + """ + Builds a lambda function representing a predicate on a tree node + from the conjunction of several other such lambda functions. + + This is prototypically called for expressions like + (`tgrep_rel_conjunction`):: + + < NP & < AP < VP + + where tokens is a list of predicates representing the relations + (`< NP`, `< AP`, and `< VP`), possibly with the character `&` + included (as in the example here). + + This is also called for expressions like (`tgrep_node_expr2`):: + + NP < NN + S=s < /NP/=n : s < /VP/=v : n .. v + + tokens[0] is a tgrep_expr predicate; tokens[1:] are an (optional) + list of segmented patterns (`tgrep_expr_labeled`, processed by + `_tgrep_segmented_pattern_action`). + """ + # filter out the ampersand + tokens = [x for x in tokens if x != join_char] + if len(tokens) == 1: + return tokens[0] + else: + return ( + lambda ts: lambda n, m=None, l=None: all( + predicate(n, m, l) for predicate in ts + ) + )(tokens) + + +def _tgrep_segmented_pattern_action(_s, _l, tokens): + """ + Builds a lambda function representing a segmented pattern. + + Called for expressions like (`tgrep_expr_labeled`):: + + =s .. =v < =n + + This is a segmented pattern, a tgrep2 expression which begins with + a node label. + + The problem is that for segemented_pattern_action (': =v < =s'), + the first element (in this case, =v) is specifically selected by + virtue of matching a particular node in the tree; to retrieve + the node, we need the label, not a lambda function. For node + labels inside a tgrep_node_expr, we need a lambda function which + returns true if the node visited is the same as =v. + + We solve this by creating two copies of a node_label_use in the + grammar; the label use inside a tgrep_expr_labeled has a separate + parse action to the pred use inside a node_expr. See + `_tgrep_node_label_use_action` and + `_tgrep_node_label_pred_use_action`. + """ + # tokens[0] is a string containing the node label + node_label = tokens[0] + # tokens[1:] is an (optional) list of predicates which must all + # hold of the bound node + reln_preds = tokens[1:] + + def pattern_segment_pred(n, m=None, l=None): + """This predicate function ignores its node argument.""" + # look up the bound node using its label + if l is None or node_label not in l: + raise TgrepException(f"node_label ={node_label} not bound in pattern") + node = l[node_label] + # match the relation predicates against the node + return all(pred(node, m, l) for pred in reln_preds) + + return pattern_segment_pred + + +def _tgrep_node_label_use_action(_s, _l, tokens): + """ + Returns the node label used to begin a tgrep_expr_labeled. See + `_tgrep_segmented_pattern_action`. + + Called for expressions like (`tgrep_node_label_use`):: + + =s + + when they appear as the first element of a `tgrep_expr_labeled` + expression (see `_tgrep_segmented_pattern_action`). + + It returns the node label. + """ + assert len(tokens) == 1 + assert tokens[0].startswith("=") + return tokens[0][1:] + + +def _tgrep_node_label_pred_use_action(_s, _l, tokens): + """ + Builds a lambda function representing a predicate on a tree node + which describes the use of a previously bound node label. + + Called for expressions like (`tgrep_node_label_use_pred`):: + + =s + + when they appear inside a tgrep_node_expr (for example, inside a + relation). The predicate returns true if and only if its node + argument is identical the the node looked up in the node label + dictionary using the node's label. + """ + assert len(tokens) == 1 + assert tokens[0].startswith("=") + node_label = tokens[0][1:] + + def node_label_use_pred(n, m=None, l=None): + # look up the bound node using its label + if l is None or node_label not in l: + raise TgrepException(f"node_label ={node_label} not bound in pattern") + node = l[node_label] + # truth means the given node is this node + return n is node + + return node_label_use_pred + + +def _tgrep_bind_node_label_action(_s, _l, tokens): + """ + Builds a lambda function representing a predicate on a tree node + which can optionally bind a matching node into the tgrep2 string's + label_dict. + + Called for expressions like (`tgrep_node_expr2`):: + + /NP/ + @NP=n + """ + # tokens[0] is a tgrep_node_expr + if len(tokens) == 1: + return tokens[0] + else: + # if present, tokens[1] is the character '=', and tokens[2] is + # a tgrep_node_label, a string value containing the node label + assert len(tokens) == 3 + assert tokens[1] == "=" + node_pred = tokens[0] + node_label = tokens[2] + + def node_label_bind_pred(n, m=None, l=None): + if node_pred(n, m, l): + # bind `n` into the dictionary `l` + if l is None: + raise TgrepException( + "cannot bind node_label {}: label_dict is None".format( + node_label + ) + ) + l[node_label] = n + return True + else: + return False + + return node_label_bind_pred + + +def _tgrep_rel_disjunction_action(_s, _l, tokens): + """ + Builds a lambda function representing a predicate on a tree node + from the disjunction of several other such lambda functions. + """ + # filter out the pipe + tokens = [x for x in tokens if x != "|"] + if len(tokens) == 1: + return tokens[0] + elif len(tokens) == 2: + return (lambda a, b: lambda n, m=None, l=None: a(n, m, l) or b(n, m, l))( + tokens[0], tokens[1] + ) + + +def _macro_defn_action(_s, _l, tokens): + """ + Builds a dictionary structure which defines the given macro. + """ + assert len(tokens) == 3 + assert tokens[0] == "@" + return {tokens[1]: tokens[2]} + + +def _tgrep_exprs_action(_s, _l, tokens): + """ + This is the top-lebel node in a tgrep2 search string; the + predicate function it returns binds together all the state of a + tgrep2 search string. + + Builds a lambda function representing a predicate on a tree node + from the disjunction of several tgrep expressions. Also handles + macro definitions and macro name binding, and node label + definitions and node label binding. + """ + if len(tokens) == 1: + return lambda n, m=None, l=None: tokens[0](n, None, {}) + # filter out all the semicolons + tokens = [x for x in tokens if x != ";"] + # collect all macro definitions + macro_dict = {} + macro_defs = [tok for tok in tokens if isinstance(tok, dict)] + for macro_def in macro_defs: + macro_dict.update(macro_def) + # collect all tgrep expressions + tgrep_exprs = [tok for tok in tokens if not isinstance(tok, dict)] + # create a new scope for the node label dictionary + def top_level_pred(n, m=macro_dict, l=None): + label_dict = {} + # bind macro definitions and OR together all tgrep_exprs + return any(predicate(n, m, label_dict) for predicate in tgrep_exprs) + + return top_level_pred + + +def _build_tgrep_parser(set_parse_actions=True): + """ + Builds a pyparsing-based parser object for tokenizing and + interpreting tgrep search strings. + """ + tgrep_op = pyparsing.Optional("!") + pyparsing.Regex("[$%,.<>][%,.<>0-9-':]*") + tgrep_qstring = pyparsing.QuotedString( + quoteChar='"', escChar="\\", unquoteResults=False + ) + tgrep_node_regex = pyparsing.QuotedString( + quoteChar="/", escChar="\\", unquoteResults=False + ) + tgrep_qstring_icase = pyparsing.Regex('i@\\"(?:[^"\\n\\r\\\\]|(?:\\\\.))*\\"') + tgrep_node_regex_icase = pyparsing.Regex("i@\\/(?:[^/\\n\\r\\\\]|(?:\\\\.))*\\/") + tgrep_node_literal = pyparsing.Regex("[^][ \r\t\n;:.,&|<>()$!@%'^=]+") + tgrep_expr = pyparsing.Forward() + tgrep_relations = pyparsing.Forward() + tgrep_parens = pyparsing.Literal("(") + tgrep_expr + ")" + tgrep_nltk_tree_pos = ( + pyparsing.Literal("N(") + + pyparsing.Optional( + pyparsing.Word(pyparsing.nums) + + "," + + pyparsing.Optional( + pyparsing.delimitedList(pyparsing.Word(pyparsing.nums), delim=",") + + pyparsing.Optional(",") + ) + ) + + ")" + ) + tgrep_node_label = pyparsing.Regex("[A-Za-z0-9]+") + tgrep_node_label_use = pyparsing.Combine("=" + tgrep_node_label) + # see _tgrep_segmented_pattern_action + tgrep_node_label_use_pred = tgrep_node_label_use.copy() + macro_name = pyparsing.Regex("[^];:.,&|<>()[$!@%'^=\r\t\n ]+") + macro_name.setWhitespaceChars("") + macro_use = pyparsing.Combine("@" + macro_name) + tgrep_node_expr = ( + tgrep_node_label_use_pred + | macro_use + | tgrep_nltk_tree_pos + | tgrep_qstring_icase + | tgrep_node_regex_icase + | tgrep_qstring + | tgrep_node_regex + | "*" + | tgrep_node_literal + ) + tgrep_node_expr2 = ( + tgrep_node_expr + + pyparsing.Literal("=").setWhitespaceChars("") + + tgrep_node_label.copy().setWhitespaceChars("") + ) | tgrep_node_expr + tgrep_node = tgrep_parens | ( + pyparsing.Optional("'") + + tgrep_node_expr2 + + pyparsing.ZeroOrMore("|" + tgrep_node_expr) + ) + tgrep_brackets = pyparsing.Optional("!") + "[" + tgrep_relations + "]" + tgrep_relation = tgrep_brackets | (tgrep_op + tgrep_node) + tgrep_rel_conjunction = pyparsing.Forward() + tgrep_rel_conjunction << ( + tgrep_relation + + pyparsing.ZeroOrMore(pyparsing.Optional("&") + tgrep_rel_conjunction) + ) + tgrep_relations << tgrep_rel_conjunction + pyparsing.ZeroOrMore( + "|" + tgrep_relations + ) + tgrep_expr << tgrep_node + pyparsing.Optional(tgrep_relations) + tgrep_expr_labeled = tgrep_node_label_use + pyparsing.Optional(tgrep_relations) + tgrep_expr2 = tgrep_expr + pyparsing.ZeroOrMore(":" + tgrep_expr_labeled) + macro_defn = ( + pyparsing.Literal("@") + pyparsing.White().suppress() + macro_name + tgrep_expr2 + ) + tgrep_exprs = ( + pyparsing.Optional(macro_defn + pyparsing.ZeroOrMore(";" + macro_defn) + ";") + + tgrep_expr2 + + pyparsing.ZeroOrMore(";" + (macro_defn | tgrep_expr2)) + + pyparsing.ZeroOrMore(";").suppress() + ) + if set_parse_actions: + tgrep_node_label_use.setParseAction(_tgrep_node_label_use_action) + tgrep_node_label_use_pred.setParseAction(_tgrep_node_label_pred_use_action) + macro_use.setParseAction(_tgrep_macro_use_action) + tgrep_node.setParseAction(_tgrep_node_action) + tgrep_node_expr2.setParseAction(_tgrep_bind_node_label_action) + tgrep_parens.setParseAction(_tgrep_parens_action) + tgrep_nltk_tree_pos.setParseAction(_tgrep_nltk_tree_pos_action) + tgrep_relation.setParseAction(_tgrep_relation_action) + tgrep_rel_conjunction.setParseAction(_tgrep_conjunction_action) + tgrep_relations.setParseAction(_tgrep_rel_disjunction_action) + macro_defn.setParseAction(_macro_defn_action) + # the whole expression is also the conjunction of two + # predicates: the first node predicate, and the remaining + # relation predicates + tgrep_expr.setParseAction(_tgrep_conjunction_action) + tgrep_expr_labeled.setParseAction(_tgrep_segmented_pattern_action) + tgrep_expr2.setParseAction( + functools.partial(_tgrep_conjunction_action, join_char=":") + ) + tgrep_exprs.setParseAction(_tgrep_exprs_action) + return tgrep_exprs.ignore("#" + pyparsing.restOfLine) + + +def tgrep_tokenize(tgrep_string): + """ + Tokenizes a TGrep search string into separate tokens. + """ + parser = _build_tgrep_parser(False) + if isinstance(tgrep_string, bytes): + tgrep_string = tgrep_string.decode() + return list(parser.parseString(tgrep_string)) + + +def tgrep_compile(tgrep_string): + """ + Parses (and tokenizes, if necessary) a TGrep search string into a + lambda function. + """ + parser = _build_tgrep_parser(True) + if isinstance(tgrep_string, bytes): + tgrep_string = tgrep_string.decode() + return list(parser.parseString(tgrep_string, parseAll=True))[0] + + +def treepositions_no_leaves(tree): + """ + Returns all the tree positions in the given tree which are not + leaf nodes. + """ + treepositions = tree.treepositions() + # leaves are treeposition tuples that are not prefixes of any + # other treeposition + prefixes = set() + for pos in treepositions: + for length in range(len(pos)): + prefixes.add(pos[:length]) + return [pos for pos in treepositions if pos in prefixes] + + +def tgrep_positions(pattern, trees, search_leaves=True): + """ + Return the tree positions in the trees which match the given pattern. + + :param pattern: a tgrep search pattern + :type pattern: str or output of tgrep_compile() + :param trees: a sequence of NLTK trees (usually ParentedTrees) + :type trees: iter(ParentedTree) or iter(Tree) + :param search_leaves: whether to return matching leaf nodes + :type search_leaves: bool + :rtype: iter(tree positions) + """ + + if isinstance(pattern, (bytes, str)): + pattern = tgrep_compile(pattern) + + for tree in trees: + try: + if search_leaves: + positions = tree.treepositions() + else: + positions = treepositions_no_leaves(tree) + yield [position for position in positions if pattern(tree[position])] + except AttributeError: + yield [] + + +def tgrep_nodes(pattern, trees, search_leaves=True): + """ + Return the tree nodes in the trees which match the given pattern. + + :param pattern: a tgrep search pattern + :type pattern: str or output of tgrep_compile() + :param trees: a sequence of NLTK trees (usually ParentedTrees) + :type trees: iter(ParentedTree) or iter(Tree) + :param search_leaves: whether to return matching leaf nodes + :type search_leaves: bool + :rtype: iter(tree nodes) + """ + + if isinstance(pattern, (bytes, str)): + pattern = tgrep_compile(pattern) + + for tree in trees: + try: + if search_leaves: + positions = tree.treepositions() + else: + positions = treepositions_no_leaves(tree) + yield [tree[position] for position in positions if pattern(tree[position])] + except AttributeError: + yield [] diff --git a/llmeval-env/lib/python3.10/site-packages/nltk/toolbox.py b/llmeval-env/lib/python3.10/site-packages/nltk/toolbox.py new file mode 100644 index 0000000000000000000000000000000000000000..40155cbaec4f2554a26e1762f7b86bd7eeefb5b9 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/nltk/toolbox.py @@ -0,0 +1,524 @@ +# Natural Language Toolkit: Toolbox Reader +# +# Copyright (C) 2001-2023 NLTK Project +# Author: Greg Aumann +# URL: +# For license information, see LICENSE.TXT + +""" +Module for reading, writing and manipulating +Toolbox databases and settings files. +""" + +import codecs +import re +from io import StringIO +from xml.etree.ElementTree import Element, ElementTree, SubElement, TreeBuilder + +from nltk.data import PathPointer, find + + +class StandardFormat: + """ + Class for reading and processing standard format marker files and strings. + """ + + def __init__(self, filename=None, encoding=None): + self._encoding = encoding + if filename is not None: + self.open(filename) + + def open(self, sfm_file): + """ + Open a standard format marker file for sequential reading. + + :param sfm_file: name of the standard format marker input file + :type sfm_file: str + """ + if isinstance(sfm_file, PathPointer): + self._file = sfm_file.open(self._encoding) + else: + self._file = codecs.open(sfm_file, "r", self._encoding) + + def open_string(self, s): + """ + Open a standard format marker string for sequential reading. + + :param s: string to parse as a standard format marker input file + :type s: str + """ + self._file = StringIO(s) + + def raw_fields(self): + """ + Return an iterator that returns the next field in a (marker, value) + tuple. Linebreaks and trailing white space are preserved except + for the final newline in each field. + + :rtype: iter(tuple(str, str)) + """ + join_string = "\n" + line_regexp = r"^%s(?:\\(\S+)\s*)?(.*)$" + # discard a BOM in the first line + first_line_pat = re.compile(line_regexp % "(?:\xef\xbb\xbf)?") + line_pat = re.compile(line_regexp % "") + # need to get first line outside the loop for correct handling + # of the first marker if it spans multiple lines + file_iter = iter(self._file) + # PEP 479, prevent RuntimeError when StopIteration is raised inside generator + try: + line = next(file_iter) + except StopIteration: + # no more data is available, terminate the generator + return + mobj = re.match(first_line_pat, line) + mkr, line_value = mobj.groups() + value_lines = [line_value] + self.line_num = 0 + for line in file_iter: + self.line_num += 1 + mobj = re.match(line_pat, line) + line_mkr, line_value = mobj.groups() + if line_mkr: + yield (mkr, join_string.join(value_lines)) + mkr = line_mkr + value_lines = [line_value] + else: + value_lines.append(line_value) + self.line_num += 1 + yield (mkr, join_string.join(value_lines)) + + def fields( + self, + strip=True, + unwrap=True, + encoding=None, + errors="strict", + unicode_fields=None, + ): + """ + Return an iterator that returns the next field in a ``(marker, value)`` + tuple, where ``marker`` and ``value`` are unicode strings if an ``encoding`` + was specified in the ``fields()`` method. Otherwise they are non-unicode strings. + + :param strip: strip trailing whitespace from the last line of each field + :type strip: bool + :param unwrap: Convert newlines in a field to spaces. + :type unwrap: bool + :param encoding: Name of an encoding to use. If it is specified then + the ``fields()`` method returns unicode strings rather than non + unicode strings. + :type encoding: str or None + :param errors: Error handling scheme for codec. Same as the ``decode()`` + builtin string method. + :type errors: str + :param unicode_fields: Set of marker names whose values are UTF-8 encoded. + Ignored if encoding is None. If the whole file is UTF-8 encoded set + ``encoding='utf8'`` and leave ``unicode_fields`` with its default + value of None. + :type unicode_fields: sequence + :rtype: iter(tuple(str, str)) + """ + if encoding is None and unicode_fields is not None: + raise ValueError("unicode_fields is set but not encoding.") + unwrap_pat = re.compile(r"\n+") + for mkr, val in self.raw_fields(): + if unwrap: + val = unwrap_pat.sub(" ", val) + if strip: + val = val.rstrip() + yield (mkr, val) + + def close(self): + """Close a previously opened standard format marker file or string.""" + self._file.close() + try: + del self.line_num + except AttributeError: + pass + + +class ToolboxData(StandardFormat): + def parse(self, grammar=None, **kwargs): + if grammar: + return self._chunk_parse(grammar=grammar, **kwargs) + else: + return self._record_parse(**kwargs) + + def _record_parse(self, key=None, **kwargs): + r""" + Returns an element tree structure corresponding to a toolbox data file with + all markers at the same level. + + Thus the following Toolbox database:: + \_sh v3.0 400 Rotokas Dictionary + \_DateStampHasFourDigitYear + + \lx kaa + \ps V.A + \ge gag + \gp nek i pas + + \lx kaa + \ps V.B + \ge strangle + \gp pasim nek + + after parsing will end up with the same structure (ignoring the extra + whitespace) as the following XML fragment after being parsed by + ElementTree:: + +
+ <_sh>v3.0 400 Rotokas Dictionary + <_DateStampHasFourDigitYear/> +
