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ckpts/universal/global_step40/zero/11.mlp.dense_h_to_4h_swiglu.weight/fp32.pt

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venv/lib/python3.10/site-packages/annotated_types-0.6.0.dist-info/INSTALLER

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+pip

venv/lib/python3.10/site-packages/annotated_types-0.6.0.dist-info/METADATA

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+Metadata-Version: 2.1
+Name: annotated-types
+Version: 0.6.0
+Summary: Reusable constraint types to use with typing.Annotated
+Author-email: Samuel Colvin <[email protected]>, Adrian Garcia Badaracco <[email protected]>, Zac Hatfield-Dodds <[email protected]>
+License-File: LICENSE
+Classifier: Development Status :: 4 - Beta
+Classifier: Environment :: Console
+Classifier: Environment :: MacOS X
+Classifier: Intended Audience :: Developers
+Classifier: Intended Audience :: Information Technology
+Classifier: License :: OSI Approved :: MIT License
+Classifier: Operating System :: POSIX :: Linux
+Classifier: Operating System :: Unix
+Classifier: Programming Language :: Python :: 3 :: Only
+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 :: Software Development :: Libraries :: Python Modules
+Classifier: Typing :: Typed
+Requires-Python: >=3.8
+Requires-Dist: typing-extensions>=4.0.0; python_version < '3.9'
+Description-Content-Type: text/markdown
+
+# annotated-types
+
+[![CI](https://github.com/annotated-types/annotated-types/workflows/CI/badge.svg?event=push)](https://github.com/annotated-types/annotated-types/actions?query=event%3Apush+branch%3Amain+workflow%3ACI)
+[![pypi](https://img.shields.io/pypi/v/annotated-types.svg)](https://pypi.python.org/pypi/annotated-types)
+[![versions](https://img.shields.io/pypi/pyversions/annotated-types.svg)](https://github.com/annotated-types/annotated-types)
+[![license](https://img.shields.io/github/license/annotated-types/annotated-types.svg)](https://github.com/annotated-types/annotated-types/blob/main/LICENSE)
+
+[PEP-593](https://peps.python.org/pep-0593/) added `typing.Annotated` as a way of
+adding context-specific metadata to existing types, and specifies that
+`Annotated[T, x]` _should_ be treated as `T` by any tool or library without special
+logic for `x`.
+
+This package provides metadata objects which can be used to represent common
+constraints such as upper and lower bounds on scalar values and collection sizes,
+a `Predicate` marker for runtime checks, and
+descriptions of how we intend these metadata to be interpreted. In some cases,
+we also note alternative representations which do not require this package.
+
+## Install
+
+```bash
+pip install annotated-types
+```
+
+## Examples
+
+```python
+from typing import Annotated
+from annotated_types import Gt, Len, Predicate
+
+class MyClass:
+    age: Annotated[int, Gt(18)]                         # Valid: 19, 20, ...
+                                                        # Invalid: 17, 18, "19", 19.0, ...
+    factors: list[Annotated[int, Predicate(is_prime)]]  # Valid: 2, 3, 5, 7, 11, ...
+                                                        # Invalid: 4, 8, -2, 5.0, "prime", ...
+
+    my_list: Annotated[list[int], Len(0, 10)]           # Valid: [], [10, 20, 30, 40, 50]
+                                                        # Invalid: (1, 2), ["abc"], [0] * 20
+```
+
+## Documentation
+
+_While `annotated-types` avoids runtime checks for performance, users should not
+construct invalid combinations such as `MultipleOf("non-numeric")` or `Annotated[int, Len(3)]`.
+Downstream implementors may choose to raise an error, emit a warning, silently ignore
+a metadata item, etc., if the metadata objects described below are used with an
+incompatible type - or for any other reason!_
+
+### Gt, Ge, Lt, Le
+
+Express inclusive and/or exclusive bounds on orderable values - which may be numbers,
+dates, times, strings, sets, etc. Note that the boundary value need not be of the
+same type that was annotated, so long as they can be compared: `Annotated[int, Gt(1.5)]`
+is fine, for example, and implies that the value is an integer x such that `x > 1.5`.
+
+We suggest that implementors may also interpret `functools.partial(operator.le, 1.5)`
+as being equivalent to `Gt(1.5)`, for users who wish to avoid a runtime dependency on
+the `annotated-types` package.
+
+To be explicit, these types have the following meanings:
+
+* `Gt(x)` - value must be "Greater Than" `x` - equivalent to exclusive minimum
+* `Ge(x)` - value must be "Greater than or Equal" to `x` - equivalent to inclusive minimum
+* `Lt(x)` - value must be "Less Than" `x` - equivalent to exclusive maximum
+* `Le(x)` - value must be "Less than or Equal" to `x` - equivalent to inclusive maximum
+
+### Interval
+
+`Interval(gt, ge, lt, le)` allows you to specify an upper and lower bound with a single
+metadata object. `None` attributes should be ignored, and non-`None` attributes
+treated as per the single bounds above.
+
+### MultipleOf
+
+`MultipleOf(multiple_of=x)` might be interpreted in two ways:
+
+1. Python semantics, implying `value % multiple_of == 0`, or
+2. [JSONschema semantics](https://json-schema.org/draft/2020-12/json-schema-validation.html#rfc.section.6.2.1),
+   where `int(value / multiple_of) == value / multiple_of`.
+
+We encourage users to be aware of these two common interpretations and their
+distinct behaviours, especially since very large or non-integer numbers make
+it easy to cause silent data corruption due to floating-point imprecision.
+
+We encourage libraries to carefully document which interpretation they implement.
+
+### MinLen, MaxLen, Len
+
+`Len()` implies that `min_length <= len(value) <= max_length` - lower and upper bounds are inclusive.
+
+As well as `Len()` which can optionally include upper and lower bounds, we also
+provide `MinLen(x)` and `MaxLen(y)` which are equivalent to `Len(min_length=x)`
+and `Len(max_length=y)` respectively.
+
+`Len`, `MinLen`, and `MaxLen` may be used with any type which supports `len(value)`.
+
+Examples of usage:
+
+* `Annotated[list, MaxLen(10)]` (or `Annotated[list, Len(max_length=10))`) - list must have a length of 10 or less
+* `Annotated[str, MaxLen(10)]` - string must have a length of 10 or less
+* `Annotated[list, MinLen(3))` (or `Annotated[list, Len(min_length=3))`) - list must have a length of 3 or more
+* `Annotated[list, Len(4, 6)]` - list must have a length of 4, 5, or 6
+* `Annotated[list, Len(8, 8)]` - list must have a length of exactly 8
+
+#### Changed in v0.4.0
+
+* `min_inclusive` has been renamed to `min_length`, no change in meaning
+* `max_exclusive` has been renamed to `max_length`, upper bound is now **inclusive** instead of **exclusive**
+* The recommendation that slices are interpreted as `Len` has been removed due to ambiguity and different semantic
+  meaning of the upper bound in slices vs. `Len`
+
+See [issue #23](https://github.com/annotated-types/annotated-types/issues/23) for discussion.
+
+### Timezone
+
+`Timezone` can be used with a `datetime` or a `time` to express which timezones
+are allowed. `Annotated[datetime, Timezone(None)]` must be a naive datetime.
+`Timezone[...]` ([literal ellipsis](https://docs.python.org/3/library/constants.html#Ellipsis))
+expresses that any timezone-aware datetime is allowed. You may also pass a specific
+timezone string or `timezone` object such as `Timezone(timezone.utc)` or
+`Timezone("Africa/Abidjan")` to express that you only allow a specific timezone,
+though we note that this is often a symptom of fragile design.
+
+### Predicate
+
+`Predicate(func: Callable)` expresses that `func(value)` is truthy for valid values.
+Users should prefer the statically inspectable metadata above, but if you need
+the full power and flexibility of arbitrary runtime predicates... here it is.
+
+We provide a few predefined predicates for common string constraints:
+
+* `IsLower = Predicate(str.islower)`
+* `IsUpper = Predicate(str.isupper)`
+* `IsDigit = Predicate(str.isdigit)`
+* `IsFinite = Predicate(math.isfinite)`
+* `IsNotFinite = Predicate(Not(math.isfinite))`
+* `IsNan = Predicate(math.isnan)`
+* `IsNotNan = Predicate(Not(math.isnan))`
+* `IsInfinite = Predicate(math.isinf)`
+* `IsNotInfinite = Predicate(Not(math.isinf))`
+
+Some libraries might have special logic to handle known or understandable predicates,
+for example by checking for `str.isdigit` and using its presence to both call custom
+logic to enforce digit-only strings, and customise some generated external schema.
+Users are therefore encouraged to avoid indirection like `lambda s: s.lower()`, in
+favor of introspectable methods such as `str.lower` or `re.compile("pattern").search`.
+
+To enable basic negation of commonly used predicates like `math.isnan` without introducing introspection that makes it impossible for implementers to introspect the predicate we provide a `Not` wrapper that simply negates the predicate in an introspectable manner. Several of the predicates listed above are created in this manner.
+
+We do not specify what behaviour should be expected for predicates that raise
+an exception.  For example `Annotated[int, Predicate(str.isdigit)]` might silently
+skip invalid constraints, or statically raise an error; or it might try calling it
+and then propogate or discard the resulting
+`TypeError: descriptor 'isdigit' for 'str' objects doesn't apply to a 'int' object`
+exception.  We encourage libraries to document the behaviour they choose.
+
+### Doc
+
+`doc()` can be used to add documentation information in `Annotated`, for function and method parameters, variables, class attributes, return types, and any place where `Annotated` can be used.
+
+It expects a value that can be statically analyzed, as the main use case is for static analysis, editors, documentation generators, and similar tools.
+
+It returns a `DocInfo` class with a single attribute `documentation` containing the value passed to `doc()`.
+
+This is the early adopter's alternative form of the [`typing-doc` proposal](https://github.com/tiangolo/fastapi/blob/typing-doc/typing_doc.md).
+
+### Integrating downstream types with `GroupedMetadata`
+
+Implementers may choose to provide a convenience wrapper that groups multiple pieces of metadata.
+This can help reduce verbosity and cognitive overhead for users.
+For example, an implementer like Pydantic might provide a `Field` or `Meta` type that accepts keyword arguments and transforms these into low-level metadata:
+
+```python
+from dataclasses import dataclass
+from typing import Iterator
+from annotated_types import GroupedMetadata, Ge
+
+@dataclass
+class Field(GroupedMetadata):
+    ge: int | None = None
+    description: str | None = None
+
+    def __iter__(self) -> Iterator[object]:
+        # Iterating over a GroupedMetadata object should yield annotated-types
+        # constraint metadata objects which describe it as fully as possible,
+        # and may include other unknown objects too.
+        if self.ge is not None:
+            yield Ge(self.ge)
+        if self.description is not None:
+            yield Description(self.description)
+```
+
+Libraries consuming annotated-types constraints should check for `GroupedMetadata` and unpack it by iterating over the object and treating the results as if they had been "unpacked" in the `Annotated` type.  The same logic should be applied to the [PEP 646 `Unpack` type](https://peps.python.org/pep-0646/), so that `Annotated[T, Field(...)]`, `Annotated[T, Unpack[Field(...)]]` and `Annotated[T, *Field(...)]` are all treated consistently.
+
+Libraries consuming annotated-types should also ignore any metadata they do not recongize that came from unpacking a `GroupedMetadata`, just like they ignore unrecognized metadata in `Annotated` itself.
+
+Our own `annotated_types.Interval` class is a `GroupedMetadata` which unpacks itself into `Gt`, `Lt`, etc., so this is not an abstract concern.  Similarly, `annotated_types.Len` is a `GroupedMetadata` which unpacks itself into `MinLen` (optionally) and `MaxLen`.
+
+### Consuming metadata
+
+We intend to not be prescriptive as to _how_ the metadata and constraints are used, but as an example of how one might parse constraints from types annotations see our [implementation in `test_main.py`](https://github.com/annotated-types/annotated-types/blob/f59cf6d1b5255a0fe359b93896759a180bec30ae/tests/test_main.py#L94-L103).
+
+It is up to the implementer to determine how this metadata is used.
+You could use the metadata for runtime type checking, for generating schemas or to generate example data, amongst other use cases.
+
+## Design & History
+
+This package was designed at the PyCon 2022 sprints by the maintainers of Pydantic
+and Hypothesis, with the goal of making it as easy as possible for end-users to
+provide more informative annotations for use by runtime libraries.
+
+It is deliberately minimal, and following PEP-593 allows considerable downstream
+discretion in what (if anything!) they choose to support. Nonetheless, we expect
+that staying simple and covering _only_ the most common use-cases will give users
+and maintainers the best experience we can. If you'd like more constraints for your
+types - follow our lead, by defining them and documenting them downstream!

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venv/lib/python3.10/site-packages/annotated_types-0.6.0.dist-info/WHEEL

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+Wheel-Version: 1.0
+Generator: hatchling 1.18.0
+Root-Is-Purelib: true
+Tag: py3-none-any

venv/lib/python3.10/site-packages/annotated_types-0.6.0.dist-info/licenses/LICENSE

@@ -0,0 +1,21 @@
+The MIT License (MIT)
+
+Copyright (c) 2022 the contributors
+
+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. IN NO EVENT SHALL THE
+AUTHORS 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 IN THE
+SOFTWARE.

venv/lib/python3.10/site-packages/chardet/__init__.py

@@ -0,0 +1,115 @@
+######################## BEGIN LICENSE BLOCK ########################
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
+# 02110-1301  USA
+######################### END LICENSE BLOCK #########################
+
+from typing import List, Union
+
+from .charsetgroupprober import CharSetGroupProber
+from .charsetprober import CharSetProber
+from .enums import InputState
+from .resultdict import ResultDict
+from .universaldetector import UniversalDetector
+from .version import VERSION, __version__
+
+__all__ = ["UniversalDetector", "detect", "detect_all", "__version__", "VERSION"]
+
+
+def detect(
+    byte_str: Union[bytes, bytearray], should_rename_legacy: bool = False
+) -> ResultDict:
+    """
+    Detect the encoding of the given byte string.
+
+    :param byte_str:     The byte sequence to examine.
+    :type byte_str:      ``bytes`` or ``bytearray``
+    :param should_rename_legacy:  Should we rename legacy encodings
+                                  to their more modern equivalents?
+    :type should_rename_legacy:   ``bool``
+    """
+    if not isinstance(byte_str, bytearray):
+        if not isinstance(byte_str, bytes):
+            raise TypeError(
+                f"Expected object of type bytes or bytearray, got: {type(byte_str)}"
+            )
+        byte_str = bytearray(byte_str)
+    detector = UniversalDetector(should_rename_legacy=should_rename_legacy)
+    detector.feed(byte_str)
+    return detector.close()
+
+
+def detect_all(
+    byte_str: Union[bytes, bytearray],
+    ignore_threshold: bool = False,
+    should_rename_legacy: bool = False,
+) -> List[ResultDict]:
+    """
+    Detect all the possible encodings of the given byte string.
+
+    :param byte_str:          The byte sequence to examine.
+    :type byte_str:           ``bytes`` or ``bytearray``
+    :param ignore_threshold:  Include encodings that are below
+                              ``UniversalDetector.MINIMUM_THRESHOLD``
+                              in results.
+    :type ignore_threshold:   ``bool``
+    :param should_rename_legacy:  Should we rename legacy encodings
+                                  to their more modern equivalents?
+    :type should_rename_legacy:   ``bool``
+    """
+    if not isinstance(byte_str, bytearray):
+        if not isinstance(byte_str, bytes):
+            raise TypeError(
+                f"Expected object of type bytes or bytearray, got: {type(byte_str)}"
+            )
+        byte_str = bytearray(byte_str)
+
+    detector = UniversalDetector(should_rename_legacy=should_rename_legacy)
+    detector.feed(byte_str)
+    detector.close()
+
+    if detector.input_state == InputState.HIGH_BYTE:
+        results: List[ResultDict] = []
+        probers: List[CharSetProber] = []
+        for prober in detector.charset_probers:
+            if isinstance(prober, CharSetGroupProber):
+                probers.extend(p for p in prober.probers)
+            else:
+                probers.append(prober)
+        for prober in probers:
+            if ignore_threshold or prober.get_confidence() > detector.MINIMUM_THRESHOLD:
+                charset_name = prober.charset_name or ""
+                lower_charset_name = charset_name.lower()
+                # Use Windows encoding name instead of ISO-8859 if we saw any
+                # extra Windows-specific bytes
+                if lower_charset_name.startswith("iso-8859") and detector.has_win_bytes:
+                    charset_name = detector.ISO_WIN_MAP.get(
+                        lower_charset_name, charset_name
+                    )
+                # Rename legacy encodings with superset encodings if asked
+                if should_rename_legacy:
+                    charset_name = detector.LEGACY_MAP.get(
+                        charset_name.lower(), charset_name
+                    )
+                results.append(
+                    {
+                        "encoding": charset_name,
+                        "confidence": prober.get_confidence(),
+                        "language": prober.language,
+                    }
+                )
+        if len(results) > 0:
+            return sorted(results, key=lambda result: -result["confidence"])
+
+    return [detector.result]

