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731k
| package
stringlengths 2
98
⌀ | name
stringlengths 1
76
| docstring
stringlengths 0
281k
⌀ | code
stringlengths 4
8.19k
| signature
stringlengths 2
42.8k
⌀ | embed_func_code
listlengths 768
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39,207 | astunparse.unparser | __FunctionDef_helper | null | def __FunctionDef_helper(self, t, fill_suffix):
self.write("\n")
for deco in t.decorator_list:
self.fill("@")
self.dispatch(deco)
def_str = fill_suffix+" "+t.name + "("
self.fill(def_str)
self.dispatch(t.args)
self.write(")")
if getattr(t, "returns", False):
self.write(" -> ")
self.dispatch(t.returns)
self.enter()
self.dispatch(t.body)
self.leave()
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|
39,208 | astunparse.unparser | _While | null | def _While(self, t):
self.fill("while ")
self.dispatch(t.test)
self.enter()
self.dispatch(t.body)
self.leave()
if t.orelse:
self.fill("else")
self.enter()
self.dispatch(t.orelse)
self.leave()
| (self, t) | [
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|
39,209 | astunparse.unparser | _With | null | def _With(self, t):
self._generic_With(t)
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|
39,210 | astunparse.unparser | _Yield | null | def _Yield(self, t):
self.write("(")
self.write("yield")
if t.value:
self.write(" ")
self.dispatch(t.value)
self.write(")")
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|
39,211 | astunparse.unparser | _YieldFrom | null | def _YieldFrom(self, t):
self.write("(")
self.write("yield from")
if t.value:
self.write(" ")
self.dispatch(t.value)
self.write(")")
| (self, t) | [
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|
39,212 | astunparse.unparser | __init__ | Unparser(tree, file=sys.stdout) -> None.
Print the source for tree to file. | def __init__(self, tree, file = sys.stdout):
"""Unparser(tree, file=sys.stdout) -> None.
Print the source for tree to file."""
self.f = file
self.future_imports = []
self._indent = 0
self.dispatch(tree)
print("", file=self.f)
self.f.flush()
| (self, tree, file=<_io.TextIOWrapper name='<stdout>' mode='w' encoding='utf-8'>) | [
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|
39,213 | astunparse.unparser | _alias | null | def _alias(self, t):
self.write(t.name)
if t.asname:
self.write(" as "+t.asname)
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|
39,214 | astunparse.unparser | _arg | null | def _arg(self, t):
self.write(t.arg)
if t.annotation:
self.write(": ")
self.dispatch(t.annotation)
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|
39,215 | astunparse.unparser | _arguments | null | def _arguments(self, t):
first = True
# normal arguments
all_args = getattr(t, 'posonlyargs', []) + t.args
defaults = [None] * (len(all_args) - len(t.defaults)) + t.defaults
for index, elements in enumerate(zip(all_args, defaults), 1):
a, d = elements
if first:first = False
else: self.write(", ")
self.dispatch(a)
if d:
self.write("=")
self.dispatch(d)
if index == len(getattr(t, 'posonlyargs', ())):
self.write(", /")
# varargs, or bare '*' if no varargs but keyword-only arguments present
if t.vararg or getattr(t, "kwonlyargs", False):
if first:first = False
else: self.write(", ")
self.write("*")
if t.vararg:
if hasattr(t.vararg, 'arg'):
self.write(t.vararg.arg)
if t.vararg.annotation:
self.write(": ")
self.dispatch(t.vararg.annotation)
else:
self.write(t.vararg)
if getattr(t, 'varargannotation', None):
self.write(": ")
self.dispatch(t.varargannotation)
# keyword-only arguments
if getattr(t, "kwonlyargs", False):
for a, d in zip(t.kwonlyargs, t.kw_defaults):
if first:first = False
else: self.write(", ")
self.dispatch(a),
if d:
self.write("=")
self.dispatch(d)
# kwargs
if t.kwarg:
if first:first = False
else: self.write(", ")
if hasattr(t.kwarg, 'arg'):