+ + + kaa + V.A + gag + nek i pas + + + + kaa + V.B + strangle + pasim nek + + + + :param key: Name of key marker at the start of each record. If set to + None (the default value) the first marker that doesn't begin with + an underscore is assumed to be the key. + :type key: str + :param kwargs: Keyword arguments passed to ``StandardFormat.fields()`` + :type kwargs: dict + :rtype: ElementTree._ElementInterface + :return: contents of toolbox data divided into header and records + """ + builder = TreeBuilder() + builder.start("toolbox_data", {}) + builder.start("header", {}) + in_records = False + for mkr, value in self.fields(**kwargs): + if key is None and not in_records and mkr[0] != "_": + key = mkr + if mkr == key: + if in_records: + builder.end("record") + else: + builder.end("header") + in_records = True + builder.start("record", {}) + builder.start(mkr, {}) + builder.data(value) + builder.end(mkr) + if in_records: + builder.end("record") + else: + builder.end("header") + builder.end("toolbox_data") + return builder.close() + + def _tree2etree(self, parent): + from nltk.tree import Tree + + root = Element(parent.label()) + for child in parent: + if isinstance(child, Tree): + root.append(self._tree2etree(child)) + else: + text, tag = child + e = SubElement(root, tag) + e.text = text + return root + + def _chunk_parse(self, grammar=None, root_label="record", trace=0, **kwargs): + """ + Returns an element tree structure corresponding to a toolbox data file + parsed according to the chunk grammar. + + :type grammar: str + :param grammar: Contains the chunking rules used to parse the + database. See ``chunk.RegExp`` for documentation. + :type root_label: str + :param root_label: The node value that should be used for the + top node of the chunk structure. + :type trace: int + :param trace: The level of tracing that should be used when + parsing a text. ``0`` will generate no tracing output; + ``1`` will generate normal tracing output; and ``2`` or + higher will generate verbose tracing output. + :type kwargs: dict + :param kwargs: Keyword arguments passed to ``toolbox.StandardFormat.fields()`` + :rtype: ElementTree._ElementInterface + """ + from nltk import chunk + from nltk.tree import Tree + + cp = chunk.RegexpParser(grammar, root_label=root_label, trace=trace) + db = self.parse(**kwargs) + tb_etree = Element("toolbox_data") + header = db.find("header") + tb_etree.append(header) + for record in db.findall("record"): + parsed = cp.parse([(elem.text, elem.tag) for elem in record]) + tb_etree.append(self._tree2etree(parsed)) + return tb_etree + + +_is_value = re.compile(r"\S") + + +def to_sfm_string(tree, encoding=None, errors="strict", unicode_fields=None): + """ + Return a string with a standard format representation of the toolbox + data in tree (tree can be a toolbox database or a single record). + + :param tree: flat representation of toolbox data (whole database or single record) + :type tree: ElementTree._ElementInterface + :param encoding: Name of an encoding to use. + :type encoding: str + :param errors: Error handling scheme for codec. Same as the ``encode()`` + builtin string method. + :type errors: str + :param unicode_fields: + :type unicode_fields: dict(str) or set(str) + :rtype: str + """ + if tree.tag == "record": + root = Element("toolbox_data") + root.append(tree) + tree = root + + if tree.tag != "toolbox_data": + raise ValueError("not a toolbox_data element structure") + if encoding is None and unicode_fields is not None: + raise ValueError( + "if encoding is not specified then neither should unicode_fields" + ) + l = [] + for rec in tree: + l.append("\n") + for field in rec: + mkr = field.tag + value = field.text + if encoding is not None: + if unicode_fields is not None and mkr in unicode_fields: + cur_encoding = "utf8" + else: + cur_encoding = encoding + if re.search(_is_value, value): + l.append((f"\\{mkr} {value}\n").encode(cur_encoding, errors)) + else: + l.append((f"\\{mkr}{value}\n").encode(cur_encoding, errors)) + else: + if re.search(_is_value, value): + l.append(f"\\{mkr} {value}\n") + else: + l.append(f"\\{mkr}{value}\n") + return "".join(l[1:]) + + +class ToolboxSettings(StandardFormat): + """This class is the base class for settings files.""" + + def __init__(self): + super().__init__() + + def parse(self, encoding=None, errors="strict", **kwargs): + """ + Return the contents of toolbox settings file with a nested structure. + + :param encoding: encoding used by settings file + :type encoding: str + :param errors: Error handling scheme for codec. Same as ``decode()`` builtin method. + :type errors: str + :param kwargs: Keyword arguments passed to ``StandardFormat.fields()`` + :type kwargs: dict + :rtype: ElementTree._ElementInterface + """ + builder = TreeBuilder() + for mkr, value in self.fields(encoding=encoding, errors=errors, **kwargs): + # Check whether the first char of the field marker + # indicates a block start (+) or end (-) + block = mkr[0] + if block in ("+", "-"): + mkr = mkr[1:] + else: + block = None + # Build tree on the basis of block char + if block == "+": + builder.start(mkr, {}) + builder.data(value) + elif block == "-": + builder.end(mkr) + else: + builder.start(mkr, {}) + builder.data(value) + builder.end(mkr) + return builder.close() + + +def to_settings_string(tree, encoding=None, errors="strict", unicode_fields=None): + # write XML to file + l = list() + _to_settings_string( + tree.getroot(), + l, + encoding=encoding, + errors=errors, + unicode_fields=unicode_fields, + ) + return "".join(l) + + +def _to_settings_string(node, l, **kwargs): + # write XML to file + tag = node.tag + text = node.text + if len(node) == 0: + if text: + l.append(f"\\{tag} {text}\n") + else: + l.append("\\%s\n" % tag) + else: + if text: + l.append(f"\\+{tag} {text}\n") + else: + l.append("\\+%s\n" % tag) + for n in node: + _to_settings_string(n, l, **kwargs) + l.append("\\-%s\n" % tag) + return + + +def remove_blanks(elem): + """ + Remove all elements and subelements with no text and no child elements. + + :param elem: toolbox data in an elementtree structure + :type elem: ElementTree._ElementInterface + """ + out = list() + for child in elem: + remove_blanks(child) + if child.text or len(child) > 0: + out.append(child) + elem[:] = out + + +def add_default_fields(elem, default_fields): + """ + Add blank elements and subelements specified in default_fields. + + :param elem: toolbox data in an elementtree structure + :type elem: ElementTree._ElementInterface + :param default_fields: fields to add to each type of element and subelement + :type default_fields: dict(tuple) + """ + for field in default_fields.get(elem.tag, []): + if elem.find(field) is None: + SubElement(elem, field) + for child in elem: + add_default_fields(child, default_fields) + + +def sort_fields(elem, field_orders): + """ + Sort the elements and subelements in order specified in field_orders. + + :param elem: toolbox data in an elementtree structure + :type elem: ElementTree._ElementInterface + :param field_orders: order of fields for each type of element and subelement + :type field_orders: dict(tuple) + """ + order_dicts = dict() + for field, order in field_orders.items(): + order_dicts[field] = order_key = dict() + for i, subfield in enumerate(order): + order_key[subfield] = i + _sort_fields(elem, order_dicts) + + +def _sort_fields(elem, orders_dicts): + """sort the children of elem""" + try: + order = orders_dicts[elem.tag] + except KeyError: + pass + else: + tmp = sorted( + ((order.get(child.tag, 1e9), i), child) for i, child in enumerate(elem) + ) + elem[:] = [child for key, child in tmp] + for child in elem: + if len(child): + _sort_fields(child, orders_dicts) + + +def add_blank_lines(tree, blanks_before, blanks_between): + """ + Add blank lines before all elements and subelements specified in blank_before. + + :param elem: toolbox data in an elementtree structure + :type elem: ElementTree._ElementInterface + :param blank_before: elements and subelements to add blank lines before + :type blank_before: dict(tuple) + """ + try: + before = blanks_before[tree.tag] + between = blanks_between[tree.tag] + except KeyError: + for elem in tree: + if len(elem): + add_blank_lines(elem, blanks_before, blanks_between) + else: + last_elem = None + for elem in tree: + tag = elem.tag + if last_elem is not None and last_elem.tag != tag: + if tag in before and last_elem is not None: + e = last_elem.getiterator()[-1] + e.text = (e.text or "") + "\n" + else: + if tag in between: + e = last_elem.getiterator()[-1] + e.text = (e.text or "") + "\n" + if len(elem): + add_blank_lines(elem, blanks_before, blanks_between) + last_elem = elem + + +def demo(): + from itertools import islice + + # zip_path = find('corpora/toolbox.zip') + # lexicon = ToolboxData(ZipFilePathPointer(zip_path, 'toolbox/rotokas.dic')).parse() + file_path = find("corpora/toolbox/rotokas.dic") + lexicon = ToolboxData(file_path).parse() + print("first field in fourth record:") + print(lexicon[3][0].tag) + print(lexicon[3][0].text) + + print("\nfields in sequential order:") + for field in islice(lexicon.find("record"), 10): + print(field.tag, field.text) + + print("\nlx fields:") + for field in islice(lexicon.findall("record/lx"), 10): + print(field.text) + + settings = ToolboxSettings() + file_path = find("corpora/toolbox/MDF/MDF_AltH.typ") + settings.open(file_path) + # settings.open(ZipFilePathPointer(zip_path, entry='toolbox/MDF/MDF_AltH.typ')) + tree = settings.parse(unwrap=False, encoding="cp1252") + print(tree.find("expset/expMDF/rtfPageSetup/paperSize").text) + settings_tree = ElementTree(tree) + print(to_settings_string(settings_tree).encode("utf8")) + + +if __name__ == "__main__": + demo() diff --git a/llmeval-env/lib/python3.10/site-packages/nltk/treeprettyprinter.py b/llmeval-env/lib/python3.10/site-packages/nltk/treeprettyprinter.py new file mode 100644 index 0000000000000000000000000000000000000000..ed4e766b47c123d66b7df326cbfde26a2db99363 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/nltk/treeprettyprinter.py @@ -0,0 +1,28 @@ +# Natural Language Toolkit: ASCII visualization of NLTK trees +# +# Copyright (C) 2001-2023 NLTK Project +# Author: Andreas van Cranenburgh +# Peter Ljunglöf +# URL: +# For license information, see LICENSE.TXT + +""" +Pretty-printing of discontinuous trees. +Adapted from the disco-dop project, by Andreas van Cranenburgh. +https://github.com/andreasvc/disco-dop + +Interesting reference (not used for this code): +T. Eschbach et al., Orth. Hypergraph Drawing, Journal of +Graph Algorithms and Applications, 10(2) 141--157 (2006)149. +https://jgaa.info/accepted/2006/EschbachGuentherBecker2006.10.2.pdf +""" + +from nltk.internals import Deprecated +from nltk.tree.prettyprinter import TreePrettyPrinter as TPP + + +class TreePrettyPrinter(Deprecated, TPP): + """Import `TreePrettyPrinter` using `from nltk.tree import TreePrettyPrinter` instead.""" + + +__all__ = ["TreePrettyPrinter"] diff --git a/llmeval-env/lib/python3.10/site-packages/nltk/treetransforms.py b/llmeval-env/lib/python3.10/site-packages/nltk/treetransforms.py new file mode 100644 index 0000000000000000000000000000000000000000..6ebc061f321c701c7851370cd00cacb4499a256c --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/nltk/treetransforms.py @@ -0,0 +1,126 @@ +# Natural Language Toolkit: Tree Transformations +# +# Copyright (C) 2005-2007 Oregon Graduate Institute +# Author: Nathan Bodenstab +# URL: +# For license information, see LICENSE.TXT + +r""" +A collection of methods for tree (grammar) transformations used +in parsing natural language. + +Although many of these methods are technically grammar transformations +(ie. Chomsky Norm Form), when working with treebanks it is much more +natural to visualize these modifications in a tree structure. Hence, +we will do all transformation directly to the tree itself. +Transforming the tree directly also allows us to do parent annotation. +A grammar can then be simply induced from the modified tree. + +The following is a short tutorial on the available transformations. + + 1. Chomsky Normal Form (binarization) + + It is well known that any grammar has a Chomsky Normal Form (CNF) + equivalent grammar where CNF is defined by every production having + either two non-terminals or one terminal on its right hand side. + When we have hierarchically structured data (ie. a treebank), it is + natural to view this in terms of productions where the root of every + subtree is the head (left hand side) of the production and all of + its children are the right hand side constituents. In order to + convert a tree into CNF, we simply need to ensure that every subtree + has either two subtrees as children (binarization), or one leaf node + (non-terminal). In order to binarize a subtree with more than two + children, we must introduce artificial nodes. + + There are two popular methods to convert a tree into CNF: left + factoring and right factoring. The following example demonstrates + the difference between them. Example:: + + Original Right-Factored Left-Factored + + A A A + / | \ / \ / \ + B C D ==> B A| OR A| D + / \ / \ + C D B C + + 2. Parent Annotation + + In addition to binarizing the tree, there are two standard + modifications to node labels we can do in the same traversal: parent + annotation and Markov order-N smoothing (or sibling smoothing). + + The purpose of parent annotation is to refine the probabilities of + productions by adding a small amount of context. With this simple + addition, a CYK (inside-outside, dynamic programming chart parse) + can improve from 74% to 79% accuracy. A natural generalization from + parent annotation is to grandparent annotation and beyond. The + tradeoff becomes accuracy gain vs. computational complexity. We + must also keep in mind data sparcity issues. Example:: + + Original Parent Annotation + + A A^ + / | \ / \ + B C D ==> B^ A|^ where ? is the + / \ parent of A + C^ D^ + + + 3. Markov order-N smoothing + + Markov smoothing combats data sparcity issues as well as decreasing + computational requirements by limiting the number of children + included in artificial nodes. In practice, most people use an order + 2 grammar. Example:: + + Original No Smoothing Markov order 1 Markov order 2 etc. + + __A__ A A A + / /|\ \ / \ / \ / \ + B C D E F ==> B A| ==> B A| ==> B A| + / \ / \ / \ + C ... C ... C ... + + + + Annotation decisions can be thought about in the vertical direction + (parent, grandparent, etc) and the horizontal direction (number of + siblings to keep). Parameters to the following functions specify + these values. For more information see: + + Dan Klein and Chris Manning (2003) "Accurate Unlexicalized + Parsing", ACL-03. https://www.aclweb.org/anthology/P03-1054 + + 4. Unary Collapsing + + Collapse unary productions (ie. subtrees with a single child) into a + new non-terminal (Tree node). This is useful when working with + algorithms that do not allow unary productions, yet you do not wish + to lose the parent information. Example:: + + A + | + B ==> A+B + / \ / \ + C D C D + +""" + +from nltk.internals import deprecated +from nltk.tree.transforms import chomsky_normal_form as cnf +from nltk.tree.transforms import collapse_unary as cu +from nltk.tree.transforms import un_chomsky_normal_form as ucnf + +chomsky_normal_form = deprecated( + "Import using `from nltk.tree import chomsky_normal_form` instead." +)(cnf) +un_chomsky_normal_form = deprecated( + "Import using `from nltk.tree import un_chomsky_normal_form` instead." +)(ucnf) +collapse_unary = deprecated( + "Import using `from nltk.tree import collapse_unary` instead." +)(cu) + + +__all__ = ["chomsky_normal_form", "un_chomsky_normal_form", "collapse_unary"] diff --git a/llmeval-env/lib/python3.10/site-packages/nltk/util.py b/llmeval-env/lib/python3.10/site-packages/nltk/util.py new file mode 100644 index 0000000000000000000000000000000000000000..4d2d96fb74f2ec375596ae8761f565351cbedf31 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/nltk/util.py @@ -0,0 +1,1216 @@ +# Natural Language Toolkit: Utility functions +# +# Copyright (C) 2001-2023 NLTK Project +# Author: Steven Bird +# Eric Kafe (acyclic closures) +# URL: +# For license information, see LICENSE.TXT + +import inspect +import locale +import os +import pydoc +import re +import textwrap +import warnings +from collections import defaultdict, deque +from itertools import chain, combinations, islice, tee +from pprint import pprint +from urllib.request import ( + HTTPPasswordMgrWithDefaultRealm, + ProxyBasicAuthHandler, + ProxyDigestAuthHandler, + ProxyHandler, + build_opener, + getproxies, + install_opener, +) + +from nltk.collections import * +from nltk.internals import deprecated, raise_unorderable_types, slice_bounds + +###################################################################### +# Short usage message +###################################################################### + + +@deprecated("Use help(obj) instead.") +def usage(obj): + str(obj) # In case it's lazy, this will load it. + + if not isinstance(obj, type): + obj = obj.__class__ + + print(f"{obj.__name__} supports the following operations:") + for (name, method) in sorted(pydoc.allmethods(obj).items()): + if name.startswith("_"): + continue + if getattr(method, "__deprecated__", False): + continue + + try: + sig = str(inspect.signature(method)) + except ValueError as e: + # builtins sometimes don't support introspection + if "builtin" in str(e): + continue + else: + raise + + args = sig.lstrip("(").rstrip(")").split(", ") + meth = inspect.getattr_static(obj, name) + if isinstance(meth, (classmethod, staticmethod)): + name = f"cls.{name}" + elif args and args[0] == "self": + name = f"self.{name}" + args.pop(0) + print( + textwrap.fill( + f"{name}({', '.join(args)})", + initial_indent=" - ", + subsequent_indent=" " * (len(name) + 5), + ) + ) + + +########################################################################## +# IDLE +########################################################################## + + +def in_idle(): + """ + Return True if this function is run within idle. Tkinter + programs that are run in idle should never call ``Tk.mainloop``; so + this function should be used to gate all calls to ``Tk.mainloop``. + + :warning: This function works by checking ``sys.stdin``. If the + user has modified ``sys.stdin``, then it may return incorrect + results. + :rtype: bool + """ + import sys + + return sys.stdin.__class__.__name__ in ("PyShell", "RPCProxy") + + +########################################################################## +# PRETTY PRINTING +########################################################################## + + +def pr(data, start=0, end=None): + """ + Pretty print a sequence of data items + + :param data: the data stream to print + :type data: sequence or iter + :param start: the start position + :type start: int + :param end: the end position + :type end: int + """ + pprint(list(islice(data, start, end))) + + +def print_string(s, width=70): + """ + Pretty print a string, breaking lines on whitespace + + :param s: the string to print, consisting of words and spaces + :type s: str + :param width: the display width + :type width: int + """ + print("\n".join(textwrap.wrap(s, width=width))) + + +def tokenwrap(tokens, separator=" ", width=70): + """ + Pretty print a list of text tokens, breaking lines on whitespace + + :param tokens: the tokens to print + :type tokens: list + :param separator: the string to use to separate tokens + :type separator: str + :param width: the display width (default=70) + :type width: int + """ + return "\n".join(textwrap.wrap(separator.join(tokens), width=width)) + + +########################################################################## +# Indexing +########################################################################## + + +class Index(defaultdict): + def __init__(self, pairs): + defaultdict.