venv/lib/python3.10/site-packages/chardet/big5freq.py

@@ -0,0 +1,386 @@
+######################## BEGIN LICENSE BLOCK ########################
+# The Original Code is Mozilla Communicator client code.
+#
+# The Initial Developer of the Original Code is
+# Netscape Communications Corporation.
+# Portions created by the Initial Developer are Copyright (C) 1998
+# the Initial Developer. All Rights Reserved.
+#
+# Contributor(s):
+#   Mark Pilgrim - port to Python
+#
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
+# 02110-1301  USA
+######################### END LICENSE BLOCK #########################
+
+# Big5 frequency table
+# by Taiwan's Mandarin Promotion Council
+# <http://www.edu.tw:81/mandr/>
+#
+# 128  --> 0.42261
+# 256  --> 0.57851
+# 512  --> 0.74851
+# 1024 --> 0.89384
+# 2048 --> 0.97583
+#
+# Ideal Distribution Ratio = 0.74851/(1-0.74851) =2.98
+# Random Distribution Ration = 512/(5401-512)=0.105
+#
+# Typical Distribution Ratio about 25% of Ideal one, still much higher than RDR
+
+BIG5_TYPICAL_DISTRIBUTION_RATIO = 0.75
+
+# Char to FreqOrder table
+BIG5_TABLE_SIZE = 5376
+# fmt: off
+BIG5_CHAR_TO_FREQ_ORDER = (
+   1,1801,1506, 255,1431, 198,   9,  82,   6,5008, 177, 202,3681,1256,2821, 110, #   16
+3814,  33,3274, 261,  76,  44,2114,  16,2946,2187,1176, 659,3971,  26,3451,2653, #   32
+1198,3972,3350,4202, 410,2215, 302, 590, 361,1964,   8, 204,  58,4510,5009,1932, #   48
+  63,5010,5011, 317,1614,  75, 222, 159,4203,2417,1480,5012,3555,3091, 224,2822, #   64
+3682,   3,  10,3973,1471,  29,2787,1135,2866,1940, 873, 130,3275,1123, 312,5013, #   80
+4511,2052, 507, 252, 682,5014, 142,1915, 124, 206,2947,  34,3556,3204,  64, 604, #   96
+5015,2501,1977,1978, 155,1991, 645, 641,1606,5016,3452, 337,  72, 406,5017,  80, #  112
+ 630, 238,3205,1509, 263, 939,1092,2654, 756,1440,1094,3453, 449,  69,2987, 591, #  128
+ 179,2096, 471, 115,2035,1844,  60,  50,2988, 134, 806,1869, 734,2036,3454, 180, #  144
+ 995,1607, 156, 537,2907, 688,5018, 319,1305, 779,2145, 514,2379, 298,4512, 359, #  160
+2502,  90,2716,1338, 663,  11, 906,1099,2553,  20,2441, 182, 532,1716,5019, 732, #  176
+1376,4204,1311,1420,3206,  25,2317,1056, 113, 399, 382,1950, 242,3455,2474, 529, #  192
+3276, 475,1447,3683,5020, 117,  21, 656, 810,1297,2300,2334,3557,5021, 126,4205, #  208
+ 706, 456, 150, 613,4513,  71,1118,2037,4206, 145,3092,  85, 835, 486,2115,1246, #  224
+1426, 428, 727,1285,1015, 800, 106, 623, 303,1281,5022,2128,2359, 347,3815, 221, #  240
+3558,3135,5023,1956,1153,4207,  83, 296,1199,3093, 192, 624,  93,5024, 822,1898, #  256
+2823,3136, 795,2065, 991,1554,1542,1592,  27,  43,2867, 859, 139,1456, 860,4514, #  272
+ 437, 712,3974, 164,2397,3137, 695, 211,3037,2097, 195,3975,1608,3559,3560,3684, #  288
+3976, 234, 811,2989,2098,3977,2233,1441,3561,1615,2380, 668,2077,1638, 305, 228, #  304
+1664,4515, 467, 415,5025, 262,2099,1593, 239, 108, 300, 200,1033, 512,1247,2078, #  320
+5026,5027,2176,3207,3685,2682, 593, 845,1062,3277,  88,1723,2038,3978,1951, 212, #  336
+ 266, 152, 149, 468,1899,4208,4516,  77, 187,5028,3038,  37,   5,2990,5029,3979, #  352
+5030,5031,  39,2524,4517,2908,3208,2079,  55, 148,  74,4518, 545, 483,1474,1029, #  368
+1665, 217,1870,1531,3138,1104,2655,4209,  24, 172,3562, 900,3980,3563,3564,4519, #  384
+  32,1408,2824,1312, 329, 487,2360,2251,2717, 784,2683,   4,3039,3351,1427,1789, #  400
+ 188, 109, 499,5032,3686,1717,1790, 888,1217,3040,4520,5033,3565,5034,3352,1520, #  416
+3687,3981, 196,1034, 775,5035,5036, 929,1816, 249, 439,  38,5037,1063,5038, 794, #  432
+3982,1435,2301,  46, 178,3278,2066,5039,2381,5040, 214,1709,4521, 804,  35, 707, #  448
+ 324,3688,1601,2554, 140, 459,4210,5041,5042,1365, 839, 272, 978,2262,2580,3456, #  464
+2129,1363,3689,1423, 697, 100,3094,  48,  70,1231, 495,3139,2196,5043,1294,5044, #  480
+2080, 462, 586,1042,3279, 853, 256, 988, 185,2382,3457,1698, 434,1084,5045,3458, #  496
+ 314,2625,2788,4522,2335,2336, 569,2285, 637,1817,2525, 757,1162,1879,1616,3459, #  512
+ 287,1577,2116, 768,4523,1671,2868,3566,2526,1321,3816, 909,2418,5046,4211, 933, #  528
+3817,4212,2053,2361,1222,4524, 765,2419,1322, 786,4525,5047,1920,1462,1677,2909, #  544
+1699,5048,4526,1424,2442,3140,3690,2600,3353,1775,1941,3460,3983,4213, 309,1369, #  560
+1130,2825, 364,2234,1653,1299,3984,3567,3985,3986,2656, 525,1085,3041, 902,2001, #  576
+1475, 964,4527, 421,1845,1415,1057,2286, 940,1364,3141, 376,4528,4529,1381,   7, #  592
+2527, 983,2383, 336,1710,2684,1846, 321,3461, 559,1131,3042,2752,1809,1132,1313, #  608
+ 265,1481,1858,5049, 352,1203,2826,3280, 167,1089, 420,2827, 776, 792,1724,3568, #  624
+4214,2443,3281,5050,4215,5051, 446, 229, 333,2753, 901,3818,1200,1557,4530,2657, #  640
+1921, 395,2754,2685,3819,4216,1836, 125, 916,3209,2626,4531,5052,5053,3820,5054, #  656
+5055,5056,4532,3142,3691,1133,2555,1757,3462,1510,2318,1409,3569,5057,2146, 438, #  672
+2601,2910,2384,3354,1068, 958,3043, 461, 311,2869,2686,4217,1916,3210,4218,1979, #  688
+ 383, 750,2755,2627,4219, 274, 539, 385,1278,1442,5058,1154,1965, 384, 561, 210, #  704
+  98,1295,2556,3570,5059,1711,2420,1482,3463,3987,2911,1257, 129,5060,3821, 642, #  720
+ 523,2789,2790,2658,5061, 141,2235,1333,  68, 176, 441, 876, 907,4220, 603,2602, #  736
+ 710, 171,3464, 404, 549,  18,3143,2398,1410,3692,1666,5062,3571,4533,2912,4534, #  752
+5063,2991, 368,5064, 146, 366,  99, 871,3693,1543, 748, 807,1586,1185,  22,2263, #  768
+ 379,3822,3211,5065,3212, 505,1942,2628,1992,1382,2319,5066, 380,2362, 218, 702, #  784
+1818,1248,3465,3044,3572,3355,3282,5067,2992,3694, 930,3283,3823,5068,  59,5069, #  800
+ 585, 601,4221, 497,3466,1112,1314,4535,1802,5070,1223,1472,2177,5071, 749,1837, #  816
+ 690,1900,3824,1773,3988,1476, 429,1043,1791,2236,2117, 917,4222, 447,1086,1629, #  832
+5072, 556,5073,5074,2021,1654, 844,1090, 105, 550, 966,1758,2828,1008,1783, 686, #  848
+1095,5075,2287, 793,1602,5076,3573,2603,4536,4223,2948,2302,4537,3825, 980,2503, #  864
+ 544, 353, 527,4538, 908,2687,2913,5077, 381,2629,1943,1348,5078,1341,1252, 560, #  880
+3095,5079,3467,2870,5080,2054, 973, 886,2081, 143,4539,5081,5082, 157,3989, 496, #  896
+4224,  57, 840, 540,2039,4540,4541,3468,2118,1445, 970,2264,1748,1966,2082,4225, #  912
+3144,1234,1776,3284,2829,3695, 773,1206,2130,1066,2040,1326,3990,1738,1725,4226, #  928
+ 279,3145,  51,1544,2604, 423,1578,2131,2067, 173,4542,1880,5083,5084,1583, 264, #  944
+ 610,3696,4543,2444, 280, 154,5085,5086,5087,1739, 338,1282,3096, 693,2871,1411, #  960
+1074,3826,2445,5088,4544,5089,5090,1240, 952,2399,5091,2914,1538,2688, 685,1483, #  976
+4227,2475,1436, 953,4228,2055,4545, 671,2400,  79,4229,2446,3285, 608, 567,2689, #  992
+3469,4230,4231,1691, 393,1261,1792,2401,5092,4546,5093,5094,5095,5096,1383,1672, # 1008
+3827,3213,1464, 522,1119, 661,1150, 216, 675,4547,3991,1432,3574, 609,4548,2690, # 1024
+2402,5097,5098,5099,4232,3045,   0,5100,2476, 315, 231,2447, 301,3356,4549,2385, # 1040
+5101, 233,4233,3697,1819,4550,4551,5102,  96,1777,1315,2083,5103, 257,5104,1810, # 1056
+3698,2718,1139,1820,4234,2022,1124,2164,2791,1778,2659,5105,3097, 363,1655,3214, # 1072
+5106,2993,5107,5108,5109,3992,1567,3993, 718, 103,3215, 849,1443, 341,3357,2949, # 1088
+1484,5110,1712, 127,  67, 339,4235,2403, 679,1412, 821,5111,5112, 834, 738, 351, # 1104
+2994,2147, 846, 235,1497,1881, 418,1993,3828,2719, 186,1100,2148,2756,3575,1545, # 1120
+1355,2950,2872,1377, 583,3994,4236,2581,2995,5113,1298,3699,1078,2557,3700,2363, # 1136
+  78,3829,3830, 267,1289,2100,2002,1594,4237, 348, 369,1274,2197,2178,1838,4552, # 1152
+1821,2830,3701,2757,2288,2003,4553,2951,2758, 144,3358, 882,4554,3995,2759,3470, # 1168
+4555,2915,5114,4238,1726, 320,5115,3996,3046, 788,2996,5116,2831,1774,1327,2873, # 1184
+3997,2832,5117,1306,4556,2004,1700,3831,3576,2364,2660, 787,2023, 506, 824,3702, # 1200
+ 534, 323,4557,1044,3359,2024,1901, 946,3471,5118,1779,1500,1678,5119,1882,4558, # 1216
+ 165, 243,4559,3703,2528, 123, 683,4239, 764,4560,  36,3998,1793, 589,2916, 816, # 1232
+ 626,1667,3047,2237,1639,1555,1622,3832,3999,5120,4000,2874,1370,1228,1933, 891, # 1248
+2084,2917, 304,4240,5121, 292,2997,2720,3577, 691,2101,4241,1115,4561, 118, 662, # 1264
+5122, 611,1156, 854,2386,1316,2875,   2, 386, 515,2918,5123,5124,3286, 868,2238, # 1280
+1486, 855,2661, 785,2216,3048,5125,1040,3216,3578,5126,3146, 448,5127,1525,5128, # 1296
+2165,4562,5129,3833,5130,4242,2833,3579,3147, 503, 818,4001,3148,1568, 814, 676, # 1312
+1444, 306,1749,5131,3834,1416,1030, 197,1428, 805,2834,1501,4563,5132,5133,5134, # 1328
+1994,5135,4564,5136,5137,2198,  13,2792,3704,2998,3149,1229,1917,5138,3835,2132, # 1344
+5139,4243,4565,2404,3580,5140,2217,1511,1727,1120,5141,5142, 646,3836,2448, 307, # 1360
+5143,5144,1595,3217,5145,5146,5147,3705,1113,1356,4002,1465,2529,2530,5148, 519, # 1376
+5149, 128,2133,  92,2289,1980,5150,4003,1512, 342,3150,2199,5151,2793,2218,1981, # 1392
+3360,4244, 290,1656,1317, 789, 827,2365,5152,3837,4566, 562, 581,4004,5153, 401, # 1408
+4567,2252,  94,4568,5154,1399,2794,5155,1463,2025,4569,3218,1944,5156, 828,1105, # 1424
+4245,1262,1394,5157,4246, 605,4570,5158,1784,2876,5159,2835, 819,2102, 578,2200, # 1440
+2952,5160,1502, 436,3287,4247,3288,2836,4005,2919,3472,3473,5161,2721,2320,5162, # 1456
+5163,2337,2068,  23,4571, 193, 826,3838,2103, 699,1630,4248,3098, 390,1794,1064, # 1472
+3581,5164,1579,3099,3100,1400,5165,4249,1839,1640,2877,5166,4572,4573, 137,4250, # 1488
+ 598,3101,1967, 780, 104, 974,2953,5167, 278, 899, 253, 402, 572, 504, 493,1339, # 1504
+5168,4006,1275,4574,2582,2558,5169,3706,3049,3102,2253, 565,1334,2722, 863,  41, # 1520
+5170,5171,4575,5172,1657,2338,  19, 463,2760,4251, 606,5173,2999,3289,1087,2085, # 1536
+1323,2662,3000,5174,1631,1623,1750,4252,2691,5175,2878, 791,2723,2663,2339, 232, # 1552
+2421,5176,3001,1498,5177,2664,2630, 755,1366,3707,3290,3151,2026,1609, 119,1918, # 1568
+3474, 862,1026,4253,5178,4007,3839,4576,4008,4577,2265,1952,2477,5179,1125, 817, # 1584
+4254,4255,4009,1513,1766,2041,1487,4256,3050,3291,2837,3840,3152,5180,5181,1507, # 1600
+5182,2692, 733,  40,1632,1106,2879, 345,4257, 841,2531, 230,4578,3002,1847,3292, # 1616
+3475,5183,1263, 986,3476,5184, 735, 879, 254,1137, 857, 622,1300,1180,1388,1562, # 1632
+4010,4011,2954, 967,2761,2665,1349, 592,2134,1692,3361,3003,1995,4258,1679,4012, # 1648
+1902,2188,5185, 739,3708,2724,1296,1290,5186,4259,2201,2202,1922,1563,2605,2559, # 1664
+1871,2762,3004,5187, 435,5188, 343,1108, 596,  17,1751,4579,2239,3477,3709,5189, # 1680
+4580, 294,3582,2955,1693, 477, 979, 281,2042,3583, 643,2043,3710,2631,2795,2266, # 1696
+1031,2340,2135,2303,3584,4581, 367,1249,2560,5190,3585,5191,4582,1283,3362,2005, # 1712
+ 240,1762,3363,4583,4584, 836,1069,3153, 474,5192,2149,2532, 268,3586,5193,3219, # 1728
+1521,1284,5194,1658,1546,4260,5195,3587,3588,5196,4261,3364,2693,1685,4262, 961, # 1744
+1673,2632, 190,2006,2203,3841,4585,4586,5197, 570,2504,3711,1490,5198,4587,2633, # 1760
+3293,1957,4588, 584,1514, 396,1045,1945,5199,4589,1968,2449,5200,5201,4590,4013, # 1776
+ 619,5202,3154,3294, 215,2007,2796,2561,3220,4591,3221,4592, 763,4263,3842,4593, # 1792
+5203,5204,1958,1767,2956,3365,3712,1174, 452,1477,4594,3366,3155,5205,2838,1253, # 1808
+2387,2189,1091,2290,4264, 492,5206, 638,1169,1825,2136,1752,4014, 648, 926,1021, # 1824
+1324,4595, 520,4596, 997, 847,1007, 892,4597,3843,2267,1872,3713,2405,1785,4598, # 1840
+1953,2957,3103,3222,1728,4265,2044,3714,4599,2008,1701,3156,1551,  30,2268,4266, # 1856
+5207,2027,4600,3589,5208, 501,5209,4267, 594,3478,2166,1822,3590,3479,3591,3223, # 1872
+ 829,2839,4268,5210,1680,3157,1225,4269,5211,3295,4601,4270,3158,2341,5212,4602, # 1888
+4271,5213,4015,4016,5214,1848,2388,2606,3367,5215,4603, 374,4017, 652,4272,4273, # 1904
+ 375,1140, 798,5216,5217,5218,2366,4604,2269, 546,1659, 138,3051,2450,4605,5219, # 1920
+2254, 612,1849, 910, 796,3844,1740,1371, 825,3845,3846,5220,2920,2562,5221, 692, # 1936
+ 444,3052,2634, 801,4606,4274,5222,1491, 244,1053,3053,4275,4276, 340,5223,4018, # 1952
+1041,3005, 293,1168,  87,1357,5224,1539, 959,5225,2240, 721, 694,4277,3847, 219, # 1968
+1478, 644,1417,3368,2666,1413,1401,1335,1389,4019,5226,5227,3006,2367,3159,1826, # 1984
+ 730,1515, 184,2840,  66,4607,5228,1660,2958, 246,3369, 378,1457, 226,3480, 975, # 2000
+4020,2959,1264,3592, 674, 696,5229, 163,5230,1141,2422,2167, 713,3593,3370,4608, # 2016
+4021,5231,5232,1186,  15,5233,1079,1070,5234,1522,3224,3594, 276,1050,2725, 758, # 2032
+1126, 653,2960,3296,5235,2342, 889,3595,4022,3104,3007, 903,1250,4609,4023,3481, # 2048
+3596,1342,1681,1718, 766,3297, 286,  89,2961,3715,5236,1713,5237,2607,3371,3008, # 2064
+5238,2962,2219,3225,2880,5239,4610,2505,2533, 181, 387,1075,4024, 731,2190,3372, # 2080
+5240,3298, 310, 313,3482,2304, 770,4278,  54,3054, 189,4611,3105,3848,4025,5241, # 2096
+1230,1617,1850, 355,3597,4279,4612,3373, 111,4280,3716,1350,3160,3483,3055,4281, # 2112
+2150,3299,3598,5242,2797,4026,4027,3009, 722,2009,5243,1071, 247,1207,2343,2478, # 2128
+1378,4613,2010, 864,1437,1214,4614, 373,3849,1142,2220, 667,4615, 442,2763,2563, # 2144
+3850,4028,1969,4282,3300,1840, 837, 170,1107, 934,1336,1883,5244,5245,2119,4283, # 2160
+2841, 743,1569,5246,4616,4284, 582,2389,1418,3484,5247,1803,5248, 357,1395,1729, # 2176
+3717,3301,2423,1564,2241,5249,3106,3851,1633,4617,1114,2086,4285,1532,5250, 482, # 2192
+2451,4618,5251,5252,1492, 833,1466,5253,2726,3599,1641,2842,5254,1526,1272,3718, # 2208
+4286,1686,1795, 416,2564,1903,1954,1804,5255,3852,2798,3853,1159,2321,5256,2881, # 2224
+4619,1610,1584,3056,2424,2764, 443,3302,1163,3161,5257,5258,4029,5259,4287,2506, # 2240
+3057,4620,4030,3162,2104,1647,3600,2011,1873,4288,5260,4289, 431,3485,5261, 250, # 2256
+  97,  81,4290,5262,1648,1851,1558, 160, 848,5263, 866, 740,1694,5264,2204,2843, # 2272
+3226,4291,4621,3719,1687, 950,2479, 426, 469,3227,3720,3721,4031,5265,5266,1188, # 2288
+ 424,1996, 861,3601,4292,3854,2205,2694, 168,1235,3602,4293,5267,2087,1674,4622, # 2304
+3374,3303, 220,2565,1009,5268,3855, 670,3010, 332,1208, 717,5269,5270,3603,2452, # 2320
+4032,3375,5271, 513,5272,1209,2882,3376,3163,4623,1080,5273,5274,5275,5276,2534, # 2336
+3722,3604, 815,1587,4033,4034,5277,3605,3486,3856,1254,4624,1328,3058,1390,4035, # 2352
+1741,4036,3857,4037,5278, 236,3858,2453,3304,5279,5280,3723,3859,1273,3860,4625, # 2368
+5281, 308,5282,4626, 245,4627,1852,2480,1307,2583, 430, 715,2137,2454,5283, 270, # 2384
+ 199,2883,4038,5284,3606,2727,1753, 761,1754, 725,1661,1841,4628,3487,3724,5285, # 2400
+5286, 587,  14,3305, 227,2608, 326, 480,2270, 943,2765,3607, 291, 650,1884,5287, # 2416
+1702,1226, 102,1547,  62,3488, 904,4629,3489,1164,4294,5288,5289,1224,1548,2766, # 2432
+ 391, 498,1493,5290,1386,1419,5291,2056,1177,4630, 813, 880,1081,2368, 566,1145, # 2448
+4631,2291,1001,1035,2566,2609,2242, 394,1286,5292,5293,2069,5294,  86,1494,1730, # 2464
+4039, 491,1588, 745, 897,2963, 843,3377,4040,2767,2884,3306,1768, 998,2221,2070, # 2480
+ 397,1827,1195,1970,3725,3011,3378, 284,5295,3861,2507,2138,2120,1904,5296,4041, # 2496
+2151,4042,4295,1036,3490,1905, 114,2567,4296, 209,1527,5297,5298,2964,2844,2635, # 2512
+2390,2728,3164, 812,2568,5299,3307,5300,1559, 737,1885,3726,1210, 885,  28,2695, # 2528
+3608,3862,5301,4297,1004,1780,4632,5302, 346,1982,2222,2696,4633,3863,1742, 797, # 2544
+1642,4043,1934,1072,1384,2152, 896,4044,3308,3727,3228,2885,3609,5303,2569,1959, # 2560
+4634,2455,1786,5304,5305,5306,4045,4298,1005,1308,3728,4299,2729,4635,4636,1528, # 2576
+2610, 161,1178,4300,1983, 987,4637,1101,4301, 631,4046,1157,3229,2425,1343,1241, # 2592
+1016,2243,2570, 372, 877,2344,2508,1160, 555,1935, 911,4047,5307, 466,1170, 169, # 2608
+1051,2921,2697,3729,2481,3012,1182,2012,2571,1251,2636,5308, 992,2345,3491,1540, # 2624
+2730,1201,2071,2406,1997,2482,5309,4638, 528,1923,2191,1503,1874,1570,2369,3379, # 2640
+3309,5310, 557,1073,5311,1828,3492,2088,2271,3165,3059,3107, 767,3108,2799,4639, # 2656
+1006,4302,4640,2346,1267,2179,3730,3230, 778,4048,3231,2731,1597,2667,5312,4641, # 2672
+5313,3493,5314,5315,5316,3310,2698,1433,3311, 131,  95,1504,4049, 723,4303,3166, # 2688
+1842,3610,2768,2192,4050,2028,2105,3731,5317,3013,4051,1218,5318,3380,3232,4052, # 2704
+4304,2584, 248,1634,3864, 912,5319,2845,3732,3060,3865, 654,  53,5320,3014,5321, # 2720
+1688,4642, 777,3494,1032,4053,1425,5322, 191, 820,2121,2846, 971,4643, 931,3233, # 2736
+ 135, 664, 783,3866,1998, 772,2922,1936,4054,3867,4644,2923,3234, 282,2732, 640, # 2752
+1372,3495,1127, 922, 325,3381,5323,5324, 711,2045,5325,5326,4055,2223,2800,1937, # 2768
+4056,3382,2224,2255,3868,2305,5327,4645,3869,1258,3312,4057,3235,2139,2965,4058, # 2784
+4059,5328,2225, 258,3236,4646, 101,1227,5329,3313,1755,5330,1391,3314,5331,2924, # 2800
+2057, 893,5332,5333,5334,1402,4305,2347,5335,5336,3237,3611,5337,5338, 878,1325, # 2816
+1781,2801,4647, 259,1385,2585, 744,1183,2272,4648,5339,4060,2509,5340, 684,1024, # 2832
+4306,5341, 472,3612,3496,1165,3315,4061,4062, 322,2153, 881, 455,1695,1152,1340, # 2848
+ 660, 554,2154,4649,1058,4650,4307, 830,1065,3383,4063,4651,1924,5342,1703,1919, # 2864
+5343, 932,2273, 122,5344,4652, 947, 677,5345,3870,2637, 297,1906,1925,2274,4653, # 2880
+2322,3316,5346,5347,4308,5348,4309,  84,4310, 112, 989,5349, 547,1059,4064, 701, # 2896
+3613,1019,5350,4311,5351,3497, 942, 639, 457,2306,2456, 993,2966, 407, 851, 494, # 2912
+4654,3384, 927,5352,1237,5353,2426,3385, 573,4312, 680, 921,2925,1279,1875, 285, # 2928
+ 790,1448,1984, 719,2168,5354,5355,4655,4065,4066,1649,5356,1541, 563,5357,1077, # 2944
+5358,3386,3061,3498, 511,3015,4067,4068,3733,4069,1268,2572,3387,3238,4656,4657, # 2960
+5359, 535,1048,1276,1189,2926,2029,3167,1438,1373,2847,2967,1134,2013,5360,4313, # 2976
+1238,2586,3109,1259,5361, 700,5362,2968,3168,3734,4314,5363,4315,1146,1876,1907, # 2992
+4658,2611,4070, 781,2427, 132,1589, 203, 147, 273,2802,2407, 898,1787,2155,4071, # 3008
+4072,5364,3871,2803,5365,5366,4659,4660,5367,3239,5368,1635,3872, 965,5369,1805, # 3024
+2699,1516,3614,1121,1082,1329,3317,4073,1449,3873,  65,1128,2848,2927,2769,1590, # 3040
+3874,5370,5371,  12,2668,  45, 976,2587,3169,4661, 517,2535,1013,1037,3240,5372, # 3056
+3875,2849,5373,3876,5374,3499,5375,2612, 614,1999,2323,3877,3110,2733,2638,5376, # 3072
+2588,4316, 599,1269,5377,1811,3735,5378,2700,3111, 759,1060, 489,1806,3388,3318, # 3088
+1358,5379,5380,2391,1387,1215,2639,2256, 490,5381,5382,4317,1759,2392,2348,5383, # 3104
+4662,3878,1908,4074,2640,1807,3241,4663,3500,3319,2770,2349, 874,5384,5385,3501, # 3120
+3736,1859,  91,2928,3737,3062,3879,4664,5386,3170,4075,2669,5387,3502,1202,1403, # 3136
+3880,2969,2536,1517,2510,4665,3503,2511,5388,4666,5389,2701,1886,1495,1731,4076, # 3152
+2370,4667,5390,2030,5391,5392,4077,2702,1216, 237,2589,4318,2324,4078,3881,4668, # 3168
+4669,2703,3615,3504, 445,4670,5393,5394,5395,5396,2771,  61,4079,3738,1823,4080, # 3184
+5397, 687,2046, 935, 925, 405,2670, 703,1096,1860,2734,4671,4081,1877,1367,2704, # 3200
+3389, 918,2106,1782,2483, 334,3320,1611,1093,4672, 564,3171,3505,3739,3390, 945, # 3216
+2641,2058,4673,5398,1926, 872,4319,5399,3506,2705,3112, 349,4320,3740,4082,4674, # 3232
+3882,4321,3741,2156,4083,4675,4676,4322,4677,2408,2047, 782,4084, 400, 251,4323, # 3248
+1624,5400,5401, 277,3742, 299,1265, 476,1191,3883,2122,4324,4325,1109, 205,5402, # 3264
+2590,1000,2157,3616,1861,5403,5404,5405,4678,5406,4679,2573, 107,2484,2158,4085, # 3280
+3507,3172,5407,1533, 541,1301, 158, 753,4326,2886,3617,5408,1696, 370,1088,4327, # 3296
+4680,3618, 579, 327, 440, 162,2244, 269,1938,1374,3508, 968,3063,  56,1396,3113, # 3312
+2107,3321,3391,5409,1927,2159,4681,3016,5410,3619,5411,5412,3743,4682,2485,5413, # 3328
+2804,5414,1650,4683,5415,2613,5416,5417,4086,2671,3392,1149,3393,4087,3884,4088, # 3344
+5418,1076,  49,5419, 951,3242,3322,3323, 450,2850, 920,5420,1812,2805,2371,4328, # 3360
+1909,1138,2372,3885,3509,5421,3243,4684,1910,1147,1518,2428,4685,3886,5422,4686, # 3376
+2393,2614, 260,1796,3244,5423,5424,3887,3324, 708,5425,3620,1704,5426,3621,1351, # 3392
+1618,3394,3017,1887, 944,4329,3395,4330,3064,3396,4331,5427,3744, 422, 413,1714, # 3408
+3325, 500,2059,2350,4332,2486,5428,1344,1911, 954,5429,1668,5430,5431,4089,2409, # 3424
+4333,3622,3888,4334,5432,2307,1318,2512,3114, 133,3115,2887,4687, 629,  31,2851, # 3440
+2706,3889,4688, 850, 949,4689,4090,2970,1732,2089,4335,1496,1853,5433,4091, 620, # 3456
+3245, 981,1242,3745,3397,1619,3746,1643,3326,2140,2457,1971,1719,3510,2169,5434, # 3472
+3246,5435,5436,3398,1829,5437,1277,4690,1565,2048,5438,1636,3623,3116,5439, 869, # 3488
+2852, 655,3890,3891,3117,4092,3018,3892,1310,3624,4691,5440,5441,5442,1733, 558, # 3504
+4692,3747, 335,1549,3065,1756,4336,3748,1946,3511,1830,1291,1192, 470,2735,2108, # 3520
+2806, 913,1054,4093,5443,1027,5444,3066,4094,4693, 982,2672,3399,3173,3512,3247, # 3536
+3248,1947,2807,5445, 571,4694,5446,1831,5447,3625,2591,1523,2429,5448,2090, 984, # 3552
+4695,3749,1960,5449,3750, 852, 923,2808,3513,3751, 969,1519, 999,2049,2325,1705, # 3568
+5450,3118, 615,1662, 151, 597,4095,2410,2326,1049, 275,4696,3752,4337, 568,3753, # 3584
+3626,2487,4338,3754,5451,2430,2275, 409,3249,5452,1566,2888,3514,1002, 769,2853, # 3600
+ 194,2091,3174,3755,2226,3327,4339, 628,1505,5453,5454,1763,2180,3019,4096, 521, # 3616
+1161,2592,1788,2206,2411,4697,4097,1625,4340,4341, 412,  42,3119, 464,5455,2642, # 3632
+4698,3400,1760,1571,2889,3515,2537,1219,2207,3893,2643,2141,2373,4699,4700,3328, # 3648
+1651,3401,3627,5456,5457,3628,2488,3516,5458,3756,5459,5460,2276,2092, 460,5461, # 3664
+4701,5462,3020, 962, 588,3629, 289,3250,2644,1116,  52,5463,3067,1797,5464,5465, # 3680
+5466,1467,5467,1598,1143,3757,4342,1985,1734,1067,4702,1280,3402, 465,4703,1572, # 3696
+ 510,5468,1928,2245,1813,1644,3630,5469,4704,3758,5470,5471,2673,1573,1534,5472, # 3712
+5473, 536,1808,1761,3517,3894,3175,2645,5474,5475,5476,4705,3518,2929,1912,2809, # 3728
+5477,3329,1122, 377,3251,5478, 360,5479,5480,4343,1529, 551,5481,2060,3759,1769, # 3744
+2431,5482,2930,4344,3330,3120,2327,2109,2031,4706,1404, 136,1468,1479, 672,1171, # 3760
+3252,2308, 271,3176,5483,2772,5484,2050, 678,2736, 865,1948,4707,5485,2014,4098, # 3776
+2971,5486,2737,2227,1397,3068,3760,4708,4709,1735,2931,3403,3631,5487,3895, 509, # 3792
+2854,2458,2890,3896,5488,5489,3177,3178,4710,4345,2538,4711,2309,1166,1010, 552, # 3808
+ 681,1888,5490,5491,2972,2973,4099,1287,1596,1862,3179, 358, 453, 736, 175, 478, # 3824
+1117, 905,1167,1097,5492,1854,1530,5493,1706,5494,2181,3519,2292,3761,3520,3632, # 3840
+4346,2093,4347,5495,3404,1193,2489,4348,1458,2193,2208,1863,1889,1421,3331,2932, # 3856
+3069,2182,3521, 595,2123,5496,4100,5497,5498,4349,1707,2646, 223,3762,1359, 751, # 3872
+3121, 183,3522,5499,2810,3021, 419,2374, 633, 704,3897,2394, 241,5500,5501,5502, # 3888
+ 838,3022,3763,2277,2773,2459,3898,1939,2051,4101,1309,3122,2246,1181,5503,1136, # 3904
+2209,3899,2375,1446,4350,2310,4712,5504,5505,4351,1055,2615, 484,3764,5506,4102, # 3920
+ 625,4352,2278,3405,1499,4353,4103,5507,4104,4354,3253,2279,2280,3523,5508,5509, # 3936
+2774, 808,2616,3765,3406,4105,4355,3123,2539, 526,3407,3900,4356, 955,5510,1620, # 3952
+4357,2647,2432,5511,1429,3766,1669,1832, 994, 928,5512,3633,1260,5513,5514,5515, # 3968
+1949,2293, 741,2933,1626,4358,2738,2460, 867,1184, 362,3408,1392,5516,5517,4106, # 3984
+4359,1770,1736,3254,2934,4713,4714,1929,2707,1459,1158,5518,3070,3409,2891,1292, # 4000
+1930,2513,2855,3767,1986,1187,2072,2015,2617,4360,5519,2574,2514,2170,3768,2490, # 4016
+3332,5520,3769,4715,5521,5522, 666,1003,3023,1022,3634,4361,5523,4716,1814,2257, # 4032
+ 574,3901,1603, 295,1535, 705,3902,4362, 283, 858, 417,5524,5525,3255,4717,4718, # 4048
+3071,1220,1890,1046,2281,2461,4107,1393,1599, 689,2575, 388,4363,5526,2491, 802, # 4064
+5527,2811,3903,2061,1405,2258,5528,4719,3904,2110,1052,1345,3256,1585,5529, 809, # 4080
+5530,5531,5532, 575,2739,3524, 956,1552,1469,1144,2328,5533,2329,1560,2462,3635, # 4096
+3257,4108, 616,2210,4364,3180,2183,2294,5534,1833,5535,3525,4720,5536,1319,3770, # 4112
+3771,1211,3636,1023,3258,1293,2812,5537,5538,5539,3905, 607,2311,3906, 762,2892, # 4128
+1439,4365,1360,4721,1485,3072,5540,4722,1038,4366,1450,2062,2648,4367,1379,4723, # 4144
+2593,5541,5542,4368,1352,1414,2330,2935,1172,5543,5544,3907,3908,4724,1798,1451, # 4160
+5545,5546,5547,5548,2936,4109,4110,2492,2351, 411,4111,4112,3637,3333,3124,4725, # 4176
+1561,2674,1452,4113,1375,5549,5550,  47,2974, 316,5551,1406,1591,2937,3181,5552, # 4192
+1025,2142,3125,3182, 354,2740, 884,2228,4369,2412, 508,3772, 726,3638, 996,2433, # 4208
+3639, 729,5553, 392,2194,1453,4114,4726,3773,5554,5555,2463,3640,2618,1675,2813, # 4224
+ 919,2352,2975,2353,1270,4727,4115,  73,5556,5557, 647,5558,3259,2856,2259,1550, # 4240
+1346,3024,5559,1332, 883,3526,5560,5561,5562,5563,3334,2775,5564,1212, 831,1347, # 4256
+4370,4728,2331,3909,1864,3073, 720,3910,4729,4730,3911,5565,4371,5566,5567,4731, # 4272
+5568,5569,1799,4732,3774,2619,4733,3641,1645,2376,4734,5570,2938, 669,2211,2675, # 4288
+2434,5571,2893,5572,5573,1028,3260,5574,4372,2413,5575,2260,1353,5576,5577,4735, # 4304
+3183, 518,5578,4116,5579,4373,1961,5580,2143,4374,5581,5582,3025,2354,2355,3912, # 4320
+ 516,1834,1454,4117,2708,4375,4736,2229,2620,1972,1129,3642,5583,2776,5584,2976, # 4336
+1422, 577,1470,3026,1524,3410,5585,5586, 432,4376,3074,3527,5587,2594,1455,2515, # 4352
+2230,1973,1175,5588,1020,2741,4118,3528,4737,5589,2742,5590,1743,1361,3075,3529, # 4368
+2649,4119,4377,4738,2295, 895, 924,4378,2171, 331,2247,3076, 166,1627,3077,1098, # 4384
+5591,1232,2894,2231,3411,4739, 657, 403,1196,2377, 542,3775,3412,1600,4379,3530, # 4400
+5592,4740,2777,3261, 576, 530,1362,4741,4742,2540,2676,3776,4120,5593, 842,3913, # 4416
+5594,2814,2032,1014,4121, 213,2709,3413, 665, 621,4380,5595,3777,2939,2435,5596, # 4432
+2436,3335,3643,3414,4743,4381,2541,4382,4744,3644,1682,4383,3531,1380,5597, 724, # 4448
+2282, 600,1670,5598,1337,1233,4745,3126,2248,5599,1621,4746,5600, 651,4384,5601, # 4464
+1612,4385,2621,5602,2857,5603,2743,2312,3078,5604, 716,2464,3079, 174,1255,2710, # 4480
+4122,3645, 548,1320,1398, 728,4123,1574,5605,1891,1197,3080,4124,5606,3081,3082, # 4496
+3778,3646,3779, 747,5607, 635,4386,4747,5608,5609,5610,4387,5611,5612,4748,5613, # 4512
+3415,4749,2437, 451,5614,3780,2542,2073,4388,2744,4389,4125,5615,1764,4750,5616, # 4528
+4390, 350,4751,2283,2395,2493,5617,4391,4126,2249,1434,4127, 488,4752, 458,4392, # 4544
+4128,3781, 771,1330,2396,3914,2576,3184,2160,2414,1553,2677,3185,4393,5618,2494, # 4560
+2895,2622,1720,2711,4394,3416,4753,5619,2543,4395,5620,3262,4396,2778,5621,2016, # 4576
+2745,5622,1155,1017,3782,3915,5623,3336,2313, 201,1865,4397,1430,5624,4129,5625, # 4592
+5626,5627,5628,5629,4398,1604,5630, 414,1866, 371,2595,4754,4755,3532,2017,3127, # 4608
+4756,1708, 960,4399, 887, 389,2172,1536,1663,1721,5631,2232,4130,2356,2940,1580, # 4624
+5632,5633,1744,4757,2544,4758,4759,5634,4760,5635,2074,5636,4761,3647,3417,2896, # 4640
+4400,5637,4401,2650,3418,2815, 673,2712,2465, 709,3533,4131,3648,4402,5638,1148, # 4656
+ 502, 634,5639,5640,1204,4762,3649,1575,4763,2623,3783,5641,3784,3128, 948,3263, # 4672
+ 121,1745,3916,1110,5642,4403,3083,2516,3027,4132,3785,1151,1771,3917,1488,4133, # 4688
+1987,5643,2438,3534,5644,5645,2094,5646,4404,3918,1213,1407,2816, 531,2746,2545, # 4704
+3264,1011,1537,4764,2779,4405,3129,1061,5647,3786,3787,1867,2897,5648,2018, 120, # 4720
+4406,4407,2063,3650,3265,2314,3919,2678,3419,1955,4765,4134,5649,3535,1047,2713, # 4736
+1266,5650,1368,4766,2858, 649,3420,3920,2546,2747,1102,2859,2679,5651,5652,2000, # 4752
+5653,1111,3651,2977,5654,2495,3921,3652,2817,1855,3421,3788,5655,5656,3422,2415, # 4768
+2898,3337,3266,3653,5657,2577,5658,3654,2818,4135,1460, 856,5659,3655,5660,2899, # 4784
+2978,5661,2900,3922,5662,4408, 632,2517, 875,3923,1697,3924,2296,5663,5664,4767, # 4800
+3028,1239, 580,4768,4409,5665, 914, 936,2075,1190,4136,1039,2124,5666,5667,5668, # 4816
+5669,3423,1473,5670,1354,4410,3925,4769,2173,3084,4137, 915,3338,4411,4412,3339, # 4832
+1605,1835,5671,2748, 398,3656,4413,3926,4138, 328,1913,2860,4139,3927,1331,4414, # 4848
+3029, 937,4415,5672,3657,4140,4141,3424,2161,4770,3425, 524, 742, 538,3085,1012, # 4864
+5673,5674,3928,2466,5675, 658,1103, 225,3929,5676,5677,4771,5678,4772,5679,3267, # 4880
+1243,5680,4142, 963,2250,4773,5681,2714,3658,3186,5682,5683,2596,2332,5684,4774, # 4896
+5685,5686,5687,3536, 957,3426,2547,2033,1931,2941,2467, 870,2019,3659,1746,2780, # 4912
+2781,2439,2468,5688,3930,5689,3789,3130,3790,3537,3427,3791,5690,1179,3086,5691, # 4928
+3187,2378,4416,3792,2548,3188,3131,2749,4143,5692,3428,1556,2549,2297, 977,2901, # 4944
+2034,4144,1205,3429,5693,1765,3430,3189,2125,1271, 714,1689,4775,3538,5694,2333, # 4960
+3931, 533,4417,3660,2184, 617,5695,2469,3340,3539,2315,5696,5697,3190,5698,5699, # 4976
+3932,1988, 618, 427,2651,3540,3431,5700,5701,1244,1690,5702,2819,4418,4776,5703, # 4992
+3541,4777,5704,2284,1576, 473,3661,4419,3432, 972,5705,3662,5706,3087,5707,5708, # 5008
+4778,4779,5709,3793,4145,4146,5710, 153,4780, 356,5711,1892,2902,4420,2144, 408, # 5024
+ 803,2357,5712,3933,5713,4421,1646,2578,2518,4781,4782,3934,5714,3935,4422,5715, # 5040
+2416,3433, 752,5716,5717,1962,3341,2979,5718, 746,3030,2470,4783,4423,3794, 698, # 5056
+4784,1893,4424,3663,2550,4785,3664,3936,5719,3191,3434,5720,1824,1302,4147,2715, # 5072
+3937,1974,4425,5721,4426,3192, 823,1303,1288,1236,2861,3542,4148,3435, 774,3938, # 5088
+5722,1581,4786,1304,2862,3939,4787,5723,2440,2162,1083,3268,4427,4149,4428, 344, # 5104
+1173, 288,2316, 454,1683,5724,5725,1461,4788,4150,2597,5726,5727,4789, 985, 894, # 5120
+5728,3436,3193,5729,1914,2942,3795,1989,5730,2111,1975,5731,4151,5732,2579,1194, # 5136
+ 425,5733,4790,3194,1245,3796,4429,5734,5735,2863,5736, 636,4791,1856,3940, 760, # 5152
+1800,5737,4430,2212,1508,4792,4152,1894,1684,2298,5738,5739,4793,4431,4432,2213, # 5168
+ 479,5740,5741, 832,5742,4153,2496,5743,2980,2497,3797, 990,3132, 627,1815,2652, # 5184
+4433,1582,4434,2126,2112,3543,4794,5744, 799,4435,3195,5745,4795,2113,1737,3031, # 5200
+1018, 543, 754,4436,3342,1676,4796,4797,4154,4798,1489,5746,3544,5747,2624,2903, # 5216
+4155,5748,5749,2981,5750,5751,5752,5753,3196,4799,4800,2185,1722,5754,3269,3270, # 5232
+1843,3665,1715, 481, 365,1976,1857,5755,5756,1963,2498,4801,5757,2127,3666,3271, # 5248
+ 433,1895,2064,2076,5758, 602,2750,5759,5760,5761,5762,5763,3032,1628,3437,5764, # 5264
+3197,4802,4156,2904,4803,2519,5765,2551,2782,5766,5767,5768,3343,4804,2905,5769, # 5280
+4805,5770,2864,4806,4807,1221,2982,4157,2520,5771,5772,5773,1868,1990,5774,5775, # 5296
+5776,1896,5777,5778,4808,1897,4158, 318,5779,2095,4159,4437,5780,5781, 485,5782, # 5312
+ 938,3941, 553,2680, 116,5783,3942,3667,5784,3545,2681,2783,3438,3344,2820,5785, # 5328
+3668,2943,4160,1747,2944,2983,5786,5787, 207,5788,4809,5789,4810,2521,5790,3033, # 5344
+ 890,3669,3943,5791,1878,3798,3439,5792,2186,2358,3440,1652,5793,5794,5795, 941, # 5360
+2299, 208,3546,4161,2020, 330,4438,3944,2906,2499,3799,4439,4811,5796,5797,5798, # 5376
+)
+# fmt: on

venv/lib/python3.10/site-packages/chardet/big5prober.py

@@ -0,0 +1,47 @@
+######################## BEGIN LICENSE BLOCK ########################
+# The Original Code is Mozilla Communicator client code.
+#
+# The Initial Developer of the Original Code is
+# Netscape Communications Corporation.
+# Portions created by the Initial Developer are Copyright (C) 1998
+# the Initial Developer. All Rights Reserved.
+#
+# Contributor(s):
+#   Mark Pilgrim - port to Python
+#
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
+# 02110-1301  USA
+######################### END LICENSE BLOCK #########################
+
+from .chardistribution import Big5DistributionAnalysis
+from .codingstatemachine import CodingStateMachine
+from .mbcharsetprober import MultiByteCharSetProber
+from .mbcssm import BIG5_SM_MODEL
+
+
+class Big5Prober(MultiByteCharSetProber):
+    def __init__(self) -> None:
+        super().__init__()
+        self.coding_sm = CodingStateMachine(BIG5_SM_MODEL)
+        self.distribution_analyzer = Big5DistributionAnalysis()
+        self.reset()
+
+    @property
+    def charset_name(self) -> str:
+        return "Big5"
+
+    @property
+    def language(self) -> str:
+        return "Chinese"

venv/lib/python3.10/site-packages/chardet/chardistribution.py

@@ -0,0 +1,261 @@
+######################## BEGIN LICENSE BLOCK ########################
+# The Original Code is Mozilla Communicator client code.
+#
+# The Initial Developer of the Original Code is
+# Netscape Communications Corporation.
+# Portions created by the Initial Developer are Copyright (C) 1998
+# the Initial Developer. All Rights Reserved.
+#
+# Contributor(s):
+#   Mark Pilgrim - port to Python
+#
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
+# 02110-1301  USA
+######################### END LICENSE BLOCK #########################
+
+from typing import Tuple, Union
+
+from .big5freq import (
+    BIG5_CHAR_TO_FREQ_ORDER,
+    BIG5_TABLE_SIZE,
+    BIG5_TYPICAL_DISTRIBUTION_RATIO,
+)
+from .euckrfreq import (
+    EUCKR_CHAR_TO_FREQ_ORDER,
+    EUCKR_TABLE_SIZE,
+    EUCKR_TYPICAL_DISTRIBUTION_RATIO,
+)
+from .euctwfreq import (
+    EUCTW_CHAR_TO_FREQ_ORDER,
+    EUCTW_TABLE_SIZE,
+    EUCTW_TYPICAL_DISTRIBUTION_RATIO,
+)
+from .gb2312freq import (
+    GB2312_CHAR_TO_FREQ_ORDER,
+    GB2312_TABLE_SIZE,
+    GB2312_TYPICAL_DISTRIBUTION_RATIO,
+)
+from .jisfreq import (
+    JIS_CHAR_TO_FREQ_ORDER,
+    JIS_TABLE_SIZE,
+    JIS_TYPICAL_DISTRIBUTION_RATIO,
+)
+from .johabfreq import JOHAB_TO_EUCKR_ORDER_TABLE
+
+
+class CharDistributionAnalysis:
+    ENOUGH_DATA_THRESHOLD = 1024
+    SURE_YES = 0.99
+    SURE_NO = 0.01
+    MINIMUM_DATA_THRESHOLD = 3
+
+    def __init__(self) -> None:
+        # Mapping table to get frequency order from char order (get from
+        # GetOrder())
+        self._char_to_freq_order: Tuple[int, ...] = tuple()
+        self._table_size = 0  # Size of above table
+        # This is a constant value which varies from language to language,
+        # used in calculating confidence.  See
+        # http://www.mozilla.org/projects/intl/UniversalCharsetDetection.html
+        # for further detail.
+        self.typical_distribution_ratio = 0.0
+        self._done = False
+        self._total_chars = 0
+        self._freq_chars = 0
+        self.reset()
+
+    def reset(self) -> None:
+        """reset analyser, clear any state"""
+        # If this flag is set to True, detection is done and conclusion has
+        # been made
+        self._done = False
+        self._total_chars = 0  # Total characters encountered
+        # The number of characters whose frequency order is less than 512
+        self._freq_chars = 0
+
+    def feed(self, char: Union[bytes, bytearray], char_len: int) -> None:
+        """feed a character with known length"""
+        if char_len == 2:
+            # we only care about 2-bytes character in our distribution analysis
+            order = self.get_order(char)
+        else:
+            order = -1
+        if order >= 0:
+            self._total_chars += 1
+            # order is valid
+            if order < self._table_size:
+                if 512 > self._char_to_freq_order[order]:
+                    self._freq_chars += 1
+
+    def get_confidence(self) -> float:
+        """return confidence based on existing data"""
+        # if we didn't receive any character in our consideration range,
+        # return negative answer
+        if self._total_chars <= 0 or self._freq_chars <= self.MINIMUM_DATA_THRESHOLD:
+            return self.SURE_NO
+
+        if self._total_chars != self._freq_chars:
+            r = self._freq_chars / (
+                (self._total_chars - self._freq_chars) * self.typical_distribution_ratio
+            )
+            if r < self.SURE_YES:
+                return r
+
+        # normalize confidence (we don't want to be 100% sure)
+        return self.SURE_YES
+
+    def got_enough_data(self) -> bool:
+        # It is not necessary to receive all data to draw conclusion.
+        # For charset detection, certain amount of data is enough
+        return self._total_chars > self.ENOUGH_DATA_THRESHOLD
+
+    def get_order(self, _: Union[bytes, bytearray]) -> int:
+        # We do not handle characters based on the original encoding string,
+        # but convert this encoding string to a number, here called order.
+        # This allows multiple encodings of a language to share one frequency
+        # table.
+        return -1
+
+
+class EUCTWDistributionAnalysis(CharDistributionAnalysis):
+    def __init__(self) -> None:
+        super().__init__()
+        self._char_to_freq_order = EUCTW_CHAR_TO_FREQ_ORDER
+        self._table_size = EUCTW_TABLE_SIZE
+        self.typical_distribution_ratio = EUCTW_TYPICAL_DISTRIBUTION_RATIO
+
+    def get_order(self, byte_str: Union[bytes, bytearray]) -> int:
+        # for euc-TW encoding, we are interested
+        #   first  byte range: 0xc4 -- 0xfe
+        #   second byte range: 0xa1 -- 0xfe
+        # no validation needed here. State machine has done that
+        first_char = byte_str[0]
+        if first_char >= 0xC4:
+            return 94 * (first_char - 0xC4) + byte_str[1] - 0xA1
+        return -1
+
+
+class EUCKRDistributionAnalysis(CharDistributionAnalysis):
+    def __init__(self) -> None:
+        super().__init__()
+        self._char_to_freq_order = EUCKR_CHAR_TO_FREQ_ORDER
+        self._table_size = EUCKR_TABLE_SIZE
+        self.typical_distribution_ratio = EUCKR_TYPICAL_DISTRIBUTION_RATIO
+
+    def get_order(self, byte_str: Union[bytes, bytearray]) -> int:
+        # for euc-KR encoding, we are interested
+        #   first  byte range: 0xb0 -- 0xfe
+        #   second byte range: 0xa1 -- 0xfe
+        # no validation needed here. State machine has done that
+        first_char = byte_str[0]
+        if first_char >= 0xB0:
+            return 94 * (first_char - 0xB0) + byte_str[1] - 0xA1
+        return -1
+
+
+class JOHABDistributionAnalysis(CharDistributionAnalysis):
+    def __init__(self) -> None:
+        super().__init__()
+        self._char_to_freq_order = EUCKR_CHAR_TO_FREQ_ORDER
+        self._table_size = EUCKR_TABLE_SIZE
+        self.typical_distribution_ratio = EUCKR_TYPICAL_DISTRIBUTION_RATIO
+
+    def get_order(self, byte_str: Union[bytes, bytearray]) -> int:
+        first_char = byte_str[0]
+        if 0x88 <= first_char < 0xD4:
+            code = first_char * 256 + byte_str[1]
+            return JOHAB_TO_EUCKR_ORDER_TABLE.get(code, -1)
+        return -1
+
+
+class GB2312DistributionAnalysis(CharDistributionAnalysis):
+    def __init__(self) -> None:
+        super().__init__()
+        self._char_to_freq_order = GB2312_CHAR_TO_FREQ_ORDER
+        self._table_size = GB2312_TABLE_SIZE
+        self.typical_distribution_ratio = GB2312_TYPICAL_DISTRIBUTION_RATIO
+
+    def get_order(self, byte_str: Union[bytes, bytearray]) -> int:
+        # for GB2312 encoding, we are interested
+        #  first  byte range: 0xb0 -- 0xfe
+        #  second byte range: 0xa1 -- 0xfe
+        # no validation needed here. State machine has done that
+        first_char, second_char = byte_str[0], byte_str[1]
+        if (first_char >= 0xB0) and (second_char >= 0xA1):
+            return 94 * (first_char - 0xB0) + second_char - 0xA1
+        return -1
+
+
+class Big5DistributionAnalysis(CharDistributionAnalysis):
+    def __init__(self) -> None:
+        super().__init__()
+        self._char_to_freq_order = BIG5_CHAR_TO_FREQ_ORDER
+        self._table_size = BIG5_TABLE_SIZE
+        self.typical_distribution_ratio = BIG5_TYPICAL_DISTRIBUTION_RATIO
+
+    def get_order(self, byte_str: Union[bytes, bytearray]) -> int:
+        # for big5 encoding, we are interested
+        #   first  byte range: 0xa4 -- 0xfe
+        #   second byte range: 0x40 -- 0x7e , 0xa1 -- 0xfe
+        # no validation needed here. State machine has done that
+        first_char, second_char = byte_str[0], byte_str[1]
+        if first_char >= 0xA4:
+            if second_char >= 0xA1:
+                return 157 * (first_char - 0xA4) + second_char - 0xA1 + 63
+            return 157 * (first_char - 0xA4) + second_char - 0x40
+        return -1
+
+
+class SJISDistributionAnalysis(CharDistributionAnalysis):
+    def __init__(self) -> None:
+        super().__init__()
+        self._char_to_freq_order = JIS_CHAR_TO_FREQ_ORDER
+        self._table_size = JIS_TABLE_SIZE
+        self.typical_distribution_ratio = JIS_TYPICAL_DISTRIBUTION_RATIO
+
+    def get_order(self, byte_str: Union[bytes, bytearray]) -> int:
+        # for sjis encoding, we are interested
+        #   first  byte range: 0x81 -- 0x9f , 0xe0 -- 0xfe
+        #   second byte range: 0x40 -- 0x7e,  0x81 -- oxfe
+        # no validation needed here. State machine has done that
+        first_char, second_char = byte_str[0], byte_str[1]
+        if 0x81 <= first_char <= 0x9F:
+            order = 188 * (first_char - 0x81)
+        elif 0xE0 <= first_char <= 0xEF:
+            order = 188 * (first_char - 0xE0 + 31)
+        else:
+            return -1
+        order = order + second_char - 0x40
+        if second_char > 0x7F:
+            order = -1
+        return order
+
+
+class EUCJPDistributionAnalysis(CharDistributionAnalysis):
+    def __init__(self) -> None:
+        super().__init__()
+        self._char_to_freq_order = JIS_CHAR_TO_FREQ_ORDER
+        self._table_size = JIS_TABLE_SIZE
+        self.typical_distribution_ratio = JIS_TYPICAL_DISTRIBUTION_RATIO
+
+    def get_order(self, byte_str: Union[bytes, bytearray]) -> int:
+        # for euc-JP encoding, we are interested
+        #   first  byte range: 0xa0 -- 0xfe
+        #   second byte range: 0xa1 -- 0xfe
+        # no validation needed here. State machine has done that
+        char = byte_str[0]
+        if char >= 0xA0:
+            return 94 * (char - 0xA1) + byte_str[1] - 0xA1
+        return -1

venv/lib/python3.10/site-packages/chardet/charsetgroupprober.py

@@ -0,0 +1,106 @@
+######################## BEGIN LICENSE BLOCK ########################
+# The Original Code is Mozilla Communicator client code.
+#
+# The Initial Developer of the Original Code is
+# Netscape Communications Corporation.
+# Portions created by the Initial Developer are Copyright (C) 1998
+# the Initial Developer. All Rights Reserved.
+#
+# Contributor(s):
+#   Mark Pilgrim - port to Python
+#
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
+# 02110-1301  USA
+######################### END LICENSE BLOCK #########################
+
+from typing import List, Optional, Union
+
+from .charsetprober import CharSetProber
+from .enums import LanguageFilter, ProbingState
+
+
+class CharSetGroupProber(CharSetProber):
+    def __init__(self, lang_filter: LanguageFilter = LanguageFilter.NONE) -> None:
+        super().__init__(lang_filter=lang_filter)
+        self._active_num = 0
+        self.probers: List[CharSetProber] = []
+        self._best_guess_prober: Optional[CharSetProber] = None
+
+    def reset(self) -> None:
+        super().reset()
+        self._active_num = 0
+        for prober in self.probers:
+            prober.reset()
+            prober.active = True
+            self._active_num += 1
+        self._best_guess_prober = None
+
+    @property
+    def charset_name(self) -> Optional[str]:
+        if not self._best_guess_prober:
+            self.get_confidence()
+            if not self._best_guess_prober:
+                return None
+        return self._best_guess_prober.charset_name
+
+    @property
+    def language(self) -> Optional[str]:
+        if not self._best_guess_prober:
+            self.get_confidence()
+            if not self._best_guess_prober:
+                return None
+        return self._best_guess_prober.language
+
+    def feed(self, byte_str: Union[bytes, bytearray]) -> ProbingState:
+        for prober in self.probers:
+            if not prober.active:
+                continue
+            state = prober.feed(byte_str)
+            if not state:
+                continue
+            if state == ProbingState.FOUND_IT:
+                self._best_guess_prober = prober
+                self._state = ProbingState.FOUND_IT
+                return self.state
+            if state == ProbingState.NOT_ME:
+                prober.active = False
+                self._active_num -= 1
+                if self._active_num <= 0:
+                    self._state = ProbingState.NOT_ME
+                    return self.state
+        return self.state
+
+    def get_confidence(self) -> float:
+        state = self.state
+        if state == ProbingState.FOUND_IT:
+            return 0.99
+        if state == ProbingState.NOT_ME:
+            return 0.01
+        best_conf = 0.0
+        self._best_guess_prober = None
+        for prober in self.probers:
+            if not prober.active:
+                self.logger.debug("%s not active", prober.charset_name)
+                continue
+            conf = prober.get_confidence()
+            self.logger.debug(
+                "%s %s confidence = %s", prober.charset_name, prober.language, conf
+            )
+            if best_conf < conf:
+                best_conf = conf
+                self._best_guess_prober = prober
+        if not self._best_guess_prober:
+            return 0.0
+        return best_conf