self.write("**"+t.kwarg.arg)
if t.kwarg.annotation:
self.write(": ")
self.dispatch(t.kwarg.annotation)
else:
self.write("**"+t.kwarg)
if getattr(t, 'kwargannotation', None):
self.write(": ")
self.dispatch(t.kwargannotation)
| (self, t) | [
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|
39,216 | astunparse.unparser | _comprehension | null | def _comprehension(self, t):
if getattr(t, 'is_async', False):
self.write(" async for ")
else:
self.write(" for ")
self.dispatch(t.target)
self.write(" in ")
self.dispatch(t.iter)
for if_clause in t.ifs:
self.write(" if ")
self.dispatch(if_clause)
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|
39,217 | astunparse.unparser | _fstring_Constant | null | def _fstring_Constant(self, t, write):
assert isinstance(t.value, str)
value = t.value.replace("{", "{{").replace("}", "}}")
write(value)
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|
39,218 | astunparse.unparser | _fstring_FormattedValue | null | def _fstring_FormattedValue(self, t, write):
write("{")
expr = StringIO()
Unparser(t.value, expr)
expr = expr.getvalue().rstrip("\n")
if expr.startswith("{"):
write(" ") # Separate pair of opening brackets as "{ {"
write(expr)
if t.conversion != -1:
conversion = chr(t.conversion)
assert conversion in "sra"
write("!{conversion}".format(conversion=conversion))
if t.format_spec:
write(":")
meth = getattr(self, "_fstring_" + type(t.format_spec).__name__)
meth(t.format_spec, write)
write("}")
| (self, t, write) | [
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|
39,219 | astunparse.unparser | _fstring_JoinedStr | null | def _fstring_JoinedStr(self, t, write):
for value in t.values:
meth = getattr(self, "_fstring_" + type(value).__name__)
meth(value, write)
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|
39,220 | astunparse.unparser | _fstring_Str | null | def _fstring_Str(self, t, write):
value = t.s.replace("{", "{{").replace("}", "}}")
write(value)
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|
39,221 | astunparse.unparser | _generic_With | null | def _generic_With(self, t, async_=False):
self.fill("async with " if async_ else "with ")
if hasattr(t, 'items'):
interleave(lambda: self.write(", "), self.dispatch, t.items)
else:
self.dispatch(t.context_expr)
if t.optional_vars:
self.write(" as ")
self.dispatch(t.optional_vars)
self.enter()
self.dispatch(t.body)
self.leave()
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|
39,222 | astunparse.unparser | _keyword | null | def _keyword(self, t):
if t.arg is None:
# starting from Python 3.5 this denotes a kwargs part of the invocation
self.write("**")
else:
self.write(t.arg)
self.write("=")
self.dispatch(t.value)
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|
39,223 | astunparse.unparser | _withitem | null | def _withitem(self, t):
self.dispatch(t.context_expr)
if t.optional_vars:
self.write(" as ")
self.dispatch(t.optional_vars)
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|
39,224 | astunparse.unparser | _write_constant | null | def _write_constant(self, value):
if isinstance(value, (float, complex)):
# Substitute overflowing decimal literal for AST infinities.
self.write(repr(value).replace("inf", INFSTR))
else:
self.write(repr(value))
| (self, value) | [
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|
39,225 | astunparse.unparser | dispatch | Dispatcher function, dispatching tree type T to method _T. | def dispatch(self, tree):
"Dispatcher function, dispatching tree type T to method _T."
if isinstance(tree, list):
for t in tree:
self.dispatch(t)
return
meth = getattr(self, "_"+tree.__class__.__name__)
meth(tree)
| (self, tree) | [
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|
39,226 | astunparse.unparser | enter | Print ':', and increase the indentation. | def enter(self):
"Print ':', and increase the indentation."