__init__(self, list) + for key, value in pairs: + self[key].append(value) + + +###################################################################### +## Regexp display (thanks to David Mertz) +###################################################################### + + +def re_show(regexp, string, left="{", right="}"): + """ + Return a string with markers surrounding the matched substrings. + Search str for substrings matching ``regexp`` and wrap the matches + with braces. This is convenient for learning about regular expressions. + + :param regexp: The regular expression. + :type regexp: str + :param string: The string being matched. + :type string: str + :param left: The left delimiter (printed before the matched substring) + :type left: str + :param right: The right delimiter (printed after the matched substring) + :type right: str + :rtype: str + """ + print(re.compile(regexp, re.M).sub(left + r"\g<0>" + right, string.rstrip())) + + +########################################################################## +# READ FROM FILE OR STRING +########################################################################## + +# recipe from David Mertz +def filestring(f): + if hasattr(f, "read"): + return f.read() + elif isinstance(f, str): + with open(f) as infile: + return infile.read() + else: + raise ValueError("Must be called with a filename or file-like object") + + +########################################################################## +# Breadth-First Search +########################################################################## + + +def breadth_first(tree, children=iter, maxdepth=-1): + """Traverse the nodes of a tree in breadth-first order. + (No check for cycles.) + The first argument should be the tree root; + children should be a function taking as argument a tree node + and returning an iterator of the node's children. + """ + queue = deque([(tree, 0)]) + + while queue: + node, depth = queue.popleft() + yield node + + if depth != maxdepth: + try: + queue.extend((c, depth + 1) for c in children(node)) + except TypeError: + pass + + +########################################################################## +# Graph Drawing +########################################################################## + + +def edge_closure(tree, children=iter, maxdepth=-1, verbose=False): + """Yield the edges of a graph in breadth-first order, + discarding eventual cycles. + The first argument should be the start node; + children should be a function taking as argument a graph node + and returning an iterator of the node's children. + + >>> from nltk.util import edge_closure + >>> print(list(edge_closure('A', lambda node:{'A':['B','C'], 'B':'C', 'C':'B'}[node]))) + [('A', 'B'), ('A', 'C'), ('B', 'C'), ('C', 'B')] + """ + traversed = set() + edges = set() + queue = deque([(tree, 0)]) + while queue: + node, depth = queue.popleft() + traversed.add(node) + if depth != maxdepth: + try: + for child in children(node): + if child not in traversed: + queue.append((child, depth + 1)) + else: + if verbose: + warnings.warn( + f"Discarded redundant search for {child} at depth {depth + 1}", + stacklevel=2, + ) + edge = (node, child) + if edge not in edges: + yield edge + edges.add(edge) + except TypeError: + pass + + +def edges2dot(edges, shapes=None, attr=None): + """ + :param edges: the set (or list) of edges of a directed graph. + + :return dot_string: a representation of 'edges' as a string in the DOT + graph language, which can be converted to an image by the 'dot' program + from the Graphviz package, or nltk.parse.dependencygraph.dot2img(dot_string). + + :param shapes: dictionary of strings that trigger a specified shape. + :param attr: dictionary with global graph attributes + + >>> import nltk + >>> from nltk.util import edges2dot + >>> print(edges2dot([('A', 'B'), ('A', 'C'), ('B', 'C'), ('C', 'B')])) + digraph G { + "A" -> "B"; + "A" -> "C"; + "B" -> "C"; + "C" -> "B"; + } + + """ + if not shapes: + shapes = dict() + if not attr: + attr = dict() + + dot_string = "digraph G {\n" + + for pair in attr.items(): + dot_string += f"{pair[0]} = {pair[1]};\n" + + for edge in edges: + for shape in shapes.items(): + for node in range(2): + if shape[0] in repr(edge[node]): + dot_string += f'"{edge[node]}" [shape = {shape[1]}];\n' + dot_string += f'"{edge[0]}" -> "{edge[1]}";\n' + + dot_string += "}\n" + return dot_string + + +def unweighted_minimum_spanning_digraph(tree, children=iter, shapes=None, attr=None): + """ + + Build a Minimum Spanning Tree (MST) of an unweighted graph, + by traversing the nodes of a tree in breadth-first order, + discarding eventual cycles. + + Return a representation of this MST as a string in the DOT graph language, + which can be converted to an image by the 'dot' program from the Graphviz + package, or nltk.parse.dependencygraph.dot2img(dot_string). + + The first argument should be the tree root; + children should be a function taking as argument a tree node + and returning an iterator of the node's children. + + >>> import nltk + >>> wn=nltk.corpus.wordnet + >>> from nltk.util import unweighted_minimum_spanning_digraph as umsd + >>> print(umsd(wn.synset('bound.a.01'), lambda s:s.also_sees())) + digraph G { + "Synset('bound.a.01')" -> "Synset('unfree.a.02')"; + "Synset('unfree.a.02')" -> "Synset('confined.a.02')"; + "Synset('unfree.a.02')" -> "Synset('dependent.a.01')"; + "Synset('unfree.a.02')" -> "Synset('restricted.a.01')"; + "Synset('restricted.a.01')" -> "Synset('classified.a.02')"; + } + + """ + return edges2dot( + edge_closure( + tree, lambda node: unweighted_minimum_spanning_dict(tree, children)[node] + ), + shapes, + attr, + ) + + +########################################################################## +# Breadth-First / Depth-first Searches with Cycle Detection +########################################################################## + + +def acyclic_breadth_first(tree, children=iter, maxdepth=-1): + """Traverse the nodes of a tree in breadth-first order, + discarding eventual cycles. + + The first argument should be the tree root; + children should be a function taking as argument a tree node + and returning an iterator of the node's children. + """ + traversed = set() + queue = deque([(tree, 0)]) + while queue: + node, depth = queue.popleft() + yield node + traversed.add(node) + if depth != maxdepth: + try: + for child in children(node): + if child not in traversed: + queue.append((child, depth + 1)) + else: + warnings.warn( + "Discarded redundant search for {} at depth {}".format( + child, depth + 1 + ), + stacklevel=2, + ) + except TypeError: + pass + + +def acyclic_depth_first(tree, children=iter, depth=-1, cut_mark=None, traversed=None): + """Traverse the nodes of a tree in depth-first order, + discarding eventual cycles within any branch, + adding cut_mark (when specified) if cycles were truncated. + + The first argument should be the tree root; + children should be a function taking as argument a tree node + and returning an iterator of the node's children. + + Catches all cycles: + + >>> import nltk + >>> from nltk.util import acyclic_depth_first as acyclic_tree + >>> wn=nltk.corpus.wordnet + >>> from pprint import pprint + >>> pprint(acyclic_tree(wn.synset('dog.n.01'), lambda s:s.hypernyms(),cut_mark='...')) + [Synset('dog.n.01'), + [Synset('canine.n.02'), + [Synset('carnivore.n.01'), + [Synset('placental.n.01'), + [Synset('mammal.n.01'), + [Synset('vertebrate.n.01'), + [Synset('chordate.n.01'), + [Synset('animal.n.01'), + [Synset('organism.n.01'), + [Synset('living_thing.n.01'), + [Synset('whole.n.02'), + [Synset('object.n.01'), + [Synset('physical_entity.n.01'), + [Synset('entity.n.01')]]]]]]]]]]]]], + [Synset('domestic_animal.n.01'), "Cycle(Synset('animal.n.01'),-3,...)"]] + """ + if traversed is None: + traversed = {tree} + out_tree = [tree] + if depth != 0: + try: + for child in children(tree): + if child not in traversed: + # Recurse with a common "traversed" set for all children: + traversed.add(child) + out_tree += [ + acyclic_depth_first( + child, children, depth - 1, cut_mark, traversed + ) + ] + else: + warnings.warn( + "Discarded redundant search for {} at depth {}".format( + child, depth - 1 + ), + stacklevel=3, + ) + if cut_mark: + out_tree += [f"Cycle({child},{depth - 1},{cut_mark})"] + except TypeError: + pass + elif cut_mark: + out_tree += [cut_mark] + return out_tree + + +def acyclic_branches_depth_first( + tree, children=iter, depth=-1, cut_mark=None, traversed=None +): + """Traverse the nodes of a tree in depth-first order, + discarding eventual cycles within the same branch, + but keep duplicate paths in different branches. + Add cut_mark (when defined) if cycles were truncated. + + The first argument should be the tree root; + children should be a function taking as argument a tree node + and returning an iterator of the node's children. + + Catches only only cycles within the same branch, + but keeping cycles from different branches: + + >>> import nltk + >>> from nltk.util import acyclic_branches_depth_first as tree + >>> wn=nltk.corpus.wordnet + >>> from pprint import pprint + >>> pprint(tree(wn.synset('certified.a.01'), lambda s:s.also_sees(), cut_mark='...', depth=4)) + [Synset('certified.a.01'), + [Synset('authorized.a.01'), + [Synset('lawful.a.01'), + [Synset('legal.a.01'), + "Cycle(Synset('lawful.a.01'),0,...)", + [Synset('legitimate.a.01'), '...']], + [Synset('straight.a.06'), + [Synset('honest.a.01'), '...'], + "Cycle(Synset('lawful.a.01'),0,...)"]], + [Synset('legitimate.a.01'), + "Cycle(Synset('authorized.a.01'),1,...)", + [Synset('legal.a.01'), + [Synset('lawful.a.01'), '...'], + "Cycle(Synset('legitimate.a.01'),0,...)"], + [Synset('valid.a.01'), + "Cycle(Synset('legitimate.a.01'),0,...)", + [Synset('reasonable.a.01'), '...']]], + [Synset('official.a.01'), "Cycle(Synset('authorized.a.01'),1,...)"]], + [Synset('documented.a.01')]] + """ + if traversed is None: + traversed = {tree} + out_tree = [tree] + if depth != 0: + try: + for child in children(tree): + if child not in traversed: + # Recurse with a different "traversed" set for each child: + out_tree += [ + acyclic_branches_depth_first( + child, + children, + depth - 1, + cut_mark, + traversed.union({child}), + ) + ] + else: + warnings.warn( + "Discarded redundant search for {} at depth {}".format( + child, depth - 1 + ), + stacklevel=3, + ) + if cut_mark: + out_tree += [f"Cycle({child},{depth - 1},{cut_mark})"] + except TypeError: + pass + elif cut_mark: + out_tree += [cut_mark] + return out_tree + + +def acyclic_dic2tree(node, dic): + """Convert acyclic dictionary 'dic', where the keys are nodes, and the + values are lists of children, to output tree suitable for pprint(), + starting at root 'node', with subtrees as nested lists.""" + return [node] + [acyclic_dic2tree(child, dic) for child in dic[node]] + + +def unweighted_minimum_spanning_dict(tree, children=iter): + """ + Output a dictionary representing a Minimum Spanning Tree (MST) + of an unweighted graph, by traversing the nodes of a tree in + breadth-first order, discarding eventual cycles. + + The first argument should be the tree root; + children should be a function taking as argument a tree node + and returning an iterator of the node's children. + + >>> import nltk + >>> from nltk.corpus import wordnet as wn + >>> from nltk.util import unweighted_minimum_spanning_dict as umsd + >>> from pprint import pprint + >>> pprint(umsd(wn.synset('bound.a.01'), lambda s:s.also_sees())) + {Synset('bound.a.01'): [Synset('unfree.a.02')], + Synset('classified.a.02'): [], + Synset('confined.a.02'): [], + Synset('dependent.a.01'): [], + Synset('restricted.a.01'): [Synset('classified.a.02')], + Synset('unfree.a.02'): [Synset('confined.a.02'), + Synset('dependent.a.01'), + Synset('restricted.a.01')]} + + """ + traversed = set() # Empty set of traversed nodes + queue = deque([tree]) # Initialize queue + agenda = {tree} # Set of all nodes ever queued + mstdic = {} # Empty MST dictionary + while queue: + node = queue.popleft() # Node is not yet in the MST dictionary, + mstdic[node] = [] # so add it with an empty list of children + if node not in traversed: # Avoid cycles + traversed.add(node) + for child in children(node): + if child not in agenda: # Queue nodes only once + mstdic[node].append(child) # Add child to the MST + queue.append(child) # Add child to queue + agenda.add(child) + return mstdic + + +def unweighted_minimum_spanning_tree(tree, children=iter): + """ + Output a Minimum Spanning Tree (MST) of an unweighted graph, + by traversing the nodes of a tree in breadth-first order, + discarding eventual cycles. + + The first argument should be the tree root; + children should be a function taking as argument a tree node + and returning an iterator of the node's children. + + >>> import nltk + >>> from nltk.util import unweighted_minimum_spanning_tree as mst + >>> wn=nltk.corpus.wordnet + >>> from pprint import pprint + >>> pprint(mst(wn.synset('bound.a.01'), lambda s:s.also_sees())) + [Synset('bound.a.01'), + [Synset('unfree.a.02'), + [Synset('confined.a.02')], + [Synset('dependent.a.01')], + [Synset('restricted.a.01'), [Synset('classified.a.02')]]]] + """ + return acyclic_dic2tree(tree, unweighted_minimum_spanning_dict(tree, children)) + + +########################################################################## +# Guess Character Encoding +########################################################################## + +# adapted from io.py in the docutils extension module (https://docutils.sourceforge.io/) +# http://www.pyzine.com/Issue008/Section_Articles/article_Encodings.html + + +def guess_encoding(data): + """ + Given a byte string, attempt to decode it. + Tries the standard 'UTF8' and 'latin-1' encodings, + Plus several gathered from locale information. + + The calling program *must* first call:: + + locale.setlocale(locale.LC_ALL, '') + + If successful it returns ``(decoded_unicode, successful_encoding)``. + If unsuccessful it raises a ``UnicodeError``. + """ + successful_encoding = None + # we make 'utf-8' the first encoding + encodings = ["utf-8"] + # + # next we add anything we can learn from the locale + try: + encodings.append(locale.nl_langinfo(locale.CODESET)) + except AttributeError: + pass + try: + encodings.append(locale.getlocale()[1]) + except (AttributeError, IndexError): + pass + try: + encodings.append(locale.getdefaultlocale()[1]) + except (AttributeError, IndexError): + pass + # + # we try 'latin-1' last + encodings.append("latin-1") + for enc in encodings: + # some of the locale calls + # may have returned None + if not enc: + continue + try: + decoded = str(data, enc) + successful_encoding = enc + + except (UnicodeError, LookupError): + pass + else: + break + if not successful_encoding: + raise UnicodeError( + "Unable to decode input data. " + "Tried the following encodings: %s." + % ", ".join([repr(enc) for enc in encodings if enc]) + ) + else: + return (decoded, successful_encoding) + + +########################################################################## +# Remove repeated elements from a list deterministcally +########################################################################## + + +def unique_list(xs): + seen = set() + # not seen.add(x) here acts to make the code shorter without using if statements, seen.add(x) always returns None. + return [x for x in xs if x not in seen and not seen.add(x)] + + +########################################################################## +# Invert a dictionary +########################################################################## + + +def invert_dict(d): + inverted_dict = defaultdict(list) + for key in d: + if hasattr(d[key], "__iter__"): + for term in d[key]: + inverted_dict[term].append(key) + else: + inverted_dict[d[key]] = key + return inverted_dict + + +########################################################################## +# Utilities for directed graphs: transitive closure, and inversion +# The graph is represented as a dictionary of sets +########################################################################## + + +def transitive_closure(graph, reflexive=False): + """ + Calculate the transitive closure of a directed graph, + optionally the reflexive transitive closure. + + The algorithm is a slight modification of the "Marking Algorithm" of + Ioannidis & Ramakrishnan (1998) "Efficient Transitive Closure Algorithms". + + :param graph: the initial graph, represented as a dictionary of sets + :type graph: dict(set) + :param reflexive: if set, also make the closure reflexive + :type reflexive: bool + :rtype: dict(set) + """ + if reflexive: + base_set = lambda k: {k} + else: + base_set = lambda k: set() + # The graph U_i in the article: + agenda_graph = {k: graph[k].copy() for k in graph} + # The graph M_i in the article: + closure_graph = {k: base_set(k) for k in graph} + for i in graph: + agenda = agenda_graph[i] + closure = closure_graph[i] + while agenda: + j = agenda.pop() + closure.add(j) + closure |= closure_graph.setdefault(j, base_set(j)) + agenda |= agenda_graph.get(j, base_set(j)) + agenda -= closure + return closure_graph + + +def invert_graph(graph): + """ + Inverts a directed graph. + + :param graph: the graph, represented as a dictionary of sets + :type graph: dict(set) + :return: the inverted graph + :rtype: dict(set) + """ + inverted = {} + for key in graph: + for value in graph[key]: + inverted.setdefault(value, set()).add(key) + return inverted + + +########################################################################## +# HTML Cleaning +########################################################################## + + +def clean_html(html): + raise NotImplementedError( + "To remove HTML markup, use BeautifulSoup's get_text() function" + ) + + +def clean_url(url): + raise NotImplementedError( + "To remove HTML markup, use BeautifulSoup's get_text() function" + ) + + +########################################################################## +# FLATTEN LISTS +########################################################################## + + +def flatten(*args): + """ + Flatten a list. + + >>> from nltk.util import flatten + >>> flatten(1, 2, ['b', 'a' , ['c', 'd']], 3) + [1, 2, 'b', 'a', 'c', 'd', 3] + + :param args: items and lists to be combined into a single list + :rtype: list + """ + + x = [] + for l in args: + if not isinstance(l, (list, tuple)): + l = [l] + for item in l: + if isinstance(item, (list, tuple)): + x.extend(flatten(item)) + else: + x.append(item) + return x + + +########################################################################## +# Ngram iteration +########################################################################## + + +def pad_sequence( + sequence, + n, + pad_left=False, + pad_right=False, + left_pad_symbol=None, + right_pad_symbol=None, +): + """ + Returns a padded sequence of items before ngram extraction. + + >>> list(pad_sequence([1,2,3,4,5], 2, pad_left=True, pad_right=True, left_pad_symbol='', right_pad_symbol='')) + ['', 1, 2, 3, 4, 5, ''] + >>> list(pad_sequence([1,2,3,4,5], 2, pad_left=True, left_pad_symbol='')) + ['', 1, 2, 3, 4, 5] + >>> list(pad_sequence([1,2,3,4,5], 2, pad_right=True, right_pad_symbol='')) + [1, 2, 3, 4, 5, ''] + + :param sequence: the source data to be padded + :type sequence: sequence or iter + :param n: the degree of the ngrams + :type n: int + :param pad_left: whether the ngrams should be left-padded + :type pad_left: bool + :param pad_right: whether the ngrams should be right-padded + :type pad_right: bool + :param left_pad_symbol: the symbol to use for left padding (default is None) + :type left_pad_symbol: any + :param right_pad_symbol: the symbol to use for