venv/lib/python3.10/site-packages/chardet/codingstatemachine.py

@@ -0,0 +1,90 @@
+######################## BEGIN LICENSE BLOCK ########################
+# The Original Code is mozilla.org code.
+#
+# The Initial Developer of the Original Code is
+# Netscape Communications Corporation.
+# Portions created by the Initial Developer are Copyright (C) 1998
+# the Initial Developer. All Rights Reserved.
+#
+# Contributor(s):
+#   Mark Pilgrim - port to Python
+#
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
+# 02110-1301  USA
+######################### END LICENSE BLOCK #########################
+
+import logging
+
+from .codingstatemachinedict import CodingStateMachineDict
+from .enums import MachineState
+
+
+class CodingStateMachine:
+    """
+    A state machine to verify a byte sequence for a particular encoding. For
+    each byte the detector receives, it will feed that byte to every active
+    state machine available, one byte at a time. The state machine changes its
+    state based on its previous state and the byte it receives. There are 3
+    states in a state machine that are of interest to an auto-detector:
+
+    START state: This is the state to start with, or a legal byte sequence
+                 (i.e. a valid code point) for character has been identified.
+
+    ME state:  This indicates that the state machine identified a byte sequence
+               that is specific to the charset it is designed for and that
+               there is no other possible encoding which can contain this byte
+               sequence. This will to lead to an immediate positive answer for
+               the detector.
+
+    ERROR state: This indicates the state machine identified an illegal byte
+                 sequence for that encoding. This will lead to an immediate
+                 negative answer for this encoding. Detector will exclude this
+                 encoding from consideration from here on.
+    """
+
+    def __init__(self, sm: CodingStateMachineDict) -> None:
+        self._model = sm
+        self._curr_byte_pos = 0
+        self._curr_char_len = 0
+        self._curr_state = MachineState.START
+        self.active = True
+        self.logger = logging.getLogger(__name__)
+        self.reset()
+
+    def reset(self) -> None:
+        self._curr_state = MachineState.START
+
+    def next_state(self, c: int) -> int:
+        # for each byte we get its class
+        # if it is first byte, we also get byte length
+        byte_class = self._model["class_table"][c]
+        if self._curr_state == MachineState.START:
+            self._curr_byte_pos = 0
+            self._curr_char_len = self._model["char_len_table"][byte_class]
+        # from byte's class and state_table, we get its next state
+        curr_state = self._curr_state * self._model["class_factor"] + byte_class
+        self._curr_state = self._model["state_table"][curr_state]
+        self._curr_byte_pos += 1
+        return self._curr_state
+
+    def get_current_charlen(self) -> int:
+        return self._curr_char_len
+
+    def get_coding_state_machine(self) -> str:
+        return self._model["name"]
+
+    @property
+    def language(self) -> str:
+        return self._model["language"]

venv/lib/python3.10/site-packages/chardet/codingstatemachinedict.py

@@ -0,0 +1,19 @@
+from typing import TYPE_CHECKING, Tuple
+
+if TYPE_CHECKING:
+    # TypedDict was introduced in Python 3.8.
+    #
+    # TODO: Remove the else block and TYPE_CHECKING check when dropping support
+    # for Python 3.7.
+    from typing import TypedDict
+
+    class CodingStateMachineDict(TypedDict, total=False):
+        class_table: Tuple[int, ...]
+        class_factor: int
+        state_table: Tuple[int, ...]
+        char_len_table: Tuple[int, ...]
+        name: str
+        language: str  # Optional key
+
+else:
+    CodingStateMachineDict = dict

venv/lib/python3.10/site-packages/chardet/enums.py

@@ -0,0 +1,85 @@
+"""
+All of the Enums that are used throughout the chardet package.
+
+:author: Dan Blanchard ([email protected])
+"""
+
+from enum import Enum, Flag
+
+
+class InputState:
+    """
+    This enum represents the different states a universal detector can be in.
+    """
+
+    PURE_ASCII = 0
+    ESC_ASCII = 1
+    HIGH_BYTE = 2
+
+
+class LanguageFilter(Flag):
+    """
+    This enum represents the different language filters we can apply to a
+    ``UniversalDetector``.
+    """
+
+    NONE = 0x00
+    CHINESE_SIMPLIFIED = 0x01
+    CHINESE_TRADITIONAL = 0x02
+    JAPANESE = 0x04
+    KOREAN = 0x08
+    NON_CJK = 0x10
+    ALL = 0x1F
+    CHINESE = CHINESE_SIMPLIFIED | CHINESE_TRADITIONAL
+    CJK = CHINESE | JAPANESE | KOREAN
+
+
+class ProbingState(Enum):
+    """
+    This enum represents the different states a prober can be in.
+    """
+
+    DETECTING = 0
+    FOUND_IT = 1
+    NOT_ME = 2
+
+
+class MachineState:
+    """
+    This enum represents the different states a state machine can be in.
+    """
+
+    START = 0
+    ERROR = 1
+    ITS_ME = 2
+
+
+class SequenceLikelihood:
+    """
+    This enum represents the likelihood of a character following the previous one.
+    """
+
+    NEGATIVE = 0
+    UNLIKELY = 1
+    LIKELY = 2
+    POSITIVE = 3
+
+    @classmethod
+    def get_num_categories(cls) -> int:
+        """:returns: The number of likelihood categories in the enum."""
+        return 4
+
+
+class CharacterCategory:
+    """
+    This enum represents the different categories language models for
+    ``SingleByteCharsetProber`` put characters into.
+
+    Anything less than CONTROL is considered a letter.
+    """
+
+    UNDEFINED = 255
+    LINE_BREAK = 254
+    SYMBOL = 253
+    DIGIT = 252
+    CONTROL = 251

venv/lib/python3.10/site-packages/chardet/escprober.py

@@ -0,0 +1,102 @@
+######################## BEGIN LICENSE BLOCK ########################
+# The Original Code is mozilla.org code.
+#
+# The Initial Developer of the Original Code is
+# Netscape Communications Corporation.
+# Portions created by the Initial Developer are Copyright (C) 1998
+# the Initial Developer. All Rights Reserved.
+#
+# Contributor(s):
+#   Mark Pilgrim - port to Python
+#
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
+# 02110-1301  USA
+######################### END LICENSE BLOCK #########################
+
+from typing import Optional, Union
+
+from .charsetprober import CharSetProber
+from .codingstatemachine import CodingStateMachine
+from .enums import LanguageFilter, MachineState, ProbingState
+from .escsm import (
+    HZ_SM_MODEL,
+    ISO2022CN_SM_MODEL,
+    ISO2022JP_SM_MODEL,
+    ISO2022KR_SM_MODEL,
+)
+
+
+class EscCharSetProber(CharSetProber):
+    """
+    This CharSetProber uses a "code scheme" approach for detecting encodings,
+    whereby easily recognizable escape or shift sequences are relied on to
+    identify these encodings.
+    """
+
+    def __init__(self, lang_filter: LanguageFilter = LanguageFilter.NONE) -> None:
+        super().__init__(lang_filter=lang_filter)
+        self.coding_sm = []
+        if self.lang_filter & LanguageFilter.CHINESE_SIMPLIFIED:
+            self.coding_sm.append(CodingStateMachine(HZ_SM_MODEL))
+            self.coding_sm.append(CodingStateMachine(ISO2022CN_SM_MODEL))
+        if self.lang_filter & LanguageFilter.JAPANESE:
+            self.coding_sm.append(CodingStateMachine(ISO2022JP_SM_MODEL))
+        if self.lang_filter & LanguageFilter.KOREAN:
+            self.coding_sm.append(CodingStateMachine(ISO2022KR_SM_MODEL))
+        self.active_sm_count = 0
+        self._detected_charset: Optional[str] = None
+        self._detected_language: Optional[str] = None
+        self._state = ProbingState.DETECTING
+        self.reset()
+
+    def reset(self) -> None:
+        super().reset()
+        for coding_sm in self.coding_sm:
+            coding_sm.active = True
+            coding_sm.reset()
+        self.active_sm_count = len(self.coding_sm)
+        self._detected_charset = None
+        self._detected_language = None
+
+    @property
+    def charset_name(self) -> Optional[str]:
+        return self._detected_charset
+
+    @property
+    def language(self) -> Optional[str]:
+        return self._detected_language
+
+    def get_confidence(self) -> float:
+        return 0.99 if self._detected_charset else 0.00
+
+    def feed(self, byte_str: Union[bytes, bytearray]) -> ProbingState:
+        for c in byte_str:
+            for coding_sm in self.coding_sm:
+                if not coding_sm.active:
+                    continue
+                coding_state = coding_sm.next_state(c)
+                if coding_state == MachineState.ERROR:
+                    coding_sm.active = False
+                    self.active_sm_count -= 1
+                    if self.active_sm_count <= 0:
+                        self._state = ProbingState.NOT_ME
+                        return self.state
+                elif coding_state == MachineState.ITS_ME:
+                    self._state = ProbingState.FOUND_IT
+                    self._detected_charset = coding_sm.get_coding_state_machine()
+                    self._detected_language = coding_sm.language
+                    return self.state
+
+        return self.state

venv/lib/python3.10/site-packages/chardet/escsm.py

@@ -0,0 +1,261 @@
+######################## BEGIN LICENSE BLOCK ########################
+# The Original Code is mozilla.org code.
+#
+# The Initial Developer of the Original Code is
+# Netscape Communications Corporation.
+# Portions created by the Initial Developer are Copyright (C) 1998
+# the Initial Developer. All Rights Reserved.
+#
+# Contributor(s):
+#   Mark Pilgrim - port to Python
+#
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License,  or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not,  write to the Free Software
+# Foundation,  Inc.,  51 Franklin St,  Fifth Floor,  Boston,  MA
+# 02110-1301  USA
+######################### END LICENSE BLOCK #########################
+
+from .codingstatemachinedict import CodingStateMachineDict
+from .enums import MachineState
+
+# fmt: off
+HZ_CLS = (
+    1, 0, 0, 0, 0, 0, 0, 0,  # 00 - 07
+    0, 0, 0, 0, 0, 0, 0, 0,  # 08 - 0f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 10 - 17
+    0, 0, 0, 1, 0, 0, 0, 0,  # 18 - 1f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 20 - 27
+    0, 0, 0, 0, 0, 0, 0, 0,  # 28 - 2f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 30 - 37
+    0, 0, 0, 0, 0, 0, 0, 0,  # 38 - 3f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 40 - 47
+    0, 0, 0, 0, 0, 0, 0, 0,  # 48 - 4f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 50 - 57
+    0, 0, 0, 0, 0, 0, 0, 0,  # 58 - 5f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 60 - 67
+    0, 0, 0, 0, 0, 0, 0, 0,  # 68 - 6f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 70 - 77
+    0, 0, 0, 4, 0, 5, 2, 0,  # 78 - 7f
+    1, 1, 1, 1, 1, 1, 1, 1,  # 80 - 87
+    1, 1, 1, 1, 1, 1, 1, 1,  # 88 - 8f
+    1, 1, 1, 1, 1, 1, 1, 1,  # 90 - 97
+    1, 1, 1, 1, 1, 1, 1, 1,  # 98 - 9f
+    1, 1, 1, 1, 1, 1, 1, 1,  # a0 - a7
+    1, 1, 1, 1, 1, 1, 1, 1,  # a8 - af
+    1, 1, 1, 1, 1, 1, 1, 1,  # b0 - b7
+    1, 1, 1, 1, 1, 1, 1, 1,  # b8 - bf
+    1, 1, 1, 1, 1, 1, 1, 1,  # c0 - c7
+    1, 1, 1, 1, 1, 1, 1, 1,  # c8 - cf
+    1, 1, 1, 1, 1, 1, 1, 1,  # d0 - d7
+    1, 1, 1, 1, 1, 1, 1, 1,  # d8 - df
+    1, 1, 1, 1, 1, 1, 1, 1,  # e0 - e7
+    1, 1, 1, 1, 1, 1, 1, 1,  # e8 - ef
+    1, 1, 1, 1, 1, 1, 1, 1,  # f0 - f7
+    1, 1, 1, 1, 1, 1, 1, 1,  # f8 - ff
+)
+
+HZ_ST = (
+MachineState.START, MachineState.ERROR,      3, MachineState.START, MachineState.START, MachineState.START, MachineState.ERROR, MachineState.ERROR, # 00-07
+MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ITS_ME, MachineState.ITS_ME, MachineState.ITS_ME, MachineState.ITS_ME, # 08-0f
+MachineState.ITS_ME, MachineState.ITS_ME, MachineState.ERROR, MachineState.ERROR, MachineState.START, MachineState.START,      4, MachineState.ERROR, # 10-17
+     5, MachineState.ERROR,      6, MachineState.ERROR,      5,      5,      4, MachineState.ERROR, # 18-1f
+     4, MachineState.ERROR,      4,      4,      4, MachineState.ERROR,      4, MachineState.ERROR, # 20-27
+     4, MachineState.ITS_ME, MachineState.START, MachineState.START, MachineState.START, MachineState.START, MachineState.START, MachineState.START, # 28-2f
+)
+# fmt: on
+
+HZ_CHAR_LEN_TABLE = (0, 0, 0, 0, 0, 0)
+
+HZ_SM_MODEL: CodingStateMachineDict = {
+    "class_table": HZ_CLS,
+    "class_factor": 6,
+    "state_table": HZ_ST,
+    "char_len_table": HZ_CHAR_LEN_TABLE,
+    "name": "HZ-GB-2312",
+    "language": "Chinese",
+}
+
+# fmt: off
+ISO2022CN_CLS = (
+    2, 0, 0, 0, 0, 0, 0, 0,  # 00 - 07
+    0, 0, 0, 0, 0, 0, 0, 0,  # 08 - 0f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 10 - 17
+    0, 0, 0, 1, 0, 0, 0, 0,  # 18 - 1f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 20 - 27
+    0, 3, 0, 0, 0, 0, 0, 0,  # 28 - 2f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 30 - 37
+    0, 0, 0, 0, 0, 0, 0, 0,  # 38 - 3f
+    0, 0, 0, 4, 0, 0, 0, 0,  # 40 - 47
+    0, 0, 0, 0, 0, 0, 0, 0,  # 48 - 4f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 50 - 57
+    0, 0, 0, 0, 0, 0, 0, 0,  # 58 - 5f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 60 - 67
+    0, 0, 0, 0, 0, 0, 0, 0,  # 68 - 6f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 70 - 77
+    0, 0, 0, 0, 0, 0, 0, 0,  # 78 - 7f
+    2, 2, 2, 2, 2, 2, 2, 2,  # 80 - 87
+    2, 2, 2, 2, 2, 2, 2, 2,  # 88 - 8f
+    2, 2, 2, 2, 2, 2, 2, 2,  # 90 - 97
+    2, 2, 2, 2, 2, 2, 2, 2,  # 98 - 9f
+    2, 2, 2, 2, 2, 2, 2, 2,  # a0 - a7
+    2, 2, 2, 2, 2, 2, 2, 2,  # a8 - af
+    2, 2, 2, 2, 2, 2, 2, 2,  # b0 - b7
+    2, 2, 2, 2, 2, 2, 2, 2,  # b8 - bf
+    2, 2, 2, 2, 2, 2, 2, 2,  # c0 - c7
+    2, 2, 2, 2, 2, 2, 2, 2,  # c8 - cf
+    2, 2, 2, 2, 2, 2, 2, 2,  # d0 - d7
+    2, 2, 2, 2, 2, 2, 2, 2,  # d8 - df
+    2, 2, 2, 2, 2, 2, 2, 2,  # e0 - e7
+    2, 2, 2, 2, 2, 2, 2, 2,  # e8 - ef
+    2, 2, 2, 2, 2, 2, 2, 2,  # f0 - f7
+    2, 2, 2, 2, 2, 2, 2, 2,  # f8 - ff
+)
+
+ISO2022CN_ST = (
+    MachineState.START,      3, MachineState.ERROR, MachineState.START, MachineState.START, MachineState.START, MachineState.START, MachineState.START, # 00-07
+    MachineState.START, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, # 08-0f
+    MachineState.ERROR, MachineState.ERROR, MachineState.ITS_ME, MachineState.ITS_ME, MachineState.ITS_ME, MachineState.ITS_ME, MachineState.ITS_ME, MachineState.ITS_ME, # 10-17
+    MachineState.ITS_ME, MachineState.ITS_ME, MachineState.ITS_ME, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR,      4, MachineState.ERROR, # 18-1f
+    MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ITS_ME, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, # 20-27
+        5,      6, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, # 28-2f
+    MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ITS_ME, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, # 30-37
+    MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ITS_ME, MachineState.ERROR, MachineState.START, # 38-3f
+)
+# fmt: on
+
+ISO2022CN_CHAR_LEN_TABLE = (0, 0, 0, 0, 0, 0, 0, 0, 0)
+
+ISO2022CN_SM_MODEL: CodingStateMachineDict = {
+    "class_table": ISO2022CN_CLS,
+    "class_factor": 9,
+    "state_table": ISO2022CN_ST,
+    "char_len_table": ISO2022CN_CHAR_LEN_TABLE,
+    "name": "ISO-2022-CN",
+    "language": "Chinese",
+}
+
+# fmt: off
+ISO2022JP_CLS = (
+    2, 0, 0, 0, 0, 0, 0, 0,  # 00 - 07
+    0, 0, 0, 0, 0, 0, 2, 2,  # 08 - 0f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 10 - 17
+    0, 0, 0, 1, 0, 0, 0, 0,  # 18 - 1f
+    0, 0, 0, 0, 7, 0, 0, 0,  # 20 - 27
+    3, 0, 0, 0, 0, 0, 0, 0,  # 28 - 2f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 30 - 37
+    0, 0, 0, 0, 0, 0, 0, 0,  # 38 - 3f
+    6, 0, 4, 0, 8, 0, 0, 0,  # 40 - 47
+    0, 9, 5, 0, 0, 0, 0, 0,  # 48 - 4f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 50 - 57
+    0, 0, 0, 0, 0, 0, 0, 0,  # 58 - 5f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 60 - 67
+    0, 0, 0, 0, 0, 0, 0, 0,  # 68 - 6f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 70 - 77
+    0, 0, 0, 0, 0, 0, 0, 0,  # 78 - 7f
+    2, 2, 2, 2, 2, 2, 2, 2,  # 80 - 87
+    2, 2, 2, 2, 2, 2, 2, 2,  # 88 - 8f
+    2, 2, 2, 2, 2, 2, 2, 2,  # 90 - 97
+    2, 2, 2, 2, 2, 2, 2, 2,  # 98 - 9f
+    2, 2, 2, 2, 2, 2, 2, 2,  # a0 - a7
+    2, 2, 2, 2, 2, 2, 2, 2,  # a8 - af
+    2, 2, 2, 2, 2, 2, 2, 2,  # b0 - b7
+    2, 2, 2, 2, 2, 2, 2, 2,  # b8 - bf
+    2, 2, 2, 2, 2, 2, 2, 2,  # c0 - c7
+    2, 2, 2, 2, 2, 2, 2, 2,  # c8 - cf
+    2, 2, 2, 2, 2, 2, 2, 2,  # d0 - d7
+    2, 2, 2, 2, 2, 2, 2, 2,  # d8 - df
+    2, 2, 2, 2, 2, 2, 2, 2,  # e0 - e7
+    2, 2, 2, 2, 2, 2, 2, 2,  # e8 - ef
+    2, 2, 2, 2, 2, 2, 2, 2,  # f0 - f7
+    2, 2, 2, 2, 2, 2, 2, 2,  # f8 - ff
+)
+
+ISO2022JP_ST = (
+    MachineState.START,      3, MachineState.ERROR, MachineState.START, MachineState.START, MachineState.START, MachineState.START, MachineState.START, # 00-07
+    MachineState.START, MachineState.START, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, # 08-0f
+    MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ITS_ME, MachineState.ITS_ME, MachineState.ITS_ME, MachineState.ITS_ME, # 10-17
+    MachineState.ITS_ME, MachineState.ITS_ME, MachineState.ITS_ME, MachineState.ITS_ME, MachineState.ITS_ME, MachineState.ITS_ME, MachineState.ERROR, MachineState.ERROR, # 18-1f
+    MachineState.ERROR,      5, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR,      4, MachineState.ERROR, MachineState.ERROR, # 20-27
+    MachineState.ERROR, MachineState.ERROR, MachineState.ERROR,      6, MachineState.ITS_ME, MachineState.ERROR, MachineState.ITS_ME, MachineState.ERROR, # 28-2f
+    MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ITS_ME, MachineState.ITS_ME, # 30-37
+    MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ITS_ME, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, # 38-3f
+    MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ITS_ME, MachineState.ERROR, MachineState.START, MachineState.START, # 40-47
+)
+# fmt: on
+
+ISO2022JP_CHAR_LEN_TABLE = (0, 0, 0, 0, 0, 0, 0, 0, 0, 0)
+
+ISO2022JP_SM_MODEL: CodingStateMachineDict = {
+    "class_table": ISO2022JP_CLS,
+    "class_factor": 10,
+    "state_table": ISO2022JP_ST,
+    "char_len_table": ISO2022JP_CHAR_LEN_TABLE,
+    "name": "ISO-2022-JP",
+    "language": "Japanese",
+}
+
+# fmt: off
+ISO2022KR_CLS = (
+    2, 0, 0, 0, 0, 0, 0, 0,  # 00 - 07
+    0, 0, 0, 0, 0, 0, 0, 0,  # 08 - 0f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 10 - 17
+    0, 0, 0, 1, 0, 0, 0, 0,  # 18 - 1f
+    0, 0, 0, 0, 3, 0, 0, 0,  # 20 - 27
+    0, 4, 0, 0, 0, 0, 0, 0,  # 28 - 2f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 30 - 37
+    0, 0, 0, 0, 0, 0, 0, 0,  # 38 - 3f
+    0, 0, 0, 5, 0, 0, 0, 0,  # 40 - 47
+    0, 0, 0, 0, 0, 0, 0, 0,  # 48 - 4f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 50 - 57
+    0, 0, 0, 0, 0, 0, 0, 0,  # 58 - 5f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 60 - 67
+    0, 0, 0, 0, 0, 0, 0, 0,  # 68 - 6f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 70 - 77
+    0, 0, 0, 0, 0, 0, 0, 0,  # 78 - 7f
+    2, 2, 2, 2, 2, 2, 2, 2,  # 80 - 87
+    2, 2, 2, 2, 2, 2, 2, 2,  # 88 - 8f
+    2, 2, 2, 2, 2, 2, 2, 2,  # 90 - 97
+    2, 2, 2, 2, 2, 2, 2, 2,  # 98 - 9f
+    2, 2, 2, 2, 2, 2, 2, 2,  # a0 - a7
+    2, 2, 2, 2, 2, 2, 2, 2,  # a8 - af
+    2, 2, 2, 2, 2, 2, 2, 2,  # b0 - b7
+    2, 2, 2, 2, 2, 2, 2, 2,  # b8 - bf
+    2, 2, 2, 2, 2, 2, 2, 2,  # c0 - c7
+    2, 2, 2, 2, 2, 2, 2, 2,  # c8 - cf
+    2, 2, 2, 2, 2, 2, 2, 2,  # d0 - d7
+    2, 2, 2, 2, 2, 2, 2, 2,  # d8 - df
+    2, 2, 2, 2, 2, 2, 2, 2,  # e0 - e7
+    2, 2, 2, 2, 2, 2, 2, 2,  # e8 - ef
+    2, 2, 2, 2, 2, 2, 2, 2,  # f0 - f7
+    2, 2, 2, 2, 2, 2, 2, 2,  # f8 - ff
+)
+
+ISO2022KR_ST = (
+    MachineState.START,      3, MachineState.ERROR, MachineState.START, MachineState.START, MachineState.START, MachineState.ERROR, MachineState.ERROR, # 00-07
+    MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ITS_ME, MachineState.ITS_ME, MachineState.ITS_ME, MachineState.ITS_ME, # 08-0f
+    MachineState.ITS_ME, MachineState.ITS_ME, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR,      4, MachineState.ERROR, MachineState.ERROR, # 10-17
+    MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR,      5, MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, # 18-1f
+    MachineState.ERROR, MachineState.ERROR, MachineState.ERROR, MachineState.ITS_ME, MachineState.START, MachineState.START, MachineState.START, MachineState.START, # 20-27
+)
+# fmt: on
+
+ISO2022KR_CHAR_LEN_TABLE = (0, 0, 0, 0, 0, 0)
+
+ISO2022KR_SM_MODEL: CodingStateMachineDict = {
+    "class_table": ISO2022KR_CLS,
+    "class_factor": 6,
+    "state_table": ISO2022KR_ST,
+    "char_len_table": ISO2022KR_CHAR_LEN_TABLE,
+    "name": "ISO-2022-KR",
+    "language": "Korean",
+}

venv/lib/python3.10/site-packages/chardet/eucjpprober.py

@@ -0,0 +1,102 @@
+######################## BEGIN LICENSE BLOCK ########################
+# The Original Code is mozilla.org code.
+#
+# The Initial Developer of the Original Code is
+# Netscape Communications Corporation.
+# Portions created by the Initial Developer are Copyright (C) 1998
+# the Initial Developer. All Rights Reserved.
+#
+# Contributor(s):
+#   Mark Pilgrim - port to Python
+#
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
+# 02110-1301  USA
+######################### END LICENSE BLOCK #########################
+
+from typing import Union
+
+from .chardistribution import EUCJPDistributionAnalysis
+from .codingstatemachine import CodingStateMachine
+from .enums import MachineState, ProbingState
+from .jpcntx import EUCJPContextAnalysis
+from .mbcharsetprober import MultiByteCharSetProber
+from .mbcssm import EUCJP_SM_MODEL
+
+
+class EUCJPProber(MultiByteCharSetProber):
+    def __init__(self) -> None:
+        super().__init__()
+        self.coding_sm = CodingStateMachine(EUCJP_SM_MODEL)
+        self.distribution_analyzer = EUCJPDistributionAnalysis()
+        self.context_analyzer = EUCJPContextAnalysis()
+        self.reset()
+
+    def reset(self) -> None:
+        super().reset()
+        self.context_analyzer.reset()
+
+    @property
+    def charset_name(self) -> str:
+        return "EUC-JP"
+
+    @property
+    def language(self) -> str:
+        return "Japanese"
+
+    def feed(self, byte_str: Union[bytes, bytearray]) -> ProbingState:
+        assert self.coding_sm is not None
+        assert self.distribution_analyzer is not None
+
+        for i, byte in enumerate(byte_str):
+            # PY3K: byte_str is a byte array, so byte is an int, not a byte
+            coding_state = self.coding_sm.next_state(byte)
+            if coding_state == MachineState.ERROR:
+                self.logger.debug(
+                    "%s %s prober hit error at byte %s",
+                    self.charset_name,
+                    self.language,
+                    i,
+                )
+                self._state = ProbingState.NOT_ME
+                break
+            if coding_state == MachineState.ITS_ME:
+                self._state = ProbingState.FOUND_IT
+                break
+            if coding_state == MachineState.START:
+                char_len = self.coding_sm.get_current_charlen()
+                if i == 0:
+                    self._last_char[1] = byte
+                    self.context_analyzer.feed(self._last_char, char_len)
+                    self.distribution_analyzer.feed(self._last_char, char_len)
+                else:
+                    self.context_analyzer.feed(byte_str[i - 1 : i + 1], char_len)
+                    self.distribution_analyzer.feed(byte_str[i - 1 : i + 1], char_len)
+
+        self._last_char[0] = byte_str[-1]
+
+        if self.state == ProbingState.DETECTING:
+            if self.context_analyzer.got_enough_data() and (
+                self.get_confidence() > self.SHORTCUT_THRESHOLD
+            ):
+                self._state = ProbingState.FOUND_IT
+
+        return self.state
+
+    def get_confidence(self) -> float:
+        assert self.distribution_analyzer is not None
+
+        context_conf = self.context_analyzer.get_confidence()
+        distrib_conf = self.distribution_analyzer.get_confidence()
+        return max(context_conf, distrib_conf)