self.write(":")
self._indent += 1
| (self) | [
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|
39,227 | astunparse.unparser | fill | Indent a piece of text, according to the current indentation level | def fill(self, text = ""):
"Indent a piece of text, according to the current indentation level"
self.f.write("\n"+" "*self._indent + text)
| (self, text='') | [
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|
39,228 | astunparse.unparser | leave | Decrease the indentation level. | def leave(self):
"Decrease the indentation level."
self._indent -= 1
| (self) | [
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|
39,229 | astunparse.unparser | write | Append a piece of text to the current line. | def write(self, text):
"Append a piece of text to the current line."
self.f.write(six.text_type(text))
| (self, text) | [
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|
39,231 | astunparse | dump | null | def dump(tree):
v = cStringIO()
Printer(file=v).visit(tree)
return v.getvalue()
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|
39,233 | astunparse | unparse | null | def unparse(tree):
v = cStringIO()
Unparser(tree, file=v)
return v.getvalue()
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|
39,236 | idna_ssl | patch_match_hostname | null | def patch_match_hostname():
if PY_370:
return
if hasattr(ssl.match_hostname, 'patched'):
return
ssl.match_hostname = patched_match_hostname
ssl.match_hostname.patched = True
| () | [
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|
39,237 | idna_ssl | patched_match_hostname | null | def patched_match_hostname(cert, hostname):
try:
hostname = idna.encode(hostname, uts46=True).decode('ascii')
except UnicodeError:
hostname = hostname.encode('idna').decode('ascii')
return real_match_hostname(cert, hostname)
| (cert, hostname) | [
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0.04367334023118019,
0.05440809950232506,
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|
39,238 | ssl | match_hostname | Verify that *cert* (in decoded format as returned by
SSLSocket.getpeercert()) matches the *hostname*. RFC 2818 and RFC 6125
rules are followed.
The function matches IP addresses rather than dNSNames if hostname is a
valid ipaddress string. IPv4 addresses are supported on all platforms.
IPv6 addresses are supported on platforms with IPv6 support (AF_INET6
and inet_pton).
CertificateError is raised on failure. On success, the function
returns nothing.
| def match_hostname(cert, hostname):
"""Verify that *cert* (in decoded format as returned by
SSLSocket.getpeercert()) matches the *hostname*. RFC 2818 and RFC 6125
rules are followed.
The function matches IP addresses rather than dNSNames if hostname is a
valid ipaddress string. IPv4 addresses are supported on all platforms.
IPv6 addresses are supported on platforms with IPv6 support (AF_INET6
and inet_pton).
CertificateError is raised on failure. On success, the function
returns nothing.
"""
warnings.warn(
"ssl.match_hostname() is deprecated",
category=DeprecationWarning,
stacklevel=2
)
if not cert:
raise ValueError("empty or no certificate, match_hostname needs a "
"SSL socket or SSL context with either "
"CERT_OPTIONAL or CERT_REQUIRED")
try:
host_ip = _inet_paton(hostname)
except ValueError:
# Not an IP address (common case)
host_ip = None
dnsnames = []
san = cert.get('subjectAltName', ())
for key, value in san:
if key == 'DNS':
if host_ip is None and _dnsname_match(value, hostname):
return
dnsnames.append(value)
elif key == 'IP Address':
if host_ip is not None and _ipaddress_match(value, host_ip):
return
dnsnames.append(value)
if not dnsnames:
# The subject is only checked when there is no dNSName entry
# in subjectAltName
for sub in cert.get('subject', ()):
for key, value in sub:
# XXX according to RFC 2818, the most specific Common Name
# must be used.
if key == 'commonName':
if _dnsname_match(value, hostname):
return
dnsnames.append(value)
if len(dnsnames) > 1:
raise CertificateError("hostname %r "
"doesn't match either of %s"
% (hostname, ', '.join(map(repr, dnsnames))))
elif len(dnsnames) == 1:
raise CertificateError("hostname %r "
"doesn't match %r"
% (hostname, dnsnames[0]))
else:
raise CertificateError("no appropriate commonName or "
"subjectAltName fields were found")
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|
39,239 | idna_ssl | reset_match_hostname | null | def reset_match_hostname():
if PY_370:
return
if not hasattr(ssl.match_hostname, 'patched'):
return
ssl.match_hostname = real_match_hostname
| () | [
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|
39,242 | segno.encoder | DataOverflowError | Indicates a problem that the provided data does not fit into the
provided QR Code version or the data is too large in general.