right padding (default is None) + :type right_pad_symbol: any + :rtype: sequence or iter + """ + sequence = iter(sequence) + if pad_left: + sequence = chain((left_pad_symbol,) * (n - 1), sequence) + if pad_right: + sequence = chain(sequence, (right_pad_symbol,) * (n - 1)) + return sequence + + +# add a flag to pad the sequence so we get peripheral ngrams? + + +def ngrams(sequence, n, **kwargs): + """ + Return the ngrams generated from a sequence of items, as an iterator. + For example: + + >>> from nltk.util import ngrams + >>> list(ngrams([1,2,3,4,5], 3)) + [(1, 2, 3), (2, 3, 4), (3, 4, 5)] + + Wrap with list for a list version of this function. Set pad_left + or pad_right to true in order to get additional ngrams: + + >>> list(ngrams([1,2,3,4,5], 2, pad_right=True)) + [(1, 2), (2, 3), (3, 4), (4, 5), (5, None)] + >>> list(ngrams([1,2,3,4,5], 2, pad_right=True, right_pad_symbol='')) + [(1, 2), (2, 3), (3, 4), (4, 5), (5, '')] + >>> list(ngrams([1,2,3,4,5], 2, pad_left=True, left_pad_symbol='')) + [('', 1), (1, 2), (2, 3), (3, 4), (4, 5)] + >>> list(ngrams([1,2,3,4,5], 2, pad_left=True, pad_right=True, left_pad_symbol='', right_pad_symbol='')) + [('', 1), (1, 2), (2, 3), (3, 4), (4, 5), (5, '')] + + + :param sequence: the source data to be converted into ngrams + :type sequence: sequence or iter + :param n: the degree of the ngrams + :type n: int + :param pad_left: whether the ngrams should be left-padded + :type pad_left: bool + :param pad_right: whether the ngrams should be right-padded + :type pad_right: bool + :param left_pad_symbol: the symbol to use for left padding (default is None) + :type left_pad_symbol: any + :param right_pad_symbol: the symbol to use for right padding (default is None) + :type right_pad_symbol: any + :rtype: sequence or iter + """ + sequence = pad_sequence(sequence, n, **kwargs) + + # Creates the sliding window, of n no. of items. + # `iterables` is a tuple of iterables where each iterable is a window of n items. + iterables = tee(sequence, n) + + for i, sub_iterable in enumerate(iterables): # For each window, + for _ in range(i): # iterate through every order of ngrams + next(sub_iterable, None) # generate the ngrams within the window. + return zip(*iterables) # Unpack and flattens the iterables. + + +def bigrams(sequence, **kwargs): + """ + Return the bigrams generated from a sequence of items, as an iterator. + For example: + + >>> from nltk.util import bigrams + >>> list(bigrams([1,2,3,4,5])) + [(1, 2), (2, 3), (3, 4), (4, 5)] + + Use bigrams for a list version of this function. + + :param sequence: the source data to be converted into bigrams + :type sequence: sequence or iter + :rtype: iter(tuple) + """ + + yield from ngrams(sequence, 2, **kwargs) + + +def trigrams(sequence, **kwargs): + """ + Return the trigrams generated from a sequence of items, as an iterator. + For example: + + >>> from nltk.util import trigrams + >>> list(trigrams([1,2,3,4,5])) + [(1, 2, 3), (2, 3, 4), (3, 4, 5)] + + Use trigrams for a list version of this function. + + :param sequence: the source data to be converted into trigrams + :type sequence: sequence or iter + :rtype: iter(tuple) + """ + + yield from ngrams(sequence, 3, **kwargs) + + +def everygrams( + sequence, min_len=1, max_len=-1, pad_left=False, pad_right=False, **kwargs +): + """ + Returns all possible ngrams generated from a sequence of items, as an iterator. + + >>> sent = 'a b c'.split() + + New version outputs for everygrams. + >>> list(everygrams(sent)) + [('a',), ('a', 'b'), ('a', 'b', 'c'), ('b',), ('b', 'c'), ('c',)] + + Old version outputs for everygrams. + >>> sorted(everygrams(sent), key=len) + [('a',), ('b',), ('c',), ('a', 'b'), ('b', 'c'), ('a', 'b', 'c')] + + >>> list(everygrams(sent, max_len=2)) + [('a',), ('a', 'b'), ('b',), ('b', 'c'), ('c',)] + + :param sequence: the source data to be converted into ngrams. If max_len is + not provided, this sequence will be loaded into memory + :type sequence: sequence or iter + :param min_len: minimum length of the ngrams, aka. n-gram order/degree of ngram + :type min_len: int + :param max_len: maximum length of the ngrams (set to length of sequence by default) + :type max_len: int + :param pad_left: whether the ngrams should be left-padded + :type pad_left: bool + :param pad_right: whether the ngrams should be right-padded + :type pad_right: bool + :rtype: iter(tuple) + """ + + # Get max_len for padding. + if max_len == -1: + try: + max_len = len(sequence) + except TypeError: + sequence = list(sequence) + max_len = len(sequence) + + # Pad if indicated using max_len. + sequence = pad_sequence(sequence, max_len, pad_left, pad_right, **kwargs) + + # Sliding window to store grams. + history = list(islice(sequence, max_len)) + + # Yield ngrams from sequence. + while history: + for ngram_len in range(min_len, len(history) + 1): + yield tuple(history[:ngram_len]) + + # Append element to history if sequence has more items. + try: + history.append(next(sequence)) + except StopIteration: + pass + + del history[0] + + +def skipgrams(sequence, n, k, **kwargs): + """ + Returns all possible skipgrams generated from a sequence of items, as an iterator. + Skipgrams are ngrams that allows tokens to be skipped. + Refer to http://homepages.inf.ed.ac.uk/ballison/pdf/lrec_skipgrams.pdf + + >>> sent = "Insurgents killed in ongoing fighting".split() + >>> list(skipgrams(sent, 2, 2)) + [('Insurgents', 'killed'), ('Insurgents', 'in'), ('Insurgents', 'ongoing'), ('killed', 'in'), ('killed', 'ongoing'), ('killed', 'fighting'), ('in', 'ongoing'), ('in', 'fighting'), ('ongoing', 'fighting')] + >>> list(skipgrams(sent, 3, 2)) + [('Insurgents', 'killed', 'in'), ('Insurgents', 'killed', 'ongoing'), ('Insurgents', 'killed', 'fighting'), ('Insurgents', 'in', 'ongoing'), ('Insurgents', 'in', 'fighting'), ('Insurgents', 'ongoing', 'fighting'), ('killed', 'in', 'ongoing'), ('killed', 'in', 'fighting'), ('killed', 'ongoing', 'fighting'), ('in', 'ongoing', 'fighting')] + + :param sequence: the source data to be converted into trigrams + :type sequence: sequence or iter + :param n: the degree of the ngrams + :type n: int + :param k: the skip distance + :type k: int + :rtype: iter(tuple) + """ + + # Pads the sequence as desired by **kwargs. + if "pad_left" in kwargs or "pad_right" in kwargs: + sequence = pad_sequence(sequence, n, **kwargs) + + # Note when iterating through the ngrams, the pad_right here is not + # the **kwargs padding, it's for the algorithm to detect the SENTINEL + # object on the right pad to stop inner loop. + SENTINEL = object() + for ngram in ngrams(sequence, n + k, pad_right=True, right_pad_symbol=SENTINEL): + head = ngram[:1] + tail = ngram[1:] + for skip_tail in combinations(tail, n - 1): + if skip_tail[-1] is SENTINEL: + continue + yield head + skip_tail + + +###################################################################### +# Binary Search in a File +###################################################################### + +# inherited from pywordnet, by Oliver Steele +def binary_search_file(file, key, cache=None, cacheDepth=-1): + """ + Return the line from the file with first word key. + Searches through a sorted file using the binary search algorithm. + + :type file: file + :param file: the file to be searched through. + :type key: str + :param key: the identifier we are searching for. + """ + + key = key + " " + keylen = len(key) + start = 0 + currentDepth = 0 + + if hasattr(file, "name"): + end = os.stat(file.name).st_size - 1 + else: + file.seek(0, 2) + end = file.tell() - 1 + file.seek(0) + + if cache is None: + cache = {} + + while start < end: + lastState = start, end + middle = (start + end) // 2 + + if cache.get(middle): + offset, line = cache[middle] + + else: + line = "" + while True: + file.seek(max(0, middle - 1)) + if middle > 0: + file.discard_line() + offset = file.tell() + line = file.readline() + if line != "": + break + # at EOF; try to find start of the last line + middle = (start + middle) // 2 + if middle == end - 1: + return None + if currentDepth < cacheDepth: + cache[middle] = (offset, line) + + if offset > end: + assert end != middle - 1, "infinite loop" + end = middle - 1 + elif line[:keylen] == key: + return line + elif line > key: + assert end != middle - 1, "infinite loop" + end = middle - 1 + elif line < key: + start = offset + len(line) - 1 + + currentDepth += 1 + thisState = start, end + + if lastState == thisState: + # Detects the condition where we're searching past the end + # of the file, which is otherwise difficult to detect + return None + + return None + + +###################################################################### +# Proxy configuration +###################################################################### + + +def set_proxy(proxy, user=None, password=""): + """ + Set the HTTP proxy for Python to download through. + + If ``proxy`` is None then tries to set proxy from environment or system + settings. + + :param proxy: The HTTP proxy server to use. For example: + 'http://proxy.example.com:3128/' + :param user: The username to authenticate with. Use None to disable + authentication. + :param password: The password to authenticate with. + """ + if proxy is None: + # Try and find the system proxy settings + try: + proxy = getproxies()["http"] + except KeyError as e: + raise ValueError("Could not detect default proxy settings") from e + + # Set up the proxy handler + proxy_handler = ProxyHandler({"https": proxy, "http": proxy}) + opener = build_opener(proxy_handler) + + if user is not None: + # Set up basic proxy authentication if provided + password_manager = HTTPPasswordMgrWithDefaultRealm() + password_manager.add_password(realm=None, uri=proxy, user=user, passwd=password) + opener.add_handler(ProxyBasicAuthHandler(password_manager)) + opener.add_handler(ProxyDigestAuthHandler(password_manager)) + + # Override the existing url opener + install_opener(opener) + + +###################################################################### +# ElementTree pretty printing from https://www.effbot.org/zone/element-lib.htm +###################################################################### + + +def elementtree_indent(elem, level=0): + """ + Recursive function to indent an ElementTree._ElementInterface + used for pretty printing. Run indent on elem and then output + in the normal way. + + :param elem: element to be indented. will be modified. + :type elem: ElementTree._ElementInterface + :param level: level of indentation for this element + :type level: nonnegative integer + :rtype: ElementTree._ElementInterface + :return: Contents of elem indented to reflect its structure + """ + + i = "\n" + level * " " + if len(elem): + if not elem.text or not elem.text.strip(): + elem.text = i + " " + for elem in elem: + elementtree_indent(elem, level + 1) + if not elem.tail or not elem.tail.strip(): + elem.tail = i + else: + if level and (not elem.tail or not elem.tail.strip()): + elem.tail = i + + +###################################################################### +# Mathematical approximations +###################################################################### + + +def choose(n, k): + """ + This function is a fast way to calculate binomial coefficients, commonly + known as nCk, i.e. the number of combinations of n things taken k at a time. + (https://en.wikipedia.org/wiki/Binomial_coefficient). + + This is the *scipy.special.comb()* with long integer computation but this + approximation is faster, see https://github.com/nltk/nltk/issues/1181 + + >>> choose(4, 2) + 6 + >>> choose(6, 2) + 15 + + :param n: The number of things. + :type n: int + :param r: The number of times a thing is taken. + :type r: int + """ + if 0 <= k <= n: + ntok, ktok = 1, 1 + for t in range(1, min(k, n - k) + 1): + ntok *= n + ktok *= t + n -= 1 + return ntok // ktok + else: + return 0 + + +###################################################################### +# Iteration utilities +###################################################################### + + +def pairwise(iterable): + """s -> (s0,s1), (s1,s2), (s2, s3), ...""" + a, b = tee(iterable) + next(b, None) + return zip(a, b) + + +###################################################################### +# Parallelization. +###################################################################### + + +def parallelize_preprocess(func, iterator, processes, progress_bar=False): + from joblib import Parallel, delayed + from tqdm import tqdm + + iterator = tqdm(iterator) if progress_bar else iterator + if processes <= 1: + return map(func, iterator) + return Parallel(n_jobs=processes)(delayed(func)(line) for line in iterator) diff --git a/llmeval-env/lib/python3.10/site-packages/nltk/wsd.py b/llmeval-env/lib/python3.10/site-packages/nltk/wsd.py new file mode 100644 index 0000000000000000000000000000000000000000..8e29ce1e44b302d751a55d9512363f364a7c3f47 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/nltk/wsd.py @@ -0,0 +1,51 @@ +# Natural Language Toolkit: Word Sense Disambiguation Algorithms +# +# Authors: Liling Tan , +# Dmitrijs Milajevs +# +# Copyright (C) 2001-2023 NLTK Project +# URL: +# For license information, see LICENSE.TXT + +from nltk.corpus import wordnet + + +def lesk(context_sentence, ambiguous_word, pos=None, synsets=None): + """Return a synset for an ambiguous word in a context. + + :param iter context_sentence: The context sentence where the ambiguous word + occurs, passed as an iterable of words. + :param str ambiguous_word: The ambiguous word that requires WSD. + :param str pos: A specified Part-of-Speech (POS). + :param iter synsets: Possible synsets of the ambiguous word. + :return: ``lesk_sense`` The Synset() object with the highest signature overlaps. + + This function is an implementation of the original Lesk algorithm (1986) [1]. + + Usage example:: + + >>> lesk(['I', 'went', 'to', 'the', 'bank', 'to', 'deposit', 'money', '.'], 'bank', 'n') + Synset('savings_bank.n.02') + + [1] Lesk, Michael. "Automatic sense disambiguation using machine + readable dictionaries: how to tell a pine cone from an ice cream + cone." Proceedings of the 5th Annual International Conference on + Systems Documentation. ACM, 1986. + https://dl.acm.org/citation.cfm?id=318728 + """ + + context = set(context_sentence) + if synsets is None: + synsets = wordnet.synsets(ambiguous_word) + + if pos: + synsets = [ss for ss in synsets if str(ss.pos()) == pos] + + if not synsets: + return None + + _, sense = max( + (len(context.intersection(ss.definition().split())), ss) for ss in synsets + ) + + return sense diff --git a/llmeval-env/lib/python3.10/site-packages/nvidia_cufft_cu12-11.0.2.54.dist-info/INSTALLER b/llmeval-env/lib/python3.10/site-packages/nvidia_cufft_cu12-11.0.2.54.dist-info/INSTALLER new file mode 100644 index 0000000000000000000000000000000000000000..a1b589e38a32041e49332e5e81c2d363dc418d68 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/nvidia_cufft_cu12-11.0.2.54.dist-info/INSTALLER @@ -0,0 +1 @@ +pip diff --git a/llmeval-env/lib/python3.10/site-packages/nvidia_cufft_cu12-11.0.2.54.dist-info/License.txt b/llmeval-env/lib/python3.10/site-packages/nvidia_cufft_cu12-11.0.2.54.dist-info/License.txt new file mode 100644 index 0000000000000000000000000000000000000000..b491c70e0aef319022ded661e111ddbd45b8a17f --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/nvidia_cufft_cu12-11.0.2.54.dist-info/License.txt @@ -0,0 +1,1568 @@ +End User License Agreement +-------------------------- + + +Preface +------- + +The Software License Agreement in Chapter 1 and the Supplement +in Chapter 2 contain license terms and conditions that govern +the use of NVIDIA software. By accepting this agreement, you +agree to comply with all the terms and conditions applicable +to the product(s) included herein. + + +NVIDIA Driver + + +Description + +This package contains the operating system driver and +fundamental system software components for NVIDIA GPUs. + + +NVIDIA CUDA Toolkit + + +Description + +The NVIDIA CUDA Toolkit provides command-line and graphical +tools for building, debugging and optimizing the performance +of applications accelerated by NVIDIA GPUs, runtime and math +libraries, and documentation including programming guides, +user manuals, and API references. + + +Default Install Location of CUDA Toolkit + +Windows platform: + +%ProgramFiles%\NVIDIA GPU Computing Toolkit\CUDA\v#.# + +Linux platform: + +/usr/local/cuda-#.# + +Mac platform: + +/Developer/NVIDIA/CUDA-#.# + + +NVIDIA CUDA Samples + + +Description + +This package includes over 100+ CUDA examples that demonstrate +various CUDA programming principles, and efficient CUDA +implementation of algorithms in specific application domains. + + +Default Install Location of CUDA Samples + +Windows platform: + +%ProgramData%\NVIDIA Corporation\CUDA Samples\v#.# + +Linux platform: + +/usr/local/cuda-#.#/samples + +and + +$HOME/NVIDIA_CUDA-#.#_Samples + +Mac platform: + +/Developer/NVIDIA/CUDA-#.#/samples + + +NVIDIA Nsight Visual Studio Edition (Windows only) + + +Description + +NVIDIA Nsight Development Platform, Visual Studio Edition is a +development environment integrated into Microsoft Visual +Studio that provides tools for debugging, profiling, analyzing +and optimizing your GPU computing and graphics applications. + + +Default Install Location of Nsight Visual Studio Edition + +Windows platform: + +%ProgramFiles(x86)%\NVIDIA Corporation\Nsight Visual Studio Edition #.# + + +1. 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CUDA Toolkit Supplement to Software License Agreement for +NVIDIA Software Development Kits +------------------------------------------------------------ + + +Release date: August 16, 2018 +----------------------------- + +The terms in this supplement govern your use of the NVIDIA +CUDA Toolkit SDK under the terms of your license agreement +(“Agreement”) as modified by this supplement. Capitalized +terms used but not defined below have the meaning assigned to +them in the Agreement. + +This supplement is an exhibit to the Agreement and is +incorporated as an integral part of the Agreement. In the +event of conflict between the terms in this supplement and the +terms in the Agreement, the terms in this supplement govern. + + +2.1. License Scope + +The SDK is licensed for you to develop applications only for +use in systems with NVIDIA GPUs. + + +2.2. Distribution + +The portions of the SDK that are distributable under the +Agreement are listed in Attachment A. + + +2.3. 