venv/lib/python3.10/site-packages/chardet/euckrfreq.py

@@ -0,0 +1,196 @@
+######################## BEGIN LICENSE BLOCK ########################
+# The Original Code is Mozilla Communicator client code.
+#
+# The Initial Developer of the Original Code is
+# Netscape Communications Corporation.
+# Portions created by the Initial Developer are Copyright (C) 1998
+# the Initial Developer. All Rights Reserved.
+#
+# Contributor(s):
+#   Mark Pilgrim - port to Python
+#
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
+# 02110-1301  USA
+######################### END LICENSE BLOCK #########################
+
+# Sampling from about 20M text materials include literature and computer technology
+
+# 128  --> 0.79
+# 256  --> 0.92
+# 512  --> 0.986
+# 1024 --> 0.99944
+# 2048 --> 0.99999
+#
+# Idea Distribution Ratio = 0.98653 / (1-0.98653) = 73.24
+# Random Distribution Ration = 512 / (2350-512) = 0.279.
+#
+# Typical Distribution Ratio
+
+EUCKR_TYPICAL_DISTRIBUTION_RATIO = 6.0
+
+EUCKR_TABLE_SIZE = 2352
+
+# Char to FreqOrder table ,
+# fmt: off
+EUCKR_CHAR_TO_FREQ_ORDER = (
+  13, 130, 120,1396, 481,1719,1720, 328, 609, 212,1721, 707, 400, 299,1722,  87,
+1397,1723, 104, 536,1117,1203,1724,1267, 685,1268, 508,1725,1726,1727,1728,1398,
+1399,1729,1730,1731, 141, 621, 326,1057, 368,1732, 267, 488,  20,1733,1269,1734,
+ 945,1400,1735,  47, 904,1270,1736,1737, 773, 248,1738, 409, 313, 786, 429,1739,
+ 116, 987, 813,1401, 683,  75,1204, 145,1740,1741,1742,1743,  16, 847, 667, 622,
+ 708,1744,1745,1746, 966, 787, 304, 129,1747,  60, 820, 123, 676,1748,1749,1750,
+1751, 617,1752, 626,1753,1754,1755,1756, 653,1757,1758,1759,1760,1761,1762, 856,
+ 344,1763,1764,1765,1766,  89, 401, 418, 806, 905, 848,1767,1768,1769, 946,1205,
+ 709,1770,1118,1771, 241,1772,1773,1774,1271,1775, 569,1776, 999,1777,1778,1779,
+1780, 337, 751,1058,  28, 628, 254,1781, 177, 906, 270, 349, 891,1079,1782,  19,
+1783, 379,1784, 315,1785, 629, 754,1402, 559,1786, 636, 203,1206,1787, 710, 567,
+1788, 935, 814,1789,1790,1207, 766, 528,1791,1792,1208,1793,1794,1795,1796,1797,
+1403,1798,1799, 533,1059,1404,1405,1156,1406, 936, 884,1080,1800, 351,1801,1802,
+1803,1804,1805, 801,1806,1807,1808,1119,1809,1157, 714, 474,1407,1810, 298, 899,
+ 885,1811,1120, 802,1158,1812, 892,1813,1814,1408, 659,1815,1816,1121,1817,1818,
+1819,1820,1821,1822, 319,1823, 594, 545,1824, 815, 937,1209,1825,1826, 573,1409,
+1022,1827,1210,1828,1829,1830,1831,1832,1833, 556, 722, 807,1122,1060,1834, 697,
+1835, 900, 557, 715,1836,1410, 540,1411, 752,1159, 294, 597,1211, 976, 803, 770,
+1412,1837,1838,  39, 794,1413, 358,1839, 371, 925,1840, 453, 661, 788, 531, 723,
+ 544,1023,1081, 869,  91,1841, 392, 430, 790, 602,1414, 677,1082, 457,1415,1416,
+1842,1843, 475, 327,1024,1417, 795, 121,1844, 733, 403,1418,1845,1846,1847, 300,
+ 119, 711,1212, 627,1848,1272, 207,1849,1850, 796,1213, 382,1851, 519,1852,1083,
+ 893,1853,1854,1855, 367, 809, 487, 671,1856, 663,1857,1858, 956, 471, 306, 857,
+1859,1860,1160,1084,1861,1862,1863,1864,1865,1061,1866,1867,1868,1869,1870,1871,
+ 282,  96, 574,1872, 502,1085,1873,1214,1874, 907,1875,1876, 827, 977,1419,1420,
+1421, 268,1877,1422,1878,1879,1880, 308,1881,   2, 537,1882,1883,1215,1884,1885,
+ 127, 791,1886,1273,1423,1887,  34, 336, 404, 643,1888, 571, 654, 894, 840,1889,
+   0, 886,1274, 122, 575, 260, 908, 938,1890,1275, 410, 316,1891,1892, 100,1893,
+1894,1123,  48,1161,1124,1025,1895, 633, 901,1276,1896,1897, 115, 816,1898, 317,
+1899, 694,1900, 909, 734,1424, 572, 866,1425, 691,  85, 524,1010, 543, 394, 841,
+1901,1902,1903,1026,1904,1905,1906,1907,1908,1909,  30, 451, 651, 988, 310,1910,
+1911,1426, 810,1216,  93,1912,1913,1277,1217,1914, 858, 759,  45,  58, 181, 610,
+ 269,1915,1916, 131,1062, 551, 443,1000, 821,1427, 957, 895,1086,1917,1918, 375,
+1919, 359,1920, 687,1921, 822,1922, 293,1923,1924,  40, 662, 118, 692,  29, 939,
+ 887, 640, 482, 174,1925,  69,1162, 728,1428, 910,1926,1278,1218,1279, 386, 870,
+ 217, 854,1163, 823,1927,1928,1929,1930, 834,1931,  78,1932, 859,1933,1063,1934,
+1935,1936,1937, 438,1164, 208, 595,1938,1939,1940,1941,1219,1125,1942, 280, 888,
+1429,1430,1220,1431,1943,1944,1945,1946,1947,1280, 150, 510,1432,1948,1949,1950,
+1951,1952,1953,1954,1011,1087,1955,1433,1043,1956, 881,1957, 614, 958,1064,1065,
+1221,1958, 638,1001, 860, 967, 896,1434, 989, 492, 553,1281,1165,1959,1282,1002,
+1283,1222,1960,1961,1962,1963,  36, 383, 228, 753, 247, 454,1964, 876, 678,1965,
+1966,1284, 126, 464, 490, 835, 136, 672, 529, 940,1088,1435, 473,1967,1968, 467,
+  50, 390, 227, 587, 279, 378, 598, 792, 968, 240, 151, 160, 849, 882,1126,1285,
+ 639,1044, 133, 140, 288, 360, 811, 563,1027, 561, 142, 523,1969,1970,1971,   7,
+ 103, 296, 439, 407, 506, 634, 990,1972,1973,1974,1975, 645,1976,1977,1978,1979,
+1980,1981, 236,1982,1436,1983,1984,1089, 192, 828, 618, 518,1166, 333,1127,1985,
+ 818,1223,1986,1987,1988,1989,1990,1991,1992,1993, 342,1128,1286, 746, 842,1994,
+1995, 560, 223,1287,  98,   8, 189, 650, 978,1288,1996,1437,1997,  17, 345, 250,
+ 423, 277, 234, 512, 226,  97, 289,  42, 167,1998, 201,1999,2000, 843, 836, 824,
+ 532, 338, 783,1090, 182, 576, 436,1438,1439, 527, 500,2001, 947, 889,2002,2003,
+2004,2005, 262, 600, 314, 447,2006, 547,2007, 693, 738,1129,2008,  71,1440, 745,
+ 619, 688,2009, 829,2010,2011, 147,2012,  33, 948,2013,2014,  74, 224,2015,  61,
+ 191, 918, 399, 637,2016,1028,1130, 257, 902,2017,2018,2019,2020,2021,2022,2023,
+2024,2025,2026, 837,2027,2028,2029,2030, 179, 874, 591,  52, 724, 246,2031,2032,
+2033,2034,1167, 969,2035,1289, 630, 605, 911,1091,1168,2036,2037,2038,1441, 912,
+2039, 623,2040,2041, 253,1169,1290,2042,1442, 146, 620, 611, 577, 433,2043,1224,
+ 719,1170, 959, 440, 437, 534,  84, 388, 480,1131, 159, 220, 198, 679,2044,1012,
+ 819,1066,1443, 113,1225, 194, 318,1003,1029,2045,2046,2047,2048,1067,2049,2050,
+2051,2052,2053,  59, 913, 112,2054, 632,2055, 455, 144, 739,1291,2056, 273, 681,
+ 499,2057, 448,2058,2059, 760,2060,2061, 970, 384, 169, 245,1132,2062,2063, 414,
+1444,2064,2065,  41, 235,2066, 157, 252, 877, 568, 919, 789, 580,2067, 725,2068,
+2069,1292,2070,2071,1445,2072,1446,2073,2074,  55, 588,  66,1447, 271,1092,2075,
+1226,2076, 960,1013, 372,2077,2078,2079,2080,2081,1293,2082,2083,2084,2085, 850,
+2086,2087,2088,2089,2090, 186,2091,1068, 180,2092,2093,2094, 109,1227, 522, 606,
+2095, 867,1448,1093, 991,1171, 926, 353,1133,2096, 581,2097,2098,2099,1294,1449,
+1450,2100, 596,1172,1014,1228,2101,1451,1295,1173,1229,2102,2103,1296,1134,1452,
+ 949,1135,2104,2105,1094,1453,1454,1455,2106,1095,2107,2108,2109,2110,2111,2112,
+2113,2114,2115,2116,2117, 804,2118,2119,1230,1231, 805,1456, 405,1136,2120,2121,
+2122,2123,2124, 720, 701,1297, 992,1457, 927,1004,2125,2126,2127,2128,2129,2130,
+  22, 417,2131, 303,2132, 385,2133, 971, 520, 513,2134,1174,  73,1096, 231, 274,
+ 962,1458, 673,2135,1459,2136, 152,1137,2137,2138,2139,2140,1005,1138,1460,1139,
+2141,2142,2143,2144,  11, 374, 844,2145, 154,1232,  46,1461,2146, 838, 830, 721,
+1233, 106,2147,  90, 428, 462, 578, 566,1175, 352,2148,2149, 538,1234, 124,1298,
+2150,1462, 761, 565,2151, 686,2152, 649,2153,  72, 173,2154, 460, 415,2155,1463,
+2156,1235, 305,2157,2158,2159,2160,2161,2162, 579,2163,2164,2165,2166,2167, 747,
+2168,2169,2170,2171,1464, 669,2172,2173,2174,2175,2176,1465,2177,  23, 530, 285,
+2178, 335, 729,2179, 397,2180,2181,2182,1030,2183,2184, 698,2185,2186, 325,2187,
+2188, 369,2189, 799,1097,1015, 348,2190,1069, 680,2191, 851,1466,2192,2193,  10,
+2194, 613, 424,2195, 979, 108, 449, 589,  27, 172,  81,1031,  80, 774, 281, 350,
+1032, 525, 301, 582,1176,2196, 674,1045,2197,2198,1467, 730, 762,2199,2200,2201,
+2202,1468,2203, 993,2204,2205, 266,1070, 963,1140,2206,2207,2208, 664,1098, 972,
+2209,2210,2211,1177,1469,1470, 871,2212,2213,2214,2215,2216,1471,2217,2218,2219,
+2220,2221,2222,2223,2224,2225,2226,2227,1472,1236,2228,2229,2230,2231,2232,2233,
+2234,2235,1299,2236,2237, 200,2238, 477, 373,2239,2240, 731, 825, 777,2241,2242,
+2243, 521, 486, 548,2244,2245,2246,1473,1300,  53, 549, 137, 875,  76, 158,2247,
+1301,1474, 469, 396,1016, 278, 712,2248, 321, 442, 503, 767, 744, 941,1237,1178,
+1475,2249,  82, 178,1141,1179, 973,2250,1302,2251, 297,2252,2253, 570,2254,2255,
+2256,  18, 450, 206,2257, 290, 292,1142,2258, 511, 162,  99, 346, 164, 735,2259,
+1476,1477,   4, 554, 343, 798,1099,2260,1100,2261,  43, 171,1303, 139, 215,2262,
+2263, 717, 775,2264,1033, 322, 216,2265, 831,2266, 149,2267,1304,2268,2269, 702,
+1238, 135, 845, 347, 309,2270, 484,2271, 878, 655, 238,1006,1478,2272,  67,2273,
+ 295,2274,2275, 461,2276, 478, 942, 412,2277,1034,2278,2279,2280, 265,2281, 541,
+2282,2283,2284,2285,2286,  70, 852,1071,2287,2288,2289,2290,  21,  56, 509, 117,
+ 432,2291,2292, 331, 980, 552,1101, 148, 284, 105, 393,1180,1239, 755,2293, 187,
+2294,1046,1479,2295, 340,2296,  63,1047, 230,2297,2298,1305, 763,1306, 101, 800,
+ 808, 494,2299,2300,2301, 903,2302,  37,1072,  14,   5,2303,  79, 675,2304, 312,
+2305,2306,2307,2308,2309,1480,   6,1307,2310,2311,2312,   1, 470,  35,  24, 229,
+2313, 695, 210,  86, 778,  15, 784, 592, 779,  32,  77, 855, 964,2314, 259,2315,
+ 501, 380,2316,2317,  83, 981, 153, 689,1308,1481,1482,1483,2318,2319, 716,1484,
+2320,2321,2322,2323,2324,2325,1485,2326,2327, 128,  57,  68, 261,1048, 211, 170,
+1240,  31,2328,  51, 435, 742,2329,2330,2331, 635,2332, 264, 456,2333,2334,2335,
+ 425,2336,1486, 143, 507, 263, 943,2337, 363, 920,1487, 256,1488,1102, 243, 601,
+1489,2338,2339,2340,2341,2342,2343,2344, 861,2345,2346,2347,2348,2349,2350, 395,
+2351,1490,1491,  62, 535, 166, 225,2352,2353, 668, 419,1241, 138, 604, 928,2354,
+1181,2355,1492,1493,2356,2357,2358,1143,2359, 696,2360, 387, 307,1309, 682, 476,
+2361,2362, 332,  12, 222, 156,2363, 232,2364, 641, 276, 656, 517,1494,1495,1035,
+ 416, 736,1496,2365,1017, 586,2366,2367,2368,1497,2369, 242,2370,2371,2372,1498,
+2373, 965, 713,2374,2375,2376,2377, 740, 982,1499, 944,1500,1007,2378,2379,1310,
+1501,2380,2381,2382, 785, 329,2383,2384,1502,2385,2386,2387, 932,2388,1503,2389,
+2390,2391,2392,1242,2393,2394,2395,2396,2397, 994, 950,2398,2399,2400,2401,1504,
+1311,2402,2403,2404,2405,1049, 749,2406,2407, 853, 718,1144,1312,2408,1182,1505,
+2409,2410, 255, 516, 479, 564, 550, 214,1506,1507,1313, 413, 239, 444, 339,1145,
+1036,1508,1509,1314,1037,1510,1315,2411,1511,2412,2413,2414, 176, 703, 497, 624,
+ 593, 921, 302,2415, 341, 165,1103,1512,2416,1513,2417,2418,2419, 376,2420, 700,
+2421,2422,2423, 258, 768,1316,2424,1183,2425, 995, 608,2426,2427,2428,2429, 221,
+2430,2431,2432,2433,2434,2435,2436,2437, 195, 323, 726, 188, 897, 983,1317, 377,
+ 644,1050, 879,2438, 452,2439,2440,2441,2442,2443,2444, 914,2445,2446,2447,2448,
+ 915, 489,2449,1514,1184,2450,2451, 515,  64, 427, 495,2452, 583,2453, 483, 485,
+1038, 562, 213,1515, 748, 666,2454,2455,2456,2457, 334,2458, 780, 996,1008, 705,
+1243,2459,2460,2461,2462,2463, 114,2464, 493,1146, 366, 163,1516, 961,1104,2465,
+ 291,2466,1318,1105,2467,1517, 365,2468, 355, 951,1244,2469,1319,2470, 631,2471,
+2472, 218,1320, 364, 320, 756,1518,1519,1321,1520,1322,2473,2474,2475,2476, 997,
+2477,2478,2479,2480, 665,1185,2481, 916,1521,2482,2483,2484, 584, 684,2485,2486,
+ 797,2487,1051,1186,2488,2489,2490,1522,2491,2492, 370,2493,1039,1187,  65,2494,
+ 434, 205, 463,1188,2495, 125, 812, 391, 402, 826, 699, 286, 398, 155, 781, 771,
+ 585,2496, 590, 505,1073,2497, 599, 244, 219, 917,1018, 952, 646,1523,2498,1323,
+2499,2500,  49, 984, 354, 741,2501, 625,2502,1324,2503,1019, 190, 357, 757, 491,
+  95, 782, 868,2504,2505,2506,2507,2508,2509, 134,1524,1074, 422,1525, 898,2510,
+ 161,2511,2512,2513,2514, 769,2515,1526,2516,2517, 411,1325,2518, 472,1527,2519,
+2520,2521,2522,2523,2524, 985,2525,2526,2527,2528,2529,2530, 764,2531,1245,2532,
+2533,  25, 204, 311,2534, 496,2535,1052,2536,2537,2538,2539,2540,2541,2542, 199,
+ 704, 504, 468, 758, 657,1528, 196,  44, 839,1246, 272, 750,2543, 765, 862,2544,
+2545,1326,2546, 132, 615, 933,2547, 732,2548,2549,2550,1189,1529,2551, 283,1247,
+1053, 607, 929,2552,2553,2554, 930, 183, 872, 616,1040,1147,2555,1148,1020, 441,
+ 249,1075,2556,2557,2558, 466, 743,2559,2560,2561,  92, 514, 426, 420, 526,2562,
+2563,2564,2565,2566,2567,2568, 185,2569,2570,2571,2572, 776,1530, 658,2573, 362,
+2574, 361, 922,1076, 793,2575,2576,2577,2578,2579,2580,1531, 251,2581,2582,2583,
+2584,1532,  54, 612, 237,1327,2585,2586, 275, 408, 647, 111,2587,1533,1106, 465,
+   3, 458,   9,  38,2588, 107, 110, 890, 209,  26, 737, 498,2589,1534,2590, 431,
+ 202,  88,1535, 356, 287,1107, 660,1149,2591, 381,1536, 986,1150, 445,1248,1151,
+ 974,2592,2593, 846,2594, 446, 953, 184,1249,1250, 727,2595, 923, 193, 883,2596,
+2597,2598, 102, 324, 539, 817,2599, 421,1041,2600, 832,2601,  94, 175, 197, 406,
+2602, 459,2603,2604,2605,2606,2607, 330, 555,2608,2609,2610, 706,1108, 389,2611,
+2612,2613,2614, 233,2615, 833, 558, 931, 954,1251,2616,2617,1537, 546,2618,2619,
+1009,2620,2621,2622,1538, 690,1328,2623, 955,2624,1539,2625,2626, 772,2627,2628,
+2629,2630,2631, 924, 648, 863, 603,2632,2633, 934,1540, 864, 865,2634, 642,1042,
+ 670,1190,2635,2636,2637,2638, 168,2639, 652, 873, 542,1054,1541,2640,2641,2642,  # 512, 256
+)
+# fmt: on

venv/lib/python3.10/site-packages/chardet/gb2312freq.py

@@ -0,0 +1,284 @@
+######################## BEGIN LICENSE BLOCK ########################
+# The Original Code is Mozilla Communicator client code.
+#
+# The Initial Developer of the Original Code is
+# Netscape Communications Corporation.
+# Portions created by the Initial Developer are Copyright (C) 1998
+# the Initial Developer. All Rights Reserved.
+#
+# Contributor(s):
+#   Mark Pilgrim - port to Python
+#
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
+# 02110-1301  USA
+######################### END LICENSE BLOCK #########################
+
+# GB2312 most frequently used character table
+#
+# Char to FreqOrder table , from hz6763
+
+# 512  --> 0.79  -- 0.79
+# 1024 --> 0.92  -- 0.13
+# 2048 --> 0.98  -- 0.06
+# 6768 --> 1.00  -- 0.02
+#
+# Ideal Distribution Ratio = 0.79135/(1-0.79135) = 3.79
+# Random Distribution Ration = 512 / (3755 - 512) = 0.157
+#
+# Typical Distribution Ratio about 25% of Ideal one, still much higher that RDR
+
+GB2312_TYPICAL_DISTRIBUTION_RATIO = 0.9
+
+GB2312_TABLE_SIZE = 3760
+
+# fmt: off
+GB2312_CHAR_TO_FREQ_ORDER = (
+1671, 749,1443,2364,3924,3807,2330,3921,1704,3463,2691,1511,1515, 572,3191,2205,
+2361, 224,2558, 479,1711, 963,3162, 440,4060,1905,2966,2947,3580,2647,3961,3842,
+2204, 869,4207, 970,2678,5626,2944,2956,1479,4048, 514,3595, 588,1346,2820,3409,
+ 249,4088,1746,1873,2047,1774, 581,1813, 358,1174,3590,1014,1561,4844,2245, 670,
+1636,3112, 889,1286, 953, 556,2327,3060,1290,3141, 613, 185,3477,1367, 850,3820,
+1715,2428,2642,2303,2732,3041,2562,2648,3566,3946,1349, 388,3098,2091,1360,3585,
+ 152,1687,1539, 738,1559,  59,1232,2925,2267,1388,1249,1741,1679,2960, 151,1566,
+1125,1352,4271, 924,4296, 385,3166,4459, 310,1245,2850,  70,3285,2729,3534,3575,
+2398,3298,3466,1960,2265, 217,3647, 864,1909,2084,4401,2773,1010,3269,5152, 853,
+3051,3121,1244,4251,1895, 364,1499,1540,2313,1180,3655,2268, 562, 715,2417,3061,
+ 544, 336,3768,2380,1752,4075, 950, 280,2425,4382, 183,2759,3272, 333,4297,2155,
+1688,2356,1444,1039,4540, 736,1177,3349,2443,2368,2144,2225, 565, 196,1482,3406,
+ 927,1335,4147, 692, 878,1311,1653,3911,3622,1378,4200,1840,2969,3149,2126,1816,
+2534,1546,2393,2760, 737,2494,  13, 447, 245,2747,  38,2765,2129,2589,1079, 606,
+ 360, 471,3755,2890, 404, 848, 699,1785,1236, 370,2221,1023,3746,2074,2026,2023,
+2388,1581,2119, 812,1141,3091,2536,1519, 804,2053, 406,1596,1090, 784, 548,4414,
+1806,2264,2936,1100, 343,4114,5096, 622,3358, 743,3668,1510,1626,5020,3567,2513,
+3195,4115,5627,2489,2991,  24,2065,2697,1087,2719,  48,1634, 315,  68, 985,2052,
+ 198,2239,1347,1107,1439, 597,2366,2172, 871,3307, 919,2487,2790,1867, 236,2570,
+1413,3794, 906,3365,3381,1701,1982,1818,1524,2924,1205, 616,2586,2072,2004, 575,
+ 253,3099,  32,1365,1182, 197,1714,2454,1201, 554,3388,3224,2748, 756,2587, 250,
+2567,1507,1517,3529,1922,2761,2337,3416,1961,1677,2452,2238,3153, 615, 911,1506,
+1474,2495,1265,1906,2749,3756,3280,2161, 898,2714,1759,3450,2243,2444, 563,  26,
+3286,2266,3769,3344,2707,3677, 611,1402, 531,1028,2871,4548,1375, 261,2948, 835,
+1190,4134, 353, 840,2684,1900,3082,1435,2109,1207,1674, 329,1872,2781,4055,2686,
+2104, 608,3318,2423,2957,2768,1108,3739,3512,3271,3985,2203,1771,3520,1418,2054,
+1681,1153, 225,1627,2929, 162,2050,2511,3687,1954, 124,1859,2431,1684,3032,2894,
+ 585,4805,3969,2869,2704,2088,2032,2095,3656,2635,4362,2209, 256, 518,2042,2105,
+3777,3657, 643,2298,1148,1779, 190, 989,3544, 414,  11,2135,2063,2979,1471, 403,
+3678, 126, 770,1563, 671,2499,3216,2877, 600,1179, 307,2805,4937,1268,1297,2694,
+ 252,4032,1448,1494,1331,1394, 127,2256, 222,1647,1035,1481,3056,1915,1048, 873,
+3651, 210,  33,1608,2516, 200,1520, 415, 102,   0,3389,1287, 817,  91,3299,2940,
+ 836,1814, 549,2197,1396,1669,2987,3582,2297,2848,4528,1070, 687,  20,1819, 121,
+1552,1364,1461,1968,2617,3540,2824,2083, 177, 948,4938,2291, 110,4549,2066, 648,
+3359,1755,2110,2114,4642,4845,1693,3937,3308,1257,1869,2123, 208,1804,3159,2992,
+2531,2549,3361,2418,1350,2347,2800,2568,1291,2036,2680,  72, 842,1990, 212,1233,
+1154,1586,  75,2027,3410,4900,1823,1337,2710,2676, 728,2810,1522,3026,4995, 157,
+ 755,1050,4022, 710, 785,1936,2194,2085,1406,2777,2400, 150,1250,4049,1206, 807,
+1910, 534, 529,3309,1721,1660, 274,  39,2827, 661,2670,1578, 925,3248,3815,1094,
+4278,4901,4252,  41,1150,3747,2572,2227,4501,3658,4902,3813,3357,3617,2884,2258,
+ 887, 538,4187,3199,1294,2439,3042,2329,2343,2497,1255, 107, 543,1527, 521,3478,
+3568, 194,5062,  15, 961,3870,1241,1192,2664,  66,5215,3260,2111,1295,1127,2152,
+3805,4135, 901,1164,1976, 398,1278, 530,1460, 748, 904,1054,1966,1426,  53,2909,
+ 509, 523,2279,1534, 536,1019, 239,1685, 460,2353, 673,1065,2401,3600,4298,2272,
+1272,2363, 284,1753,3679,4064,1695,  81, 815,2677,2757,2731,1386, 859, 500,4221,
+2190,2566, 757,1006,2519,2068,1166,1455, 337,2654,3203,1863,1682,1914,3025,1252,
+1409,1366, 847, 714,2834,2038,3209, 964,2970,1901, 885,2553,1078,1756,3049, 301,
+1572,3326, 688,2130,1996,2429,1805,1648,2930,3421,2750,3652,3088, 262,1158,1254,
+ 389,1641,1812, 526,1719, 923,2073,1073,1902, 468, 489,4625,1140, 857,2375,3070,
+3319,2863, 380, 116,1328,2693,1161,2244, 273,1212,1884,2769,3011,1775,1142, 461,
+3066,1200,2147,2212, 790, 702,2695,4222,1601,1058, 434,2338,5153,3640,  67,2360,
+4099,2502, 618,3472,1329, 416,1132, 830,2782,1807,2653,3211,3510,1662, 192,2124,
+ 296,3979,1739,1611,3684,  23, 118, 324, 446,1239,1225, 293,2520,3814,3795,2535,
+3116,  17,1074, 467,2692,2201, 387,2922,  45,1326,3055,1645,3659,2817, 958, 243,
+1903,2320,1339,2825,1784,3289, 356, 576, 865,2315,2381,3377,3916,1088,3122,1713,
+1655, 935, 628,4689,1034,1327, 441, 800, 720, 894,1979,2183,1528,5289,2702,1071,
+4046,3572,2399,1571,3281,  79, 761,1103, 327, 134, 758,1899,1371,1615, 879, 442,
+ 215,2605,2579, 173,2048,2485,1057,2975,3317,1097,2253,3801,4263,1403,1650,2946,
+ 814,4968,3487,1548,2644,1567,1285,   2, 295,2636,  97, 946,3576, 832, 141,4257,
+3273, 760,3821,3521,3156,2607, 949,1024,1733,1516,1803,1920,2125,2283,2665,3180,
+1501,2064,3560,2171,1592, 803,3518,1416, 732,3897,4258,1363,1362,2458, 119,1427,
+ 602,1525,2608,1605,1639,3175, 694,3064,  10, 465,  76,2000,4846,4208, 444,3781,
+1619,3353,2206,1273,3796, 740,2483, 320,1723,2377,3660,2619,1359,1137,1762,1724,
+2345,2842,1850,1862, 912, 821,1866, 612,2625,1735,2573,3369,1093, 844,  89, 937,
+ 930,1424,3564,2413,2972,1004,3046,3019,2011, 711,3171,1452,4178, 428, 801,1943,
+ 432, 445,2811, 206,4136,1472, 730, 349,  73, 397,2802,2547, 998,1637,1167, 789,
+ 396,3217, 154,1218, 716,1120,1780,2819,4826,1931,3334,3762,2139,1215,2627, 552,
+3664,3628,3232,1405,2383,3111,1356,2652,3577,3320,3101,1703, 640,1045,1370,1246,
+4996, 371,1575,2436,1621,2210, 984,4033,1734,2638,  16,4529, 663,2755,3255,1451,
+3917,2257,1253,1955,2234,1263,2951, 214,1229, 617, 485, 359,1831,1969, 473,2310,
+ 750,2058, 165,  80,2864,2419, 361,4344,2416,2479,1134, 796,3726,1266,2943, 860,
+2715, 938, 390,2734,1313,1384, 248, 202, 877,1064,2854, 522,3907, 279,1602, 297,
+2357, 395,3740, 137,2075, 944,4089,2584,1267,3802,  62,1533,2285, 178, 176, 780,
+2440, 201,3707, 590, 478,1560,4354,2117,1075,  30,  74,4643,4004,1635,1441,2745,
+ 776,2596, 238,1077,1692,1912,2844, 605, 499,1742,3947, 241,3053, 980,1749, 936,
+2640,4511,2582, 515,1543,2162,5322,2892,2993, 890,2148,1924, 665,1827,3581,1032,
+ 968,3163, 339,1044,1896, 270, 583,1791,1720,4367,1194,3488,3669,  43,2523,1657,
+ 163,2167, 290,1209,1622,3378, 550, 634,2508,2510, 695,2634,2384,2512,1476,1414,
+ 220,1469,2341,2138,2852,3183,2900,4939,2865,3502,1211,3680, 854,3227,1299,2976,
+3172, 186,2998,1459, 443,1067,3251,1495, 321,1932,3054, 909, 753,1410,1828, 436,
+2441,1119,1587,3164,2186,1258, 227, 231,1425,1890,3200,3942, 247, 959, 725,5254,
+2741, 577,2158,2079, 929, 120, 174, 838,2813, 591,1115, 417,2024,  40,3240,1536,
+1037, 291,4151,2354, 632,1298,2406,2500,3535,1825,1846,3451, 205,1171, 345,4238,
+  18,1163, 811, 685,2208,1217, 425,1312,1508,1175,4308,2552,1033, 587,1381,3059,
+2984,3482, 340,1316,4023,3972, 792,3176, 519, 777,4690, 918, 933,4130,2981,3741,
+  90,3360,2911,2200,5184,4550, 609,3079,2030, 272,3379,2736, 363,3881,1130,1447,
+ 286, 779, 357,1169,3350,3137,1630,1220,2687,2391, 747,1277,3688,2618,2682,2601,
+1156,3196,5290,4034,3102,1689,3596,3128, 874, 219,2783, 798, 508,1843,2461, 269,
+1658,1776,1392,1913,2983,3287,2866,2159,2372, 829,4076,  46,4253,2873,1889,1894,
+ 915,1834,1631,2181,2318, 298, 664,2818,3555,2735, 954,3228,3117, 527,3511,2173,
+ 681,2712,3033,2247,2346,3467,1652, 155,2164,3382, 113,1994, 450, 899, 494, 994,
+1237,2958,1875,2336,1926,3727, 545,1577,1550, 633,3473, 204,1305,3072,2410,1956,
+2471, 707,2134, 841,2195,2196,2663,3843,1026,4940, 990,3252,4997, 368,1092, 437,
+3212,3258,1933,1829, 675,2977,2893, 412, 943,3723,4644,3294,3283,2230,2373,5154,
+2389,2241,2661,2323,1404,2524, 593, 787, 677,3008,1275,2059, 438,2709,2609,2240,
+2269,2246,1446,  36,1568,1373,3892,1574,2301,1456,3962, 693,2276,5216,2035,1143,
+2720,1919,1797,1811,2763,4137,2597,1830,1699,1488,1198,2090, 424,1694, 312,3634,
+3390,4179,3335,2252,1214, 561,1059,3243,2295,2561, 975,5155,2321,2751,3772, 472,
+1537,3282,3398,1047,2077,2348,2878,1323,3340,3076, 690,2906,  51, 369, 170,3541,
+1060,2187,2688,3670,2541,1083,1683, 928,3918, 459, 109,4427, 599,3744,4286, 143,
+2101,2730,2490,  82,1588,3036,2121, 281,1860, 477,4035,1238,2812,3020,2716,3312,
+1530,2188,2055,1317, 843, 636,1808,1173,3495, 649, 181,1002, 147,3641,1159,2414,
+3750,2289,2795, 813,3123,2610,1136,4368,   5,3391,4541,2174, 420, 429,1728, 754,
+1228,2115,2219, 347,2223,2733, 735,1518,3003,2355,3134,1764,3948,3329,1888,2424,
+1001,1234,1972,3321,3363,1672,1021,1450,1584, 226, 765, 655,2526,3404,3244,2302,
+3665, 731, 594,2184, 319,1576, 621, 658,2656,4299,2099,3864,1279,2071,2598,2739,
+ 795,3086,3699,3908,1707,2352,2402,1382,3136,2475,1465,4847,3496,3865,1085,3004,
+2591,1084, 213,2287,1963,3565,2250, 822, 793,4574,3187,1772,1789,3050, 595,1484,
+1959,2770,1080,2650, 456, 422,2996, 940,3322,4328,4345,3092,2742, 965,2784, 739,
+4124, 952,1358,2498,2949,2565, 332,2698,2378, 660,2260,2473,4194,3856,2919, 535,
+1260,2651,1208,1428,1300,1949,1303,2942, 433,2455,2450,1251,1946, 614,1269, 641,
+1306,1810,2737,3078,2912, 564,2365,1419,1415,1497,4460,2367,2185,1379,3005,1307,
+3218,2175,1897,3063, 682,1157,4040,4005,1712,1160,1941,1399, 394, 402,2952,1573,
+1151,2986,2404, 862, 299,2033,1489,3006, 346, 171,2886,3401,1726,2932, 168,2533,
+  47,2507,1030,3735,1145,3370,1395,1318,1579,3609,4560,2857,4116,1457,2529,1965,
+ 504,1036,2690,2988,2405, 745,5871, 849,2397,2056,3081, 863,2359,3857,2096,  99,
+1397,1769,2300,4428,1643,3455,1978,1757,3718,1440,  35,4879,3742,1296,4228,2280,
+ 160,5063,1599,2013, 166, 520,3479,1646,3345,3012, 490,1937,1545,1264,2182,2505,
+1096,1188,1369,1436,2421,1667,2792,2460,1270,2122, 727,3167,2143, 806,1706,1012,
+1800,3037, 960,2218,1882, 805, 139,2456,1139,1521, 851,1052,3093,3089, 342,2039,
+ 744,5097,1468,1502,1585,2087, 223, 939, 326,2140,2577, 892,2481,1623,4077, 982,
+3708, 135,2131,  87,2503,3114,2326,1106, 876,1616, 547,2997,2831,2093,3441,4530,
+4314,   9,3256,4229,4148, 659,1462,1986,1710,2046,2913,2231,4090,4880,5255,3392,
+3274,1368,3689,4645,1477, 705,3384,3635,1068,1529,2941,1458,3782,1509, 100,1656,
+2548, 718,2339, 408,1590,2780,3548,1838,4117,3719,1345,3530, 717,3442,2778,3220,
+2898,1892,4590,3614,3371,2043,1998,1224,3483, 891, 635, 584,2559,3355, 733,1766,
+1729,1172,3789,1891,2307, 781,2982,2271,1957,1580,5773,2633,2005,4195,3097,1535,
+3213,1189,1934,5693,3262, 586,3118,1324,1598, 517,1564,2217,1868,1893,4445,3728,
+2703,3139,1526,1787,1992,3882,2875,1549,1199,1056,2224,1904,2711,5098,4287, 338,
+1993,3129,3489,2689,1809,2815,1997, 957,1855,3898,2550,3275,3057,1105,1319, 627,
+1505,1911,1883,3526, 698,3629,3456,1833,1431, 746,  77,1261,2017,2296,1977,1885,
+ 125,1334,1600, 525,1798,1109,2222,1470,1945, 559,2236,1186,3443,2476,1929,1411,
+2411,3135,1777,3372,2621,1841,1613,3229, 668,1430,1839,2643,2916, 195,1989,2671,
+2358,1387, 629,3205,2293,5256,4439, 123,1310, 888,1879,4300,3021,3605,1003,1162,
+3192,2910,2010, 140,2395,2859,  55,1082,2012,2901, 662, 419,2081,1438, 680,2774,
+4654,3912,1620,1731,1625,5035,4065,2328, 512,1344, 802,5443,2163,2311,2537, 524,
+3399,  98,1155,2103,1918,2606,3925,2816,1393,2465,1504,3773,2177,3963,1478,4346,
+ 180,1113,4655,3461,2028,1698, 833,2696,1235,1322,1594,4408,3623,3013,3225,2040,
+3022, 541,2881, 607,3632,2029,1665,1219, 639,1385,1686,1099,2803,3231,1938,3188,
+2858, 427, 676,2772,1168,2025, 454,3253,2486,3556, 230,1950, 580, 791,1991,1280,
+1086,1974,2034, 630, 257,3338,2788,4903,1017,  86,4790, 966,2789,1995,1696,1131,
+ 259,3095,4188,1308, 179,1463,5257, 289,4107,1248,  42,3413,1725,2288, 896,1947,
+ 774,4474,4254, 604,3430,4264, 392,2514,2588, 452, 237,1408,3018, 988,4531,1970,
+3034,3310, 540,2370,1562,1288,2990, 502,4765,1147,   4,1853,2708, 207, 294,2814,
+4078,2902,2509, 684,  34,3105,3532,2551, 644, 709,2801,2344, 573,1727,3573,3557,
+2021,1081,3100,4315,2100,3681, 199,2263,1837,2385, 146,3484,1195,2776,3949, 997,
+1939,3973,1008,1091,1202,1962,1847,1149,4209,5444,1076, 493, 117,5400,2521, 972,
+1490,2934,1796,4542,2374,1512,2933,2657, 413,2888,1135,2762,2314,2156,1355,2369,
+ 766,2007,2527,2170,3124,2491,2593,2632,4757,2437, 234,3125,3591,1898,1750,1376,
+1942,3468,3138, 570,2127,2145,3276,4131, 962, 132,1445,4196,  19, 941,3624,3480,
+3366,1973,1374,4461,3431,2629, 283,2415,2275, 808,2887,3620,2112,2563,1353,3610,
+ 955,1089,3103,1053,  96,  88,4097, 823,3808,1583, 399, 292,4091,3313, 421,1128,
+ 642,4006, 903,2539,1877,2082, 596,  29,4066,1790, 722,2157, 130, 995,1569, 769,
+1485, 464, 513,2213, 288,1923,1101,2453,4316, 133, 486,2445,  50, 625, 487,2207,
+  57, 423, 481,2962, 159,3729,1558, 491, 303, 482, 501, 240,2837, 112,3648,2392,
+1783, 362,   8,3433,3422, 610,2793,3277,1390,1284,1654,  21,3823, 734, 367, 623,
+ 193, 287, 374,1009,1483, 816, 476, 313,2255,2340,1262,2150,2899,1146,2581, 782,
+2116,1659,2018,1880, 255,3586,3314,1110,2867,2137,2564, 986,2767,5185,2006, 650,
+ 158, 926, 762, 881,3157,2717,2362,3587, 306,3690,3245,1542,3077,2427,1691,2478,
+2118,2985,3490,2438, 539,2305, 983, 129,1754, 355,4201,2386, 827,2923, 104,1773,
+2838,2771, 411,2905,3919, 376, 767, 122,1114, 828,2422,1817,3506, 266,3460,1007,
+1609,4998, 945,2612,4429,2274, 726,1247,1964,2914,2199,2070,4002,4108, 657,3323,
+1422, 579, 455,2764,4737,1222,2895,1670, 824,1223,1487,2525, 558, 861,3080, 598,
+2659,2515,1967, 752,2583,2376,2214,4180, 977, 704,2464,4999,2622,4109,1210,2961,
+ 819,1541, 142,2284,  44, 418, 457,1126,3730,4347,4626,1644,1876,3671,1864, 302,
+1063,5694, 624, 723,1984,3745,1314,1676,2488,1610,1449,3558,3569,2166,2098, 409,
+1011,2325,3704,2306, 818,1732,1383,1824,1844,3757, 999,2705,3497,1216,1423,2683,
+2426,2954,2501,2726,2229,1475,2554,5064,1971,1794,1666,2014,1343, 783, 724, 191,
+2434,1354,2220,5065,1763,2752,2472,4152, 131, 175,2885,3434,  92,1466,4920,2616,
+3871,3872,3866, 128,1551,1632, 669,1854,3682,4691,4125,1230, 188,2973,3290,1302,
+1213, 560,3266, 917, 763,3909,3249,1760, 868,1958, 764,1782,2097, 145,2277,3774,
+4462,  64,1491,3062, 971,2132,3606,2442, 221,1226,1617, 218, 323,1185,3207,3147,
+ 571, 619,1473,1005,1744,2281, 449,1887,2396,3685, 275, 375,3816,1743,3844,3731,
+ 845,1983,2350,4210,1377, 773, 967,3499,3052,3743,2725,4007,1697,1022,3943,1464,
+3264,2855,2722,1952,1029,2839,2467,  84,4383,2215, 820,1391,2015,2448,3672, 377,
+1948,2168, 797,2545,3536,2578,2645,  94,2874,1678, 405,1259,3071, 771, 546,1315,
+ 470,1243,3083, 895,2468, 981, 969,2037, 846,4181, 653,1276,2928,  14,2594, 557,
+3007,2474, 156, 902,1338,1740,2574, 537,2518, 973,2282,2216,2433,1928, 138,2903,
+1293,2631,1612, 646,3457, 839,2935, 111, 496,2191,2847, 589,3186, 149,3994,2060,
+4031,2641,4067,3145,1870,  37,3597,2136,1025,2051,3009,3383,3549,1121,1016,3261,
+1301, 251,2446,2599,2153, 872,3246, 637, 334,3705, 831, 884, 921,3065,3140,4092,
+2198,1944, 246,2964, 108,2045,1152,1921,2308,1031, 203,3173,4170,1907,3890, 810,
+1401,2003,1690, 506, 647,1242,2828,1761,1649,3208,2249,1589,3709,2931,5156,1708,
+ 498, 666,2613, 834,3817,1231, 184,2851,1124, 883,3197,2261,3710,1765,1553,2658,
+1178,2639,2351,  93,1193, 942,2538,2141,4402, 235,1821, 870,1591,2192,1709,1871,
+3341,1618,4126,2595,2334, 603, 651,  69, 701, 268,2662,3411,2555,1380,1606, 503,
+ 448, 254,2371,2646, 574,1187,2309,1770, 322,2235,1292,1801, 305, 566,1133, 229,
+2067,2057, 706, 167, 483,2002,2672,3295,1820,3561,3067, 316, 378,2746,3452,1112,
+ 136,1981, 507,1651,2917,1117, 285,4591, 182,2580,3522,1304, 335,3303,1835,2504,
+1795,1792,2248, 674,1018,2106,2449,1857,2292,2845, 976,3047,1781,2600,2727,1389,
+1281,  52,3152, 153, 265,3950, 672,3485,3951,4463, 430,1183, 365, 278,2169,  27,
+1407,1336,2304, 209,1340,1730,2202,1852,2403,2883, 979,1737,1062, 631,2829,2542,
+3876,2592, 825,2086,2226,3048,3625, 352,1417,3724, 542, 991, 431,1351,3938,1861,
+2294, 826,1361,2927,3142,3503,1738, 463,2462,2723, 582,1916,1595,2808, 400,3845,
+3891,2868,3621,2254,  58,2492,1123, 910,2160,2614,1372,1603,1196,1072,3385,1700,
+3267,1980, 696, 480,2430, 920, 799,1570,2920,1951,2041,4047,2540,1321,4223,2469,
+3562,2228,1271,2602, 401,2833,3351,2575,5157, 907,2312,1256, 410, 263,3507,1582,
+ 996, 678,1849,2316,1480, 908,3545,2237, 703,2322, 667,1826,2849,1531,2604,2999,
+2407,3146,2151,2630,1786,3711, 469,3542, 497,3899,2409, 858, 837,4446,3393,1274,
+ 786, 620,1845,2001,3311, 484, 308,3367,1204,1815,3691,2332,1532,2557,1842,2020,
+2724,1927,2333,4440, 567,  22,1673,2728,4475,1987,1858,1144,1597, 101,1832,3601,
+  12, 974,3783,4391, 951,1412,   1,3720, 453,4608,4041, 528,1041,1027,3230,2628,
+1129, 875,1051,3291,1203,2262,1069,2860,2799,2149,2615,3278, 144,1758,3040,  31,
+ 475,1680, 366,2685,3184, 311,1642,4008,2466,5036,1593,1493,2809, 216,1420,1668,
+ 233, 304,2128,3284, 232,1429,1768,1040,2008,3407,2740,2967,2543, 242,2133, 778,
+1565,2022,2620, 505,2189,2756,1098,2273, 372,1614, 708, 553,2846,2094,2278, 169,
+3626,2835,4161, 228,2674,3165, 809,1454,1309, 466,1705,1095, 900,3423, 880,2667,
+3751,5258,2317,3109,2571,4317,2766,1503,1342, 866,4447,1118,  63,2076, 314,1881,
+1348,1061, 172, 978,3515,1747, 532, 511,3970,   6, 601, 905,2699,3300,1751, 276,
+1467,3725,2668,  65,4239,2544,2779,2556,1604, 578,2451,1802, 992,2331,2624,1320,
+3446, 713,1513,1013, 103,2786,2447,1661, 886,1702, 916, 654,3574,2031,1556, 751,
+2178,2821,2179,1498,1538,2176, 271, 914,2251,2080,1325, 638,1953,2937,3877,2432,
+2754,  95,3265,1716, 260,1227,4083, 775, 106,1357,3254, 426,1607, 555,2480, 772,
+1985, 244,2546, 474, 495,1046,2611,1851,2061,  71,2089,1675,2590, 742,3758,2843,
+3222,1433, 267,2180,2576,2826,2233,2092,3913,2435, 956,1745,3075, 856,2113,1116,
+ 451,   3,1988,2896,1398, 993,2463,1878,2049,1341,2718,2721,2870,2108, 712,2904,
+4363,2753,2324, 277,2872,2349,2649, 384, 987, 435, 691,3000, 922, 164,3939, 652,
+1500,1184,4153,2482,3373,2165,4848,2335,3775,3508,3154,2806,2830,1554,2102,1664,
+2530,1434,2408, 893,1547,2623,3447,2832,2242,2532,3169,2856,3223,2078,  49,3770,
+3469, 462, 318, 656,2259,3250,3069, 679,1629,2758, 344,1138,1104,3120,1836,1283,
+3115,2154,1437,4448, 934, 759,1999, 794,2862,1038, 533,2560,1722,2342, 855,2626,
+1197,1663,4476,3127,  85,4240,2528,  25,1111,1181,3673, 407,3470,4561,2679,2713,
+ 768,1925,2841,3986,1544,1165, 932, 373,1240,2146,1930,2673, 721,4766, 354,4333,
+ 391,2963, 187,  61,3364,1442,1102, 330,1940,1767, 341,3809,4118, 393,2496,2062,
+2211, 105, 331, 300, 439, 913,1332, 626, 379,3304,1557, 328, 689,3952, 309,1555,
+ 931, 317,2517,3027, 325, 569, 686,2107,3084,  60,1042,1333,2794, 264,3177,4014,
+1628, 258,3712,   7,4464,1176,1043,1778, 683, 114,1975,  78,1492, 383,1886, 510,
+ 386, 645,5291,2891,2069,3305,4138,3867,2939,2603,2493,1935,1066,1848,3588,1015,
+1282,1289,4609, 697,1453,3044,2666,3611,1856,2412,  54, 719,1330, 568,3778,2459,
+1748, 788, 492, 551,1191,1000, 488,3394,3763, 282,1799, 348,2016,1523,3155,2390,
+1049, 382,2019,1788,1170, 729,2968,3523, 897,3926,2785,2938,3292, 350,2319,3238,
+1718,1717,2655,3453,3143,4465, 161,2889,2980,2009,1421,  56,1908,1640,2387,2232,
+1917,1874,2477,4921, 148,  83,3438, 592,4245,2882,1822,1055, 741, 115,1496,1624,
+ 381,1638,4592,1020, 516,3214, 458, 947,4575,1432, 211,1514,2926,1865,2142, 189,
+ 852,1221,1400,1486, 882,2299,4036, 351,  28,1122, 700,6479,6480,6481,6482,6483,  #last 512
+)
+# fmt: on