This exception is inherited from :py:exc:`ValueError` and is only raised
if the data does not fit into the provided (Micro) QR Code version.
Basically it is sufficient to catch a :py:exc:`ValueError`.
| class DataOverflowError(ValueError):
"""\
Indicates a problem that the provided data does not fit into the
provided QR Code version or the data is too large in general.
This exception is inherited from :py:exc:`ValueError` and is only raised
if the data does not fit into the provided (Micro) QR Code version.
Basically it is sufficient to catch a :py:exc:`ValueError`.
"""
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|
39,243 | segno | QRCode | Represents a (Micro) QR Code.
| class QRCode:
"""\
Represents a (Micro) QR Code.
"""
__slots__ = ('matrix', 'mask', '_version', '_error', '_mode', '_matrix_size')
def __init__(self, code):
"""\
Initializes the QR Code object.
:param code: An object with a ``matrix``, ``version``, ``error``,
``mask`` and ``segments`` attribute.
"""
matrix = code.matrix
self.matrix = matrix
"""Returns the matrix.
:rtype: tuple of :py:class:`bytearray` instances.
"""
self.mask = code.mask
"""Returns the data mask pattern reference
:rtype: int
"""
self._matrix_size = len(matrix[0]), len(matrix)
self._version = code.version
self._error = code.error
self._mode = code.segments[0].mode if len(code.segments) == 1 else None
@property
def version(self):
"""\
(Micro) QR Code version. Either a string ("M1", "M2", "M3", "M4") or
an integer in the range of 1 .. 40.
:rtype: str or int
"""
return encoder.get_version_name(self._version)
@property
def error(self):
"""\
Error correction level; either a string ("L", "M", "Q", "H") or ``None``
if the QR code provides no error correction (Micro QR Code version M1)
:rtype: str
"""
if self._error is None:
return None
return encoder.get_error_name(self._error)
@property
def mode(self):
"""\
String indicating the mode ("numeric", "alphanumeric", "byte", "kanji",
or "hanzi").
May be ``None`` if multiple modes are used.
:rtype: str or None
"""
if self._mode is not None:
return encoder.get_mode_name(self._mode)
return None
@property
def designator(self):
"""\
Returns the version and error correction level as string `V-E` where
`V` represents the version number and `E` the error level.
:rtype: str
"""
version = str(self.version)
return '-'.join((version, self.error) if self.error else (version,))
@property
def default_border_size(self):
"""\
Indicates the default border size aka quiet zone.
QR Codes have a quiet zone of four light modules, while Micro QR Codes
have a quiet zone of two light modules.
:rtype: int
"""
return utils.get_default_border_size(self._matrix_size)
@property
def is_micro(self):
"""\
Indicates if this QR code is a Micro QR code
:rtype: bool
"""
return self._version < 1
def __eq__(self, other):
return self.__class__ == other.__class__ and self.matrix == other.matrix
__hash__ = None
def symbol_size(self, scale=1, border=None):
"""\
Returns the symbol size (width x height) with the provided border and
scaling factor.
:param scale: Indicates the size of a single module (default: 1).
The size of a module depends on the used output format; i.e.
in a PNG context, a scaling factor of 2 indicates that a module
has a size of 2 x 2 pixel. Some outputs (i.e. SVG) accept
floating point values.
:type scale: int or float
:param int border: The border size or ``None`` to specify the
default quiet zone (4 for QR Codes, 2 for Micro QR Codes).
:rtype: tuple (width, height)
"""
return utils.get_symbol_size(self._matrix_size, scale=scale, border=border)
def matrix_iter(self, scale=1, border=None, verbose=False):
"""\
Returns an iterator over the matrix which includes the border.