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Attachment A + +The following portions of the SDK are distributable under the +Agreement: + +Component + +CUDA Runtime + +Windows + +cudart.dll, cudart_static.lib, cudadevrt.lib + +Mac OSX + +libcudart.dylib, libcudart_static.a, libcudadevrt.a + +Linux + +libcudart.so, libcudart_static.a, libcudadevrt.a + +Android + +libcudart.so, libcudart_static.a, libcudadevrt.a + +Component + +CUDA FFT Library + +Windows + +cufft.dll, cufftw.dll, cufft.lib, cufftw.lib + +Mac OSX + +libcufft.dylib, libcufft_static.a, libcufftw.dylib, +libcufftw_static.a + +Linux + +libcufft.so, libcufft_static.a, libcufftw.so, +libcufftw_static.a + +Android + +libcufft.so, libcufft_static.a, libcufftw.so, +libcufftw_static.a + +Component + +CUDA BLAS Library + +Windows + +cublas.dll, cublasLt.dll + +Mac OSX + +libcublas.dylib, libcublasLt.dylib, libcublas_static.a, +libcublasLt_static.a + +Linux + +libcublas.so, libcublasLt.so, libcublas_static.a, +libcublasLt_static.a + +Android + +libcublas.so, libcublasLt.so, libcublas_static.a, +libcublasLt_static.a + +Component + +NVIDIA "Drop-in" BLAS Library + +Windows + +nvblas.dll + +Mac OSX + +libnvblas.dylib + +Linux + +libnvblas.so + +Component + +CUDA Sparse Matrix Library + +Windows + +cusparse.dll, cusparse.lib + +Mac OSX + +libcusparse.dylib, libcusparse_static.a + +Linux + +libcusparse.so, libcusparse_static.a + +Android + +libcusparse.so, libcusparse_static.a + +Component + +CUDA Linear Solver Library + +Windows + +cusolver.dll, cusolver.lib + +Mac OSX + +libcusolver.dylib, libcusolver_static.a + +Linux + +libcusolver.so, libcusolver_static.a + +Android + +libcusolver.so, libcusolver_static.a + +Component + +CUDA Random Number Generation Library + +Windows + +curand.dll, curand.lib + +Mac OSX + +libcurand.dylib, libcurand_static.a + +Linux + +libcurand.so, libcurand_static.a + +Android + +libcurand.so, libcurand_static.a + +Component + +CUDA Accelerated Graph Library + +Component + +NVIDIA Performance Primitives Library + +Windows + +nppc.dll, nppc.lib, nppial.dll, nppial.lib, nppicc.dll, +nppicc.lib, nppicom.dll, nppicom.lib, nppidei.dll, +nppidei.lib, nppif.dll, nppif.lib, nppig.dll, nppig.lib, +nppim.dll, nppim.lib, nppist.dll, nppist.lib, nppisu.dll, +nppisu.lib, nppitc.dll, nppitc.lib, npps.dll, npps.lib + +Mac OSX + +libnppc.dylib, libnppc_static.a, libnppial.dylib, +libnppial_static.a, libnppicc.dylib, libnppicc_static.a, +libnppicom.dylib, libnppicom_static.a, libnppidei.dylib, +libnppidei_static.a, libnppif.dylib, libnppif_static.a, +libnppig.dylib, libnppig_static.a, libnppim.dylib, +libnppisu_static.a, libnppitc.dylib, libnppitc_static.a, +libnpps.dylib, libnpps_static.a + +Linux + +libnppc.so, libnppc_static.a, libnppial.so, +libnppial_static.a, libnppicc.so, libnppicc_static.a, +libnppicom.so, libnppicom_static.a, libnppidei.so, +libnppidei_static.a, libnppif.so, libnppif_static.a +libnppig.so, libnppig_static.a, libnppim.so, +libnppim_static.a, libnppist.so, libnppist_static.a, +libnppisu.so, libnppisu_static.a, libnppitc.so +libnppitc_static.a, libnpps.so, libnpps_static.a + +Android + +libnppc.so, libnppc_static.a, libnppial.so, +libnppial_static.a, libnppicc.so, libnppicc_static.a, +libnppicom.so, libnppicom_static.a, libnppidei.so, +libnppidei_static.a, libnppif.so, libnppif_static.a +libnppig.so, libnppig_static.a, libnppim.so, +libnppim_static.a, libnppist.so, libnppist_static.a, +libnppisu.so, libnppisu_static.a, libnppitc.so +libnppitc_static.a, libnpps.so, libnpps_static.a + +Component + +NVIDIA JPEG Library + +Linux + +libnvjpeg.so, libnvjpeg_static.a + +Component + +Internal common library required for statically linking to +cuBLAS, cuSPARSE, cuFFT, cuRAND, nvJPEG and NPP + +Mac OSX + +libculibos.a + +Linux + +libculibos.a + +Component + +NVIDIA Runtime Compilation Library and Header + +All + +nvrtc.h + +Windows + +nvrtc.dll, nvrtc-builtins.dll + +Mac OSX + +libnvrtc.dylib, libnvrtc-builtins.dylib + +Linux + +libnvrtc.so, libnvrtc-builtins.so + +Component + +NVIDIA Optimizing Compiler Library + +Windows + +nvvm.dll + +Mac OSX + +libnvvm.dylib + +Linux + +libnvvm.so + +Component + +NVIDIA Common Device Math Functions Library + +Windows + +libdevice.10.bc + +Mac OSX + +libdevice.10.bc + +Linux + +libdevice.10.bc + +Component + +CUDA Occupancy Calculation Header Library + +All + +cuda_occupancy.h + +Component + +CUDA Half Precision Headers + +All + +cuda_fp16.h, cuda_fp16.hpp + +Component + +CUDA Profiling Tools Interface (CUPTI) Library + +Windows + +cupti.dll + +Mac OSX + +libcupti.dylib + +Linux + +libcupti.so + +Component + +NVIDIA Tools Extension Library + +Windows + +nvToolsExt.dll, nvToolsExt.lib + +Mac OSX + +libnvToolsExt.dylib + +Linux + +libnvToolsExt.so + +Component + +NVIDIA CUDA Driver Libraries + +Linux + +libcuda.so, libnvidia-fatbinaryloader.so, +libnvidia-ptxjitcompiler.so + +The NVIDIA CUDA Driver Libraries are only distributable in +applications that meet this criteria: + + 1. The application was developed starting from a NVIDIA CUDA + container obtained from Docker Hub or the NVIDIA GPU + Cloud, and + + 2. The resulting application is packaged as a Docker + container and distributed to users on Docker Hub or the + NVIDIA GPU Cloud only. + + +2.7. Attachment B + + +Additional Licensing Obligations + +The following third party components included in the SOFTWARE +are licensed to Licensee pursuant to the following terms and +conditions: + + 1. Licensee's use of the GDB third party component is + subject to the terms and conditions of GNU GPL v3: + + This product includes copyrighted third-party software licensed + under the terms of the GNU General Public License v3 ("GPL v3"). + All third-party software packages are copyright by their respective + authors. GPL v3 terms and conditions are hereby incorporated into + the Agreement by this reference: http://www.gnu.org/licenses/gpl.txt + + Consistent with these licensing requirements, the software + listed below is provided under the terms of the specified + open source software licenses. To obtain source code for + software provided under licenses that require + redistribution of source code, including the GNU General + Public License (GPL) and GNU Lesser General Public License + (LGPL), contact oss-requests@nvidia.com. This offer is + valid for a period of three (3) years from the date of the + distribution of this product by NVIDIA CORPORATION. + + Component License + CUDA-GDB GPL v3 + + 2. Licensee represents and warrants that any and all third + party licensing and/or royalty payment obligations in + connection with Licensee's use of the H.264 video codecs + are solely the responsibility of Licensee. + + 3. Licensee's use of the Thrust library is subject to the + terms and conditions of the Apache License Version 2.0. + All third-party software packages are copyright by their + respective authors. Apache License Version 2.0 terms and + conditions are hereby incorporated into the Agreement by + this reference. + http://www.apache.org/licenses/LICENSE-2.0.html + + In addition, Licensee acknowledges the following notice: + Thrust includes source code from the Boost Iterator, + Tuple, System, and Random Number libraries. + + Boost Software License - Version 1.0 - August 17th, 2003 + . . . . + + Permission is hereby granted, free of charge, to any person or + organization obtaining a copy of the software and accompanying + documentation covered by this license (the "Software") to use, + reproduce, display, distribute, execute, and transmit the Software, + and to prepare derivative works of the Software, and to permit + third-parties to whom the Software is furnished to do so, all + subject to the following: + + The copyright notices in the Software and this entire statement, + including the above license grant, this restriction and the following + disclaimer, must be included in all copies of the Software, in whole + or in part, and all derivative works of the Software, unless such + copies or derivative works are solely in the form of machine-executable + object code generated by a source language processor. + + THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, + EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF + MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE, TITLE AND + NON-INFRINGEMENT. IN NO EVENT SHALL THE COPYRIGHT HOLDERS OR + ANYONE DISTRIBUTING THE SOFTWARE BE LIABLE FOR ANY DAMAGES OR + OTHER LIABILITY, WHETHER IN CONTRACT, TORT OR OTHERWISE, ARISING + FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR + OTHER DEALINGS IN THE SOFTWARE. + + 4. Licensee's use of the LLVM third party component is + subject to the following terms and conditions: + + ====================================================== + LLVM Release License + ====================================================== + University of Illinois/NCSA + Open Source License + + Copyright (c) 2003-2010 University of Illinois at Urbana-Champaign. + All rights reserved. + + Developed by: + + LLVM Team + + University of Illinois at Urbana-Champaign + + http://llvm.org + + Permission is hereby granted, free of charge, to any person obtaining a copy + of this software and associated documentation files (the "Software"), to + deal with the Software without restriction, including without limitation the + rights to use, copy, modify, merge, publish, distribute, sublicense, and/or + sell copies of the Software, and to permit persons to whom the Software is + furnished to do so, subject to the following conditions: + + * Redistributions of source code must retain the above copyright notice, + this list of conditions and the following disclaimers. + + * Redistributions in binary form must reproduce the above copyright + notice, this list of conditions and the following disclaimers in the + documentation and/or other materials provided with the distribution. + + * Neither the names of the LLVM Team, University of Illinois at Urbana- + Champaign, nor the names of its contributors may be used to endorse or + promote products derived from this Software without specific prior + written permission. + + THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR + IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, + FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL + THE CONTRIBUTORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR + OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, + ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER + DEALINGS WITH THE SOFTWARE. + + 5. Licensee's use (e.g. nvprof) of the PCRE third party + component is subject to the following terms and + conditions: + + ------------ + PCRE LICENCE + ------------ + PCRE is a library of functions to support regular expressions whose syntax + and semantics are as close as possible to those of the Perl 5 language. + Release 8 of PCRE is distributed under the terms of the "BSD" licence, as + specified below. The documentation for PCRE, supplied in the "doc" + directory, is distributed under the same terms as the software itself. The + basic library functions are written in C and are freestanding. Also + included in the distribution is a set of C++ wrapper functions, and a just- + in-time compiler that can be used to optimize pattern matching. These are + both optional features that can be omitted when the library is built. + + THE BASIC LIBRARY FUNCTIONS + --------------------------- + Written by: Philip Hazel + Email local part: ph10 + Email domain: cam.ac.uk + University of Cambridge Computing Service, + Cambridge, England. + Copyright (c) 1997-2012 University of Cambridge + All rights reserved. + + PCRE JUST-IN-TIME COMPILATION SUPPORT + ------------------------------------- + Written by: Zoltan Herczeg + Email local part: hzmester + Emain domain: freemail.hu + Copyright(c) 2010-2012 Zoltan Herczeg + All rights reserved. + + STACK-LESS JUST-IN-TIME COMPILER + -------------------------------- + Written by: Zoltan Herczeg + Email local part: hzmester + Emain domain: freemail.hu + Copyright(c) 2009-2012 Zoltan Herczeg + All rights reserved. + + THE C++ WRAPPER FUNCTIONS + ------------------------- + Contributed by: Google Inc. + Copyright (c) 2007-2012, Google Inc. + All rights reserved. + + THE "BSD" LICENCE + ----------------- + Redistribution and use in source and binary forms, with or without + modification, are permitted provided that the following conditions are met: + + * Redistributions of source code must retain the above copyright notice, + this list of conditions and the following disclaimer. + + * Redistributions in binary form must reproduce the above copyright + notice, this list of conditions and the following disclaimer in the + documentation and/or other materials provided with the distribution. + + * Neither the name of the University of Cambridge nor the name of Google + Inc. nor the names of their contributors may be used to endorse or + promote products derived from this software without specific prior + written permission. + + THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" + AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE + IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE + ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE + LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR + CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF + SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS + INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN + CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) + ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE + POSSIBILITY OF SUCH DAMAGE. + + 6. Some of the cuBLAS library routines were written by or + derived from code written by Vasily Volkov and are subject + to the Modified Berkeley Software Distribution License as + follows: + + Copyright (c) 2007-2009, Regents of the University of California + + All rights reserved. + + Redistribution and use in source and binary forms, with or without + modification, are permitted provided that the following conditions are + met: + * Redistributions of source code must retain the above copyright + notice, this list of conditions and the following disclaimer. + * Redistributions in binary form must reproduce the above + copyright notice, this list of conditions and the following + disclaimer in the documentation and/or other materials provided + with the distribution. + * Neither the name of the University of California, Berkeley nor + the names of its contributors may be used to endorse or promote + products derived from this software without specific prior + written permission. + + THIS SOFTWARE IS PROVIDED BY THE AUTHOR "AS IS" AND ANY EXPRESS OR + IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED + WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE + DISCLAIMED. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT, + INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES + (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR + SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) + HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, + STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING + IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE + POSSIBILITY OF SUCH DAMAGE. + + 7. Some of the cuBLAS library routines were written by or + derived from code written by Davide Barbieri and are + subject to the Modified Berkeley Software Distribution + License as follows: + + Copyright (c) 2008-2009 Davide Barbieri @ University of Rome Tor Vergata. + + All rights reserved. + + Redistribution and use in source and binary forms, with or without + modification, are permitted provided that the following conditions are + met: + * Redistributions of source code must retain the above copyright + notice, this list of conditions and the following disclaimer. + * Redistributions in binary form must reproduce the above + copyright notice, this list of conditions and the following + disclaimer in the documentation and/or other materials provided + with the distribution. + * The name of the author may not be used to endorse or promote + products derived from this software without specific prior + written permission. + + THIS SOFTWARE IS PROVIDED BY THE AUTHOR "AS IS" AND ANY EXPRESS OR + IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED + WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE + DISCLAIMED. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT, + INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES + (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR + SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) + HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, + STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING + IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE + POSSIBILITY OF SUCH DAMAGE. + + 8. Some of the cuBLAS library routines were derived from + code developed by the University of Tennessee and are + subject to the Modified Berkeley Software Distribution + License as follows: + + Copyright (c) 2010 The University of Tennessee. + + All rights reserved. + + Redistribution and use in source and binary forms, with or without + modification, are permitted provided that the following conditions are + met: + * Redistributions of source code must retain the above copyright + notice, this list of conditions and the following disclaimer. + * Redistributions in binary form must reproduce the above + copyright notice, this list of conditions and the following + disclaimer listed in this license in the documentation and/or + other materials provided with the distribution. + * Neither the name of the copyright holders nor the names of its + contributors may be used to endorse or promote products derived + from this software without specific prior written permission. + + THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS + "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT + LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR + A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT + OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, + SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT + LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, + DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY + THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT + (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE + OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + + 9. Some of the cuBLAS library routines were written by or + derived from code written by Jonathan Hogg and are subject + to the Modified Berkeley Software Distribution License as + follows: + + Copyright (c) 2012, The Science and Technology Facilities Council (STFC). + + All rights reserved. + + Redistribution and use in source and binary forms, with or without + modification, are permitted provided that the following conditions are + met: + * Redistributions of source code must retain the above copyright + notice, this list of conditions and the following disclaimer. + * Redistributions in binary form must reproduce the above + copyright notice, this list of conditions and the following + disclaimer in the documentation and/or other materials provided + with the distribution. + * Neither the name of the STFC nor the names of its contributors + may be used to endorse or promote products derived from this + software without specific prior written permission. + + THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS + "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT + LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR + A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE STFC BE + LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR + CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF + SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR + BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, + WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE + OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN + IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + + 10. Some of the cuBLAS library routines were written by or + derived from code written by Ahmad M. Abdelfattah, David + Keyes, and Hatem Ltaief, and