venv/lib/python3.10/site-packages/chardet/gb2312prober.py

@@ -0,0 +1,47 @@
+######################## BEGIN LICENSE BLOCK ########################
+# The Original Code is mozilla.org code.
+#
+# The Initial Developer of the Original Code is
+# Netscape Communications Corporation.
+# Portions created by the Initial Developer are Copyright (C) 1998
+# the Initial Developer. All Rights Reserved.
+#
+# Contributor(s):
+#   Mark Pilgrim - port to Python
+#
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
+# 02110-1301  USA
+######################### END LICENSE BLOCK #########################
+
+from .chardistribution import GB2312DistributionAnalysis
+from .codingstatemachine import CodingStateMachine
+from .mbcharsetprober import MultiByteCharSetProber
+from .mbcssm import GB2312_SM_MODEL
+
+
+class GB2312Prober(MultiByteCharSetProber):
+    def __init__(self) -> None:
+        super().__init__()
+        self.coding_sm = CodingStateMachine(GB2312_SM_MODEL)
+        self.distribution_analyzer = GB2312DistributionAnalysis()
+        self.reset()
+
+    @property
+    def charset_name(self) -> str:
+        return "GB2312"
+
+    @property
+    def language(self) -> str:
+        return "Chinese"

venv/lib/python3.10/site-packages/chardet/hebrewprober.py

@@ -0,0 +1,316 @@
+######################## BEGIN LICENSE BLOCK ########################
+# The Original Code is Mozilla Universal charset detector code.
+#
+# The Initial Developer of the Original Code is
+#          Shy Shalom
+# Portions created by the Initial Developer are Copyright (C) 2005
+# the Initial Developer. All Rights Reserved.
+#
+# Contributor(s):
+#   Mark Pilgrim - port to Python
+#
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
+# 02110-1301  USA
+######################### END LICENSE BLOCK #########################
+
+from typing import Optional, Union
+
+from .charsetprober import CharSetProber
+from .enums import ProbingState
+from .sbcharsetprober import SingleByteCharSetProber
+
+# This prober doesn't actually recognize a language or a charset.
+# It is a helper prober for the use of the Hebrew model probers
+
+### General ideas of the Hebrew charset recognition ###
+#
+# Four main charsets exist in Hebrew:
+# "ISO-8859-8" - Visual Hebrew
+# "windows-1255" - Logical Hebrew
+# "ISO-8859-8-I" - Logical Hebrew
+# "x-mac-hebrew" - ?? Logical Hebrew ??
+#
+# Both "ISO" charsets use a completely identical set of code points, whereas
+# "windows-1255" and "x-mac-hebrew" are two different proper supersets of
+# these code points. windows-1255 defines additional characters in the range
+# 0x80-0x9F as some misc punctuation marks as well as some Hebrew-specific
+# diacritics and additional 'Yiddish' ligature letters in the range 0xc0-0xd6.
+# x-mac-hebrew defines similar additional code points but with a different
+# mapping.
+#
+# As far as an average Hebrew text with no diacritics is concerned, all four
+# charsets are identical with respect to code points. Meaning that for the
+# main Hebrew alphabet, all four map the same values to all 27 Hebrew letters
+# (including final letters).
+#
+# The dominant difference between these charsets is their directionality.
+# "Visual" directionality means that the text is ordered as if the renderer is
+# not aware of a BIDI rendering algorithm. The renderer sees the text and
+# draws it from left to right. The text itself when ordered naturally is read
+# backwards. A buffer of Visual Hebrew generally looks like so:
+# "[last word of first line spelled backwards] [whole line ordered backwards
+# and spelled backwards] [first word of first line spelled backwards]
+# [end of line] [last word of second line] ... etc' "
+# adding punctuation marks, numbers and English text to visual text is
+# naturally also "visual" and from left to right.
+#
+# "Logical" directionality means the text is ordered "naturally" according to
+# the order it is read. It is the responsibility of the renderer to display
+# the text from right to left. A BIDI algorithm is used to place general
+# punctuation marks, numbers and English text in the text.
+#
+# Texts in x-mac-hebrew are almost impossible to find on the Internet. From
+# what little evidence I could find, it seems that its general directionality
+# is Logical.
+#
+# To sum up all of the above, the Hebrew probing mechanism knows about two
+# charsets:
+# Visual Hebrew - "ISO-8859-8" - backwards text - Words and sentences are
+#    backwards while line order is natural. For charset recognition purposes
+#    the line order is unimportant (In fact, for this implementation, even
+#    word order is unimportant).
+# Logical Hebrew - "windows-1255" - normal, naturally ordered text.
+#
+# "ISO-8859-8-I" is a subset of windows-1255 and doesn't need to be
+#    specifically identified.
+# "x-mac-hebrew" is also identified as windows-1255. A text in x-mac-hebrew
+#    that contain special punctuation marks or diacritics is displayed with
+#    some unconverted characters showing as question marks. This problem might
+#    be corrected using another model prober for x-mac-hebrew. Due to the fact
+#    that x-mac-hebrew texts are so rare, writing another model prober isn't
+#    worth the effort and performance hit.
+#
+#### The Prober ####
+#
+# The prober is divided between two SBCharSetProbers and a HebrewProber,
+# all of which are managed, created, fed data, inquired and deleted by the
+# SBCSGroupProber. The two SBCharSetProbers identify that the text is in
+# fact some kind of Hebrew, Logical or Visual. The final decision about which
+# one is it is made by the HebrewProber by combining final-letter scores
+# with the scores of the two SBCharSetProbers to produce a final answer.
+#
+# The SBCSGroupProber is responsible for stripping the original text of HTML
+# tags, English characters, numbers, low-ASCII punctuation characters, spaces
+# and new lines. It reduces any sequence of such characters to a single space.
+# The buffer fed to each prober in the SBCS group prober is pure text in
+# high-ASCII.
+# The two SBCharSetProbers (model probers) share the same language model:
+# Win1255Model.
+# The first SBCharSetProber uses the model normally as any other
+# SBCharSetProber does, to recognize windows-1255, upon which this model was
+# built. The second SBCharSetProber is told to make the pair-of-letter
+# lookup in the language model backwards. This in practice exactly simulates
+# a visual Hebrew model using the windows-1255 logical Hebrew model.
+#
+# The HebrewProber is not using any language model. All it does is look for
+# final-letter evidence suggesting the text is either logical Hebrew or visual
+# Hebrew. Disjointed from the model probers, the results of the HebrewProber
+# alone are meaningless. HebrewProber always returns 0.00 as confidence
+# since it never identifies a charset by itself. Instead, the pointer to the
+# HebrewProber is passed to the model probers as a helper "Name Prober".
+# When the Group prober receives a positive identification from any prober,
+# it asks for the name of the charset identified. If the prober queried is a
+# Hebrew model prober, the model prober forwards the call to the
+# HebrewProber to make the final decision. In the HebrewProber, the
+# decision is made according to the final-letters scores maintained and Both
+# model probers scores. The answer is returned in the form of the name of the
+# charset identified, either "windows-1255" or "ISO-8859-8".
+
+
+class HebrewProber(CharSetProber):
+    SPACE = 0x20
+    # windows-1255 / ISO-8859-8 code points of interest
+    FINAL_KAF = 0xEA
+    NORMAL_KAF = 0xEB
+    FINAL_MEM = 0xED
+    NORMAL_MEM = 0xEE
+    FINAL_NUN = 0xEF
+    NORMAL_NUN = 0xF0
+    FINAL_PE = 0xF3
+    NORMAL_PE = 0xF4
+    FINAL_TSADI = 0xF5
+    NORMAL_TSADI = 0xF6
+
+    # Minimum Visual vs Logical final letter score difference.
+    # If the difference is below this, don't rely solely on the final letter score
+    # distance.
+    MIN_FINAL_CHAR_DISTANCE = 5
+
+    # Minimum Visual vs Logical model score difference.
+    # If the difference is below this, don't rely at all on the model score
+    # distance.
+    MIN_MODEL_DISTANCE = 0.01
+
+    VISUAL_HEBREW_NAME = "ISO-8859-8"
+    LOGICAL_HEBREW_NAME = "windows-1255"
+
+    def __init__(self) -> None:
+        super().__init__()
+        self._final_char_logical_score = 0
+        self._final_char_visual_score = 0
+        self._prev = self.SPACE
+        self._before_prev = self.SPACE
+        self._logical_prober: Optional[SingleByteCharSetProber] = None
+        self._visual_prober: Optional[SingleByteCharSetProber] = None
+        self.reset()
+
+    def reset(self) -> None:
+        self._final_char_logical_score = 0
+        self._final_char_visual_score = 0
+        # The two last characters seen in the previous buffer,
+        # mPrev and mBeforePrev are initialized to space in order to simulate
+        # a word delimiter at the beginning of the data
+        self._prev = self.SPACE
+        self._before_prev = self.SPACE
+        # These probers are owned by the group prober.
+
+    def set_model_probers(
+        self,
+        logical_prober: SingleByteCharSetProber,
+        visual_prober: SingleByteCharSetProber,
+    ) -> None:
+        self._logical_prober = logical_prober
+        self._visual_prober = visual_prober
+
+    def is_final(self, c: int) -> bool:
+        return c in [
+            self.FINAL_KAF,
+            self.FINAL_MEM,
+            self.FINAL_NUN,
+            self.FINAL_PE,
+            self.FINAL_TSADI,
+        ]
+
+    def is_non_final(self, c: int) -> bool:
+        # The normal Tsadi is not a good Non-Final letter due to words like
+        # 'lechotet' (to chat) containing an apostrophe after the tsadi. This
+        # apostrophe is converted to a space in FilterWithoutEnglishLetters
+        # causing the Non-Final tsadi to appear at an end of a word even
+        # though this is not the case in the original text.
+        # The letters Pe and Kaf rarely display a related behavior of not being
+        # a good Non-Final letter. Words like 'Pop', 'Winamp' and 'Mubarak'
+        # for example legally end with a Non-Final Pe or Kaf. However, the
+        # benefit of these letters as Non-Final letters outweighs the damage
+        # since these words are quite rare.
+        return c in [self.NORMAL_KAF, self.NORMAL_MEM, self.NORMAL_NUN, self.NORMAL_PE]
+
+    def feed(self, byte_str: Union[bytes, bytearray]) -> ProbingState:
+        # Final letter analysis for logical-visual decision.
+        # Look for evidence that the received buffer is either logical Hebrew
+        # or visual Hebrew.
+        # The following cases are checked:
+        # 1) A word longer than 1 letter, ending with a final letter. This is
+        #    an indication that the text is laid out "naturally" since the
+        #    final letter really appears at the end. +1 for logical score.
+        # 2) A word longer than 1 letter, ending with a Non-Final letter. In
+        #    normal Hebrew, words ending with Kaf, Mem, Nun, Pe or Tsadi,
+        #    should not end with the Non-Final form of that letter. Exceptions
+        #    to this rule are mentioned above in isNonFinal(). This is an
+        #    indication that the text is laid out backwards. +1 for visual
+        #    score
+        # 3) A word longer than 1 letter, starting with a final letter. Final
+        #    letters should not appear at the beginning of a word. This is an
+        #    indication that the text is laid out backwards. +1 for visual
+        #    score.
+        #
+        # The visual score and logical score are accumulated throughout the
+        # text and are finally checked against each other in GetCharSetName().
+        # No checking for final letters in the middle of words is done since
+        # that case is not an indication for either Logical or Visual text.
+        #
+        # We automatically filter out all 7-bit characters (replace them with
+        # spaces) so the word boundary detection works properly. [MAP]
+
+        if self.state == ProbingState.NOT_ME:
+            # Both model probers say it's not them. No reason to continue.
+            return ProbingState.NOT_ME
+
+        byte_str = self.filter_high_byte_only(byte_str)
+
+        for cur in byte_str:
+            if cur == self.SPACE:
+                # We stand on a space - a word just ended
+                if self._before_prev != self.SPACE:
+                    # next-to-last char was not a space so self._prev is not a
+                    # 1 letter word
+                    if self.is_final(self._prev):
+                        # case (1) [-2:not space][-1:final letter][cur:space]
+                        self._final_char_logical_score += 1
+                    elif self.is_non_final(self._prev):
+                        # case (2) [-2:not space][-1:Non-Final letter][
+                        #  cur:space]
+                        self._final_char_visual_score += 1
+            else:
+                # Not standing on a space
+                if (
+                    (self._before_prev == self.SPACE)
+                    and (self.is_final(self._prev))
+                    and (cur != self.SPACE)
+                ):
+                    # case (3) [-2:space][-1:final letter][cur:not space]
+                    self._final_char_visual_score += 1
+            self._before_prev = self._prev
+            self._prev = cur
+
+        # Forever detecting, till the end or until both model probers return
+        # ProbingState.NOT_ME (handled above)
+        return ProbingState.DETECTING
+
+    @property
+    def charset_name(self) -> str:
+        assert self._logical_prober is not None
+        assert self._visual_prober is not None
+
+        # Make the decision: is it Logical or Visual?
+        # If the final letter score distance is dominant enough, rely on it.
+        finalsub = self._final_char_logical_score - self._final_char_visual_score
+        if finalsub >= self.MIN_FINAL_CHAR_DISTANCE:
+            return self.LOGICAL_HEBREW_NAME
+        if finalsub <= -self.MIN_FINAL_CHAR_DISTANCE:
+            return self.VISUAL_HEBREW_NAME
+
+        # It's not dominant enough, try to rely on the model scores instead.
+        modelsub = (
+            self._logical_prober.get_confidence() - self._visual_prober.get_confidence()
+        )
+        if modelsub > self.MIN_MODEL_DISTANCE:
+            return self.LOGICAL_HEBREW_NAME
+        if modelsub < -self.MIN_MODEL_DISTANCE:
+            return self.VISUAL_HEBREW_NAME
+
+        # Still no good, back to final letter distance, maybe it'll save the
+        # day.
+        if finalsub < 0.0:
+            return self.VISUAL_HEBREW_NAME
+
+        # (finalsub > 0 - Logical) or (don't know what to do) default to
+        # Logical.
+        return self.LOGICAL_HEBREW_NAME
+
+    @property
+    def language(self) -> str:
+        return "Hebrew"
+
+    @property
+    def state(self) -> ProbingState:
+        assert self._logical_prober is not None
+        assert self._visual_prober is not None
+
+        # Remain active as long as any of the model probers are active.
+        if (self._logical_prober.state == ProbingState.NOT_ME) and (
+            self._visual_prober.state == ProbingState.NOT_ME
+        ):
+            return ProbingState.NOT_ME
+        return ProbingState.DETECTING

venv/lib/python3.10/site-packages/chardet/jisfreq.py

@@ -0,0 +1,325 @@
+######################## BEGIN LICENSE BLOCK ########################
+# The Original Code is Mozilla Communicator client code.
+#
+# The Initial Developer of the Original Code is
+# Netscape Communications Corporation.
+# Portions created by the Initial Developer are Copyright (C) 1998
+# the Initial Developer. All Rights Reserved.
+#
+# Contributor(s):
+#   Mark Pilgrim - port to Python
+#
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
+# 02110-1301  USA
+######################### END LICENSE BLOCK #########################
+
+# Sampling from about 20M text materials include literature and computer technology
+#
+# Japanese frequency table, applied to both S-JIS and EUC-JP
+# They are sorted in order.
+
+# 128  --> 0.77094
+# 256  --> 0.85710
+# 512  --> 0.92635
+# 1024 --> 0.97130
+# 2048 --> 0.99431
+#
+# Ideal Distribution Ratio = 0.92635 / (1-0.92635) = 12.58
+# Random Distribution Ration = 512 / (2965+62+83+86-512) = 0.191
+#
+# Typical Distribution Ratio, 25% of IDR
+
+JIS_TYPICAL_DISTRIBUTION_RATIO = 3.0
+
+# Char to FreqOrder table ,
+JIS_TABLE_SIZE = 4368
+
+# fmt: off
+JIS_CHAR_TO_FREQ_ORDER = (
+  40,   1,   6, 182, 152, 180, 295,2127, 285, 381,3295,4304,3068,4606,3165,3510, #   16
+3511,1822,2785,4607,1193,2226,5070,4608, 171,2996,1247,  18, 179,5071, 856,1661, #   32
+1262,5072, 619, 127,3431,3512,3230,1899,1700, 232, 228,1294,1298, 284, 283,2041, #   48
+2042,1061,1062,  48,  49,  44,  45, 433, 434,1040,1041, 996, 787,2997,1255,4305, #   64
+2108,4609,1684,1648,5073,5074,5075,5076,5077,5078,3687,5079,4610,5080,3927,3928, #   80
+5081,3296,3432, 290,2285,1471,2187,5082,2580,2825,1303,2140,1739,1445,2691,3375, #   96
+1691,3297,4306,4307,4611, 452,3376,1182,2713,3688,3069,4308,5083,5084,5085,5086, #  112
+5087,5088,5089,5090,5091,5092,5093,5094,5095,5096,5097,5098,5099,5100,5101,5102, #  128
+5103,5104,5105,5106,5107,5108,5109,5110,5111,5112,4097,5113,5114,5115,5116,5117, #  144
+5118,5119,5120,5121,5122,5123,5124,5125,5126,5127,5128,5129,5130,5131,5132,5133, #  160
+5134,5135,5136,5137,5138,5139,5140,5141,5142,5143,5144,5145,5146,5147,5148,5149, #  176
+5150,5151,5152,4612,5153,5154,5155,5156,5157,5158,5159,5160,5161,5162,5163,5164, #  192
+5165,5166,5167,5168,5169,5170,5171,5172,5173,5174,5175,1472, 598, 618, 820,1205, #  208
+1309,1412,1858,1307,1692,5176,5177,5178,5179,5180,5181,5182,1142,1452,1234,1172, #  224
+1875,2043,2149,1793,1382,2973, 925,2404,1067,1241, 960,1377,2935,1491, 919,1217, #  240
+1865,2030,1406,1499,2749,4098,5183,5184,5185,5186,5187,5188,2561,4099,3117,1804, #  256
+2049,3689,4309,3513,1663,5189,3166,3118,3298,1587,1561,3433,5190,3119,1625,2998, #  272
+3299,4613,1766,3690,2786,4614,5191,5192,5193,5194,2161,  26,3377,   2,3929,  20, #  288
+3691,  47,4100,  50,  17,  16,  35, 268,  27, 243,  42, 155,  24, 154,  29, 184, #  304
+   4,  91,  14,  92,  53, 396,  33, 289,   9,  37,  64, 620,  21,  39, 321,   5, #  320
+  12,  11,  52,  13,   3, 208, 138,   0,   7,  60, 526, 141, 151,1069, 181, 275, #  336
+1591,  83, 132,1475, 126, 331, 829,  15,  69, 160,  59,  22, 157,  55,1079, 312, #  352
+ 109,  38,  23,  25,  10,  19,  79,5195,  61, 382,1124,   8,  30,5196,5197,5198, #  368
+5199,5200,5201,5202,5203,5204,5205,5206,  89,  62,  74,  34,2416, 112, 139, 196, #  384
+ 271, 149,  84, 607, 131, 765,  46,  88, 153, 683,  76, 874, 101, 258,  57,  80, #  400
+  32, 364, 121,1508, 169,1547,  68, 235, 145,2999,  41, 360,3027,  70,  63,  31, #  416
+  43, 259, 262,1383,  99, 533, 194,  66,  93, 846, 217, 192,  56, 106,  58, 565, #  432
+ 280, 272, 311, 256, 146,  82, 308,  71, 100, 128, 214, 655, 110, 261, 104,1140, #  448
+  54,  51,  36,  87,  67,3070, 185,2618,2936,2020,  28,1066,2390,2059,5207,5208, #  464
+5209,5210,5211,5212,5213,5214,5215,5216,4615,5217,5218,5219,5220,5221,5222,5223, #  480
+5224,5225,5226,5227,5228,5229,5230,5231,5232,5233,5234,5235,5236,3514,5237,5238, #  496
+5239,5240,5241,5242,5243,5244,2297,2031,4616,4310,3692,5245,3071,5246,3598,5247, #  512
+4617,3231,3515,5248,4101,4311,4618,3808,4312,4102,5249,4103,4104,3599,5250,5251, #  528
+5252,5253,5254,5255,5256,5257,5258,5259,5260,5261,5262,5263,5264,5265,5266,5267, #  544
+5268,5269,5270,5271,5272,5273,5274,5275,5276,5277,5278,5279,5280,5281,5282,5283, #  560
+5284,5285,5286,5287,5288,5289,5290,5291,5292,5293,5294,5295,5296,5297,5298,5299, #  576
+5300,5301,5302,5303,5304,5305,5306,5307,5308,5309,5310,5311,5312,5313,5314,5315, #  592
+5316,5317,5318,5319,5320,5321,5322,5323,5324,5325,5326,5327,5328,5329,5330,5331, #  608
+5332,5333,5334,5335,5336,5337,5338,5339,5340,5341,5342,5343,5344,5345,5346,5347, #  624
+5348,5349,5350,5351,5352,5353,5354,5355,5356,5357,5358,5359,5360,5361,5362,5363, #  640
+5364,5365,5366,5367,5368,5369,5370,5371,5372,5373,5374,5375,5376,5377,5378,5379, #  656
+5380,5381, 363, 642,2787,2878,2788,2789,2316,3232,2317,3434,2011, 165,1942,3930, #  672
+3931,3932,3933,5382,4619,5383,4620,5384,5385,5386,5387,5388,5389,5390,5391,5392, #  688
+5393,5394,5395,5396,5397,5398,5399,5400,5401,5402,5403,5404,5405,5406,5407,5408, #  704
+5409,5410,5411,5412,5413,5414,5415,5416,5417,5418,5419,5420,5421,5422,5423,5424, #  720
+5425,5426,5427,5428,5429,5430,5431,5432,5433,5434,5435,5436,5437,5438,5439,5440, #  736
+5441,5442,5443,5444,5445,5446,5447,5448,5449,5450,5451,5452,5453,5454,5455,5456, #  752
+5457,5458,5459,5460,5461,5462,5463,5464,5465,5466,5467,5468,5469,5470,5471,5472, #  768
+5473,5474,5475,5476,5477,5478,5479,5480,5481,5482,5483,5484,5485,5486,5487,5488, #  784
+5489,5490,5491,5492,5493,5494,5495,5496,5497,5498,5499,5500,5501,5502,5503,5504, #  800
+5505,5506,5507,5508,5509,5510,5511,5512,5513,5514,5515,5516,5517,5518,5519,5520, #  816
+5521,5522,5523,5524,5525,5526,5527,5528,5529,5530,5531,5532,5533,5534,5535,5536, #  832
+5537,5538,5539,5540,5541,5542,5543,5544,5545,5546,5547,5548,5549,5550,5551,5552, #  848
+5553,5554,5555,5556,5557,5558,5559,5560,5561,5562,5563,5564,5565,5566,5567,5568, #  864
+5569,5570,5571,5572,5573,5574,5575,5576,5577,5578,5579,5580,5581,5582,5583,5584, #  880
+5585,5586,5587,5588,5589,5590,5591,5592,5593,5594,5595,5596,5597,5598,5599,5600, #  896
+5601,5602,5603,5604,5605,5606,5607,5608,5609,5610,5611,5612,5613,5614,5615,5616, #  912
+5617,5618,5619,5620,5621,5622,5623,5624,5625,5626,5627,5628,5629,5630,5631,5632, #  928
+5633,5634,5635,5636,5637,5638,5639,5640,5641,5642,5643,5644,5645,5646,5647,5648, #  944
+5649,5650,5651,5652,5653,5654,5655,5656,5657,5658,5659,5660,5661,5662,5663,5664, #  960
+5665,5666,5667,5668,5669,5670,5671,5672,5673,5674,5675,5676,5677,5678,5679,5680, #  976
+5681,5682,5683,5684,5685,5686,5687,5688,5689,5690,5691,5692,5693,5694,5695,5696, #  992
+5697,5698,5699,5700,5701,5702,5703,5704,5705,5706,5707,5708,5709,5710,5711,5712, # 1008
+5713,5714,5715,5716,5717,5718,5719,5720,5721,5722,5723,5724,5725,5726,5727,5728, # 1024
+5729,5730,5731,5732,5733,5734,5735,5736,5737,5738,5739,5740,5741,5742,5743,5744, # 1040
+5745,5746,5747,5748,5749,5750,5751,5752,5753,5754,5755,5756,5757,5758,5759,5760, # 1056
+5761,5762,5763,5764,5765,5766,5767,5768,5769,5770,5771,5772,5773,5774,5775,5776, # 1072
+5777,5778,5779,5780,5781,5782,5783,5784,5785,5786,5787,5788,5789,5790,5791,5792, # 1088
+5793,5794,5795,5796,5797,5798,5799,5800,5801,5802,5803,5804,5805,5806,5807,5808, # 1104
+5809,5810,5811,5812,5813,5814,5815,5816,5817,5818,5819,5820,5821,5822,5823,5824, # 1120
+5825,5826,5827,5828,5829,5830,5831,5832,5833,5834,5835,5836,5837,5838,5839,5840, # 1136
+5841,5842,5843,5844,5845,5846,5847,5848,5849,5850,5851,5852,5853,5854,5855,5856, # 1152
+5857,5858,5859,5860,5861,5862,5863,5864,5865,5866,5867,5868,5869,5870,5871,5872, # 1168
+5873,5874,5875,5876,5877,5878,5879,5880,5881,5882,5883,5884,5885,5886,5887,5888, # 1184
+5889,5890,5891,5892,5893,5894,5895,5896,5897,5898,5899,5900,5901,5902,5903,5904, # 1200
+5905,5906,5907,5908,5909,5910,5911,5912,5913,5914,5915,5916,5917,5918,5919,5920, # 1216
+5921,5922,5923,5924,5925,5926,5927,5928,5929,5930,5931,5932,5933,5934,5935,5936, # 1232
+5937,5938,5939,5940,5941,5942,5943,5944,5945,5946,5947,5948,5949,5950,5951,5952, # 1248
+5953,5954,5955,5956,5957,5958,5959,5960,5961,5962,5963,5964,5965,5966,5967,5968, # 1264
+5969,5970,5971,5972,5973,5974,5975,5976,5977,5978,5979,5980,5981,5982,5983,5984, # 1280
+5985,5986,5987,5988,5989,5990,5991,5992,5993,5994,5995,5996,5997,5998,5999,6000, # 1296
+6001,6002,6003,6004,6005,6006,6007,6008,6009,6010,6011,6012,6013,6014,6015,6016, # 1312
+6017,6018,6019,6020,6021,6022,6023,6024,6025,6026,6027,6028,6029,6030,6031,6032, # 1328
+6033,6034,6035,6036,6037,6038,6039,6040,6041,6042,6043,6044,6045,6046,6047,6048, # 1344
+6049,6050,6051,6052,6053,6054,6055,6056,6057,6058,6059,6060,6061,6062,6063,6064, # 1360
+6065,6066,6067,6068,6069,6070,6071,6072,6073,6074,6075,6076,6077,6078,6079,6080, # 1376
+6081,6082,6083,6084,6085,6086,6087,6088,6089,6090,6091,6092,6093,6094,6095,6096, # 1392
+6097,6098,6099,6100,6101,6102,6103,6104,6105,6106,6107,6108,6109,6110,6111,6112, # 1408
+6113,6114,2044,2060,4621, 997,1235, 473,1186,4622, 920,3378,6115,6116, 379,1108, # 1424
+4313,2657,2735,3934,6117,3809, 636,3233, 573,1026,3693,3435,2974,3300,2298,4105, # 1440
+ 854,2937,2463, 393,2581,2417, 539, 752,1280,2750,2480, 140,1161, 440, 708,1569, # 1456
+ 665,2497,1746,1291,1523,3000, 164,1603, 847,1331, 537,1997, 486, 508,1693,2418, # 1472
+1970,2227, 878,1220, 299,1030, 969, 652,2751, 624,1137,3301,2619,  65,3302,2045, # 1488
+1761,1859,3120,1930,3694,3516, 663,1767, 852, 835,3695, 269, 767,2826,2339,1305, # 1504
+ 896,1150, 770,1616,6118, 506,1502,2075,1012,2519, 775,2520,2975,2340,2938,4314, # 1520
+3028,2086,1224,1943,2286,6119,3072,4315,2240,1273,1987,3935,1557, 175, 597, 985, # 1536
+3517,2419,2521,1416,3029, 585, 938,1931,1007,1052,1932,1685,6120,3379,4316,4623, # 1552
+ 804, 599,3121,1333,2128,2539,1159,1554,2032,3810, 687,2033,2904, 952, 675,1467, # 1568
+3436,6121,2241,1096,1786,2440,1543,1924, 980,1813,2228, 781,2692,1879, 728,1918, # 1584
+3696,4624, 548,1950,4625,1809,1088,1356,3303,2522,1944, 502, 972, 373, 513,2827, # 1600
+ 586,2377,2391,1003,1976,1631,6122,2464,1084, 648,1776,4626,2141, 324, 962,2012, # 1616
+2177,2076,1384, 742,2178,1448,1173,1810, 222, 102, 301, 445, 125,2420, 662,2498, # 1632
+ 277, 200,1476,1165,1068, 224,2562,1378,1446, 450,1880, 659, 791, 582,4627,2939, # 1648
+3936,1516,1274, 555,2099,3697,1020,1389,1526,3380,1762,1723,1787,2229, 412,2114, # 1664
+1900,2392,3518, 512,2597, 427,1925,2341,3122,1653,1686,2465,2499, 697, 330, 273, # 1680
+ 380,2162, 951, 832, 780, 991,1301,3073, 965,2270,3519, 668,2523,2636,1286, 535, # 1696
+1407, 518, 671, 957,2658,2378, 267, 611,2197,3030,6123, 248,2299, 967,1799,2356, # 1712
+ 850,1418,3437,1876,1256,1480,2828,1718,6124,6125,1755,1664,2405,6126,4628,2879, # 1728
+2829, 499,2179, 676,4629, 557,2329,2214,2090, 325,3234, 464, 811,3001, 992,2342, # 1744
+2481,1232,1469, 303,2242, 466,1070,2163, 603,1777,2091,4630,2752,4631,2714, 322, # 1760
+2659,1964,1768, 481,2188,1463,2330,2857,3600,2092,3031,2421,4632,2318,2070,1849, # 1776
+2598,4633,1302,2254,1668,1701,2422,3811,2905,3032,3123,2046,4106,1763,1694,4634, # 1792
+1604, 943,1724,1454, 917, 868,2215,1169,2940, 552,1145,1800,1228,1823,1955, 316, # 1808
+1080,2510, 361,1807,2830,4107,2660,3381,1346,1423,1134,4108,6127, 541,1263,1229, # 1824
+1148,2540, 545, 465,1833,2880,3438,1901,3074,2482, 816,3937, 713,1788,2500, 122, # 1840
+1575, 195,1451,2501,1111,6128, 859, 374,1225,2243,2483,4317, 390,1033,3439,3075, # 1856
+2524,1687, 266, 793,1440,2599, 946, 779, 802, 507, 897,1081, 528,2189,1292, 711, # 1872
+1866,1725,1167,1640, 753, 398,2661,1053, 246, 348,4318, 137,1024,3440,1600,2077, # 1888
+2129, 825,4319, 698, 238, 521, 187,2300,1157,2423,1641,1605,1464,1610,1097,2541, # 1904
+1260,1436, 759,2255,1814,2150, 705,3235, 409,2563,3304, 561,3033,2005,2564, 726, # 1920
+1956,2343,3698,4109, 949,3812,3813,3520,1669, 653,1379,2525, 881,2198, 632,2256, # 1936
+1027, 778,1074, 733,1957, 514,1481,2466, 554,2180, 702,3938,1606,1017,1398,6129, # 1952
+1380,3521, 921, 993,1313, 594, 449,1489,1617,1166, 768,1426,1360, 495,1794,3601, # 1968
+1177,3602,1170,4320,2344, 476, 425,3167,4635,3168,1424, 401,2662,1171,3382,1998, # 1984
+1089,4110, 477,3169, 474,6130,1909, 596,2831,1842, 494, 693,1051,1028,1207,3076, # 2000
+ 606,2115, 727,2790,1473,1115, 743,3522, 630, 805,1532,4321,2021, 366,1057, 838, # 2016
+ 684,1114,2142,4322,2050,1492,1892,1808,2271,3814,2424,1971,1447,1373,3305,1090, # 2032
+1536,3939,3523,3306,1455,2199, 336, 369,2331,1035, 584,2393, 902, 718,2600,6131, # 2048
+2753, 463,2151,1149,1611,2467, 715,1308,3124,1268, 343,1413,3236,1517,1347,2663, # 2064
+2093,3940,2022,1131,1553,2100,2941,1427,3441,2942,1323,2484,6132,1980, 872,2368, # 2080
+2441,2943, 320,2369,2116,1082, 679,1933,3941,2791,3815, 625,1143,2023, 422,2200, # 2096
+3816,6133, 730,1695, 356,2257,1626,2301,2858,2637,1627,1778, 937, 883,2906,2693, # 2112
+3002,1769,1086, 400,1063,1325,3307,2792,4111,3077, 456,2345,1046, 747,6134,1524, # 2128
+ 884,1094,3383,1474,2164,1059, 974,1688,2181,2258,1047, 345,1665,1187, 358, 875, # 2144
+3170, 305, 660,3524,2190,1334,1135,3171,1540,1649,2542,1527, 927, 968,2793, 885, # 2160
+1972,1850, 482, 500,2638,1218,1109,1085,2543,1654,2034, 876,  78,2287,1482,1277, # 2176
+ 861,1675,1083,1779, 724,2754, 454, 397,1132,1612,2332, 893, 672,1237, 257,2259, # 2192
+2370, 135,3384, 337,2244, 547, 352, 340, 709,2485,1400, 788,1138,2511, 540, 772, # 2208
+1682,2260,2272,2544,2013,1843,1902,4636,1999,1562,2288,4637,2201,1403,1533, 407, # 2224
+ 576,3308,1254,2071, 978,3385, 170, 136,1201,3125,2664,3172,2394, 213, 912, 873, # 2240
+3603,1713,2202, 699,3604,3699, 813,3442, 493, 531,1054, 468,2907,1483, 304, 281, # 2256
+4112,1726,1252,2094, 339,2319,2130,2639, 756,1563,2944, 748, 571,2976,1588,2425, # 2272
+2715,1851,1460,2426,1528,1392,1973,3237, 288,3309, 685,3386, 296, 892,2716,2216, # 2288
+1570,2245, 722,1747,2217, 905,3238,1103,6135,1893,1441,1965, 251,1805,2371,3700, # 2304
+2601,1919,1078,  75,2182,1509,1592,1270,2640,4638,2152,6136,3310,3817, 524, 706, # 2320
+1075, 292,3818,1756,2602, 317,  98,3173,3605,3525,1844,2218,3819,2502, 814, 567, # 2336
+ 385,2908,1534,6137, 534,1642,3239, 797,6138,1670,1529, 953,4323, 188,1071, 538, # 2352
+ 178, 729,3240,2109,1226,1374,2000,2357,2977, 731,2468,1116,2014,2051,6139,1261, # 2368
+1593, 803,2859,2736,3443, 556, 682, 823,1541,6140,1369,2289,1706,2794, 845, 462, # 2384
+2603,2665,1361, 387, 162,2358,1740, 739,1770,1720,1304,1401,3241,1049, 627,1571, # 2400
+2427,3526,1877,3942,1852,1500, 431,1910,1503, 677, 297,2795, 286,1433,1038,1198, # 2416
+2290,1133,1596,4113,4639,2469,1510,1484,3943,6141,2442, 108, 712,4640,2372, 866, # 2432
+3701,2755,3242,1348, 834,1945,1408,3527,2395,3243,1811, 824, 994,1179,2110,1548, # 2448
+1453, 790,3003, 690,4324,4325,2832,2909,3820,1860,3821, 225,1748, 310, 346,1780, # 2464
+2470, 821,1993,2717,2796, 828, 877,3528,2860,2471,1702,2165,2910,2486,1789, 453, # 2480
+ 359,2291,1676,  73,1164,1461,1127,3311, 421, 604, 314,1037, 589, 116,2487, 737, # 2496
+ 837,1180, 111, 244, 735,6142,2261,1861,1362, 986, 523, 418, 581,2666,3822, 103, # 2512
+ 855, 503,1414,1867,2488,1091, 657,1597, 979, 605,1316,4641,1021,2443,2078,2001, # 2528
+1209,  96, 587,2166,1032, 260,1072,2153, 173,  94, 226,3244, 819,2006,4642,4114, # 2544
+2203, 231,1744, 782,  97,2667, 786,3387, 887, 391, 442,2219,4326,1425,6143,2694, # 2560
+ 633,1544,1202, 483,2015, 592,2052,1958,2472,1655, 419, 129,4327,3444,3312,1714, # 2576
+1257,3078,4328,1518,1098, 865,1310,1019,1885,1512,1734, 469,2444, 148, 773, 436, # 2592
+1815,1868,1128,1055,4329,1245,2756,3445,2154,1934,1039,4643, 579,1238, 932,2320, # 2608
+ 353, 205, 801, 115,2428, 944,2321,1881, 399,2565,1211, 678, 766,3944, 335,2101, # 2624
+1459,1781,1402,3945,2737,2131,1010, 844, 981,1326,1013, 550,1816,1545,2620,1335, # 2640
+1008, 371,2881, 936,1419,1613,3529,1456,1395,2273,1834,2604,1317,2738,2503, 416, # 2656
+1643,4330, 806,1126, 229, 591,3946,1314,1981,1576,1837,1666, 347,1790, 977,3313, # 2672
+ 764,2861,1853, 688,2429,1920,1462,  77, 595, 415,2002,3034, 798,1192,4115,6144, # 2688
+2978,4331,3035,2695,2582,2072,2566, 430,2430,1727, 842,1396,3947,3702, 613, 377, # 2704
+ 278, 236,1417,3388,3314,3174, 757,1869, 107,3530,6145,1194, 623,2262, 207,1253, # 2720
+2167,3446,3948, 492,1117,1935, 536,1838,2757,1246,4332, 696,2095,2406,1393,1572, # 2736
+3175,1782, 583, 190, 253,1390,2230, 830,3126,3389, 934,3245,1703,1749,2979,1870, # 2752
+2545,1656,2204, 869,2346,4116,3176,1817, 496,1764,4644, 942,1504, 404,1903,1122, # 2768
+1580,3606,2945,1022, 515, 372,1735, 955,2431,3036,6146,2797,1110,2302,2798, 617, # 2784
+6147, 441, 762,1771,3447,3607,3608,1904, 840,3037,  86, 939,1385, 572,1370,2445, # 2800
+1336, 114,3703, 898, 294, 203,3315, 703,1583,2274, 429, 961,4333,1854,1951,3390, # 2816
+2373,3704,4334,1318,1381, 966,1911,2322,1006,1155, 309, 989, 458,2718,1795,1372, # 2832
+1203, 252,1689,1363,3177, 517,1936, 168,1490, 562, 193,3823,1042,4117,1835, 551, # 2848
+ 470,4645, 395, 489,3448,1871,1465,2583,2641, 417,1493, 279,1295, 511,1236,1119, # 2864
+  72,1231,1982,1812,3004, 871,1564, 984,3449,1667,2696,2096,4646,2347,2833,1673, # 2880
+3609, 695,3246,2668, 807,1183,4647, 890, 388,2333,1801,1457,2911,1765,1477,1031, # 2896
+3316,3317,1278,3391,2799,2292,2526, 163,3450,4335,2669,1404,1802,6148,2323,2407, # 2912
+1584,1728,1494,1824,1269, 298, 909,3318,1034,1632, 375, 776,1683,2061, 291, 210, # 2928
+1123, 809,1249,1002,2642,3038, 206,1011,2132, 144, 975, 882,1565, 342, 667, 754, # 2944
+1442,2143,1299,2303,2062, 447, 626,2205,1221,2739,2912,1144,1214,2206,2584, 760, # 2960
+1715, 614, 950,1281,2670,2621, 810, 577,1287,2546,4648, 242,2168, 250,2643, 691, # 2976
+ 123,2644, 647, 313,1029, 689,1357,2946,1650, 216, 771,1339,1306, 808,2063, 549, # 2992
+ 913,1371,2913,2914,6149,1466,1092,1174,1196,1311,2605,2396,1783,1796,3079, 406, # 3008
+2671,2117,3949,4649, 487,1825,2220,6150,2915, 448,2348,1073,6151,2397,1707, 130, # 3024
+ 900,1598, 329, 176,1959,2527,1620,6152,2275,4336,3319,1983,2191,3705,3610,2155, # 3040
+3706,1912,1513,1614,6153,1988, 646, 392,2304,1589,3320,3039,1826,1239,1352,1340, # 3056
+2916, 505,2567,1709,1437,2408,2547, 906,6154,2672, 384,1458,1594,1100,1329, 710, # 3072
+ 423,3531,2064,2231,2622,1989,2673,1087,1882, 333, 841,3005,1296,2882,2379, 580, # 3088
+1937,1827,1293,2585, 601, 574, 249,1772,4118,2079,1120, 645, 901,1176,1690, 795, # 3104
+2207, 478,1434, 516,1190,1530, 761,2080, 930,1264, 355, 435,1552, 644,1791, 987, # 3120
+ 220,1364,1163,1121,1538, 306,2169,1327,1222, 546,2645, 218, 241, 610,1704,3321, # 3136
+1984,1839,1966,2528, 451,6155,2586,3707,2568, 907,3178, 254,2947, 186,1845,4650, # 3152
+ 745, 432,1757, 428,1633, 888,2246,2221,2489,3611,2118,1258,1265, 956,3127,1784, # 3168
+4337,2490, 319, 510, 119, 457,3612, 274,2035,2007,4651,1409,3128, 970,2758, 590, # 3184
+2800, 661,2247,4652,2008,3950,1420,1549,3080,3322,3951,1651,1375,2111, 485,2491, # 3200
+1429,1156,6156,2548,2183,1495, 831,1840,2529,2446, 501,1657, 307,1894,3247,1341, # 3216
+ 666, 899,2156,1539,2549,1559, 886, 349,2208,3081,2305,1736,3824,2170,2759,1014, # 3232
+1913,1386, 542,1397,2948, 490, 368, 716, 362, 159, 282,2569,1129,1658,1288,1750, # 3248
+2674, 276, 649,2016, 751,1496, 658,1818,1284,1862,2209,2087,2512,3451, 622,2834, # 3264
+ 376, 117,1060,2053,1208,1721,1101,1443, 247,1250,3179,1792,3952,2760,2398,3953, # 3280
+6157,2144,3708, 446,2432,1151,2570,3452,2447,2761,2835,1210,2448,3082, 424,2222, # 3296
+1251,2449,2119,2836, 504,1581,4338, 602, 817, 857,3825,2349,2306, 357,3826,1470, # 3312
+1883,2883, 255, 958, 929,2917,3248, 302,4653,1050,1271,1751,2307,1952,1430,2697, # 3328
+2719,2359, 354,3180, 777, 158,2036,4339,1659,4340,4654,2308,2949,2248,1146,2232, # 3344
+3532,2720,1696,2623,3827,6158,3129,1550,2698,1485,1297,1428, 637, 931,2721,2145, # 3360
+ 914,2550,2587,  81,2450, 612, 827,2646,1242,4655,1118,2884, 472,1855,3181,3533, # 3376
+3534, 569,1353,2699,1244,1758,2588,4119,2009,2762,2171,3709,1312,1531,6159,1152, # 3392
+1938, 134,1830, 471,3710,2276,1112,1535,3323,3453,3535, 982,1337,2950, 488, 826, # 3408
+ 674,1058,1628,4120,2017, 522,2399, 211, 568,1367,3454, 350, 293,1872,1139,3249, # 3424
+1399,1946,3006,1300,2360,3324, 588, 736,6160,2606, 744, 669,3536,3828,6161,1358, # 3440
+ 199, 723, 848, 933, 851,1939,1505,1514,1338,1618,1831,4656,1634,3613, 443,2740, # 3456
+3829, 717,1947, 491,1914,6162,2551,1542,4121,1025,6163,1099,1223, 198,3040,2722, # 3472
+ 370, 410,1905,2589, 998,1248,3182,2380, 519,1449,4122,1710, 947, 928,1153,4341, # 3488
+2277, 344,2624,1511, 615, 105, 161,1212,1076,1960,3130,2054,1926,1175,1906,2473, # 3504
+ 414,1873,2801,6164,2309, 315,1319,3325, 318,2018,2146,2157, 963, 631, 223,4342, # 3520
+4343,2675, 479,3711,1197,2625,3712,2676,2361,6165,4344,4123,6166,2451,3183,1886, # 3536
+2184,1674,1330,1711,1635,1506, 799, 219,3250,3083,3954,1677,3713,3326,2081,3614, # 3552
+1652,2073,4657,1147,3041,1752, 643,1961, 147,1974,3955,6167,1716,2037, 918,3007, # 3568
+1994, 120,1537, 118, 609,3184,4345, 740,3455,1219, 332,1615,3830,6168,1621,2980, # 3584
+1582, 783, 212, 553,2350,3714,1349,2433,2082,4124, 889,6169,2310,1275,1410, 973, # 3600
+ 166,1320,3456,1797,1215,3185,2885,1846,2590,2763,4658, 629, 822,3008, 763, 940, # 3616
+1990,2862, 439,2409,1566,1240,1622, 926,1282,1907,2764, 654,2210,1607, 327,1130, # 3632
+3956,1678,1623,6170,2434,2192, 686, 608,3831,3715, 903,3957,3042,6171,2741,1522, # 3648
+1915,1105,1555,2552,1359, 323,3251,4346,3457, 738,1354,2553,2311,2334,1828,2003, # 3664
+3832,1753,2351,1227,6172,1887,4125,1478,6173,2410,1874,1712,1847, 520,1204,2607, # 3680
+ 264,4659, 836,2677,2102, 600,4660,3833,2278,3084,6174,4347,3615,1342, 640, 532, # 3696
+ 543,2608,1888,2400,2591,1009,4348,1497, 341,1737,3616,2723,1394, 529,3252,1321, # 3712
+ 983,4661,1515,2120, 971,2592, 924, 287,1662,3186,4349,2700,4350,1519, 908,1948, # 3728
+2452, 156, 796,1629,1486,2223,2055, 694,4126,1259,1036,3392,1213,2249,2742,1889, # 3744
+1230,3958,1015, 910, 408, 559,3617,4662, 746, 725, 935,4663,3959,3009,1289, 563, # 3760
+ 867,4664,3960,1567,2981,2038,2626, 988,2263,2381,4351, 143,2374, 704,1895,6175, # 3776
+1188,3716,2088, 673,3085,2362,4352, 484,1608,1921,2765,2918, 215, 904,3618,3537, # 3792
+ 894, 509, 976,3043,2701,3961,4353,2837,2982, 498,6176,6177,1102,3538,1332,3393, # 3808
+1487,1636,1637, 233, 245,3962, 383, 650, 995,3044, 460,1520,1206,2352, 749,3327, # 3824
+ 530, 700, 389,1438,1560,1773,3963,2264, 719,2951,2724,3834, 870,1832,1644,1000, # 3840
+ 839,2474,3717, 197,1630,3394, 365,2886,3964,1285,2133, 734, 922, 818,1106, 732, # 3856
+ 480,2083,1774,3458, 923,2279,1350, 221,3086,  85,2233,2234,3835,1585,3010,2147, # 3872
+1387,1705,2382,1619,2475, 133, 239,2802,1991,1016,2084,2383, 411,2838,1113, 651, # 3888
+1985,1160,3328, 990,1863,3087,1048,1276,2647, 265,2627,1599,3253,2056, 150, 638, # 3904
+2019, 656, 853, 326,1479, 680,1439,4354,1001,1759, 413,3459,3395,2492,1431, 459, # 3920
+4355,1125,3329,2265,1953,1450,2065,2863, 849, 351,2678,3131,3254,3255,1104,1577, # 3936
+ 227,1351,1645,2453,2193,1421,2887, 812,2121, 634,  95,2435, 201,2312,4665,1646, # 3952
+1671,2743,1601,2554,2702,2648,2280,1315,1366,2089,3132,1573,3718,3965,1729,1189, # 3968
+ 328,2679,1077,1940,1136, 558,1283, 964,1195, 621,2074,1199,1743,3460,3619,1896, # 3984
+1916,1890,3836,2952,1154,2112,1064, 862, 378,3011,2066,2113,2803,1568,2839,6178, # 4000
+3088,2919,1941,1660,2004,1992,2194, 142, 707,1590,1708,1624,1922,1023,1836,1233, # 4016
+1004,2313, 789, 741,3620,6179,1609,2411,1200,4127,3719,3720,4666,2057,3721, 593, # 4032
+2840, 367,2920,1878,6180,3461,1521, 628,1168, 692,2211,2649, 300, 720,2067,2571, # 4048
+2953,3396, 959,2504,3966,3539,3462,1977, 701,6181, 954,1043, 800, 681, 183,3722, # 4064
+1803,1730,3540,4128,2103, 815,2314, 174, 467, 230,2454,1093,2134, 755,3541,3397, # 4080
+1141,1162,6182,1738,2039, 270,3256,2513,1005,1647,2185,3837, 858,1679,1897,1719, # 4096
+2954,2324,1806, 402, 670, 167,4129,1498,2158,2104, 750,6183, 915, 189,1680,1551, # 4112
+ 455,4356,1501,2455, 405,1095,2955, 338,1586,1266,1819, 570, 641,1324, 237,1556, # 4128
+2650,1388,3723,6184,1368,2384,1343,1978,3089,2436, 879,3724, 792,1191, 758,3012, # 4144
+1411,2135,1322,4357, 240,4667,1848,3725,1574,6185, 420,3045,1546,1391, 714,4358, # 4160
+1967, 941,1864, 863, 664, 426, 560,1731,2680,1785,2864,1949,2363, 403,3330,1415, # 4176
+1279,2136,1697,2335, 204, 721,2097,3838,  90,6186,2085,2505, 191,3967, 124,2148, # 4192
+1376,1798,1178,1107,1898,1405, 860,4359,1243,1272,2375,2983,1558,2456,1638, 113, # 4208
+3621, 578,1923,2609, 880, 386,4130, 784,2186,2266,1422,2956,2172,1722, 497, 263, # 4224
+2514,1267,2412,2610, 177,2703,3542, 774,1927,1344, 616,1432,1595,1018, 172,4360, # 4240
+2325, 911,4361, 438,1468,3622, 794,3968,2024,2173,1681,1829,2957, 945, 895,3090, # 4256
+ 575,2212,2476, 475,2401,2681, 785,2744,1745,2293,2555,1975,3133,2865, 394,4668, # 4272
+3839, 635,4131, 639, 202,1507,2195,2766,1345,1435,2572,3726,1908,1184,1181,2457, # 4288
+3727,3134,4362, 843,2611, 437, 916,4669, 234, 769,1884,3046,3047,3623, 833,6187, # 4304
+1639,2250,2402,1355,1185,2010,2047, 999, 525,1732,1290,1488,2612, 948,1578,3728, # 4320
+2413,2477,1216,2725,2159, 334,3840,1328,3624,2921,1525,4132, 564,1056, 891,4363, # 4336
+1444,1698,2385,2251,3729,1365,2281,2235,1717,6188, 864,3841,2515, 444, 527,2767, # 4352
+2922,3625, 544, 461,6189, 566, 209,2437,3398,2098,1065,2068,3331,3626,3257,2137, # 4368  #last 512
+)
+# fmt: on