The border is returned as sequence of light modules.
Dark modules are reported as ``0x1``, light modules have the value
``0x0``.
The following example converts the QR code matrix into a list of
lists which use boolean values for the modules (True = dark module,
False = light module)::
>>> import segno
>>> qrcode = segno.make('The Beatles')
>>> width, height = qrcode.symbol_size(scale=2)
>>> res = []
>>> # Scaling factor 2, default border
>>> for row in qrcode.matrix_iter(scale=2):
>>> res.append([col == 0x1 for col in row])
>>> width == len(res[0])
True
>>> height == len(res)
True
If `verbose` is ``True``, the iterator returns integer constants which
indicate the type of the module, i.e. ``segno.consts.TYPE_FINDER_PATTERN_DARK``,
``segno.consts.TYPE_FINDER_PATTERN_LIGHT``, ``segno.consts.TYPE_QUIET_ZONE`` etc.
To check if the returned module type is dark or light, use::
if mt >> 8:
print('dark module')
if not mt >> 8:
print('light module')
:param int scale: The scaling factor (default: ``1``).
:param int border: The size of border / quiet zone or ``None`` to
indicate the default border.
:param bool verbose: Indicates if the type of the module should be returned
instead of ``0x1`` and ``0x0`` values.
See :py:mod:`segno.consts` for the return values.
This feature is currently in EXPERIMENTAL state.
:raises: :py:exc:`ValueError` if the scaling factor or the border is
invalid (i.e. negative).
"""
iterfn = utils.matrix_iter_verbose if verbose else utils.matrix_iter
return iterfn(self.matrix, self._matrix_size, scale, border)
def show(self, delete_after=20, scale=10, border=None, dark='#000',
light='#fff'): # pragma: no cover
"""\
Displays this QR code.
This method is mainly intended for debugging purposes.
This method saves the QR code as an image (by default with a scaling
factor of 10) to a temporary file and opens it with the standard PNG
viewer application or within the standard webbrowser.
The temporary file is deleted afterwards (unless
:paramref:`delete_after <segno.QRCode.show.delete_after>` is set to ``None``).
If this method does not show any result, try to increase the
:paramref:`delete_after <segno.QRCode.show.delete_after>` value or set
it to ``None``
:param delete_after: Time in seconds to wait till the temporary file is
deleted.
:type delete_after: int or None
:param int scale: Integer indicating the size of a single module.
:param border: Integer indicating the size of the quiet zone.
If set to ``None`` (default), the recommended border size
will be used.
:type border: int or None
:param dark: The color of the dark modules (default: black).
:param light: The color of the light modules (default: white).
"""
import os
import time
import tempfile
import webbrowser
import threading
from urllib.parse import urljoin
from urllib.request import pathname2url
def delete_file(name):
time.sleep(delete_after)
try:
os.unlink(name)
except OSError:
pass
f = tempfile.NamedTemporaryFile('wb', suffix='.png', delete=False)
try:
self.save(f, scale=scale, dark=dark, light=light, border=border)
except: # noqa: E722
f.close()
os.unlink(f.name)
raise
f.close()
webbrowser.open_new_tab(urljoin('file:', pathname2url(f.name)))
if delete_after is not None:
t = threading.Thread(target=delete_file, args=(f.name,))
t.start()
def svg_data_uri(self, xmldecl=False, encode_minimal=False,
omit_charset=False, nl=False, **kw):
"""\
Converts the QR code into an SVG data URI.
The XML declaration is omitted by default (set
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|
39,244 | segno | __eq__ | null | def __eq__(self, other):
return self.__class__ == other.__class__ and self.matrix == other.matrix
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|
39,245 | segno | __getattr__ | This is used to plug-in external serializers.
When a "to_<name>" method is invoked, this method tries to find
a ``segno.plugin.converter`` plugin with the provided ``<name>``.
If such a plugin exists, a callable function is returned. The result
of invoking the function depends on the plugin.
| def __getattr__(self, name):
"""\
This is used to plug-in external serializers.