are subject to the Apache + License, Version 2.0, as follows: + + -- (C) Copyright 2013 King Abdullah University of Science and Technology + Authors: + Ahmad Abdelfattah (ahmad.ahmad@kaust.edu.sa) + David Keyes (david.keyes@kaust.edu.sa) + Hatem Ltaief (hatem.ltaief@kaust.edu.sa) + + Redistribution and use in source and binary forms, with or without + modification, are permitted provided that the following conditions + are met: + + * Redistributions of source code must retain the above copyright + notice, this list of conditions and the following disclaimer. + * Redistributions in binary form must reproduce the above copyright + notice, this list of conditions and the following disclaimer in the + documentation and/or other materials provided with the distribution. + * Neither the name of the King Abdullah University of Science and + Technology nor the names of its contributors may be used to endorse + or promote products derived from this software without specific prior + written permission. + + THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS + ``AS IS'' AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT + LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR + A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT + HOLDERS OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, + SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT + LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, + DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY + THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT + (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE + OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE + + 11. Some of the cuSPARSE library routines were written by or + derived from code written by Li-Wen Chang and are subject + to the NCSA Open Source License as follows: + + Copyright (c) 2012, University of Illinois. + + All rights reserved. + + Developed by: IMPACT Group, University of Illinois, http://impact.crhc.illinois.edu + + Permission is hereby granted, free of charge, to any person obtaining + a copy of this software and associated documentation files (the + "Software"), to deal with the Software without restriction, including + without limitation the rights to use, copy, modify, merge, publish, + distribute, sublicense, and/or sell copies of the Software, and to + permit persons to whom the Software is furnished to do so, subject to + the following conditions: + * Redistributions of source code must retain the above copyright + notice, this list of conditions and the following disclaimer. + * Redistributions in binary form must reproduce the above + copyright notice, this list of conditions and the following + disclaimers in the documentation and/or other materials provided + with the distribution. + * Neither the names of IMPACT Group, University of Illinois, nor + the names of its contributors may be used to endorse or promote + products derived from this Software without specific prior + written permission. + + THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, + EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF + MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND + NONINFRINGEMENT. IN NO EVENT SHALL THE CONTRIBUTORS OR COPYRIGHT + HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER + IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR + IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS WITH THE + SOFTWARE. + + 12. Some of the cuRAND library routines were written by or + derived from code written by Mutsuo Saito and Makoto + Matsumoto and are subject to the following license: + + Copyright (c) 2009, 2010 Mutsuo Saito, Makoto Matsumoto and Hiroshima + University. All rights reserved. + + Copyright (c) 2011 Mutsuo Saito, Makoto Matsumoto, Hiroshima + University and University of Tokyo. All rights reserved. + + Redistribution and use in source and binary forms, with or without + modification, are permitted provided that the following conditions are + met: + * Redistributions of source code must retain the above copyright + notice, this list of conditions and the following disclaimer. + * Redistributions in binary form must reproduce the above + copyright notice, this list of conditions and the following + disclaimer in the documentation and/or other materials provided + with the distribution. + * Neither the name of the Hiroshima University nor the names of + its contributors may be used to endorse or promote products + derived from this software without specific prior written + permission. + + THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS + "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT + LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR + A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT + OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, + SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT + LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, + DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY + THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT + (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE + OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + + 13. Some of the cuRAND library routines were derived from + code developed by D. E. Shaw Research and are subject to + the following license: + + Copyright 2010-2011, D. E. Shaw Research. + + All rights reserved. + + Redistribution and use in source and binary forms, with or without + modification, are permitted provided that the following conditions are + met: + * Redistributions of source code must retain the above copyright + notice, this list of conditions, and the following disclaimer. + * Redistributions in binary form must reproduce the above + copyright notice, this list of conditions, and the following + disclaimer in the documentation and/or other materials provided + with the distribution. + * Neither the name of D. E. Shaw Research nor the names of its + contributors may be used to endorse or promote products derived + from this software without specific prior written permission. + + THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS + "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT + LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR + A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT + OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, + SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT + LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, + DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY + THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT + (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE + OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + + 14. Some of the Math library routines were written by or + derived from code developed by Norbert Juffa and are + subject to the following license: + + Copyright (c) 2015-2017, Norbert Juffa + All rights reserved. + + Redistribution and use in source and binary forms, with or without + modification, are permitted provided that the following conditions + are met: + + 1. Redistributions of source code must retain the above copyright + notice, this list of conditions and the following disclaimer. + + 2. Redistributions in binary form must reproduce the above copyright + notice, this list of conditions and the following disclaimer in the + documentation and/or other materials provided with the distribution. + + THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS + "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT + LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR + A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT + HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, + SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT + LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, + DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY + THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT + (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE + OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + + 15. Licensee's use of the lz4 third party component is + subject to the following terms and conditions: + + Copyright (C) 2011-2013, Yann Collet. + BSD 2-Clause License (http://www.opensource.org/licenses/bsd-license.php) + + Redistribution and use in source and binary forms, with or without + modification, are permitted provided that the following conditions are + met: + + * Redistributions of source code must retain the above copyright + notice, this list of conditions and the following disclaimer. + * Redistributions in binary form must reproduce the above + copyright notice, this list of conditions and the following disclaimer + in the documentation and/or other materials provided with the + distribution. + + THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS + "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT + LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR + A PARTICULAR PURPOSE ARE DISCLAIMED. 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Some of the cuBLAS library routines uses code from + OpenAI, which is subject to the following license: + + License URL + https://github.com/openai/openai-gemm/blob/master/LICENSE + + License Text + The MIT License + + Copyright (c) 2016 OpenAI (http://openai.com), 2016 Google Inc. + + Permission is hereby granted, free of charge, to any person obtaining a copy + of this software and associated documentation files (the "Software"), to deal + in the Software without restriction, including without limitation the rights + to use, copy, modify, merge, publish, distribute, sublicense, and/or sell + copies of the Software, and to permit persons to whom the Software is + furnished to do so, subject to the following conditions: + + The above copyright notice and this permission notice shall be included in + all copies or substantial portions of the Software. + + THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR + IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, + FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. 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The DX12-CUDA sample uses the d3dx12.h header, which is + subject to the MIT license . + +----------------- diff --git a/llmeval-env/lib/python3.10/site-packages/nvidia_cufft_cu12-11.0.2.54.dist-info/METADATA b/llmeval-env/lib/python3.10/site-packages/nvidia_cufft_cu12-11.0.2.54.dist-info/METADATA new file mode 100644 index 0000000000000000000000000000000000000000..aa9af815101f2d67ea98b8c381febb35a2ebc7d7 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/nvidia_cufft_cu12-11.0.2.54.dist-info/METADATA @@ -0,0 +1,35 @@ +Metadata-Version: 2.1 +Name: nvidia-cufft-cu12 +Version: 11.0.2.54 +Summary: CUFFT native runtime libraries +Home-page: https://developer.nvidia.com/cuda-zone +Author: Nvidia CUDA Installer Team +Author-email: cuda_installer@nvidia.com +License: NVIDIA Proprietary Software +Keywords: cuda,nvidia,runtime,machine learning,deep learning +Classifier: Development Status :: 4 - Beta +Classifier: Intended Audience :: Developers +Classifier: Intended Audience :: 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We also recommend that a + file or class name and description of purpose be included on the + same "printed page" as the copyright notice for easier + identification within third-party archives. + + Copyright 2020 Matthew Barnett + + Licensed under the Apache License, Version 2.0 (the "License"); + you may not use this file except in compliance with the License. + You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + + Unless required by applicable law or agreed to in writing, software + distributed under the License is distributed on an "AS IS" BASIS, + WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + See the License for the specific language governing permissions and + limitations under the License. diff --git a/llmeval-env/lib/python3.10/site-packages/regex-2024.4.28.dist-info/METADATA b/llmeval-env/lib/python3.10/site-packages/regex-2024.4.28.dist-info/METADATA new file mode 100644 index 0000000000000000000000000000000000000000..f5b57e171b2682de669feb41eab4723bdb67a6f9 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/regex-2024.4.28.dist-info/METADATA @@ -0,0 +1,1075 @@ +Metadata-Version: 2.1 +Name: regex +Version: 2024.4.28 +Summary: Alternative regular expression module, to replace re. +Home-page: https://github.com/mrabarnett/mrab-regex +Author: Matthew Barnett +Author-email: regex@mrabarnett.plus.com +License: Apache Software License +Classifier: Development Status :: 5 - Production/Stable +Classifier: Intended Audience :: Developers +Classifier: License :: OSI Approved :: Apache Software License +Classifier: Operating System :: OS Independent +Classifier: Programming Language :: Python :: 3.8 +Classifier: Programming Language :: Python :: 3.9 +Classifier: Programming Language :: Python :: 3.10 +Classifier: Programming Language :: Python :: 3.11 +Classifier: Programming Language :: Python :: 3.12 +Classifier: Topic :: Scientific/Engineering :: Information Analysis +Classifier: Topic :: Software Development :: Libraries :: Python Modules +Classifier: Topic :: Text Processing +Classifier: Topic :: Text Processing :: General +Requires-Python: >=3.8 +Description-Content-Type: text/x-rst +License-File: LICENSE.txt + +Introduction +------------ + +This regex implementation is backwards-compatible with the standard 're' module, but offers additional functionality. + +Note +---- + +The re module's behaviour with zero-width matches changed in Python 3.7, and this module follows that behaviour when compiled for Python 3.7. + +Python 2 +-------- + +Python 2 is no longer supported. The last release that supported Python 2 was 2021.11.10. + +PyPy +---- + +This module is targeted at CPython. It expects that all codepoints are the same width, so it won't behave properly with PyPy outside U+0000..U+007F because PyPy stores strings as UTF-8. + +Multithreading +-------------- + +The regex module releases the GIL during matching on instances of the built-in (immutable) string classes, enabling other Python threads to run concurrently. It is also possible to force the regex module to release the GIL during matching by calling the matching methods with the keyword argument ``concurrent=True``. The behaviour is undefined if the string changes during matching, so use it *only* when it is guaranteed that that won't happen. + +Unicode +------- + +This module supports Unicode 15.1.0. Full Unicode case-folding is supported. + +Flags +----- + +There are 2 kinds of flag: scoped and global. Scoped flags can apply to only part of a pattern and can be turned on or off; global flags apply to the entire pattern and can only be turned on. + +The scoped flags are: ``ASCII (?a)``, ``FULLCASE (?f)``, ``IGNORECASE (?i)``, ``LOCALE (?L)``, ``MULTILINE (?m)``, ``DOTALL (?s)``, ``UNICODE (?u)``, ``VERBOSE (?x)``, ``WORD (?w)``. + +The global flags are: ``BESTMATCH (?b)``, ``ENHANCEMATCH (?e)``, ``POSIX (?p)``, ``REVERSE (?r)``, ``VERSION0 (?V0)``, ``VERSION1 (?V1)``. + +If neither the ``ASCII``, ``LOCALE`` nor ``UNICODE`` flag is specified, it will default to ``UNICODE`` if the regex pattern is a Unicode string and ``ASCII`` if it's a bytestring. + +The ``ENHANCEMATCH`` flag makes fuzzy matching attempt to improve the fit of the next match that it finds. + +The ``BESTMATCH`` flag makes fuzzy matching search for the best match instead of the next match. + +Old vs new behaviour +-------------------- + +In order to be compatible with the re module, this module has 2 behaviours: + +* **Version 0** behaviour (old behaviour, compatible with the re module): + + Please note that the re module's behaviour may change over time, and I'll endeavour to match that behaviour in version 0. + + * Indicated by the ``VERSION0`` flag. + + * Zero-width matches are not handled correctly in the re module before Python 3.7. The behaviour in those earlier versions is: + + * ``.split`` won't split a string at a zero-width match. + + * ``.sub`` will advance by one character after a zero-width match. + + * Inline flags apply to the entire pattern, and they can't be turned off. + + * Only simple sets are supported. + + * Case-insensitive matches in Unicode use simple case-folding by default. + +* **Version 1** behaviour (new behaviour, possibly different from the re module): + + * Indicated by the ``VERSION1`` flag. + + * Zero-width matches are handled correctly. + + * Inline flags apply to the end of the group or pattern, and they can be turned off. + + * Nested sets and set operations are supported. + + * Case-insensitive matches in Unicode use full case-folding by default. + +If no version is specified, the regex module will default to ``regex.DEFAULT_VERSION``. + +Case-insensitive matches in Unicode +----------------------------------- + +The regex module supports both simple and full case-folding for case-insensitive matches in Unicode. Use of full case-folding can be turned on using the ``FULLCASE`` flag. Please note that this flag affects how the ``IGNORECASE`` flag works; the ``FULLCASE`` flag itself does not turn on case-insensitive matching. + +Version 0 behaviour: the flag is off by default. + +Version 1 behaviour: the flag is on by default. + +Nested sets and set operations +------------------------------ + +It's not possible to support both simple sets, as used in the re module, and nested sets at the same time because of a difference in the meaning of an unescaped ``"["`` in a set. + +For example, the pattern ``[[a-z]--[aeiou]]`` is treated in the version 0 behaviour (simple sets, compatible with the re module) as: + +* Set containing "[" and the letters "a" to "z" + +* Literal "--" + +* Set containing letters "a", "e", "i", "o", "u" + +* Literal "]" + +but in the version 1 behaviour (nested sets, enhanced behaviour) as: + +* Set which is: + + * Set containing the letters "a" to "z" + +* but excluding: + + * Set containing the letters "a", "e", "i", "o", "u" + +Version 0 behaviour: only simple sets are supported. + +Version 1 behaviour: nested sets and set operations are supported. + +Notes on named groups +--------------------- + +All groups have a group number, starting from 1. + +Groups with the same group name will have the same group number, and groups with a different group name will have a different group number. + +The same name can be used by more than one group, with later captures 'overwriting' earlier captures. All the captures of the group will be available from the ``captures`` method of the match object. + +Group numbers will be reused across different branches of a branch reset, eg. ``(?|(first)|(second))`` has only group 1. If groups have different group names then they will, of course, have different group numbers, eg. ``(?|(?Pfirst)|(?Psecond))`` has group 1 ("foo") and group 2 ("bar"). + +In the regex ``(\s+)(?