venv/lib/python3.10/site-packages/chardet/macromanprober.py

@@ -0,0 +1,162 @@
+######################## BEGIN LICENSE BLOCK ########################
+# This code was modified from latin1prober.py by Rob Speer <[email protected]>.
+# The Original Code is Mozilla Universal charset detector code.
+#
+# The Initial Developer of the Original Code is
+# Netscape Communications Corporation.
+# Portions created by the Initial Developer are Copyright (C) 2001
+# the Initial Developer. All Rights Reserved.
+#
+# Contributor(s):
+#   Rob Speer - adapt to MacRoman encoding
+#   Mark Pilgrim - port to Python
+#   Shy Shalom - original C code
+#
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
+# 02110-1301  USA
+######################### END LICENSE BLOCK #########################
+
+from typing import List, Union
+
+from .charsetprober import CharSetProber
+from .enums import ProbingState
+
+FREQ_CAT_NUM = 4
+
+UDF = 0  # undefined
+OTH = 1  # other
+ASC = 2  # ascii capital letter
+ASS = 3  # ascii small letter
+ACV = 4  # accent capital vowel
+ACO = 5  # accent capital other
+ASV = 6  # accent small vowel
+ASO = 7  # accent small other
+ODD = 8  # character that is unlikely to appear
+CLASS_NUM = 9  # total classes
+
+# The change from Latin1 is that we explicitly look for extended characters
+# that are infrequently-occurring symbols, and consider them to always be
+# improbable. This should let MacRoman get out of the way of more likely
+# encodings in most situations.
+
+# fmt: off
+MacRoman_CharToClass = (
+    OTH, OTH, OTH, OTH, OTH, OTH, OTH, OTH,  # 00 - 07
+    OTH, OTH, OTH, OTH, OTH, OTH, OTH, OTH,  # 08 - 0F
+    OTH, OTH, OTH, OTH, OTH, OTH, OTH, OTH,  # 10 - 17
+    OTH, OTH, OTH, OTH, OTH, OTH, OTH, OTH,  # 18 - 1F
+    OTH, OTH, OTH, OTH, OTH, OTH, OTH, OTH,  # 20 - 27
+    OTH, OTH, OTH, OTH, OTH, OTH, OTH, OTH,  # 28 - 2F
+    OTH, OTH, OTH, OTH, OTH, OTH, OTH, OTH,  # 30 - 37
+    OTH, OTH, OTH, OTH, OTH, OTH, OTH, OTH,  # 38 - 3F
+    OTH, ASC, ASC, ASC, ASC, ASC, ASC, ASC,  # 40 - 47
+    ASC, ASC, ASC, ASC, ASC, ASC, ASC, ASC,  # 48 - 4F
+    ASC, ASC, ASC, ASC, ASC, ASC, ASC, ASC,  # 50 - 57
+    ASC, ASC, ASC, OTH, OTH, OTH, OTH, OTH,  # 58 - 5F
+    OTH, ASS, ASS, ASS, ASS, ASS, ASS, ASS,  # 60 - 67
+    ASS, ASS, ASS, ASS, ASS, ASS, ASS, ASS,  # 68 - 6F
+    ASS, ASS, ASS, ASS, ASS, ASS, ASS, ASS,  # 70 - 77
+    ASS, ASS, ASS, OTH, OTH, OTH, OTH, OTH,  # 78 - 7F
+    ACV, ACV, ACO, ACV, ACO, ACV, ACV, ASV,  # 80 - 87
+    ASV, ASV, ASV, ASV, ASV, ASO, ASV, ASV,  # 88 - 8F
+    ASV, ASV, ASV, ASV, ASV, ASV, ASO, ASV,  # 90 - 97
+    ASV, ASV, ASV, ASV, ASV, ASV, ASV, ASV,  # 98 - 9F
+    OTH, OTH, OTH, OTH, OTH, OTH, OTH, ASO,  # A0 - A7
+    OTH, OTH, ODD, ODD, OTH, OTH, ACV, ACV,  # A8 - AF
+    OTH, OTH, OTH, OTH, OTH, OTH, OTH, OTH,  # B0 - B7
+    OTH, OTH, OTH, OTH, OTH, OTH, ASV, ASV,  # B8 - BF
+    OTH, OTH, ODD, OTH, ODD, OTH, OTH, OTH,  # C0 - C7
+    OTH, OTH, OTH, ACV, ACV, ACV, ACV, ASV,  # C8 - CF
+    OTH, OTH, OTH, OTH, OTH, OTH, OTH, ODD,  # D0 - D7
+    ASV, ACV, ODD, OTH, OTH, OTH, OTH, OTH,  # D8 - DF
+    OTH, OTH, OTH, OTH, OTH, ACV, ACV, ACV,  # E0 - E7
+    ACV, ACV, ACV, ACV, ACV, ACV, ACV, ACV,  # E8 - EF
+    ODD, ACV, ACV, ACV, ACV, ASV, ODD, ODD,  # F0 - F7
+    ODD, ODD, ODD, ODD, ODD, ODD, ODD, ODD,  # F8 - FF
+)
+
+# 0 : illegal
+# 1 : very unlikely
+# 2 : normal
+# 3 : very likely
+MacRomanClassModel = (
+# UDF OTH ASC ASS ACV ACO ASV ASO ODD
+    0,  0,  0,  0,  0,  0,  0,  0,  0,  # UDF
+    0,  3,  3,  3,  3,  3,  3,  3,  1,  # OTH
+    0,  3,  3,  3,  3,  3,  3,  3,  1,  # ASC
+    0,  3,  3,  3,  1,  1,  3,  3,  1,  # ASS
+    0,  3,  3,  3,  1,  2,  1,  2,  1,  # ACV
+    0,  3,  3,  3,  3,  3,  3,  3,  1,  # ACO
+    0,  3,  1,  3,  1,  1,  1,  3,  1,  # ASV
+    0,  3,  1,  3,  1,  1,  3,  3,  1,  # ASO
+    0,  1,  1,  1,  1,  1,  1,  1,  1,  # ODD
+)
+# fmt: on
+
+
+class MacRomanProber(CharSetProber):
+    def __init__(self) -> None:
+        super().__init__()
+        self._last_char_class = OTH
+        self._freq_counter: List[int] = []
+        self.reset()
+
+    def reset(self) -> None:
+        self._last_char_class = OTH
+        self._freq_counter = [0] * FREQ_CAT_NUM
+
+        # express the prior that MacRoman is a somewhat rare encoding;
+        # this can be done by starting out in a slightly improbable state
+        # that must be overcome
+        self._freq_counter[2] = 10
+
+        super().reset()
+
+    @property
+    def charset_name(self) -> str:
+        return "MacRoman"
+
+    @property
+    def language(self) -> str:
+        return ""
+
+    def feed(self, byte_str: Union[bytes, bytearray]) -> ProbingState:
+        byte_str = self.remove_xml_tags(byte_str)
+        for c in byte_str:
+            char_class = MacRoman_CharToClass[c]
+            freq = MacRomanClassModel[(self._last_char_class * CLASS_NUM) + char_class]
+            if freq == 0:
+                self._state = ProbingState.NOT_ME
+                break
+            self._freq_counter[freq] += 1
+            self._last_char_class = char_class
+
+        return self.state
+
+    def get_confidence(self) -> float:
+        if self.state == ProbingState.NOT_ME:
+            return 0.01
+
+        total = sum(self._freq_counter)
+        confidence = (
+            0.0
+            if total < 0.01
+            else (self._freq_counter[3] - self._freq_counter[1] * 20.0) / total
+        )
+        confidence = max(confidence, 0.0)
+        # lower the confidence of MacRoman so that other more accurate
+        # detector can take priority.
+        confidence *= 0.73
+        return confidence

venv/lib/python3.10/site-packages/chardet/mbcharsetprober.py

@@ -0,0 +1,95 @@
+######################## BEGIN LICENSE BLOCK ########################
+# The Original Code is Mozilla Universal charset detector code.
+#
+# The Initial Developer of the Original Code is
+# Netscape Communications Corporation.
+# Portions created by the Initial Developer are Copyright (C) 2001
+# the Initial Developer. All Rights Reserved.
+#
+# Contributor(s):
+#   Mark Pilgrim - port to Python
+#   Shy Shalom - original C code
+#   Proofpoint, Inc.
+#
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
+# 02110-1301  USA
+######################### END LICENSE BLOCK #########################
+
+from typing import Optional, Union
+
+from .chardistribution import CharDistributionAnalysis
+from .charsetprober import CharSetProber
+from .codingstatemachine import CodingStateMachine
+from .enums import LanguageFilter, MachineState, ProbingState
+
+
+class MultiByteCharSetProber(CharSetProber):
+    """
+    MultiByteCharSetProber
+    """
+
+    def __init__(self, lang_filter: LanguageFilter = LanguageFilter.NONE) -> None:
+        super().__init__(lang_filter=lang_filter)
+        self.distribution_analyzer: Optional[CharDistributionAnalysis] = None
+        self.coding_sm: Optional[CodingStateMachine] = None
+        self._last_char = bytearray(b"\0\0")
+
+    def reset(self) -> None:
+        super().reset()
+        if self.coding_sm:
+            self.coding_sm.reset()
+        if self.distribution_analyzer:
+            self.distribution_analyzer.reset()
+        self._last_char = bytearray(b"\0\0")
+
+    def feed(self, byte_str: Union[bytes, bytearray]) -> ProbingState:
+        assert self.coding_sm is not None
+        assert self.distribution_analyzer is not None
+
+        for i, byte in enumerate(byte_str):
+            coding_state = self.coding_sm.next_state(byte)
+            if coding_state == MachineState.ERROR:
+                self.logger.debug(
+                    "%s %s prober hit error at byte %s",
+                    self.charset_name,
+                    self.language,
+                    i,
+                )
+                self._state = ProbingState.NOT_ME
+                break
+            if coding_state == MachineState.ITS_ME:
+                self._state = ProbingState.FOUND_IT
+                break
+            if coding_state == MachineState.START:
+                char_len = self.coding_sm.get_current_charlen()
+                if i == 0:
+                    self._last_char[1] = byte
+                    self.distribution_analyzer.feed(self._last_char, char_len)
+                else:
+                    self.distribution_analyzer.feed(byte_str[i - 1 : i + 1], char_len)
+
+        self._last_char[0] = byte_str[-1]
+
+        if self.state == ProbingState.DETECTING:
+            if self.distribution_analyzer.got_enough_data() and (
+                self.get_confidence() > self.SHORTCUT_THRESHOLD
+            ):
+                self._state = ProbingState.FOUND_IT
+
+        return self.state
+
+    def get_confidence(self) -> float:
+        assert self.distribution_analyzer is not None
+        return self.distribution_analyzer.get_confidence()

venv/lib/python3.10/site-packages/chardet/mbcsgroupprober.py

@@ -0,0 +1,57 @@
+######################## BEGIN LICENSE BLOCK ########################
+# The Original Code is Mozilla Universal charset detector code.
+#
+# The Initial Developer of the Original Code is
+# Netscape Communications Corporation.
+# Portions created by the Initial Developer are Copyright (C) 2001
+# the Initial Developer. All Rights Reserved.
+#
+# Contributor(s):
+#   Mark Pilgrim - port to Python
+#   Shy Shalom - original C code
+#   Proofpoint, Inc.
+#
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
+# 02110-1301  USA
+######################### END LICENSE BLOCK #########################
+
+from .big5prober import Big5Prober
+from .charsetgroupprober import CharSetGroupProber
+from .cp949prober import CP949Prober
+from .enums import LanguageFilter
+from .eucjpprober import EUCJPProber
+from .euckrprober import EUCKRProber
+from .euctwprober import EUCTWProber
+from .gb2312prober import GB2312Prober
+from .johabprober import JOHABProber
+from .sjisprober import SJISProber
+from .utf8prober import UTF8Prober
+
+
+class MBCSGroupProber(CharSetGroupProber):
+    def __init__(self, lang_filter: LanguageFilter = LanguageFilter.NONE) -> None:
+        super().__init__(lang_filter=lang_filter)
+        self.probers = [
+            UTF8Prober(),
+            SJISProber(),
+            EUCJPProber(),
+            GB2312Prober(),
+            EUCKRProber(),
+            CP949Prober(),
+            Big5Prober(),
+            EUCTWProber(),
+            JOHABProber(),
+        ]
+        self.reset()