When a "to_<name>" method is invoked, this method tries to find
a ``segno.plugin.converter`` plugin with the provided ``<name>``.
If such a plugin exists, a callable function is returned. The result
of invoking the function depends on the plugin.
"""
if name.startswith('to_'):
try:
# Try to use the 3rd party lib first. This is required for
# Python versions < 3.10
import importlib_metadata as metadata
except ImportError:
from importlib import metadata
from functools import partial
for ep in metadata.entry_points(group='segno.plugin.converter',
name=name[3:]):
plugin = ep.load()
return partial(plugin, self)
raise AttributeError('{0} object has no attribute {1}'
.format(self.__class__, name))
| (self, name) | [
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|
39,246 | segno | __init__ | Initializes the QR Code object.
:param code: An object with a ``matrix``, ``version``, ``error``,
``mask`` and ``segments`` attribute.
| def __init__(self, code):
"""\
Initializes the QR Code object.
:param code: An object with a ``matrix``, ``version``, ``error``,
``mask`` and ``segments`` attribute.
"""
matrix = code.matrix
self.matrix = matrix
"""Returns the matrix.
:rtype: tuple of :py:class:`bytearray` instances.
"""
self.mask = code.mask
"""Returns the data mask pattern reference
:rtype: int
"""
self._matrix_size = len(matrix[0]), len(matrix)
self._version = code.version
self._error = code.error
self._mode = code.segments[0].mode if len(code.segments) == 1 else None
| (self, code) | [
0.06262125819921494,
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|
39,247 | segno | matrix_iter | Returns an iterator over the matrix which includes the border.
The border is returned as sequence of light modules.
Dark modules are reported as ``0x1``, light modules have the value
``0x0``.
The following example converts the QR code matrix into a list of
lists which use boolean values for the modules (True = dark module,
False = light module)::
>>> import segno
>>> qrcode = segno.make('The Beatles')
>>> width, height = qrcode.symbol_size(scale=2)
>>> res = []
>>> # Scaling factor 2, default border
>>> for row in qrcode.matrix_iter(scale=2):
>>> res.append([col == 0x1 for col in row])
>>> width == len(res[0])
True
>>> height == len(res)
True
If `verbose` is ``True``, the iterator returns integer constants which
indicate the type of the module, i.e. ``segno.consts.TYPE_FINDER_PATTERN_DARK``,
``segno.consts.TYPE_FINDER_PATTERN_LIGHT``, ``segno.consts.TYPE_QUIET_ZONE`` etc.
To check if the returned module type is dark or light, use::
if mt >> 8:
print('dark module')
if not mt >> 8:
print('light module')
:param int scale: The scaling factor (default: ``1``).
:param int border: The size of border / quiet zone or ``None`` to
indicate the default border.
:param bool verbose: Indicates if the type of the module should be returned
instead of ``0x1`` and ``0x0`` values.
See :py:mod:`segno.consts` for the return values.
This feature is currently in EXPERIMENTAL state.
:raises: :py:exc:`ValueError` if the scaling factor or the border is
invalid (i.e. negative).
| def matrix_iter(self, scale=1, border=None, verbose=False):
"""\
Returns an iterator over the matrix which includes the border.
The border is returned as sequence of light modules.
Dark modules are reported as ``0x1``, light modules have the value
``0x0``.
The following example converts the QR code matrix into a list of
lists which use boolean values for the modules (True = dark module,
False = light module)::
>>> import segno
>>> qrcode = segno.make('The Beatles')
>>> width, height = qrcode.symbol_size(scale=2)
>>> res = []
>>> # Scaling factor 2, default border
>>> for row in qrcode.matrix_iter(scale=2):
>>> res.append([col == 0x1 for col in row])
>>> width == len(res[0])
True
>>> height == len(res)
True
If `verbose` is ``True``, the iterator returns integer constants which
indicate the type of the module, i.e. ``segno.consts.TYPE_FINDER_PATTERN_DARK``,
``segno.consts.TYPE_FINDER_PATTERN_LIGHT``, ``segno.consts.TYPE_QUIET_ZONE`` etc.