|(?P[A-Z]+)|(\w+) (?P[0-9]+)`` there are 2 groups: + +* ``(\s+)`` is group 1. + +* ``(?P[A-Z]+)`` is group 2, also called "foo". + +* ``(\w+)`` is group 2 because of the branch reset. + +* ``(?P[0-9]+)`` is group 2 because it's called "foo". + +If you want to prevent ``(\w+)`` from being group 2, you need to name it (different name, different group number). + +Additional features +------------------- + +The issue numbers relate to the Python bug tracker, except where listed otherwise. + +Added ``\p{Horiz_Space}`` and ``\p{Vert_Space}`` (`GitHub issue 477 `_) +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +``\p{Horiz_Space}`` or ``\p{H}`` matches horizontal whitespace and ``\p{Vert_Space}`` or ``\p{V}`` matches vertical whitespace. + +Added support for lookaround in conditional pattern (`Hg issue 163 `_) +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +The test of a conditional pattern can be a lookaround. + +.. sourcecode:: python + + >>> regex.match(r'(?(?=\d)\d+|\w+)', '123abc') + + >>> regex.match(r'(?(?=\d)\d+|\w+)', 'abc123') + + +This is not quite the same as putting a lookaround in the first branch of a pair of alternatives. + +.. sourcecode:: python + + >>> print(regex.match(r'(?:(?=\d)\d+\b|\w+)', '123abc')) + + >>> print(regex.match(r'(?(?=\d)\d+\b|\w+)', '123abc')) + None + +In the first example, the lookaround matched, but the remainder of the first branch failed to match, and so the second branch was attempted, whereas in the second example, the lookaround matched, and the first branch failed to match, but the second branch was **not** attempted. + +Added POSIX matching (leftmost longest) (`Hg issue 150 `_) +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +The POSIX standard for regex is to return the leftmost longest match. This can be turned on using the ``POSIX`` flag. + +.. sourcecode:: python + + >>> # Normal matching. + >>> regex.search(r'Mr|Mrs', 'Mrs') + + >>> regex.search(r'one(self)?(selfsufficient)?', 'oneselfsufficient') + + >>> # POSIX matching. + >>> regex.search(r'(?p)Mr|Mrs', 'Mrs') + + >>> regex.search(r'(?p)one(self)?(selfsufficient)?', 'oneselfsufficient') + + +Note that it will take longer to find matches because when it finds a match at a certain position, it won't return that immediately, but will keep looking to see if there's another longer match there. + +Added ``(?(DEFINE)...)`` (`Hg issue 152 `_) +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +If there's no group called "DEFINE", then ... will be ignored except that any groups defined within it can be called and that the normal rules for numbering groups still apply. + +.. sourcecode:: python + + >>> regex.search(r'(?(DEFINE)(?P\d+)(?P\w+))(?&quant) (?&item)', '5 elephants') + + +Added ``(*PRUNE)``, ``(*SKIP)`` and ``(*FAIL)`` (`Hg issue 153 `_) +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +``(*PRUNE)`` discards the backtracking info up to that point. When used in an atomic group or a lookaround, it won't affect the enclosing pattern. + +``(*SKIP)`` is similar to ``(*PRUNE)``, except that it also sets where in the text the next attempt to match will start. When used in an atomic group or a lookaround, it won't affect the enclosing pattern. + +``(*FAIL)`` causes immediate backtracking. ``(*F)`` is a permitted abbreviation. + +Added ``\K`` (`Hg issue 151 `_) +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +Keeps the part of the entire match after the position where ``\K`` occurred; the part before it is discarded. + +It does not affect what groups return. + +.. sourcecode:: python + + >>> m = regex.search(r'(\w\w\K\w\w\w)', 'abcdef') + >>> m[0] + 'cde' + >>> m[1] + 'abcde' + >>> + >>> m = regex.search(r'(?r)(\w\w\K\w\w\w)', 'abcdef') + >>> m[0] + 'bc' + >>> m[1] + 'bcdef' + +Added capture subscripting for ``expandf`` and ``subf``/``subfn`` (`Hg issue 133 `_) +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +You can use subscripting to get the captures of a repeated group. + +.. sourcecode:: python + + >>> m = regex.match(r"(\w)+", "abc") + >>> m.expandf("{1}") + 'c' + >>> m.expandf("{1[0]} {1[1]} {1[2]}") + 'a b c' + >>> m.expandf("{1[-1]} {1[-2]} {1[-3]}") + 'c b a' + >>> + >>> m = regex.match(r"(?P\w)+", "abc") + >>> m.expandf("{letter}") + 'c' + >>> m.expandf("{letter[0]} {letter[1]} {letter[2]}") + 'a b c' + >>> m.expandf("{letter[-1]} {letter[-2]} {letter[-3]}") + 'c b a' + +Added support for referring to a group by number using ``(?P=...)`` +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +This is in addition to the existing ``\g<...>``. + +Fixed the handling of locale-sensitive regexes +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +The ``LOCALE`` flag is intended for legacy code and has limited support. You're still recommended to use Unicode instead. + +Added partial matches (`Hg issue 102 `_) +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +A partial match is one that matches up to the end of string, but that string has been truncated and you want to know whether a complete match could be possible if the string had not been truncated. + +Partial matches are supported by ``match``, ``search``, ``fullmatch`` and ``finditer`` with the ``partial`` keyword argument. + +Match objects have a ``partial`` attribute, which is ``True`` if it's a partial match. + +For example, if you wanted a user to enter a 4-digit number and check it character by character as it was being entered: + +.. sourcecode:: python + + >>> pattern = regex.compile(r'\d{4}') + + >>> # Initially, nothing has been entered: + >>> print(pattern.fullmatch('', partial=True)) + + + >>> # An empty string is OK, but it's only a partial match. + >>> # The user enters a letter: + >>> print(pattern.fullmatch('a', partial=True)) + None + >>> # It'll never match. + + >>> # The user deletes that and enters a digit: + >>> print(pattern.fullmatch('1', partial=True)) + + >>> # It matches this far, but it's only a partial match. + + >>> # The user enters 2 more digits: + >>> print(pattern.fullmatch('123', partial=True)) + + >>> # It matches this far, but it's only a partial match. + + >>> # The user enters another digit: + >>> print(pattern.fullmatch('1234', partial=True)) + + >>> # It's a complete match. + + >>> # If the user enters another digit: + >>> print(pattern.fullmatch('12345', partial=True)) + None + >>> # It's no longer a match. + + >>> # This is a partial match: + >>> pattern.match('123', partial=True).partial + True + + >>> # This is a complete match: + >>> pattern.match('1233', partial=True).partial + False + +``*`` operator not working correctly with sub() (`Hg issue 106 `_) +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +Sometimes it's not clear how zero-width matches should be handled. For example, should ``.*`` match 0 characters directly after matching >0 characters? + +.. sourcecode:: python + + # Python 3.7 and later + >>> regex.sub('.*', 'x', 'test') + 'xx' + >>> regex.sub('.*?', '|', 'test') + '|||||||||' + + # Python 3.6 and earlier + >>> regex.sub('(?V0).*', 'x', 'test') + 'x' + >>> regex.sub('(?V1).*', 'x', 'test') + 'xx' + >>> regex.sub('(?V0).*?', '|', 'test') + '|t|e|s|t|' + >>> regex.sub('(?V1).*?', '|', 'test') + '|||||||||' + +Added ``capturesdict`` (`Hg issue 86 `_) +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +``capturesdict`` is a combination of ``groupdict`` and ``captures``: + +``groupdict`` returns a dict of the named groups and the last capture of those groups. + +``captures`` returns a list of all the captures of a group + +``capturesdict`` returns a dict of the named groups and lists of all the captures of those groups. + +.. sourcecode:: python + + >>> m = regex.match(r"(?:(?P\w+) (?P\d+)\n)+", "one 1\ntwo 2\nthree 3\n") + >>> m.groupdict() + {'word': 'three', 'digits': '3'} + >>> m.captures("word") + ['one', 'two', 'three'] + >>> m.captures("digits") + ['1', '2', '3'] + >>> m.capturesdict() + {'word': ['one', 'two', 'three'], 'digits': ['1', '2', '3']} + +Added ``allcaptures`` and ``allspans`` (`Git issue 474 `_) +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +``allcaptures`` returns a list of all the captures of all the groups. + +``allspans`` returns a list of all the spans of the all captures of all the groups. + +.. sourcecode:: python + + >>> m = regex.match(r"(?:(?P\w+) (?P\d+)\n)+", "one 1\ntwo 2\nthree 3\n") + >>> m.allcaptures() + (['one 1\ntwo 2\nthree 3\n'], ['one', 'two', 'three'], ['1', '2', '3']) + >>> m.allspans() + ([(0, 20)], [(0, 3), (6, 9), (12, 17)], [(4, 5), (10, 11), (18, 19)]) + +Allow duplicate names of groups (`Hg issue 87 `_) +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +Group names can be duplicated. + +.. sourcecode:: python + + >>> # With optional groups: + >>> + >>> # Both groups capture, the second capture 'overwriting' the first. + >>> m = regex.match(r"(?P\w+)? or (?P\w+)?", "first or second") + >>> m.group("item") + 'second' + >>> m.captures("item") + ['first', 'second'] + >>> # Only the second group captures. + >>> m = regex.match(r"(?P\w+)? or (?P\w+)?", " or second") + >>> m.group("item") + 'second' + >>> m.captures("item") + ['second'] + >>> # Only the first group captures. + >>> m = regex.match(r"(?P\w+)? or (?P\w+)?", "first or ") + >>> m.group("item") + 'first' + >>> m.captures("item") + ['first'] + >>> + >>> # With mandatory groups: + >>> + >>> # Both groups capture, the second capture 'overwriting' the first. + >>> m = regex.match(r"(?P\w*) or (?P\w*)?", "first or second") + >>> m.group("item") + 'second' + >>> m.captures("item") + ['first', 'second'] + >>> # Again, both groups capture, the second capture 'overwriting' the first. + >>> m = regex.match(r"(?P\w*) or (?P\w*)", " or second") + >>> m.group("item") + 'second' + >>> m.captures("item") + ['', 'second'] + >>> # And yet again, both groups capture, the second capture 'overwriting' the first. + >>> m = regex.match(r"(?P\w*) or (?P\w*)", "first or ") + >>> m.group("item") + '' + >>> m.captures("item") + ['first', ''] + +Added ``fullmatch`` (`issue #16203 `_) +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +``fullmatch`` behaves like ``match``, except that it must match all of the string. + +.. sourcecode:: python + + >>> print(regex.fullmatch(r"abc", "abc").span()) + (0, 3) + >>> print(regex.fullmatch(r"abc", "abcx")) + None + >>> print(regex.fullmatch(r"abc", "abcx", endpos=3).span()) + (0, 3) + >>> print(regex.fullmatch(r"abc", "xabcy", pos=1, endpos=4).span()) + (1, 4) + >>> + >>> regex.match(r"a.*?", "abcd").group(0) + 'a' + >>> regex.fullmatch(r"a.*?", "abcd").group(0) + 'abcd' + +Added ``subf`` and ``subfn`` +^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +``subf`` and ``subfn`` are alternatives to ``sub`` and ``subn`` respectively. When passed a replacement string, they treat it as a format string. + +.. sourcecode:: python + + >>> regex.subf(r"(\w+) (\w+)", "{0} => {2} {1}", "foo bar") + 'foo bar => bar foo' + >>> regex.subf(r"(?P\w+) (?P\w+)", "{word2} {word1}", "foo bar") + 'bar foo' + +Added ``expandf`` to match object +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +``expandf`` is an alternative to ``expand``. When passed a replacement string, it treats it as a format string. + +.. sourcecode:: python + + >>> m = regex.match(r"(\w+) (\w+)", "foo bar") + >>> m.expandf("{0} => {2} {1}") + 'foo bar => bar foo' + >>> + >>> m = regex.match(r"(?P\w+) (?P\w+)", "foo bar") + >>> m.expandf("{word2} {word1}") + 'bar foo' + +Detach searched string +^^^^^^^^^^^^^^^^^^^^^^ + +A match object contains a reference to the string that was searched, via its ``string`` attribute. The ``detach_string`` method will 'detach' that string, making it available for garbage collection, which might save valuable memory if that string is very large. + +.. sourcecode:: python + + >>> m = regex.search(r"\w+", "Hello world") + >>> print(m.group()) + Hello + >>> print(m.string) + Hello world + >>> m.detach_string() + >>> print(m.group()) + Hello + >>> print(m.string) + None + +Recursive patterns (`Hg issue 27 `_) +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +Recursive and repeated patterns are supported. + +``(?R)`` or ``(?0)`` tries to match the entire regex recursively. ``(?1)``, ``(?2)``, etc, try to match the relevant group. + +``(?&name)`` tries to match the named group. + +.. sourcecode:: python + + >>> regex.match(r"(Tarzan|Jane) loves (?1)", "Tarzan loves Jane").groups() + ('Tarzan',) + >>> regex.match(r"(Tarzan|Jane) loves (?1)", "Jane loves Tarzan").groups() + ('Jane',) + + >>> m = regex.search(r"(\w)(?:(?R)|(\w?))\1", "kayak") + >>> m.group(0, 1, 2) + ('kayak', 'k', None) + +The first two examples show how the subpattern within the group is reused, but is _not_ itself a group. In other words, ``"(Tarzan|Jane) loves (?1)"`` is equivalent to ``"(Tarzan|Jane) loves (?:Tarzan|Jane)"``. + +It's possible to backtrack into a recursed or repeated group. + +You can't call a group if there is more than one group with that group name or group number (``"ambiguous group reference"``). + +The alternative forms ``(?P>name)`` and ``(?P&name)`` are also supported. + +Full Unicode case-folding is supported +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +In version 1 behaviour, the regex module uses full case-folding when performing case-insensitive matches in Unicode. + +.. sourcecode:: python + + >>> regex.match(r"(?iV1)strasse", "stra\N{LATIN SMALL LETTER SHARP S}e").span() + (0, 6) + >>> regex.match(r"(?iV1)stra\N{LATIN SMALL LETTER SHARP S}e", "STRASSE").span() + (0, 7) + +In version 0 behaviour, it uses simple case-folding for backward compatibility with the re module. + +Approximate "fuzzy" matching (`Hg issue 12 `_, `Hg issue 41 `_, `Hg issue 109 `_) +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +Regex usually attempts an exact match, but sometimes an approximate, or "fuzzy", match is needed, for those cases where the text being searched may contain errors in the form of inserted, deleted or substituted characters. + +A fuzzy regex specifies which types of errors are permitted, and, optionally, either the minimum and maximum or only the maximum permitted number of each type. (You cannot specify only a minimum.) + +The 3 types of error are: + +* Insertion, indicated by "i" + +* Deletion, indicated by "d" + +* Substitution, indicated by "s" + +In addition, "e" indicates any type of error. + +The fuzziness of a regex item is specified between "{" and "}" after the item. + +Examples: + +* ``foo`` match "foo" exactly + +* ``(?:foo){i}`` match "foo", permitting insertions + +* ``(?:foo){d}`` match "foo", permitting deletions + +* ``(?:foo){s}`` match "foo", permitting substitutions + +* ``(?:foo){i,s}`` match "foo", permitting insertions and substitutions + +* ``(?:foo){e}`` match "foo", permitting errors + +If a certain type of error is specified, then any type not specified will **not** be permitted. + +In the following examples I'll omit the item and write only the fuzziness: + +* ``{d<=3}`` permit at most 3 deletions, but no other types + +* ``{i<=1,s<=2}`` permit at most 1 insertion and at most 2 substitutions, but no deletions + +* ``{1<=e<=3}`` permit at least 1 and at most 3 errors + +* ``{i<=2,d<=2,e<=3}`` permit at most 2 insertions, at most 2 deletions, at most 3 errors in total, but no substitutions + +It's also possible to state the costs of each type of error and the maximum permitted total cost. + +Examples: + +* ``{2i+2d+1s<=4}`` each insertion costs 2, each deletion costs 2, each substitution costs 1, the total cost must not exceed 4 + +* ``{i<=1,d<=1,s<=1,2i+2d+1s<=4}`` at most 1 insertion, at most 1 deletion, at most 1 substitution; each insertion costs 2, each deletion costs 2, each substitution costs 1, the total cost must not exceed 4 + +You can also use "<" instead of "<=" if you want an exclusive minimum or maximum. + +You can add a test to perform on a character that's substituted or inserted. + +Examples: + +* ``{s<=2:[a-z]}`` at most 2 substitutions, which must be in the character set ``[a-z]``. + +* ``{s<=2,i<=3:\d}`` at most 2 substitutions, at most 3 insertions, which must be digits. + +By default, fuzzy matching searches for the first match that meets the given constraints. The ``ENHANCEMATCH`` flag will cause it to attempt to improve the fit (i.e. reduce the number of errors) of the match that it has found. + +The ``BESTMATCH`` flag will make it search for the best match instead. + +Further examples to note: + +* ``regex.search("(dog){e}", "cat and dog")[1]`` returns ``"cat"`` because that matches ``"dog"`` with 3 errors (an unlimited number of errors is permitted). + +* ``regex.search("(dog){e<=1}", "cat and dog")[1]`` returns ``" dog"`` (with a leading space) because that matches ``"dog"`` with 1 error, which is within the limit. + +* ``regex.search("(?e)(dog){e<=1}", "cat and dog")[1]`` returns ``"dog"`` (without a leading space) because the fuzzy search matches ``" dog"`` with 1 error, which is within the limit, and the ``(?e)`` then it attempts a better fit. + +In the first two examples there are perfect matches later in the string, but in neither case is it the first possible match. + +The match object has an attribute ``fuzzy_counts`` which gives the total number of substitutions, insertions and deletions. + +.. sourcecode:: python + + >>> # A 'raw' fuzzy match: + >>> regex.fullmatch(r"(?:cats|cat){e<=1}", "cat").fuzzy_counts + (0, 0, 1) + >>> # 0 substitutions, 0 insertions, 1 deletion. + + >>> # A better match might be possible if the ENHANCEMATCH flag used: + >>> regex.fullmatch(r"(?e)(?:cats|cat){e<=1}", "cat").fuzzy_counts + (0, 0, 0) + >>> # 0 substitutions, 0 insertions, 0 deletions. + +The match object also has an attribute ``fuzzy_changes`` which gives a tuple of the positions of the substitutions, insertions and deletions. + +.. sourcecode:: python + + >>> m = regex.search('(fuu){i<=2,d<=2,e<=5}', 'anaconda foo bar') + >>> m + + >>> m.fuzzy_changes + ([], [7, 8], [10, 11]) + +What this means is that if the matched part of the string had been: + +.. sourcecode:: python + + 'anacondfuuoo bar' + +it would've been an exact match. + +However, there were insertions at positions 7 and 8: + +.. sourcecode:: python + + 'anaconda fuuoo bar' + ^^ + +and deletions at positions 10 and 11: + +.. sourcecode:: python + + 'anaconda f~~oo bar' + ^^ + +So the actual string was: + +.. sourcecode:: python + + 'anaconda foo bar' + +Named lists ``\L`` (`Hg issue 11 `_) +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +There are occasions where you may want to include a list (actually, a set) of options in a regex. + +One way is to build the pattern like this: + +.. sourcecode:: python + + >>> p = regex.compile(r"first|second|third|fourth|fifth") + +but if the list is large, parsing the resulting regex can take considerable time, and care must also be taken that the strings are properly escaped and properly ordered, for example, "cats" before "cat". + +The new alternative is to use a named list: + +.. sourcecode:: python + + >>> option_set = ["first", "second", "third", "fourth", "fifth"] + >>> p = regex.compile(r"\L", options=option_set) + +The order of the items is irrelevant, they are treated as a set. The named lists are available as the ``.named_lists`` attribute of the pattern object : + +.. sourcecode:: python + + >>> print(p.named_lists) + {'options': frozenset({'third', 'first', 'fifth', 'fourth', 'second'})} + +If there are any unused keyword arguments, ``ValueError`` will be raised unless you tell it otherwise: + +.. sourcecode:: python + + >>> option_set = ["first", "second", "third", "fourth", "fifth"] + >>> p = regex.compile(r"\L", options=option_set, other_options=[]) + Traceback (most recent call last): + File "", line 1, in + File "C:\Python310\lib\site-packages\regex\regex.py", line 353, in compile + return _compile(pattern, flags, ignore_unused, kwargs, cache_pattern) + File "C:\Python310\lib\site-packages\regex\regex.py", line 500, in _compile + complain_unused_args() + File "C:\Python310\lib\site-packages\regex\regex.py", line 483, in complain_unused_args + raise ValueError('unused keyword argument {!a}'.format(any_one)) + ValueError: unused keyword argument 'other_options' + >>> p = regex.compile(r"\L", options=option_set, other_options=[], ignore_unused=True) + >>> p = regex.compile(r"\L", options=option_set, other_options=[], ignore_unused=False) + Traceback (most recent call last): + File "", line 1, in + File "C:\Python310\lib\site-packages\regex\regex.py", line 353, in compile + return _compile(pattern, flags, ignore_unused, kwargs, cache_pattern) + File "C:\Python310\lib\site-packages\regex\regex.py", line 500, in _compile + complain_unused_args() + File "C:\Python310\lib\site-packages\regex\regex.py", line 483, in complain_unused_args + raise ValueError('unused keyword argument {!a}'.format(any_one)) + ValueError: unused keyword argument 'other_options' + >>> + +Start and end of word +^^^^^^^^^^^^^^^^^^^^^ + +``\m`` matches at the start of a word. + +``\M`` matches at the end of a word. + +Compare with ``\b``, which matches at the start or end of a word. + +Unicode line separators +^^^^^^^^^^^^^^^^^^^^^^^ + +Normally the only line separator is ``\n`` (``\x0A``), but if the ``WORD`` flag is turned on then the line separators are ``\x0D\x0A``, ``\x0A``, ``\x0B``, ``\x0C`` and ``\x0D``, plus ``\x85``, ``\u2028`` and ``\u2029`` when working with Unicode. + +This affects the regex dot ``"."