venv/lib/python3.10/site-packages/chardet/mbcssm.py

@@ -0,0 +1,661 @@
+######################## BEGIN LICENSE BLOCK ########################
+# The Original Code is mozilla.org code.
+#
+# The Initial Developer of the Original Code is
+# Netscape Communications Corporation.
+# Portions created by the Initial Developer are Copyright (C) 1998
+# the Initial Developer. All Rights Reserved.
+#
+# Contributor(s):
+#   Mark Pilgrim - port to Python
+#
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
+# 02110-1301  USA
+######################### END LICENSE BLOCK #########################
+
+from .codingstatemachinedict import CodingStateMachineDict
+from .enums import MachineState
+
+# BIG5
+
+# fmt: off
+BIG5_CLS = (
+    1, 1, 1, 1, 1, 1, 1, 1,  # 00 - 07    #allow 0x00 as legal value
+    1, 1, 1, 1, 1, 1, 0, 0,  # 08 - 0f
+    1, 1, 1, 1, 1, 1, 1, 1,  # 10 - 17
+    1, 1, 1, 0, 1, 1, 1, 1,  # 18 - 1f
+    1, 1, 1, 1, 1, 1, 1, 1,  # 20 - 27
+    1, 1, 1, 1, 1, 1, 1, 1,  # 28 - 2f
+    1, 1, 1, 1, 1, 1, 1, 1,  # 30 - 37
+    1, 1, 1, 1, 1, 1, 1, 1,  # 38 - 3f
+    2, 2, 2, 2, 2, 2, 2, 2,  # 40 - 47
+    2, 2, 2, 2, 2, 2, 2, 2,  # 48 - 4f
+    2, 2, 2, 2, 2, 2, 2, 2,  # 50 - 57
+    2, 2, 2, 2, 2, 2, 2, 2,  # 58 - 5f
+    2, 2, 2, 2, 2, 2, 2, 2,  # 60 - 67
+    2, 2, 2, 2, 2, 2, 2, 2,  # 68 - 6f
+    2, 2, 2, 2, 2, 2, 2, 2,  # 70 - 77
+    2, 2, 2, 2, 2, 2, 2, 1,  # 78 - 7f
+    4, 4, 4, 4, 4, 4, 4, 4,  # 80 - 87
+    4, 4, 4, 4, 4, 4, 4, 4,  # 88 - 8f
+    4, 4, 4, 4, 4, 4, 4, 4,  # 90 - 97
+    4, 4, 4, 4, 4, 4, 4, 4,  # 98 - 9f
+    4, 3, 3, 3, 3, 3, 3, 3,  # a0 - a7
+    3, 3, 3, 3, 3, 3, 3, 3,  # a8 - af
+    3, 3, 3, 3, 3, 3, 3, 3,  # b0 - b7
+    3, 3, 3, 3, 3, 3, 3, 3,  # b8 - bf
+    3, 3, 3, 3, 3, 3, 3, 3,  # c0 - c7
+    3, 3, 3, 3, 3, 3, 3, 3,  # c8 - cf
+    3, 3, 3, 3, 3, 3, 3, 3,  # d0 - d7
+    3, 3, 3, 3, 3, 3, 3, 3,  # d8 - df
+    3, 3, 3, 3, 3, 3, 3, 3,  # e0 - e7
+    3, 3, 3, 3, 3, 3, 3, 3,  # e8 - ef
+    3, 3, 3, 3, 3, 3, 3, 3,  # f0 - f7
+    3, 3, 3, 3, 3, 3, 3, 0  # f8 - ff
+)
+
+BIG5_ST = (
+    MachineState.ERROR,MachineState.START,MachineState.START,     3,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,#00-07
+    MachineState.ERROR,MachineState.ERROR,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ERROR,#08-0f
+    MachineState.ERROR,MachineState.START,MachineState.START,MachineState.START,MachineState.START,MachineState.START,MachineState.START,MachineState.START#10-17
+)
+# fmt: on
+
+BIG5_CHAR_LEN_TABLE = (0, 1, 1, 2, 0)
+
+BIG5_SM_MODEL: CodingStateMachineDict = {
+    "class_table": BIG5_CLS,
+    "class_factor": 5,
+    "state_table": BIG5_ST,
+    "char_len_table": BIG5_CHAR_LEN_TABLE,
+    "name": "Big5",
+}
+
+# CP949
+# fmt: off
+CP949_CLS  = (
+    1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0,  # 00 - 0f
+    1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1,  # 10 - 1f
+    1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,  # 20 - 2f
+    1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,  # 30 - 3f
+    1, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4,  # 40 - 4f
+    4, 4, 5, 5, 5, 5, 5, 5, 5, 5, 5, 1, 1, 1, 1, 1,  # 50 - 5f
+    1, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5,  # 60 - 6f
+    5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 1, 1, 1, 1, 1,  # 70 - 7f
+    0, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6,  # 80 - 8f
+    6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6,  # 90 - 9f
+    6, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 8, 8, 8,  # a0 - af
+    7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7,  # b0 - bf
+    7, 7, 7, 7, 7, 7, 9, 2, 2, 3, 2, 2, 2, 2, 2, 2,  # c0 - cf
+    2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,  # d0 - df
+    2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,  # e0 - ef
+    2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 0,  # f0 - ff
+)
+
+CP949_ST = (
+#cls=    0      1      2      3      4      5      6      7      8      9  # previous state =
+    MachineState.ERROR,MachineState.START,     3,MachineState.ERROR,MachineState.START,MachineState.START,     4,     5,MachineState.ERROR,     6, # MachineState.START
+    MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR, # MachineState.ERROR
+    MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME, # MachineState.ITS_ME
+    MachineState.ERROR,MachineState.ERROR,MachineState.START,MachineState.START,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.START,MachineState.START,MachineState.START, # 3
+    MachineState.ERROR,MachineState.ERROR,MachineState.START,MachineState.START,MachineState.START,MachineState.START,MachineState.START,MachineState.START,MachineState.START,MachineState.START, # 4
+    MachineState.ERROR,MachineState.START,MachineState.START,MachineState.START,MachineState.START,MachineState.START,MachineState.START,MachineState.START,MachineState.START,MachineState.START, # 5
+    MachineState.ERROR,MachineState.START,MachineState.START,MachineState.START,MachineState.START,MachineState.ERROR,MachineState.ERROR,MachineState.START,MachineState.START,MachineState.START, # 6
+)
+# fmt: on
+
+CP949_CHAR_LEN_TABLE = (0, 1, 2, 0, 1, 1, 2, 2, 0, 2)
+
+CP949_SM_MODEL: CodingStateMachineDict = {
+    "class_table": CP949_CLS,
+    "class_factor": 10,
+    "state_table": CP949_ST,
+    "char_len_table": CP949_CHAR_LEN_TABLE,
+    "name": "CP949",
+}
+
+# EUC-JP
+# fmt: off
+EUCJP_CLS = (
+    4, 4, 4, 4, 4, 4, 4, 4,  # 00 - 07
+    4, 4, 4, 4, 4, 4, 5, 5,  # 08 - 0f
+    4, 4, 4, 4, 4, 4, 4, 4,  # 10 - 17
+    4, 4, 4, 5, 4, 4, 4, 4,  # 18 - 1f
+    4, 4, 4, 4, 4, 4, 4, 4,  # 20 - 27
+    4, 4, 4, 4, 4, 4, 4, 4,  # 28 - 2f
+    4, 4, 4, 4, 4, 4, 4, 4,  # 30 - 37
+    4, 4, 4, 4, 4, 4, 4, 4,  # 38 - 3f
+    4, 4, 4, 4, 4, 4, 4, 4,  # 40 - 47
+    4, 4, 4, 4, 4, 4, 4, 4,  # 48 - 4f
+    4, 4, 4, 4, 4, 4, 4, 4,  # 50 - 57
+    4, 4, 4, 4, 4, 4, 4, 4,  # 58 - 5f
+    4, 4, 4, 4, 4, 4, 4, 4,  # 60 - 67
+    4, 4, 4, 4, 4, 4, 4, 4,  # 68 - 6f
+    4, 4, 4, 4, 4, 4, 4, 4,  # 70 - 77
+    4, 4, 4, 4, 4, 4, 4, 4,  # 78 - 7f
+    5, 5, 5, 5, 5, 5, 5, 5,  # 80 - 87
+    5, 5, 5, 5, 5, 5, 1, 3,  # 88 - 8f
+    5, 5, 5, 5, 5, 5, 5, 5,  # 90 - 97
+    5, 5, 5, 5, 5, 5, 5, 5,  # 98 - 9f
+    5, 2, 2, 2, 2, 2, 2, 2,  # a0 - a7
+    2, 2, 2, 2, 2, 2, 2, 2,  # a8 - af
+    2, 2, 2, 2, 2, 2, 2, 2,  # b0 - b7
+    2, 2, 2, 2, 2, 2, 2, 2,  # b8 - bf
+    2, 2, 2, 2, 2, 2, 2, 2,  # c0 - c7
+    2, 2, 2, 2, 2, 2, 2, 2,  # c8 - cf
+    2, 2, 2, 2, 2, 2, 2, 2,  # d0 - d7
+    2, 2, 2, 2, 2, 2, 2, 2,  # d8 - df
+    0, 0, 0, 0, 0, 0, 0, 0,  # e0 - e7
+    0, 0, 0, 0, 0, 0, 0, 0,  # e8 - ef
+    0, 0, 0, 0, 0, 0, 0, 0,  # f0 - f7
+    0, 0, 0, 0, 0, 0, 0, 5  # f8 - ff
+)
+
+EUCJP_ST = (
+          3,     4,     3,     5,MachineState.START,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,#00-07
+     MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,#08-0f
+     MachineState.ITS_ME,MachineState.ITS_ME,MachineState.START,MachineState.ERROR,MachineState.START,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,#10-17
+     MachineState.ERROR,MachineState.ERROR,MachineState.START,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,     3,MachineState.ERROR,#18-1f
+          3,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.START,MachineState.START,MachineState.START,MachineState.START#20-27
+)
+# fmt: on
+
+EUCJP_CHAR_LEN_TABLE = (2, 2, 2, 3, 1, 0)
+
+EUCJP_SM_MODEL: CodingStateMachineDict = {
+    "class_table": EUCJP_CLS,
+    "class_factor": 6,
+    "state_table": EUCJP_ST,
+    "char_len_table": EUCJP_CHAR_LEN_TABLE,
+    "name": "EUC-JP",
+}
+
+# EUC-KR
+# fmt: off
+EUCKR_CLS  = (
+    1, 1, 1, 1, 1, 1, 1, 1,  # 00 - 07
+    1, 1, 1, 1, 1, 1, 0, 0,  # 08 - 0f
+    1, 1, 1, 1, 1, 1, 1, 1,  # 10 - 17
+    1, 1, 1, 0, 1, 1, 1, 1,  # 18 - 1f
+    1, 1, 1, 1, 1, 1, 1, 1,  # 20 - 27
+    1, 1, 1, 1, 1, 1, 1, 1,  # 28 - 2f
+    1, 1, 1, 1, 1, 1, 1, 1,  # 30 - 37
+    1, 1, 1, 1, 1, 1, 1, 1,  # 38 - 3f
+    1, 1, 1, 1, 1, 1, 1, 1,  # 40 - 47
+    1, 1, 1, 1, 1, 1, 1, 1,  # 48 - 4f
+    1, 1, 1, 1, 1, 1, 1, 1,  # 50 - 57
+    1, 1, 1, 1, 1, 1, 1, 1,  # 58 - 5f
+    1, 1, 1, 1, 1, 1, 1, 1,  # 60 - 67
+    1, 1, 1, 1, 1, 1, 1, 1,  # 68 - 6f
+    1, 1, 1, 1, 1, 1, 1, 1,  # 70 - 77
+    1, 1, 1, 1, 1, 1, 1, 1,  # 78 - 7f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 80 - 87
+    0, 0, 0, 0, 0, 0, 0, 0,  # 88 - 8f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 90 - 97
+    0, 0, 0, 0, 0, 0, 0, 0,  # 98 - 9f
+    0, 2, 2, 2, 2, 2, 2, 2,  # a0 - a7
+    2, 2, 2, 2, 2, 3, 3, 3,  # a8 - af
+    2, 2, 2, 2, 2, 2, 2, 2,  # b0 - b7
+    2, 2, 2, 2, 2, 2, 2, 2,  # b8 - bf
+    2, 2, 2, 2, 2, 2, 2, 2,  # c0 - c7
+    2, 3, 2, 2, 2, 2, 2, 2,  # c8 - cf
+    2, 2, 2, 2, 2, 2, 2, 2,  # d0 - d7
+    2, 2, 2, 2, 2, 2, 2, 2,  # d8 - df
+    2, 2, 2, 2, 2, 2, 2, 2,  # e0 - e7
+    2, 2, 2, 2, 2, 2, 2, 2,  # e8 - ef
+    2, 2, 2, 2, 2, 2, 2, 2,  # f0 - f7
+    2, 2, 2, 2, 2, 2, 2, 0   # f8 - ff
+)
+
+EUCKR_ST = (
+    MachineState.ERROR,MachineState.START,     3,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,#00-07
+    MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ERROR,MachineState.ERROR,MachineState.START,MachineState.START #08-0f
+)
+# fmt: on
+
+EUCKR_CHAR_LEN_TABLE = (0, 1, 2, 0)
+
+EUCKR_SM_MODEL: CodingStateMachineDict = {
+    "class_table": EUCKR_CLS,
+    "class_factor": 4,
+    "state_table": EUCKR_ST,
+    "char_len_table": EUCKR_CHAR_LEN_TABLE,
+    "name": "EUC-KR",
+}
+
+# JOHAB
+# fmt: off
+JOHAB_CLS = (
+    4,4,4,4,4,4,4,4,  # 00 - 07
+    4,4,4,4,4,4,0,0,  # 08 - 0f
+    4,4,4,4,4,4,4,4,  # 10 - 17
+    4,4,4,0,4,4,4,4,  # 18 - 1f
+    4,4,4,4,4,4,4,4,  # 20 - 27
+    4,4,4,4,4,4,4,4,  # 28 - 2f
+    4,3,3,3,3,3,3,3,  # 30 - 37
+    3,3,3,3,3,3,3,3,  # 38 - 3f
+    3,1,1,1,1,1,1,1,  # 40 - 47
+    1,1,1,1,1,1,1,1,  # 48 - 4f
+    1,1,1,1,1,1,1,1,  # 50 - 57
+    1,1,1,1,1,1,1,1,  # 58 - 5f
+    1,1,1,1,1,1,1,1,  # 60 - 67
+    1,1,1,1,1,1,1,1,  # 68 - 6f
+    1,1,1,1,1,1,1,1,  # 70 - 77
+    1,1,1,1,1,1,1,2,  # 78 - 7f
+    6,6,6,6,8,8,8,8,  # 80 - 87
+    8,8,8,8,8,8,8,8,  # 88 - 8f
+    8,7,7,7,7,7,7,7,  # 90 - 97
+    7,7,7,7,7,7,7,7,  # 98 - 9f
+    7,7,7,7,7,7,7,7,  # a0 - a7
+    7,7,7,7,7,7,7,7,  # a8 - af
+    7,7,7,7,7,7,7,7,  # b0 - b7
+    7,7,7,7,7,7,7,7,  # b8 - bf
+    7,7,7,7,7,7,7,7,  # c0 - c7
+    7,7,7,7,7,7,7,7,  # c8 - cf
+    7,7,7,7,5,5,5,5,  # d0 - d7
+    5,9,9,9,9,9,9,5,  # d8 - df
+    9,9,9,9,9,9,9,9,  # e0 - e7
+    9,9,9,9,9,9,9,9,  # e8 - ef
+    9,9,9,9,9,9,9,9,  # f0 - f7
+    9,9,5,5,5,5,5,0   # f8 - ff
+)
+
+JOHAB_ST = (
+# cls = 0                   1                   2                   3                   4                   5                   6                   7                   8                   9
+    MachineState.ERROR ,MachineState.START ,MachineState.START ,MachineState.START ,MachineState.START ,MachineState.ERROR ,MachineState.ERROR ,3                  ,3                  ,4                  ,  # MachineState.START
+    MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,  # MachineState.ITS_ME
+    MachineState.ERROR ,MachineState.ERROR ,MachineState.ERROR ,MachineState.ERROR ,MachineState.ERROR ,MachineState.ERROR ,MachineState.ERROR ,MachineState.ERROR ,MachineState.ERROR ,MachineState.ERROR ,  # MachineState.ERROR
+    MachineState.ERROR ,MachineState.START ,MachineState.START ,MachineState.ERROR ,MachineState.ERROR ,MachineState.START ,MachineState.START ,MachineState.START ,MachineState.START ,MachineState.START ,  # 3
+    MachineState.ERROR ,MachineState.START ,MachineState.ERROR ,MachineState.START ,MachineState.ERROR ,MachineState.START ,MachineState.ERROR ,MachineState.START ,MachineState.ERROR ,MachineState.START ,  # 4
+)
+# fmt: on
+
+JOHAB_CHAR_LEN_TABLE = (0, 1, 1, 1, 1, 0, 0, 2, 2, 2)
+
+JOHAB_SM_MODEL: CodingStateMachineDict = {
+    "class_table": JOHAB_CLS,
+    "class_factor": 10,
+    "state_table": JOHAB_ST,
+    "char_len_table": JOHAB_CHAR_LEN_TABLE,
+    "name": "Johab",
+}
+
+# EUC-TW
+# fmt: off
+EUCTW_CLS = (
+    2, 2, 2, 2, 2, 2, 2, 2,  # 00 - 07
+    2, 2, 2, 2, 2, 2, 0, 0,  # 08 - 0f
+    2, 2, 2, 2, 2, 2, 2, 2,  # 10 - 17
+    2, 2, 2, 0, 2, 2, 2, 2,  # 18 - 1f
+    2, 2, 2, 2, 2, 2, 2, 2,  # 20 - 27
+    2, 2, 2, 2, 2, 2, 2, 2,  # 28 - 2f
+    2, 2, 2, 2, 2, 2, 2, 2,  # 30 - 37
+    2, 2, 2, 2, 2, 2, 2, 2,  # 38 - 3f
+    2, 2, 2, 2, 2, 2, 2, 2,  # 40 - 47
+    2, 2, 2, 2, 2, 2, 2, 2,  # 48 - 4f
+    2, 2, 2, 2, 2, 2, 2, 2,  # 50 - 57
+    2, 2, 2, 2, 2, 2, 2, 2,  # 58 - 5f
+    2, 2, 2, 2, 2, 2, 2, 2,  # 60 - 67
+    2, 2, 2, 2, 2, 2, 2, 2,  # 68 - 6f
+    2, 2, 2, 2, 2, 2, 2, 2,  # 70 - 77
+    2, 2, 2, 2, 2, 2, 2, 2,  # 78 - 7f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 80 - 87
+    0, 0, 0, 0, 0, 0, 6, 0,  # 88 - 8f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 90 - 97
+    0, 0, 0, 0, 0, 0, 0, 0,  # 98 - 9f
+    0, 3, 4, 4, 4, 4, 4, 4,  # a0 - a7
+    5, 5, 1, 1, 1, 1, 1, 1,  # a8 - af
+    1, 1, 1, 1, 1, 1, 1, 1,  # b0 - b7
+    1, 1, 1, 1, 1, 1, 1, 1,  # b8 - bf
+    1, 1, 3, 1, 3, 3, 3, 3,  # c0 - c7
+    3, 3, 3, 3, 3, 3, 3, 3,  # c8 - cf
+    3, 3, 3, 3, 3, 3, 3, 3,  # d0 - d7
+    3, 3, 3, 3, 3, 3, 3, 3,  # d8 - df
+    3, 3, 3, 3, 3, 3, 3, 3,  # e0 - e7
+    3, 3, 3, 3, 3, 3, 3, 3,  # e8 - ef
+    3, 3, 3, 3, 3, 3, 3, 3,  # f0 - f7
+    3, 3, 3, 3, 3, 3, 3, 0   # f8 - ff
+)
+
+EUCTW_ST = (
+    MachineState.ERROR,MachineState.ERROR,MachineState.START,     3,     3,     3,     4,MachineState.ERROR,#00-07
+    MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ITS_ME,MachineState.ITS_ME,#08-0f
+    MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ERROR,MachineState.START,MachineState.ERROR,#10-17
+    MachineState.START,MachineState.START,MachineState.START,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,#18-1f
+         5,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.START,MachineState.ERROR,MachineState.START,MachineState.START,#20-27
+    MachineState.START,MachineState.ERROR,MachineState.START,MachineState.START,MachineState.START,MachineState.START,MachineState.START,MachineState.START #28-2f
+)
+# fmt: on
+
+EUCTW_CHAR_LEN_TABLE = (0, 0, 1, 2, 2, 2, 3)
+
+EUCTW_SM_MODEL: CodingStateMachineDict = {
+    "class_table": EUCTW_CLS,
+    "class_factor": 7,
+    "state_table": EUCTW_ST,
+    "char_len_table": EUCTW_CHAR_LEN_TABLE,
+    "name": "x-euc-tw",
+}
+
+# GB2312
+# fmt: off
+GB2312_CLS = (
+    1, 1, 1, 1, 1, 1, 1, 1,  # 00 - 07
+    1, 1, 1, 1, 1, 1, 0, 0,  # 08 - 0f
+    1, 1, 1, 1, 1, 1, 1, 1,  # 10 - 17
+    1, 1, 1, 0, 1, 1, 1, 1,  # 18 - 1f
+    1, 1, 1, 1, 1, 1, 1, 1,  # 20 - 27
+    1, 1, 1, 1, 1, 1, 1, 1,  # 28 - 2f
+    3, 3, 3, 3, 3, 3, 3, 3,  # 30 - 37
+    3, 3, 1, 1, 1, 1, 1, 1,  # 38 - 3f
+    2, 2, 2, 2, 2, 2, 2, 2,  # 40 - 47
+    2, 2, 2, 2, 2, 2, 2, 2,  # 48 - 4f
+    2, 2, 2, 2, 2, 2, 2, 2,  # 50 - 57
+    2, 2, 2, 2, 2, 2, 2, 2,  # 58 - 5f
+    2, 2, 2, 2, 2, 2, 2, 2,  # 60 - 67
+    2, 2, 2, 2, 2, 2, 2, 2,  # 68 - 6f
+    2, 2, 2, 2, 2, 2, 2, 2,  # 70 - 77
+    2, 2, 2, 2, 2, 2, 2, 4,  # 78 - 7f
+    5, 6, 6, 6, 6, 6, 6, 6,  # 80 - 87
+    6, 6, 6, 6, 6, 6, 6, 6,  # 88 - 8f
+    6, 6, 6, 6, 6, 6, 6, 6,  # 90 - 97
+    6, 6, 6, 6, 6, 6, 6, 6,  # 98 - 9f
+    6, 6, 6, 6, 6, 6, 6, 6,  # a0 - a7
+    6, 6, 6, 6, 6, 6, 6, 6,  # a8 - af
+    6, 6, 6, 6, 6, 6, 6, 6,  # b0 - b7
+    6, 6, 6, 6, 6, 6, 6, 6,  # b8 - bf
+    6, 6, 6, 6, 6, 6, 6, 6,  # c0 - c7
+    6, 6, 6, 6, 6, 6, 6, 6,  # c8 - cf
+    6, 6, 6, 6, 6, 6, 6, 6,  # d0 - d7
+    6, 6, 6, 6, 6, 6, 6, 6,  # d8 - df
+    6, 6, 6, 6, 6, 6, 6, 6,  # e0 - e7
+    6, 6, 6, 6, 6, 6, 6, 6,  # e8 - ef
+    6, 6, 6, 6, 6, 6, 6, 6,  # f0 - f7
+    6, 6, 6, 6, 6, 6, 6, 0   # f8 - ff
+)
+
+GB2312_ST = (
+    MachineState.ERROR,MachineState.START,MachineState.START,MachineState.START,MachineState.START,MachineState.START,     3,MachineState.ERROR,#00-07
+    MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ITS_ME,MachineState.ITS_ME,#08-0f
+    MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ERROR,MachineState.ERROR,MachineState.START,#10-17
+         4,MachineState.ERROR,MachineState.START,MachineState.START,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,#18-1f
+    MachineState.ERROR,MachineState.ERROR,     5,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ITS_ME,MachineState.ERROR,#20-27
+    MachineState.ERROR,MachineState.ERROR,MachineState.START,MachineState.START,MachineState.START,MachineState.START,MachineState.START,MachineState.START #28-2f
+)
+# fmt: on
+
+# To be accurate, the length of class 6 can be either 2 or 4.
+# But it is not necessary to discriminate between the two since
+# it is used for frequency analysis only, and we are validating
+# each code range there as well. So it is safe to set it to be
+# 2 here.
+GB2312_CHAR_LEN_TABLE = (0, 1, 1, 1, 1, 1, 2)
+
+GB2312_SM_MODEL: CodingStateMachineDict = {
+    "class_table": GB2312_CLS,
+    "class_factor": 7,
+    "state_table": GB2312_ST,
+    "char_len_table": GB2312_CHAR_LEN_TABLE,
+    "name": "GB2312",
+}
+
+# Shift_JIS
+# fmt: off
+SJIS_CLS = (
+    1, 1, 1, 1, 1, 1, 1, 1,  # 00 - 07
+    1, 1, 1, 1, 1, 1, 0, 0,  # 08 - 0f
+    1, 1, 1, 1, 1, 1, 1, 1,  # 10 - 17
+    1, 1, 1, 0, 1, 1, 1, 1,  # 18 - 1f
+    1, 1, 1, 1, 1, 1, 1, 1,  # 20 - 27
+    1, 1, 1, 1, 1, 1, 1, 1,  # 28 - 2f
+    1, 1, 1, 1, 1, 1, 1, 1,  # 30 - 37
+    1, 1, 1, 1, 1, 1, 1, 1,  # 38 - 3f
+    2, 2, 2, 2, 2, 2, 2, 2,  # 40 - 47
+    2, 2, 2, 2, 2, 2, 2, 2,  # 48 - 4f
+    2, 2, 2, 2, 2, 2, 2, 2,  # 50 - 57
+    2, 2, 2, 2, 2, 2, 2, 2,  # 58 - 5f
+    2, 2, 2, 2, 2, 2, 2, 2,  # 60 - 67
+    2, 2, 2, 2, 2, 2, 2, 2,  # 68 - 6f
+    2, 2, 2, 2, 2, 2, 2, 2,  # 70 - 77
+    2, 2, 2, 2, 2, 2, 2, 1,  # 78 - 7f
+    3, 3, 3, 3, 3, 2, 2, 3,  # 80 - 87
+    3, 3, 3, 3, 3, 3, 3, 3,  # 88 - 8f
+    3, 3, 3, 3, 3, 3, 3, 3,  # 90 - 97
+    3, 3, 3, 3, 3, 3, 3, 3,  # 98 - 9f
+    #0xa0 is illegal in sjis encoding, but some pages does
+    #contain such byte. We need to be more error forgiven.
+    2, 2, 2, 2, 2, 2, 2, 2,  # a0 - a7
+    2, 2, 2, 2, 2, 2, 2, 2,  # a8 - af
+    2, 2, 2, 2, 2, 2, 2, 2,  # b0 - b7
+    2, 2, 2, 2, 2, 2, 2, 2,  # b8 - bf
+    2, 2, 2, 2, 2, 2, 2, 2,  # c0 - c7
+    2, 2, 2, 2, 2, 2, 2, 2,  # c8 - cf
+    2, 2, 2, 2, 2, 2, 2, 2,  # d0 - d7
+    2, 2, 2, 2, 2, 2, 2, 2,  # d8 - df
+    3, 3, 3, 3, 3, 3, 3, 3,  # e0 - e7
+    3, 3, 3, 3, 3, 4, 4, 4,  # e8 - ef
+    3, 3, 3, 3, 3, 3, 3, 3,  # f0 - f7
+    3, 3, 3, 3, 3, 0, 0, 0,  # f8 - ff
+)
+
+SJIS_ST = (
+    MachineState.ERROR,MachineState.START,MachineState.START,     3,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,#00-07
+    MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,#08-0f
+    MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ERROR,MachineState.ERROR,MachineState.START,MachineState.START,MachineState.START,MachineState.START #10-17
+)
+# fmt: on
+
+SJIS_CHAR_LEN_TABLE = (0, 1, 1, 2, 0, 0)
+
+SJIS_SM_MODEL: CodingStateMachineDict = {
+    "class_table": SJIS_CLS,
+    "class_factor": 6,
+    "state_table": SJIS_ST,
+    "char_len_table": SJIS_CHAR_LEN_TABLE,
+    "name": "Shift_JIS",
+}
+
+# UCS2-BE
+# fmt: off
+UCS2BE_CLS = (
+    0, 0, 0, 0, 0, 0, 0, 0,  # 00 - 07
+    0, 0, 1, 0, 0, 2, 0, 0,  # 08 - 0f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 10 - 17
+    0, 0, 0, 3, 0, 0, 0, 0,  # 18 - 1f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 20 - 27
+    0, 3, 3, 3, 3, 3, 0, 0,  # 28 - 2f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 30 - 37
+    0, 0, 0, 0, 0, 0, 0, 0,  # 38 - 3f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 40 - 47
+    0, 0, 0, 0, 0, 0, 0, 0,  # 48 - 4f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 50 - 57
+    0, 0, 0, 0, 0, 0, 0, 0,  # 58 - 5f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 60 - 67
+    0, 0, 0, 0, 0, 0, 0, 0,  # 68 - 6f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 70 - 77
+    0, 0, 0, 0, 0, 0, 0, 0,  # 78 - 7f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 80 - 87
+    0, 0, 0, 0, 0, 0, 0, 0,  # 88 - 8f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 90 - 97
+    0, 0, 0, 0, 0, 0, 0, 0,  # 98 - 9f
+    0, 0, 0, 0, 0, 0, 0, 0,  # a0 - a7
+    0, 0, 0, 0, 0, 0, 0, 0,  # a8 - af
+    0, 0, 0, 0, 0, 0, 0, 0,  # b0 - b7
+    0, 0, 0, 0, 0, 0, 0, 0,  # b8 - bf
+    0, 0, 0, 0, 0, 0, 0, 0,  # c0 - c7
+    0, 0, 0, 0, 0, 0, 0, 0,  # c8 - cf
+    0, 0, 0, 0, 0, 0, 0, 0,  # d0 - d7
+    0, 0, 0, 0, 0, 0, 0, 0,  # d8 - df
+    0, 0, 0, 0, 0, 0, 0, 0,  # e0 - e7
+    0, 0, 0, 0, 0, 0, 0, 0,  # e8 - ef
+    0, 0, 0, 0, 0, 0, 0, 0,  # f0 - f7
+    0, 0, 0, 0, 0, 0, 4, 5   # f8 - ff
+)
+
+UCS2BE_ST  = (
+          5,     7,     7,MachineState.ERROR,     4,     3,MachineState.ERROR,MachineState.ERROR,#00-07
+     MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,#08-0f
+     MachineState.ITS_ME,MachineState.ITS_ME,     6,     6,     6,     6,MachineState.ERROR,MachineState.ERROR,#10-17
+          6,     6,     6,     6,     6,MachineState.ITS_ME,     6,     6,#18-1f
+          6,     6,     6,     6,     5,     7,     7,MachineState.ERROR,#20-27
+          5,     8,     6,     6,MachineState.ERROR,     6,     6,     6,#28-2f
+          6,     6,     6,     6,MachineState.ERROR,MachineState.ERROR,MachineState.START,MachineState.START #30-37
+)
+# fmt: on
+
+UCS2BE_CHAR_LEN_TABLE = (2, 2, 2, 0, 2, 2)
+
+UCS2BE_SM_MODEL: CodingStateMachineDict = {
+    "class_table": UCS2BE_CLS,
+    "class_factor": 6,
+    "state_table": UCS2BE_ST,
+    "char_len_table": UCS2BE_CHAR_LEN_TABLE,
+    "name": "UTF-16BE",
+}
+
+# UCS2-LE
+# fmt: off
+UCS2LE_CLS = (
+    0, 0, 0, 0, 0, 0, 0, 0,  # 00 - 07
+    0, 0, 1, 0, 0, 2, 0, 0,  # 08 - 0f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 10 - 17
+    0, 0, 0, 3, 0, 0, 0, 0,  # 18 - 1f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 20 - 27
+    0, 3, 3, 3, 3, 3, 0, 0,  # 28 - 2f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 30 - 37
+    0, 0, 0, 0, 0, 0, 0, 0,  # 38 - 3f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 40 - 47
+    0, 0, 0, 0, 0, 0, 0, 0,  # 48 - 4f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 50 - 57
+    0, 0, 0, 0, 0, 0, 0, 0,  # 58 - 5f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 60 - 67
+    0, 0, 0, 0, 0, 0, 0, 0,  # 68 - 6f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 70 - 77
+    0, 0, 0, 0, 0, 0, 0, 0,  # 78 - 7f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 80 - 87
+    0, 0, 0, 0, 0, 0, 0, 0,  # 88 - 8f
+    0, 0, 0, 0, 0, 0, 0, 0,  # 90 - 97
+    0, 0, 0, 0, 0, 0, 0, 0,  # 98 - 9f
+    0, 0, 0, 0, 0, 0, 0, 0,  # a0 - a7
+    0, 0, 0, 0, 0, 0, 0, 0,  # a8 - af
+    0, 0, 0, 0, 0, 0, 0, 0,  # b0 - b7
+    0, 0, 0, 0, 0, 0, 0, 0,  # b8 - bf
+    0, 0, 0, 0, 0, 0, 0, 0,  # c0 - c7
+    0, 0, 0, 0, 0, 0, 0, 0,  # c8 - cf
+    0, 0, 0, 0, 0, 0, 0, 0,  # d0 - d7
+    0, 0, 0, 0, 0, 0, 0, 0,  # d8 - df
+    0, 0, 0, 0, 0, 0, 0, 0,  # e0 - e7
+    0, 0, 0, 0, 0, 0, 0, 0,  # e8 - ef
+    0, 0, 0, 0, 0, 0, 0, 0,  # f0 - f7
+    0, 0, 0, 0, 0, 0, 4, 5   # f8 - ff
+)
+
+UCS2LE_ST = (
+          6,     6,     7,     6,     4,     3,MachineState.ERROR,MachineState.ERROR,#00-07
+     MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,#08-0f
+     MachineState.ITS_ME,MachineState.ITS_ME,     5,     5,     5,MachineState.ERROR,MachineState.ITS_ME,MachineState.ERROR,#10-17
+          5,     5,     5,MachineState.ERROR,     5,MachineState.ERROR,     6,     6,#18-1f
+          7,     6,     8,     8,     5,     5,     5,MachineState.ERROR,#20-27
+          5,     5,     5,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,     5,     5,#28-2f
+          5,     5,     5,MachineState.ERROR,     5,MachineState.ERROR,MachineState.START,MachineState.START #30-37
+)
+# fmt: on
+
+UCS2LE_CHAR_LEN_TABLE = (2, 2, 2, 2, 2, 2)
+
+UCS2LE_SM_MODEL: CodingStateMachineDict = {
+    "class_table": UCS2LE_CLS,
+    "class_factor": 6,
+    "state_table": UCS2LE_ST,
+    "char_len_table": UCS2LE_CHAR_LEN_TABLE,
+    "name": "UTF-16LE",
+}
+
+# UTF-8
+# fmt: off
+UTF8_CLS = (
+    1, 1, 1, 1, 1, 1, 1, 1,  # 00 - 07  #allow 0x00 as a legal value
+    1, 1, 1, 1, 1, 1, 0, 0,  # 08 - 0f
+    1, 1, 1, 1, 1, 1, 1, 1,  # 10 - 17
+    1, 1, 1, 0, 1, 1, 1, 1,  # 18 - 1f
+    1, 1, 1, 1, 1, 1, 1, 1,  # 20 - 27
+    1, 1, 1, 1, 1, 1, 1, 1,  # 28 - 2f
+    1, 1, 1, 1, 1, 1, 1, 1,  # 30 - 37
+    1, 1, 1, 1, 1, 1, 1, 1,  # 38 - 3f
+    1, 1, 1, 1, 1, 1, 1, 1,  # 40 - 47
+    1, 1, 1, 1, 1, 1, 1, 1,  # 48 - 4f
+    1, 1, 1, 1, 1, 1, 1, 1,  # 50 - 57
+    1, 1, 1, 1, 1, 1, 1, 1,  # 58 - 5f
+    1, 1, 1, 1, 1, 1, 1, 1,  # 60 - 67
+    1, 1, 1, 1, 1, 1, 1, 1,  # 68 - 6f
+    1, 1, 1, 1, 1, 1, 1, 1,  # 70 - 77
+    1, 1, 1, 1, 1, 1, 1, 1,  # 78 - 7f
+    2, 2, 2, 2, 3, 3, 3, 3,  # 80 - 87
+    4, 4, 4, 4, 4, 4, 4, 4,  # 88 - 8f
+    4, 4, 4, 4, 4, 4, 4, 4,  # 90 - 97
+    4, 4, 4, 4, 4, 4, 4, 4,  # 98 - 9f
+    5, 5, 5, 5, 5, 5, 5, 5,  # a0 - a7
+    5, 5, 5, 5, 5, 5, 5, 5,  # a8 - af
+    5, 5, 5, 5, 5, 5, 5, 5,  # b0 - b7
+    5, 5, 5, 5, 5, 5, 5, 5,  # b8 - bf
+    0, 0, 6, 6, 6, 6, 6, 6,  # c0 - c7
+    6, 6, 6, 6, 6, 6, 6, 6,  # c8 - cf
+    6, 6, 6, 6, 6, 6, 6, 6,  # d0 - d7
+    6, 6, 6, 6, 6, 6, 6, 6,  # d8 - df
+    7, 8, 8, 8, 8, 8, 8, 8,  # e0 - e7
+    8, 8, 8, 8, 8, 9, 8, 8,  # e8 - ef
+    10, 11, 11, 11, 11, 11, 11, 11,  # f0 - f7
+    12, 13, 13, 13, 14, 15, 0, 0    # f8 - ff
+)
+
+UTF8_ST = (
+    MachineState.ERROR,MachineState.START,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,     12,   10,#00-07
+         9,     11,     8,     7,     6,     5,     4,    3,#08-0f
+    MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,#10-17
+    MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,#18-1f
+    MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,#20-27
+    MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,MachineState.ITS_ME,#28-2f
+    MachineState.ERROR,MachineState.ERROR,     5,     5,     5,     5,MachineState.ERROR,MachineState.ERROR,#30-37
+    MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,#38-3f
+    MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,     5,     5,     5,MachineState.ERROR,MachineState.ERROR,#40-47
+    MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,#48-4f
+    MachineState.ERROR,MachineState.ERROR,     7,     7,     7,     7,MachineState.ERROR,MachineState.ERROR,#50-57
+    MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,#58-5f
+    MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,     7,     7,MachineState.ERROR,MachineState.ERROR,#60-67
+    MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,#68-6f
+    MachineState.ERROR,MachineState.ERROR,     9,     9,     9,     9,MachineState.ERROR,MachineState.ERROR,#70-77
+    MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,#78-7f
+    MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,     9,MachineState.ERROR,MachineState.ERROR,#80-87
+    MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,#88-8f
+    MachineState.ERROR,MachineState.ERROR,    12,    12,    12,    12,MachineState.ERROR,MachineState.ERROR,#90-97
+    MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,#98-9f
+    MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,    12,MachineState.ERROR,MachineState.ERROR,#a0-a7
+    MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,#a8-af
+    MachineState.ERROR,MachineState.ERROR,    12,    12,    12,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,#b0-b7
+    MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,#b8-bf
+    MachineState.ERROR,MachineState.ERROR,MachineState.START,MachineState.START,MachineState.START,MachineState.START,MachineState.ERROR,MachineState.ERROR,#c0-c7
+    MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR,MachineState.ERROR #c8-cf
+)
+# fmt: on
+
+UTF8_CHAR_LEN_TABLE = (0, 1, 0, 0, 0, 0, 2, 3, 3, 3, 4, 4, 5, 5, 6, 6)
+
+UTF8_SM_MODEL: CodingStateMachineDict = {
+    "class_table": UTF8_CLS,
+    "class_factor": 16,
+    "state_table": UTF8_ST,
+    "char_len_table": UTF8_CHAR_LEN_TABLE,
+    "name": "UTF-8",
+}

venv/lib/python3.10/site-packages/chardet/resultdict.py

@@ -0,0 +1,16 @@
+from typing import TYPE_CHECKING, Optional
+
+if TYPE_CHECKING:
+    # TypedDict was introduced in Python 3.8.
+    #
+    # TODO: Remove the else block and TYPE_CHECKING check when dropping support
+    # for Python 3.7.
+    from typing import TypedDict
+
+    class ResultDict(TypedDict):
+        encoding: Optional[str]
+        confidence: float
+        language: Optional[str]
+
+else:
+    ResultDict = dict

venv/lib/python3.10/site-packages/chardet/sbcharsetprober.py

@@ -0,0 +1,162 @@
+######################## BEGIN LICENSE BLOCK ########################
+# The Original Code is Mozilla Universal charset detector code.
+#
+# The Initial Developer of the Original Code is
+# Netscape Communications Corporation.
+# Portions created by the Initial Developer are Copyright (C) 2001
+# the Initial Developer. All Rights Reserved.
+#
+# Contributor(s):
+#   Mark Pilgrim - port to Python
+#   Shy Shalom - original C code
+#
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
+# 02110-1301  USA
+######################### END LICENSE BLOCK #########################
+
+from typing import Dict, List, NamedTuple, Optional, Union
+
+from .charsetprober import CharSetProber
+from .enums import CharacterCategory, ProbingState, SequenceLikelihood
+
+
+class SingleByteCharSetModel(NamedTuple):
+    charset_name: str
+    language: str
+    char_to_order_map: Dict[int, int]
+    language_model: Dict[int, Dict[int, int]]
+    typical_positive_ratio: float
+    keep_ascii_letters: bool
+    alphabet: str
+
+
+class SingleByteCharSetProber(CharSetProber):
+    SAMPLE_SIZE = 64
+    SB_ENOUGH_REL_THRESHOLD = 1024  # 0.25 * SAMPLE_SIZE^2
+    POSITIVE_SHORTCUT_THRESHOLD = 0.95
+    NEGATIVE_SHORTCUT_THRESHOLD = 0.05
+
+    def __init__(
+        self,
+        model: SingleByteCharSetModel,
+        is_reversed: bool = False,
+        name_prober: Optional[CharSetProber] = None,
+    ) -> None:
+        super().__init__()
+        self._model = model
+        # TRUE if we need to reverse every pair in the model lookup
+        self._reversed = is_reversed
+        # Optional auxiliary prober for name decision
+        self._name_prober = name_prober
+        self._last_order = 255
+        self._seq_counters: List[int] = []
+        self._total_seqs = 0
+        self._total_char = 0
+        self._control_char = 0
+        self._freq_char = 0
+        self.reset()
+
+    def reset(self) -> None:
+        super().reset()
+        # char order of last character
+        self._last_order = 255
+        self._seq_counters = [0] * SequenceLikelihood.get_num_categories()
+        self._total_seqs = 0
+        self._total_char = 0
+        self._control_char = 0
+        # characters that fall in our sampling range
+        self._freq_char = 0
+
+    @property
+    def charset_name(self) -> Optional[str]:
+        if self._name_prober:
+            return self._name_prober.charset_name
+        return self._model.charset_name
+
+    @property
+    def language(self) -> Optional[str]:
+        if self._name_prober:
+            return self._name_prober.language
+        return self._model.language
+
+    def feed(self, byte_str: Union[bytes, bytearray]) -> ProbingState:
+        # TODO: Make filter_international_words keep things in self.alphabet
+        if not self._model.keep_ascii_letters:
+            byte_str = self.filter_international_words(byte_str)
+        else:
+            byte_str = self.remove_xml_tags(byte_str)
+        if not byte_str:
+            return self.state
+        char_to_order_map = self._model.char_to_order_map
+        language_model = self._model.language_model
+        for char in byte_str:
+            order = char_to_order_map.get(char, CharacterCategory.UNDEFINED)
+            # XXX: This was SYMBOL_CAT_ORDER before, with a value of 250, but
+            #      CharacterCategory.SYMBOL is actually 253, so we use CONTROL
+            #      to make it closer to the original intent. The only difference
+            #      is whether or not we count digits and control characters for
+            #      _total_char purposes.
+            if order < CharacterCategory.CONTROL:
+                self._total_char += 1
+            if order < self.SAMPLE_SIZE:
+                self._freq_char += 1
+                if self._last_order < self.SAMPLE_SIZE:
+                    self._total_seqs += 1
+                    if not self._reversed:
+                        lm_cat = language_model[self._last_order][order]
+                    else:
+                        lm_cat = language_model[order][self._last_order]
+                    self._seq_counters[lm_cat] += 1
+            self._last_order = order
+
+        charset_name = self._model.charset_name
+        if self.state == ProbingState.DETECTING:
+            if self._total_seqs > self.SB_ENOUGH_REL_THRESHOLD:
+                confidence = self.get_confidence()
+                if confidence > self.POSITIVE_SHORTCUT_THRESHOLD:
+                    self.logger.debug(
+                        "%s confidence = %s, we have a winner", charset_name, confidence
+                    )
+                    self._state = ProbingState.FOUND_IT
+                elif confidence < self.NEGATIVE_SHORTCUT_THRESHOLD:
+                    self.logger.debug(
+                        "%s confidence = %s, below negative shortcut threshold %s",
+                        charset_name,
+                        confidence,
+                        self.NEGATIVE_SHORTCUT_THRESHOLD,
+                    )
+                    self._state = ProbingState.NOT_ME
+
+        return self.state
+
+    def get_confidence(self) -> float:
+        r = 0.01
+        if self._total_seqs > 0:
+            r = (
+                (
+                    self._seq_counters[SequenceLikelihood.POSITIVE]
+                    + 0.25 * self._seq_counters[SequenceLikelihood.LIKELY]
+                )
+                / self._total_seqs
+                / self._model.typical_positive_ratio
+            )
+            # The more control characters (proportionnaly to the size
+            # of the text), the less confident we become in the current
+            # charset.
+            r = r * (self._total_char - self._control_char) / self._total_char
+            r = r * self._freq_char / self._total_char
+            if r >= 1.0:
+                r = 0.99
+        return r