To check if the returned module type is dark or light, use::
if mt >> 8:
print('dark module')
if not mt >> 8:
print('light module')
:param int scale: The scaling factor (default: ``1``).
:param int border: The size of border / quiet zone or ``None`` to
indicate the default border.
:param bool verbose: Indicates if the type of the module should be returned
instead of ``0x1`` and ``0x0`` values.
See :py:mod:`segno.consts` for the return values.
This feature is currently in EXPERIMENTAL state.
:raises: :py:exc:`ValueError` if the scaling factor or the border is
invalid (i.e. negative).
"""
iterfn = utils.matrix_iter_verbose if verbose else utils.matrix_iter
return iterfn(self.matrix, self._matrix_size, scale, border)
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|
39,248 | segno | png_data_uri | Converts the QR code into a PNG data URI.
Uses the same keyword parameters as the usual PNG serializer,
see :py:func:`save` and the available `PNG parameters <#png>`_
:rtype: str
| def png_data_uri(self, **kw):
"""\
Converts the QR code into a PNG data URI.
Uses the same keyword parameters as the usual PNG serializer,
see :py:func:`save` and the available `PNG parameters <#png>`_
:rtype: str
"""
return writers.as_png_data_uri(self.matrix, self._matrix_size, **kw)
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|
39,249 | segno | save | Serializes the QR code in one of the supported formats.
The serialization format depends on the filename extension.
.. _common_keywords:
**Common keywords**
========== ==============================================================
Name Description
========== ==============================================================
scale Integer or float indicating the size of a single module.
Default: 1. The interpretation of the scaling factor depends
on the serializer. For pixel-based output (like :ref:`PNG <png>`)
the scaling factor is interpreted as pixel-size (1 = 1 pixel).
:ref:`EPS <eps>` interprets ``1`` as 1 point (1/72 inch) per
module.
Some serializers (like :ref:`SVG <svg>`) accept float values.
If the serializer does not accept float values, the value will be
converted to an integer value (note: int(1.6) == 1).
border Integer indicating the size of the quiet zone.
If set to ``None`` (default), the recommended border size
will be used (``4`` for QR codes, ``2`` for a Micro QR codes).
A value of ``0`` indicates that border should be omitted.
dark A string or tuple representing a color value for the dark
modules. The default value is "black". The color can be
provided as ``(R, G, B)`` tuple, as web color name
(like "red") or in hexadecimal format (``#RGB`` or
``#RRGGBB``). Some serializers (i.e. :ref:`SVG <svg>` and
:ref:`PNG <png>`) accept an alpha transparency value like
``#RRGGBBAA``.
light A string or tuple representing a color for the light modules.
See `dark` for valid values.
The default value depends on the serializer. :ref:`SVG <svg>`
uses no color (``None``) for light modules by default, other
serializers, like :ref:`PNG <png>`, use "white" as default
light color.
========== ==============================================================
.. _module_colors:
**Module Colors**
=============== =======================================================
Name Description
=============== =======================================================
finder_dark Color of the dark modules of the finder patterns
Default: undefined, use value of "dark"
finder_light Color of the light modules of the finder patterns
Default: undefined, use value of "light"
data_dark Color of the dark data modules
Default: undefined, use value of "dark"
data_light Color of the light data modules.
Default: undefined, use value of "light".
version_dark Color of the dark modules of the version information.
Default: undefined, use value of "dark".
version_light Color of the light modules of the version information,
Default: undefined, use value of "light".
format_dark Color of the dark modules of the format information.
Default: undefined, use value of "dark".
format_light Color of the light modules of the format information.
Default: undefined, use value of "light".
alignment_dark Color of the dark modules of the alignment patterns.
Default: undefined, use value of "dark".
alignment_light Color of the light modules of the alignment patterns.