``, which, with the ``DOTALL`` flag turned off, matches any character except a line separator. It also affects the line anchors ``^`` and ``$`` (in multiline mode). + +Set operators +^^^^^^^^^^^^^ + +**Version 1 behaviour only** + +Set operators have been added, and a set ``[...]`` can include nested sets. + +The operators, in order of increasing precedence, are: + +* ``||`` for union ("x||y" means "x or y") + +* ``~~`` (double tilde) for symmetric difference ("x~~y" means "x or y, but not both") + +* ``&&`` for intersection ("x&&y" means "x and y") + +* ``--`` (double dash) for difference ("x--y" means "x but not y") + +Implicit union, ie, simple juxtaposition like in ``[ab]``, has the highest precedence. Thus, ``[ab&&cd]`` is the same as ``[[a||b]&&[c||d]]``. + +Examples: + +* ``[ab]`` # Set containing 'a' and 'b' + +* ``[a-z]`` # Set containing 'a' .. 'z' + +* ``[[a-z]--[qw]]`` # Set containing 'a' .. 'z', but not 'q' or 'w' + +* ``[a-z--qw]`` # Same as above + +* ``[\p{L}--QW]`` # Set containing all letters except 'Q' and 'W' + +* ``[\p{N}--[0-9]]`` # Set containing all numbers except '0' .. '9' + +* ``[\p{ASCII}&&\p{Letter}]`` # Set containing all characters which are ASCII and letter + +regex.escape (`issue #2650 `_) +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +regex.escape has an additional keyword parameter ``special_only``. When True, only 'special' regex characters, such as '?', are escaped. + +.. sourcecode:: python + + >>> regex.escape("foo!?", special_only=False) + 'foo\\!\\?' + >>> regex.escape("foo!?", special_only=True) + 'foo!\\?' + +regex.escape (`Hg issue 249 `_) +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +regex.escape has an additional keyword parameter ``literal_spaces``. When True, spaces are not escaped. + +.. sourcecode:: python + + >>> regex.escape("foo bar!?", literal_spaces=False) + 'foo\\ bar!\\?' + >>> regex.escape("foo bar!?", literal_spaces=True) + 'foo bar!\\?' + +Repeated captures (`issue #7132 `_) +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +A match object has additional methods which return information on all the successful matches of a repeated group. These methods are: + +* ``matchobject.captures([group1, ...])`` + + * Returns a list of the strings matched in a group or groups. Compare with ``matchobject.group([group1, ...])``. + +* ``matchobject.starts([group])`` + + * Returns a list of the start positions. Compare with ``matchobject.start([group])``. + +* ``matchobject.ends([group])`` + + * Returns a list of the end positions. Compare with ``matchobject.end([group])``. + +* ``matchobject.spans([group])`` + + * Returns a list of the spans. Compare with ``matchobject.span([group])``. + +.. sourcecode:: python + + >>> m = regex.search(r"(\w{3})+", "123456789") + >>> m.group(1) + '789' + >>> m.captures(1) + ['123', '456', '789'] + >>> m.start(1) + 6 + >>> m.starts(1) + [0, 3, 6] + >>> m.end(1) + 9 + >>> m.ends(1) + [3, 6, 9] + >>> m.span(1) + (6, 9) + >>> m.spans(1) + [(0, 3), (3, 6), (6, 9)] + +Atomic grouping ``(?>...)`` (`issue #433030 `_) +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +If the following pattern subsequently fails, then the subpattern as a whole will fail. + +Possessive quantifiers +^^^^^^^^^^^^^^^^^^^^^^ + +``(?:...)?+`` ; ``(?:...)*+`` ; ``(?:...)++`` ; ``(?:...){min,max}+`` + +The subpattern is matched up to 'max' times. If the following pattern subsequently fails, then all the repeated subpatterns will fail as a whole. For example, ``(?:...)++`` is equivalent to ``(?>(?:...)+)``. + +Scoped flags (`issue #433028 `_) +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +``(?flags-flags:...)`` + +The flags will apply only to the subpattern. Flags can be turned on or off. + +Definition of 'word' character (`issue #1693050 `_) +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +The definition of a 'word' character has been expanded for Unicode. It conforms to the Unicode specification at ``http://www.unicode.org/reports/tr29/``. + +Variable-length lookbehind +^^^^^^^^^^^^^^^^^^^^^^^^^^ + +A lookbehind can match a variable-length string. + +Flags argument for regex.split, regex.sub and regex.subn (`issue #3482 `_) +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +``regex.split``, ``regex.sub`` and ``regex.subn`` support a 'flags' argument. + +Pos and endpos arguments for regex.sub and regex.subn +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +``regex.sub`` and ``regex.subn`` support 'pos' and 'endpos' arguments. + +'Overlapped' argument for regex.findall and regex.finditer +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +``regex.findall`` and ``regex.finditer`` support an 'overlapped' flag which permits overlapped matches. + +Splititer +^^^^^^^^^ + +``regex.splititer`` has been added. It's a generator equivalent of ``regex.split``. + +Subscripting match objects for groups +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +A match object accepts access to the groups via subscripting and slicing: + +.. sourcecode:: python + + >>> m = regex.search(r"(?P.*?)(?P\d+)(?P.*)", "pqr123stu") + >>> print(m["before"]) + pqr + >>> print(len(m)) + 4 + >>> print(m[:]) + ('pqr123stu', 'pqr', '123', 'stu') + +Named groups +^^^^^^^^^^^^ + +Groups can be named with ``(?...)`` as well as the existing ``(?P...)``. + +Group references +^^^^^^^^^^^^^^^^ + +Groups can be referenced within a pattern with ``\g``. This also allows there to be more than 99 groups. + +Named characters ``\N{name}`` +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +Named characters are supported. Note that only those known by Python's Unicode database will be recognised. + +Unicode codepoint properties, including scripts and blocks +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +``\p{property=value}``; ``\P{property=value}``; ``\p{value}`` ; ``\P{value}`` + +Many Unicode properties are supported, including blocks and scripts. ``\p{property=value}`` or ``\p{property:value}`` matches a character whose property ``property`` has value ``value``. The inverse of ``\p{property=value}`` is ``\P{property=value}`` or ``\p{^property=value}``. + +If the short form ``\p{value}`` is used, the properties are checked in the order: ``General_Category``, ``Script``, ``Block``, binary property: + +* ``Latin``, the 'Latin' script (``Script=Latin``). + +* ``BasicLatin``, the 'BasicLatin' block (``Block=BasicLatin``). + +* ``Alphabetic``, the 'Alphabetic' binary property (``Alphabetic=Yes``). + +A short form starting with ``Is`` indicates a script or binary property: + +* ``IsLatin``, the 'Latin' script (``Script=Latin``). + +* ``IsAlphabetic``, the 'Alphabetic' binary property (``Alphabetic=Yes``). + +A short form starting with ``In`` indicates a block property: + +* ``InBasicLatin``, the 'BasicLatin' block (``Block=BasicLatin``). + +POSIX character classes +^^^^^^^^^^^^^^^^^^^^^^^ + +``[[:alpha:]]``; ``[[:^alpha:]]`` + +POSIX character classes are supported. These are normally treated as an alternative form of ``\p{...}``. + +The exceptions are ``alnum``, ``digit``, ``punct`` and ``xdigit``, whose definitions are different from those of Unicode. + +``[[:alnum:]]`` is equivalent to ``\p{posix_alnum}``. + +``[[:digit:]]`` is equivalent to ``\p{posix_digit}``. + +``[[:punct:]]`` is equivalent to ``\p{posix_punct}``. + +``[[:xdigit:]]`` is equivalent to ``\p{posix_xdigit}``. + +Search anchor ``\G`` +^^^^^^^^^^^^^^^^^^^^ + +A search anchor has been added. It matches at the position where each search started/continued and can be used for contiguous matches or in negative variable-length lookbehinds to limit how far back the lookbehind goes: + +.. sourcecode:: python + + >>> regex.findall(r"\w{2}", "abcd ef") + ['ab', 'cd', 'ef'] + >>> regex.findall(r"\G\w{2}", "abcd ef") + ['ab', 'cd'] + +* The search starts at position 0 and matches 'ab'. + +* The search continues at position 2 and matches 'cd'. + +* The search continues at position 4 and fails to match any letters. + +* The anchor stops the search start position from being advanced, so there are no more results. + +Reverse searching +^^^^^^^^^^^^^^^^^ + +Searches can also work backwards: + +.. sourcecode:: python + + >>> regex.findall(r".", "abc") + ['a', 'b', 'c'] + >>> regex.findall(r"(?r).", "abc") + ['c', 'b', 'a'] + +Note that the result of a reverse search is not necessarily the reverse of a forward search: + +.. sourcecode:: python + + >>> regex.findall(r"..", "abcde") + ['ab', 'cd'] + >>> regex.findall(r"(?r)..", "abcde") + ['de', 'bc'] + +Matching a single grapheme ``\X`` +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +The grapheme matcher is supported. It conforms to the Unicode specification at ``http://www.unicode.org/reports/tr29/``. + +Branch reset ``(?|...|...)`` +^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +Group numbers will be reused across the alternatives, but groups with different names will have different group numbers. + +.. sourcecode:: python + + >>> regex.match(r"(?|(first)|(second))", "first").groups() + ('first',) + >>> regex.match(r"(?|(first)|(second))", "second").groups() + ('second',) + +Note that there is only one group. + +Default Unicode word boundary +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +The ``WORD`` flag changes the definition of a 'word boundary' to that of a default Unicode word boundary. This applies to ``\b`` and ``\B``. + +Timeout +^^^^^^^ + +The matching methods and functions support timeouts. The timeout (in seconds) applies to the entire operation: + +.. sourcecode:: python + + >>> from time import sleep + >>> + >>> def fast_replace(m): + ... return 'X' + ... + >>> def slow_replace(m): + ... sleep(0.5) + ... return 'X' + ... + >>> regex.sub(r'[a-z]', fast_replace, 'abcde', timeout=2) + 'XXXXX' + >>> regex.sub(r'[a-z]', slow_replace, 'abcde', timeout=2) + Traceback (most recent call last): + File "", line 1, in + File "C:\Python310\lib\site-packages\regex\regex.py", line 278, in sub + return pat.sub(repl, string, count, pos, endpos, concurrent, timeout) + TimeoutError: regex timed out diff --git a/llmeval-env/lib/python3.10/site-packages/regex-2024.4.28.dist-info/RECORD b/llmeval-env/lib/python3.10/site-packages/regex-2024.4.28.dist-info/RECORD new file mode 100644 index 0000000000000000000000000000000000000000..4d34d56616545ae911caf1cdc62caf4c79ca7232 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/regex-2024.4.28.dist-info/RECORD @@ -0,0 +1,15 @@ +regex-2024.4.28.dist-info/INSTALLER,sha256=zuuue4knoyJ-UwPPXg8fezS7VCrXJQrAP7zeNuwvFQg,4 +regex-2024.4.28.dist-info/LICENSE.txt,sha256=v_Ve9M3MjBTOJZ-OirYOJkQYRA1jNfTcE4Jz-9UGFE0,11584 +regex-2024.4.28.dist-info/METADATA,sha256=eUBhzTUr6YA4UPlg-Wn1KaDgnUJeQngfAvWv-LlMVcg,40846 +regex-2024.4.28.dist-info/RECORD,, +regex-2024.4.28.dist-info/WHEEL,sha256=CzQQWV-lNyM92gr3iaBk8dvO35YDHRxgzkZ-dxumUIM,152 +regex-2024.4.28.dist-info/top_level.txt,sha256=aQmiDMhNTF26cCK4_7D-qaVvhbxClG0wyCTnEhkzYBs,6 +regex/__init__.py,sha256=9slNQEb4SCZ9LncNzcQvqmkyxXlcOAF7QwAwigxWjsw,65 +regex/__pycache__/__init__.cpython-310.pyc,, +regex/__pycache__/_regex_core.cpython-310.pyc,, +regex/__pycache__/regex.cpython-310.pyc,, +regex/__pycache__/test_regex.cpython-310.pyc,, +regex/_regex.cpython-310-x86_64-linux-gnu.so,sha256=eDasy28Zqt08KlBmrPsvhvzf9RC7bT77ODLqPybkzBM,2503320 +regex/_regex_core.py,sha256=MI8nzE7gBEUTDDrao8aOHg7_QhhDzE07VoKFl_WSxCM,141028 +regex/regex.py,sha256=-PoKoTZoDJkDfxOzKWB435H2wwEeoSLRF6a-38hWlSA,32683 +regex/test_regex.py,sha256=7UpS-CskT4SuPXnwAySBC6zkYkw_CBkYULRiXcWsPco,220091 diff --git a/llmeval-env/lib/python3.10/site-packages/regex-2024.4.28.dist-info/WHEEL b/llmeval-env/lib/python3.10/site-packages/regex-2024.4.28.dist-info/WHEEL new file mode 100644 index 0000000000000000000000000000000000000000..9bb86cf30c63df9170e9af3dd246ce6f41270402 --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/regex-2024.4.28.dist-info/WHEEL @@ -0,0 +1,6 @@ +Wheel-Version: 1.0 +Generator: bdist_wheel (0.43.0) +Root-Is-Purelib: false +Tag: cp310-cp310-manylinux_2_17_x86_64 +Tag: cp310-cp310-manylinux2014_x86_64 + diff --git a/llmeval-env/lib/python3.10/site-packages/regex-2024.4.28.dist-info/top_level.txt b/llmeval-env/lib/python3.10/site-packages/regex-2024.4.28.dist-info/top_level.txt new file mode 100644 index 0000000000000000000000000000000000000000..4f9256d62325c75de027d1cd48f1ff520117413e --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/regex-2024.4.28.dist-info/top_level.txt @@ -0,0 +1 @@ +regex diff --git a/llmeval-env/lib/python3.10/site-packages/rouge_score-0.1.2.egg-info/PKG-INFO b/llmeval-env/lib/python3.10/site-packages/rouge_score-0.1.2.egg-info/PKG-INFO new file mode 100644 index 0000000000000000000000000000000000000000..d353c64c8eeb1553e9da4e877071be6ce816757b --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/rouge_score-0.1.2.egg-info/PKG-INFO @@ -0,0 +1,114 @@ +Metadata-Version: 2.1 +Name: rouge-score +Version: 0.1.2 +Summary: Pure python implementation of ROUGE-1.5.5. +Home-page: https://github.com/google-research/google-research/tree/master/rouge +Author: Google LLC +Author-email: rouge-opensource@google.com +License: UNKNOWN +Platform: UNKNOWN +Classifier: Programming Language :: Python :: 3 +Classifier: License :: OSI Approved :: Apache Software License +Classifier: Operating System :: OS Independent +Requires-Python: >=3.7 +Description-Content-Type: text/markdown + +# Python ROUGE Implementation + +## Overview + +This is a native python implementation of ROUGE, designed to replicate results +from the original perl package. + +Maintainers may be contacted at rouge-opensource@google.com. + +ROUGE was originally introduced in the paper: + +Lin, Chin-Yew. ROUGE: a Package for Automatic Evaluation of Summaries. In +Proceedings of the Workshop on Text Summarization Branches Out (WAS 2004), +Barcelona, Spain, July 25 - 26, 2004. + +## ROUGE for Python + +There are ROUGE implementations available for Python, however some are not +native python due to their dependency on the perl script, and others provide +differing results when compared with the original implementation. This makes it +difficult to directly compare with known results. + +This package is designed to replicate perl results. It implements: + +* ROUGE-N (N-gram) scoring +* ROUGE-L (Longest Common Subsequence) scoring +* Text normalization +* Bootstrap resampling for confidence interval calculation +* Optional Porter stemming to remove plurals and word suffixes such as (ing, + ion, ment). + +Note that not all options provided by the original perl ROUGE script are +supported, but the subset of options that are implemented should replicate the +original functionality. + +## Stopword removal + +The original ROUGE perl script implemented optional stopword removal (using the +-s parameter). However, there were ~600 stopwords used by ROUGE, borrowed from +another now defunct package. This word list contained many words that may not be +suited to some tasks, such as day and month names and numbers. It also has no +clear license for redistribution. Since we are unable to replicate this +functionality precisely we do not include stopword removal. + +## Two flavors of ROUGE-L +In the ROUGE paper, two flavors of ROUGE are described: + +1. sentence-level: Compute longest common subsequence (LCS) between two pieces of +text. Newlines are ignored. This is called `rougeL` in this package. +2. summary-level: Newlines in the text are interpreted as sentence boundaries, +and the LCS is computed between each pair of reference and candidate sentences, +and something called union-LCS is computed. This is called `rougeLsum` in this +package. This is the ROUGE-L reported in *[Get To The Point: Summarization with +Pointer-Generator Networks](https://arxiv.org/abs/1704.04368)*, for example. +If your references/candidates do not have newline delimiters, you can use the +--split_summaries flag (or optional argument in RougeScorer). + +## How to run + +This package compares target files (containing one example per line) with +prediction files in the same format. It can be launched as follows (from +google-research/): + +```shell +python -m rouge.rouge \ + --target_filepattern=*.targets \ + --prediction_filepattern=*.decodes \ + --output_filename=scores.csv \ + --use_stemmer=true \ + --split_summaries=true +``` + +## Using pip +``` +pip install -r rouge/requirements.txt +pip install rouge-score +``` + +Then in python: + +```python +from rouge_score import rouge_scorer + +scorer = rouge_scorer.RougeScorer(['rouge1', 'rougeL'], use_stemmer=True) +scores = scorer.score('The quick brown fox jumps over the lazy dog', + 'The quick brown dog jumps on the log.') +``` + +## License + +Licensed under the +[Apache 2.0](https://github.com/google-research/google-research/blob/master/LICENSE) +License. + +## Disclaimer + +This is not an official Google product. + + diff --git a/llmeval-env/lib/python3.10/site-packages/rouge_score-0.1.2.egg-info/dependency_links.txt b/llmeval-env/lib/python3.10/site-packages/rouge_score-0.1.2.egg-info/dependency_links.txt new file mode 100644 index 0000000000000000000000000000000000000000..8b137891791fe96927ad78e64b0aad7bded08bdc --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/rouge_score-0.1.2.egg-info/dependency_links.txt @@ -0,0 +1 @@ + diff --git a/llmeval-env/lib/python3.10/site-packages/rouge_score-0.1.2.egg-info/top_level.txt b/llmeval-env/lib/python3.10/site-packages/rouge_score-0.1.2.egg-info/top_level.txt new file mode 100644 index 0000000000000000000000000000000000000000..ec47eb53957702d6fba3decef23ddecf6061f7ec --- /dev/null +++ b/llmeval-env/lib/python3.10/site-packages/rouge_score-0.1.2.egg-info/top_level.txt @@ -0,0 +1 @@ +rouge_score