venv/lib/python3.10/site-packages/chardet/utf1632prober.py

@@ -0,0 +1,225 @@
+######################## BEGIN LICENSE BLOCK ########################
+#
+# Contributor(s):
+#   Jason Zavaglia
+#
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
+# 02110-1301  USA
+######################### END LICENSE BLOCK #########################
+from typing import List, Union
+
+from .charsetprober import CharSetProber
+from .enums import ProbingState
+
+
+class UTF1632Prober(CharSetProber):
+    """
+    This class simply looks for occurrences of zero bytes, and infers
+    whether the file is UTF16 or UTF32 (low-endian or big-endian)
+    For instance, files looking like ( \0 \0 \0 [nonzero] )+
+    have a good probability to be UTF32BE.  Files looking like ( \0 [nonzero] )+
+    may be guessed to be UTF16BE, and inversely for little-endian varieties.
+    """
+
+    # how many logical characters to scan before feeling confident of prediction
+    MIN_CHARS_FOR_DETECTION = 20
+    # a fixed constant ratio of expected zeros or non-zeros in modulo-position.
+    EXPECTED_RATIO = 0.94
+
+    def __init__(self) -> None:
+        super().__init__()
+        self.position = 0
+        self.zeros_at_mod = [0] * 4
+        self.nonzeros_at_mod = [0] * 4
+        self._state = ProbingState.DETECTING
+        self.quad = [0, 0, 0, 0]
+        self.invalid_utf16be = False
+        self.invalid_utf16le = False
+        self.invalid_utf32be = False
+        self.invalid_utf32le = False
+        self.first_half_surrogate_pair_detected_16be = False
+        self.first_half_surrogate_pair_detected_16le = False
+        self.reset()
+
+    def reset(self) -> None:
+        super().reset()
+        self.position = 0
+        self.zeros_at_mod = [0] * 4
+        self.nonzeros_at_mod = [0] * 4
+        self._state = ProbingState.DETECTING
+        self.invalid_utf16be = False
+        self.invalid_utf16le = False
+        self.invalid_utf32be = False
+        self.invalid_utf32le = False
+        self.first_half_surrogate_pair_detected_16be = False
+        self.first_half_surrogate_pair_detected_16le = False
+        self.quad = [0, 0, 0, 0]
+
+    @property
+    def charset_name(self) -> str:
+        if self.is_likely_utf32be():
+            return "utf-32be"
+        if self.is_likely_utf32le():
+            return "utf-32le"
+        if self.is_likely_utf16be():
+            return "utf-16be"
+        if self.is_likely_utf16le():
+            return "utf-16le"
+        # default to something valid
+        return "utf-16"
+
+    @property
+    def language(self) -> str:
+        return ""
+
+    def approx_32bit_chars(self) -> float:
+        return max(1.0, self.position / 4.0)
+
+    def approx_16bit_chars(self) -> float:
+        return max(1.0, self.position / 2.0)
+
+    def is_likely_utf32be(self) -> bool:
+        approx_chars = self.approx_32bit_chars()
+        return approx_chars >= self.MIN_CHARS_FOR_DETECTION and (
+            self.zeros_at_mod[0] / approx_chars > self.EXPECTED_RATIO
+            and self.zeros_at_mod[1] / approx_chars > self.EXPECTED_RATIO
+            and self.zeros_at_mod[2] / approx_chars > self.EXPECTED_RATIO
+            and self.nonzeros_at_mod[3] / approx_chars > self.EXPECTED_RATIO
+            and not self.invalid_utf32be
+        )
+
+    def is_likely_utf32le(self) -> bool:
+        approx_chars = self.approx_32bit_chars()
+        return approx_chars >= self.MIN_CHARS_FOR_DETECTION and (
+            self.nonzeros_at_mod[0] / approx_chars > self.EXPECTED_RATIO
+            and self.zeros_at_mod[1] / approx_chars > self.EXPECTED_RATIO
+            and self.zeros_at_mod[2] / approx_chars > self.EXPECTED_RATIO
+            and self.zeros_at_mod[3] / approx_chars > self.EXPECTED_RATIO
+            and not self.invalid_utf32le
+        )
+
+    def is_likely_utf16be(self) -> bool:
+        approx_chars = self.approx_16bit_chars()
+        return approx_chars >= self.MIN_CHARS_FOR_DETECTION and (
+            (self.nonzeros_at_mod[1] + self.nonzeros_at_mod[3]) / approx_chars
+            > self.EXPECTED_RATIO
+            and (self.zeros_at_mod[0] + self.zeros_at_mod[2]) / approx_chars
+            > self.EXPECTED_RATIO
+            and not self.invalid_utf16be
+        )
+
+    def is_likely_utf16le(self) -> bool:
+        approx_chars = self.approx_16bit_chars()
+        return approx_chars >= self.MIN_CHARS_FOR_DETECTION and (
+            (self.nonzeros_at_mod[0] + self.nonzeros_at_mod[2]) / approx_chars
+            > self.EXPECTED_RATIO
+            and (self.zeros_at_mod[1] + self.zeros_at_mod[3]) / approx_chars
+            > self.EXPECTED_RATIO
+            and not self.invalid_utf16le
+        )
+
+    def validate_utf32_characters(self, quad: List[int]) -> None:
+        """
+        Validate if the quad of bytes is valid UTF-32.
+
+        UTF-32 is valid in the range 0x00000000 - 0x0010FFFF
+        excluding 0x0000D800 - 0x0000DFFF
+
+        https://en.wikipedia.org/wiki/UTF-32
+        """
+        if (
+            quad[0] != 0
+            or quad[1] > 0x10
+            or (quad[0] == 0 and quad[1] == 0 and 0xD8 <= quad[2] <= 0xDF)
+        ):
+            self.invalid_utf32be = True
+        if (
+            quad[3] != 0
+            or quad[2] > 0x10
+            or (quad[3] == 0 and quad[2] == 0 and 0xD8 <= quad[1] <= 0xDF)
+        ):
+            self.invalid_utf32le = True
+
+    def validate_utf16_characters(self, pair: List[int]) -> None:
+        """
+        Validate if the pair of bytes is  valid UTF-16.
+
+        UTF-16 is valid in the range 0x0000 - 0xFFFF excluding 0xD800 - 0xFFFF
+        with an exception for surrogate pairs, which must be in the range
+        0xD800-0xDBFF followed by 0xDC00-0xDFFF
+
+        https://en.wikipedia.org/wiki/UTF-16
+        """
+        if not self.first_half_surrogate_pair_detected_16be:
+            if 0xD8 <= pair[0] <= 0xDB:
+                self.first_half_surrogate_pair_detected_16be = True
+            elif 0xDC <= pair[0] <= 0xDF:
+                self.invalid_utf16be = True
+        else:
+            if 0xDC <= pair[0] <= 0xDF:
+                self.first_half_surrogate_pair_detected_16be = False
+            else:
+                self.invalid_utf16be = True
+
+        if not self.first_half_surrogate_pair_detected_16le:
+            if 0xD8 <= pair[1] <= 0xDB:
+                self.first_half_surrogate_pair_detected_16le = True
+            elif 0xDC <= pair[1] <= 0xDF:
+                self.invalid_utf16le = True
+        else:
+            if 0xDC <= pair[1] <= 0xDF:
+                self.first_half_surrogate_pair_detected_16le = False
+            else:
+                self.invalid_utf16le = True
+
+    def feed(self, byte_str: Union[bytes, bytearray]) -> ProbingState:
+        for c in byte_str:
+            mod4 = self.position % 4
+            self.quad[mod4] = c
+            if mod4 == 3:
+                self.validate_utf32_characters(self.quad)
+                self.validate_utf16_characters(self.quad[0:2])
+                self.validate_utf16_characters(self.quad[2:4])
+            if c == 0:
+                self.zeros_at_mod[mod4] += 1
+            else:
+                self.nonzeros_at_mod[mod4] += 1
+            self.position += 1
+        return self.state
+
+    @property
+    def state(self) -> ProbingState:
+        if self._state in {ProbingState.NOT_ME, ProbingState.FOUND_IT}:
+            # terminal, decided states
+            return self._state
+        if self.get_confidence() > 0.80:
+            self._state = ProbingState.FOUND_IT
+        elif self.position > 4 * 1024:
+            # if we get to 4kb into the file, and we can't conclude it's UTF,
+            # let's give up
+            self._state = ProbingState.NOT_ME
+        return self._state
+
+    def get_confidence(self) -> float:
+        return (
+            0.85
+            if (
+                self.is_likely_utf16le()
+                or self.is_likely_utf16be()
+                or self.is_likely_utf32le()
+                or self.is_likely_utf32be()
+            )
+            else 0.00
+        )

venv/lib/python3.10/site-packages/chardet/utf8prober.py

@@ -0,0 +1,82 @@
+######################## BEGIN LICENSE BLOCK ########################
+# The Original Code is mozilla.org code.
+#
+# The Initial Developer of the Original Code is
+# Netscape Communications Corporation.
+# Portions created by the Initial Developer are Copyright (C) 1998
+# the Initial Developer. All Rights Reserved.
+#
+# Contributor(s):
+#   Mark Pilgrim - port to Python
+#
+# This library is free software; you can redistribute it and/or
+# modify it under the terms of the GNU Lesser General Public
+# License as published by the Free Software Foundation; either
+# version 2.1 of the License, or (at your option) any later version.
+#
+# This library is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+# Lesser General Public License for more details.
+#
+# You should have received a copy of the GNU Lesser General Public
+# License along with this library; if not, write to the Free Software
+# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
+# 02110-1301  USA
+######################### END LICENSE BLOCK #########################
+
+from typing import Union
+
+from .charsetprober import CharSetProber
+from .codingstatemachine import CodingStateMachine
+from .enums import MachineState, ProbingState
+from .mbcssm import UTF8_SM_MODEL
+
+
+class UTF8Prober(CharSetProber):
+    ONE_CHAR_PROB = 0.5
+
+    def __init__(self) -> None:
+        super().__init__()
+        self.coding_sm = CodingStateMachine(UTF8_SM_MODEL)
+        self._num_mb_chars = 0
+        self.reset()
+
+    def reset(self) -> None:
+        super().reset()
+        self.coding_sm.reset()
+        self._num_mb_chars = 0
+
+    @property
+    def charset_name(self) -> str:
+        return "utf-8"
+
+    @property
+    def language(self) -> str:
+        return ""
+
+    def feed(self, byte_str: Union[bytes, bytearray]) -> ProbingState:
+        for c in byte_str:
+            coding_state = self.coding_sm.next_state(c)
+            if coding_state == MachineState.ERROR:
+                self._state = ProbingState.NOT_ME
+                break
+            if coding_state == MachineState.ITS_ME:
+                self._state = ProbingState.FOUND_IT
+                break
+            if coding_state == MachineState.START:
+                if self.coding_sm.get_current_charlen() >= 2:
+                    self._num_mb_chars += 1
+
+        if self.state == ProbingState.DETECTING:
+            if self.get_confidence() > self.SHORTCUT_THRESHOLD:
+                self._state = ProbingState.FOUND_IT
+
+        return self.state
+
+    def get_confidence(self) -> float:
+        unlike = 0.99
+        if self._num_mb_chars < 6:
+            unlike *= self.ONE_CHAR_PROB**self._num_mb_chars
+            return 1.0 - unlike
+        return unlike

venv/lib/python3.10/site-packages/safetensors-0.4.3.dist-info/INSTALLER

@@ -0,0 +1 @@
+pip

venv/lib/python3.10/site-packages/safetensors-0.4.3.dist-info/METADATA

@@ -0,0 +1,127 @@
+Metadata-Version: 2.3
+Name: safetensors
+Version: 0.4.3
+Classifier: Development Status :: 5 - Production/Stable
+Classifier: Intended Audience :: Developers
+Classifier: Intended Audience :: Education
+Classifier: Intended Audience :: Science/Research
+Classifier: License :: OSI Approved :: Apache Software License
+Classifier: Operating System :: OS Independent
+Classifier: Programming Language :: Python :: 3
+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: Topic :: Scientific/Engineering :: Artificial Intelligence
+Classifier: Typing :: Typed
+Requires-Dist: numpy >=1.21.6 ; extra == 'numpy'
+Requires-Dist: safetensors[numpy] ; extra == 'torch'
+Requires-Dist: torch >=1.10 ; extra == 'torch'
+Requires-Dist: safetensors[numpy] ; extra == 'tensorflow'
+Requires-Dist: tensorflow >=2.11.0 ; extra == 'tensorflow'
+Requires-Dist: safetensors[numpy] ; extra == 'pinned-tf'
+Requires-Dist: tensorflow ==2.11.0 ; extra == 'pinned-tf'
+Requires-Dist: safetensors[numpy] ; extra == 'jax'
+Requires-Dist: flax >=0.6.3 ; extra == 'jax'
+Requires-Dist: jax >=0.3.25 ; extra == 'jax'
+Requires-Dist: jaxlib >=0.3.25 ; extra == 'jax'
+Requires-Dist: mlx >=0.0.9 ; extra == 'mlx'
+Requires-Dist: safetensors[numpy] ; extra == 'paddlepaddle'
+Requires-Dist: paddlepaddle >=2.4.1 ; extra == 'paddlepaddle'
+Requires-Dist: black ==22.3 ; extra == 'quality'
+Requires-Dist: click ==8.0.4 ; extra == 'quality'
+Requires-Dist: isort >=5.5.4 ; extra == 'quality'
+Requires-Dist: flake8 >=3.8.3 ; extra == 'quality'
+Requires-Dist: safetensors[numpy] ; extra == 'testing'
+Requires-Dist: h5py >=3.7.0 ; extra == 'testing'
+Requires-Dist: huggingface-hub >=0.12.1 ; extra == 'testing'
+Requires-Dist: setuptools-rust >=1.5.2 ; extra == 'testing'
+Requires-Dist: pytest >=7.2.0 ; extra == 'testing'
+Requires-Dist: pytest-benchmark >=4.0.0 ; extra == 'testing'
+Requires-Dist: hypothesis >=6.70.2 ; extra == 'testing'
+Requires-Dist: safetensors[torch] ; extra == 'all'
+Requires-Dist: safetensors[numpy] ; extra == 'all'
+Requires-Dist: safetensors[pinned-tf] ; extra == 'all'
+Requires-Dist: safetensors[jax] ; extra == 'all'
+Requires-Dist: safetensors[paddlepaddle] ; extra == 'all'
+Requires-Dist: safetensors[quality] ; extra == 'all'
+Requires-Dist: safetensors[testing] ; extra == 'all'
+Requires-Dist: safetensors[all] ; extra == 'dev'
+Provides-Extra: numpy
+Provides-Extra: torch
+Provides-Extra: tensorflow
+Provides-Extra: pinned-tf
+Provides-Extra: jax
+Provides-Extra: mlx
+Provides-Extra: paddlepaddle
+Provides-Extra: quality
+Provides-Extra: testing
+Provides-Extra: all
+Provides-Extra: dev
+Author-email: Nicolas Patry <[email protected]>
+Requires-Python: >=3.7
+Description-Content-Type: text/markdown; charset=UTF-8; variant=GFM
+Project-URL: Homepage, https://github.com/huggingface/safetensors
+Project-URL: Source, https://github.com/huggingface/safetensors
+
+## Installation
+
+```
+pip install safetensors
+```
+
+
+## Usage
+
+### Numpy
+
+```python
+from safetensors.numpy import save_file, load_file
+import numpy as np
+
+tensors = {
+   "a": np.zeros((2, 2)),
+   "b": np.zeros((2, 3), dtype=np.uint8)
+}
+
+save_file(tensors, "./model.safetensors")
+
+
+# Now loading
+loaded = load_file("./model.safetensors")
+```
+
+### Torch
+
+```python
+from safetensors.torch import save_file, load_file
+import torch
+
+tensors = {
+   "a": torch.zeros((2, 2)),
+   "b": torch.zeros((2, 3), dtype=torch.uint8)
+}
+
+save_file(tensors, "./model.safetensors")
+
+
+# Now loading
+loaded = load_file("./model.safetensors")
+```
+
+### Developing
+
+```
+# inside ./safetensors/bindings/python
+pip install .[dev]
+```
+Should be enough to install this library locally.
+
+### Testing
+
+```
+# inside ./safetensors/bindings/python
+pip install .[dev]
+pytest -sv tests/
+```
+

venv/lib/python3.10/site-packages/safetensors-0.4.3.dist-info/RECORD

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+safetensors-0.4.3.dist-info/RECORD,,
+safetensors-0.4.3.dist-info/WHEEL,sha256=JL8sd1C0RQ2f7cmwbAn1Jp257v_vSS2r0VvTBpJeZwA,129
+safetensors/__init__.py,sha256=rFhZV2HBVDIijU2xKjg-0viTLETa-yMLMgFC9-47hdc,171
+safetensors/__init__.pyi,sha256=z6kNUzegHpyQAtFLtHu7ixUYWK9-Kwb6GqvV__6qMew,1970
+safetensors/__pycache__/__init__.cpython-310.pyc,,
+safetensors/__pycache__/flax.cpython-310.pyc,,
+safetensors/__pycache__/mlx.cpython-310.pyc,,
+safetensors/__pycache__/numpy.cpython-310.pyc,,
+safetensors/__pycache__/paddle.cpython-310.pyc,,
+safetensors/__pycache__/tensorflow.cpython-310.pyc,,
+safetensors/__pycache__/torch.cpython-310.pyc,,
+safetensors/_safetensors_rust.cpython-310-x86_64-linux-gnu.so,sha256=tjRccWtdZ62y0_JHfAfAsaIUpwqny3EQHZkyeroL-qA,4438576
+safetensors/flax.py,sha256=AuyY2YHxTBy4xeQLxhAyMledHykpz0Qsys13eKiHNYg,3846
+safetensors/mlx.py,sha256=7OTFtbdmGIqLnrjo_36RJRJ7zq1aI6HasvRPLB3d_Gw,3837
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+safetensors/paddle.py,sha256=V_RCTXymi2PJAG_jA4-qnfzbYAUB_74VYYXFzhXTLYM,4175
+safetensors/py.typed,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
+safetensors/tensorflow.py,sha256=6XaUBcxm0xL4ulNcvVsllKZ_qJ_rBSlE50rNnECCNYQ,3890
+safetensors/torch.py,sha256=_Tr2aFS0o5vmauTWKfJFo43N-UR_Ap8crx3O8XpryJI,17582

venv/lib/python3.10/site-packages/safetensors-0.4.3.dist-info/WHEEL

@@ -0,0 +1,4 @@
+Wheel-Version: 1.0
+Generator: maturin (1.5.1)
+Root-Is-Purelib: false
+Tag: cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64

venv/lib/python3.10/site-packages/sklearn/covariance/__init__.py

@@ -0,0 +1,44 @@
+"""
+The :mod:`sklearn.covariance` module includes methods and algorithms to
+robustly estimate the covariance of features given a set of points. The
+precision matrix defined as the inverse of the covariance is also estimated.
+Covariance estimation is closely related to the theory of Gaussian Graphical
+Models.
+"""
+
+from ._elliptic_envelope import EllipticEnvelope
+from ._empirical_covariance import (
+    EmpiricalCovariance,
+    empirical_covariance,
+    log_likelihood,
+)
+from ._graph_lasso import GraphicalLasso, GraphicalLassoCV, graphical_lasso
+from ._robust_covariance import MinCovDet, fast_mcd
+from ._shrunk_covariance import (
+    OAS,
+    LedoitWolf,
+    ShrunkCovariance,
+    ledoit_wolf,
+    ledoit_wolf_shrinkage,
+    oas,
+    shrunk_covariance,
+)
+
+__all__ = [
+    "EllipticEnvelope",
+    "EmpiricalCovariance",
+    "GraphicalLasso",
+    "GraphicalLassoCV",
+    "LedoitWolf",
+    "MinCovDet",
+    "OAS",
+    "ShrunkCovariance",
+    "empirical_covariance",
+    "fast_mcd",
+    "graphical_lasso",
+    "ledoit_wolf",
+    "ledoit_wolf_shrinkage",
+    "log_likelihood",
+    "oas",
+    "shrunk_covariance",
+]

venv/lib/python3.10/site-packages/sklearn/covariance/_elliptic_envelope.py

@@ -0,0 +1,267 @@
+# Author: Virgile Fritsch <[email protected]>
+#
+# License: BSD 3 clause
+
+from numbers import Real
+
+import numpy as np
+
+from ..base import OutlierMixin, _fit_context
+from ..metrics import accuracy_score
+from ..utils._param_validation import Interval
+from ..utils.validation import check_is_fitted
+from ._robust_covariance import MinCovDet
+
+
+class EllipticEnvelope(OutlierMixin, MinCovDet):
+    """An object for detecting outliers in a Gaussian distributed dataset.
+
+    Read more in the :ref:`User Guide <outlier_detection>`.
+
+    Parameters
+    ----------
+    store_precision : bool, default=True
+        Specify if the estimated precision is stored.
+
+    assume_centered : bool, default=False
+        If True, the support of robust location and covariance estimates
+        is computed, and a covariance estimate is recomputed from it,
+        without centering the data.
+        Useful to work with data whose mean is significantly equal to
+        zero but is not exactly zero.
+        If False, the robust location and covariance are directly computed
+        with the FastMCD algorithm without additional treatment.
+
+    support_fraction : float, default=None
+        The proportion of points to be included in the support of the raw
+        MCD estimate. If None, the minimum value of support_fraction will
+        be used within the algorithm: `(n_samples + n_features + 1) / 2 * n_samples`.
+        Range is (0, 1).
+
+    contamination : float, default=0.1
+        The amount of contamination of the data set, i.e. the proportion
+        of outliers in the data set. Range is (0, 0.5].
+
+    random_state : int, RandomState instance or None, default=None
+        Determines the pseudo random number generator for shuffling
+        the data. Pass an int for reproducible results across multiple function
+        calls. See :term:`Glossary <random_state>`.
+
+    Attributes
+    ----------
+    location_ : ndarray of shape (n_features,)
+        Estimated robust location.
+
+    covariance_ : ndarray of shape (n_features, n_features)
+        Estimated robust covariance matrix.
+
+    precision_ : ndarray of shape (n_features, n_features)
+        Estimated pseudo inverse matrix.
+        (stored only if store_precision is True)
+
+    support_ : ndarray of shape (n_samples,)
+        A mask of the observations that have been used to compute the
+        robust estimates of location and shape.
+
+    offset_ : float
+        Offset used to define the decision function from the raw scores.
+        We have the relation: ``decision_function = score_samples - offset_``.
+        The offset depends on the contamination parameter and is defined in
+        such a way we obtain the expected number of outliers (samples with
+        decision function < 0) in training.
+
+        .. versionadded:: 0.20
+
+    raw_location_ : ndarray of shape (n_features,)
+        The raw robust estimated location before correction and re-weighting.
+
+    raw_covariance_ : ndarray of shape (n_features, n_features)
+        The raw robust estimated covariance before correction and re-weighting.
+
+    raw_support_ : ndarray of shape (n_samples,)
+        A mask of the observations that have been used to compute
+        the raw robust estimates of location and shape, before correction
+        and re-weighting.
+
+    dist_ : ndarray of shape (n_samples,)
+        Mahalanobis distances of the training set (on which :meth:`fit` is
+        called) observations.
+
+    n_features_in_ : int
+        Number of features seen during :term:`fit`.
+
+        .. versionadded:: 0.24
+
+    feature_names_in_ : ndarray of shape (`n_features_in_`,)
+        Names of features seen during :term:`fit`. Defined only when `X`
+        has feature names that are all strings.
+
+        .. versionadded:: 1.0
+
+    See Also
+    --------
+    EmpiricalCovariance : Maximum likelihood covariance estimator.
+    GraphicalLasso : Sparse inverse covariance estimation
+        with an l1-penalized estimator.
+    LedoitWolf : LedoitWolf Estimator.
+    MinCovDet : Minimum Covariance Determinant
+        (robust estimator of covariance).
+    OAS : Oracle Approximating Shrinkage Estimator.
+    ShrunkCovariance : Covariance estimator with shrinkage.
+
+    Notes
+    -----
+    Outlier detection from covariance estimation may break or not
+    perform well in high-dimensional settings. In particular, one will
+    always take care to work with ``n_samples > n_features ** 2``.
+
+    References
+    ----------
+    .. [1] Rousseeuw, P.J., Van Driessen, K. "A fast algorithm for the
+       minimum covariance determinant estimator" Technometrics 41(3), 212
+       (1999)
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> from sklearn.covariance import EllipticEnvelope
+    >>> true_cov = np.array([[.8, .3],
+    ...                      [.3, .4]])
+    >>> X = np.random.RandomState(0).multivariate_normal(mean=[0, 0],
+    ...                                                  cov=true_cov,
+    ...                                                  size=500)
+    >>> cov = EllipticEnvelope(random_state=0).fit(X)
+    >>> # predict returns 1 for an inlier and -1 for an outlier
+    >>> cov.predict([[0, 0],
+    ...              [3, 3]])
+    array([ 1, -1])
+    >>> cov.covariance_
+    array([[0.7411..., 0.2535...],
+           [0.2535..., 0.3053...]])
+    >>> cov.location_
+    array([0.0813... , 0.0427...])
+    """
+
+    _parameter_constraints: dict = {
+        **MinCovDet._parameter_constraints,
+        "contamination": [Interval(Real, 0, 0.5, closed="right")],
+    }
+
+    def __init__(
+        self,
+        *,
+        store_precision=True,
+        assume_centered=False,
+        support_fraction=None,
+        contamination=0.1,
+        random_state=None,
+    ):
+        super().__init__(
+            store_precision=store_precision,
+            assume_centered=assume_centered,
+            support_fraction=support_fraction,
+            random_state=random_state,
+        )
+        self.contamination = contamination
+
+    @_fit_context(prefer_skip_nested_validation=True)
+    def fit(self, X, y=None):
+        """Fit the EllipticEnvelope model.
+
+        Parameters
+        ----------
+        X : array-like of shape (n_samples, n_features)
+            Training data.
+
+        y : Ignored
+            Not used, present for API consistency by convention.
+
+        Returns
+        -------
+        self : object
+            Returns the instance itself.
+        """
+        super().fit(X)
+        self.offset_ = np.percentile(-self.dist_, 100.0 * self.contamination)
+        return self
+
+    def decision_function(self, X):
+        """Compute the decision function of the given observations.
+
+        Parameters
+        ----------
+        X : array-like of shape (n_samples, n_features)
+            The data matrix.
+
+        Returns
+        -------
+        decision : ndarray of shape (n_samples,)
+            Decision function of the samples.
+            It is equal to the shifted Mahalanobis distances.
+            The threshold for being an outlier is 0, which ensures a
+            compatibility with other outlier detection algorithms.
+        """
+        check_is_fitted(self)
+        negative_mahal_dist = self.score_samples(X)
+        return negative_mahal_dist - self.offset_
+
+    def score_samples(self, X):
+        """Compute the negative Mahalanobis distances.
+
+        Parameters
+        ----------
+        X : array-like of shape (n_samples, n_features)
+            The data matrix.
+
+        Returns
+        -------
+        negative_mahal_distances : array-like of shape (n_samples,)
+            Opposite of the Mahalanobis distances.
+        """
+        check_is_fitted(self)
+        return -self.mahalanobis(X)
+
+    def predict(self, X):
+        """
+        Predict labels (1 inlier, -1 outlier) of X according to fitted model.
+
+        Parameters
+        ----------
+        X : array-like of shape (n_samples, n_features)
+            The data matrix.
+
+        Returns
+        -------
+        is_inlier : ndarray of shape (n_samples,)
+            Returns -1 for anomalies/outliers and +1 for inliers.
+        """
+        values = self.decision_function(X)
+        is_inlier = np.full(values.shape[0], -1, dtype=int)
+        is_inlier[values >= 0] = 1
+
+        return is_inlier
+
+    def score(self, X, y, sample_weight=None):
+        """Return the mean accuracy on the given test data and labels.
+
+        In multi-label classification, this is the subset accuracy
+        which is a harsh metric since you require for each sample that
+        each label set be correctly predicted.
+
+        Parameters
+        ----------
+        X : array-like of shape (n_samples, n_features)
+            Test samples.
+
+        y : array-like of shape (n_samples,) or (n_samples, n_outputs)
+            True labels for X.
+
+        sample_weight : array-like of shape (n_samples,), default=None
+            Sample weights.
+
+        Returns
+        -------
+        score : float
+            Mean accuracy of self.predict(X) w.r.t. y.
+        """
+        return accuracy_score(y, self.predict(X), sample_weight=sample_weight)

venv/lib/python3.10/site-packages/sklearn/covariance/_empirical_covariance.py

@@ -0,0 +1,364 @@
+"""
+Maximum likelihood covariance estimator.
+
+"""
+
+# Author: Alexandre Gramfort <[email protected]>
+#         Gael Varoquaux <[email protected]>
+#         Virgile Fritsch <[email protected]>
+#
+# License: BSD 3 clause
+
+# avoid division truncation
+import warnings
+
+import numpy as np
+from scipy import linalg
+
+from .. import config_context
+from ..base import BaseEstimator, _fit_context
+from ..metrics.pairwise import pairwise_distances
+from ..utils import check_array
+from ..utils._param_validation import validate_params
+from ..utils.extmath import fast_logdet
+
+
+@validate_params(
+    {
+        "emp_cov": [np.ndarray],
+        "precision": [np.ndarray],
+    },
+    prefer_skip_nested_validation=True,
+)
+def log_likelihood(emp_cov, precision):
+    """Compute the sample mean of the log_likelihood under a covariance model.
+
+    Computes the empirical expected log-likelihood, allowing for universal
+    comparison (beyond this software package), and accounts for normalization
+    terms and scaling.
+
+    Parameters
+    ----------
+    emp_cov : ndarray of shape (n_features, n_features)
+        Maximum Likelihood Estimator of covariance.
+
+    precision : ndarray of shape (n_features, n_features)
+        The precision matrix of the covariance model to be tested.
+
+    Returns
+    -------
+    log_likelihood_ : float
+        Sample mean of the log-likelihood.
+    """
+    p = precision.shape[0]
+    log_likelihood_ = -np.sum(emp_cov * precision) + fast_logdet(precision)
+    log_likelihood_ -= p * np.log(2 * np.pi)
+    log_likelihood_ /= 2.0
+    return log_likelihood_
+
+
+@validate_params(
+    {
+        "X": ["array-like"],
+        "assume_centered": ["boolean"],
+    },
+    prefer_skip_nested_validation=True,
+)
+def empirical_covariance(X, *, assume_centered=False):
+    """Compute the Maximum likelihood covariance estimator.
+
+    Parameters
+    ----------
+    X : ndarray of shape (n_samples, n_features)
+        Data from which to compute the covariance estimate.
+
+    assume_centered : bool, default=False
+        If `True`, data will not be centered before computation.
+        Useful when working with data whose mean is almost, but not exactly
+        zero.
+        If `False`, data will be centered before computation.
+
+    Returns
+    -------
+    covariance : ndarray of shape (n_features, n_features)
+        Empirical covariance (Maximum Likelihood Estimator).
+
+    Examples
+    --------
+    >>> from sklearn.covariance import empirical_covariance
+    >>> X = [[1,1,1],[1,1,1],[1,1,1],
+    ...      [0,0,0],[0,0,0],[0,0,0]]
+    >>> empirical_covariance(X)
+    array([[0.25, 0.25, 0.25],
+           [0.25, 0.25, 0.25],
+           [0.25, 0.25, 0.25]])
+    """
+    X = check_array(X, ensure_2d=False, force_all_finite=False)
+
+    if X.ndim == 1:
+        X = np.reshape(X, (1, -1))
+
+    if X.shape[0] == 1:
+        warnings.warn(
+            "Only one sample available. You may want to reshape your data array"
+        )
+
+    if assume_centered:
+        covariance = np.dot(X.T, X) / X.shape[0]
+    else:
+        covariance = np.cov(X.T, bias=1)
+
+    if covariance.ndim == 0:
+        covariance = np.array([[covariance]])
+    return covariance
+
+
+class EmpiricalCovariance(BaseEstimator):
+    """Maximum likelihood covariance estimator.
+
+    Read more in the :ref:`User Guide <covariance>`.
+
+    Parameters
+    ----------
+    store_precision : bool, default=True
+        Specifies if the estimated precision is stored.
+
+    assume_centered : bool, default=False
+        If True, data are not centered before computation.
+        Useful when working with data whose mean is almost, but not exactly
+        zero.
+        If False (default), data are centered before computation.
+
+    Attributes
+    ----------
+    location_ : ndarray of shape (n_features,)
+        Estimated location, i.e. the estimated mean.
+
+    covariance_ : ndarray of shape (n_features, n_features)
+        Estimated covariance matrix
+
+    precision_ : ndarray of shape (n_features, n_features)
+        Estimated pseudo-inverse matrix.
+        (stored only if store_precision is True)
+
+    n_features_in_ : int
+        Number of features seen during :term:`fit`.
+
+        .. versionadded:: 0.24
+
+    feature_names_in_ : ndarray of shape (`n_features_in_`,)
+        Names of features seen during :term:`fit`. Defined only when `X`
+        has feature names that are all strings.
+
+        .. versionadded:: 1.0
+
+    See Also
+    --------
+    EllipticEnvelope : An object for detecting outliers in
+        a Gaussian distributed dataset.
+    GraphicalLasso : Sparse inverse covariance estimation
+        with an l1-penalized estimator.
+    LedoitWolf : LedoitWolf Estimator.
+    MinCovDet : Minimum Covariance Determinant
+        (robust estimator of covariance).
+    OAS : Oracle Approximating Shrinkage Estimator.
+    ShrunkCovariance : Covariance estimator with shrinkage.
+
+    Examples
+    --------
+    >>> import numpy as np
+    >>> from sklearn.covariance import EmpiricalCovariance
+    >>> from sklearn.datasets import make_gaussian_quantiles
+    >>> real_cov = np.array([[.8, .3],
+    ...                      [.3, .4]])
+    >>> rng = np.random.RandomState(0)
+    >>> X = rng.multivariate_normal(mean=[0, 0],
+    ...                             cov=real_cov,
+    ...                             size=500)
+    >>> cov = EmpiricalCovariance().fit(X)
+    >>> cov.covariance_
+    array([[0.7569..., 0.2818...],
+           [0.2818..., 0.3928...]])
+    >>> cov.location_
+    array([0.0622..., 0.0193...])
+    """
+
+    _parameter_constraints: dict = {
+        "store_precision": ["boolean"],
+        "assume_centered": ["boolean"],
+    }
+
+    def __init__(self, *, store_precision=True, assume_centered=False):
+        self.store_precision = store_precision
+        self.assume_centered = assume_centered
+
+    def _set_covariance(self, covariance):
+        """Saves the covariance and precision estimates
+
+        Storage is done accordingly to `self.store_precision`.
+        Precision stored only if invertible.
+
+        Parameters
+        ----------
+        covariance : array-like of shape (n_features, n_features)
+            Estimated covariance matrix to be stored, and from which precision
+            is computed.
+        """
+        covariance = check_array(covariance)
+        # set covariance
+        self.covariance_ = covariance
+        # set precision
+        if self.store_precision:
+            self.precision_ = linalg.pinvh(covariance, check_finite=False)
+        else:
+            self.precision_ = None
+
+    def get_precision(self):
+        """Getter for the precision matrix.
+
+        Returns
+        -------
+        precision_ : array-like of shape (n_features, n_features)
+            The precision matrix associated to the current covariance object.
+        """
+        if self.store_precision:
+            precision = self.precision_
+        else:
+            precision = linalg.pinvh(self.covariance_, check_finite=False)
+        return precision
+
+    @_fit_context(prefer_skip_nested_validation=True)
+    def fit(self, X, y=None):
+        """Fit the maximum likelihood covariance estimator to X.
+
+        Parameters
+        ----------
+        X : array-like of shape (n_samples, n_features)
+          Training data, where `n_samples` is the number of samples and
+          `n_features` is the number of features.
+
+        y : Ignored
+            Not used, present for API consistency by convention.
+
+        Returns
+        -------
+        self : object
+            Returns the instance itself.
+        """
+        X = self._validate_data(X)
+        if self.assume_centered:
+            self.location_ = np.zeros(X.shape[1])
+        else:
+            self.location_ = X.mean(0)
+        covariance = empirical_covariance(X, assume_centered=self.assume_centered)
+        self._set_covariance(covariance)
+
+        return self
+
+    def score(self, X_test, y=None):
+        """Compute the log-likelihood of `X_test` under the estimated Gaussian model.
+
+        The Gaussian model is defined by its mean and covariance matrix which are
+        represented respectively by `self.location_` and `self.covariance_`.
+
+        Parameters
+        ----------
+        X_test : array-like of shape (n_samples, n_features)
+            Test data of which we compute the likelihood, where `n_samples` is
+            the number of samples and `n_features` is the number of features.
+            `X_test` is assumed to be drawn from the same distribution than
+            the data used in fit (including centering).
+
+        y : Ignored
+            Not used, present for API consistency by convention.
+
+        Returns
+        -------
+        res : float
+            The log-likelihood of `X_test` with `self.location_` and `self.covariance_`
+            as estimators of the Gaussian model mean and covariance matrix respectively.
+        """
+        X_test = self._validate_data(X_test, reset=False)
+        # compute empirical covariance of the test set
+        test_cov = empirical_covariance(X_test - self.location_, assume_centered=True)
+        # compute log likelihood
+        res = log_likelihood(test_cov, self.get_precision())
+
+        return res
+
+    def error_norm(self, comp_cov, norm="frobenius", scaling=True, squared=True):
+        """Compute the Mean Squared Error between two covariance estimators.
+
+        Parameters
+        ----------
+        comp_cov : array-like of shape (n_features, n_features)
+            The covariance to compare with.
+
+        norm : {"frobenius", "spectral"}, default="frobenius"
+            The type of norm used to compute the error. Available error types:
+            - 'frobenius' (default): sqrt(tr(A^t.A))
+            - 'spectral': sqrt(max(eigenvalues(A^t.A))
+            where A is the error ``(comp_cov - self.covariance_)``.
+
+        scaling : bool, default=True
+            If True (default), the squared error norm is divided by n_features.
+            If False, the squared error norm is not rescaled.
+
+        squared : bool, default=True
+            Whether to compute the squared error norm or the error norm.
+            If True (default), the squared error norm is returned.
+            If False, the error norm is returned.
+
+        Returns
+        -------
+        result : float
+            The Mean Squared Error (in the sense of the Frobenius norm) between
+            `self` and `comp_cov` covariance estimators.
+        """
+        # compute the error
+        error = comp_cov - self.covariance_
+        # compute the error norm
+        if norm == "frobenius":
+            squared_norm = np.sum(error**2)
+        elif norm == "spectral":
+            squared_norm = np.amax(linalg.svdvals(np.dot(error.T, error)))
+        else:
+            raise NotImplementedError(
+                "Only spectral and frobenius norms are implemented"
+            )
+        # optionally scale the error norm
+        if scaling:
+            squared_norm = squared_norm / error.shape[0]
+        # finally get either the squared norm or the norm
+        if squared:
+            result = squared_norm
+        else:
+            result = np.sqrt(squared_norm)
+
+        return result
+
+    def mahalanobis(self, X):
+        """Compute the squared Mahalanobis distances of given observations.
+
+        Parameters
+        ----------
+        X : array-like of shape (n_samples, n_features)
+            The observations, the Mahalanobis distances of the which we
+            compute. Observations are assumed to be drawn from the same
+            distribution than the data used in fit.
+
+        Returns
+        -------
+        dist : ndarray of shape (n_samples,)
+            Squared Mahalanobis distances of the observations.
+        """
+        X = self._validate_data(X, reset=False)
+
+        precision = self.get_precision()
+        with config_context(assume_finite=True):
+            # compute mahalanobis distances
+            dist = pairwise_distances(
+                X, self.location_[np.newaxis, :], metric="mahalanobis", VI=precision
+            )
+
+        return np.reshape(dist, (len(X),)) ** 2