Default: undefined, use value of "light".
timing_dark Color of the dark modules of the timing patterns.
Default: undefined, use value of "dark".
timing_light Color of the light modules of the timing patterns.
Default: undefined, use value of "light".
separator Color of the separator.
Default: undefined, use value of "light".
dark_module Color of the dark module (a single dark module which
occurs in all QR Codes but not in Micro QR Codes.
Default: undefined, use value of "dark".
quiet_zone Color of the quiet zone / border.
Default: undefined, use value of "light".
=============== =======================================================
.. _svg:
**Scalable Vector Graphics (SVG)**
All :ref:`common keywords <common_keywords>` and :ref:`module colors <module_colors>`
are supported.
================ ==============================================================
Name Description
================ ==============================================================
out Filename or :py:class:`io.BytesIO`
kind "svg" or "svgz" (to create a gzip compressed SVG)
scale integer or float
dark Default: "#000" (black)
``None`` is a valid value. If set to ``None``, the resulting
path won't have a "stroke" attribute. The "stroke" attribute
may be defined via CSS (external).
If an alpha channel is defined, the output depends of the
used SVG version. For SVG versions >= 2.0, the "stroke"
attribute will have a value like "rgba(R, G, B, A)", otherwise
the path gets another attribute "stroke-opacity" to emulate
the alpha channel.
To minimize the document size, the SVG serializer uses
automatically the shortest color representation: If
a value like "#000000" is provided, the resulting
document will have a color value of "#000". If the color
is "#FF0000", the resulting color is not "#F00", but
the web color name "red".
light Default value ``None``. If this parameter is set to another
value, the resulting image will have another path which
is used to define the color of the light modules.
If an alpha channel is used, the resulting path may
have a "fill-opacity" attribute (for SVG version < 2.0)
or the "fill" attribute has a "rgba(R, G, B, A)" value.
xmldecl Boolean value (default: ``True``) indicating whether the
document should have an XML declaration header.
Set to ``False`` to omit the header.
svgns Boolean value (default: ``True``) indicating whether the
document should have an explicit SVG namespace declaration.
Set to ``False`` to omit the namespace declaration.
The latter might be useful if the document should be
embedded into a HTML 5 document where the SVG namespace
is implicitly defined.
title String (default: ``None``) Optional title of the generated
SVG document.
desc String (default: ``None``) Optional description of the
generated SVG document.
svgid A string indicating the ID of the SVG document
(if set to ``None`` (default), the SVG element won't have
an ID).
svgclass Default: "segno". The CSS class of the SVG document
(if set to ``None``, the SVG element won't have a class).
lineclass Default: "qrline". The CSS class of the path element
(which draws the dark modules (if set to ``None``, the path
won't have a class).
omitsize Indicates if width and height attributes should be
omitted (default: ``False``). If these attributes are
omitted, a ``viewBox`` attribute will be added to the
document.
unit Default: ``None``
Indicates the unit for width / height and other coordinates.
By default, the unit is unspecified and all values are
in the user space.
Valid values: em, ex, px, pt, pc, cm, mm, in, and percentages
(any string is accepted, this parameter is not validated
by the serializer)
encoding Encoding of the XML document. "utf-8" by default.
svgversion SVG version (default: ``None``). If specified (a float),
the resulting document has an explicit "version" attribute.
If set to ``None``, the document won't have a "version"
attribute. This parameter is not validated.
compresslevel Default: 9. This parameter is only valid, if a compressed
SVG document should be created (file extension "svgz").
1 is fastest and produces the least compression, 9 is slowest
and produces the most. 0 is no compression.
draw_transparent Indicates if transparent SVG paths should be
added to the graphic (default: ``False``)
nl Indicates if the document should have a trailing newline
(default: ``True``)
================ ==============================================================
.. _png:
**Portable Network Graphics (PNG)**
This writes either a grayscale (maybe with transparency) PNG (color type 0)
or a palette-based (maybe with transparency) image (color type 3).
If the dark / light values are ``None``, white or black, the serializer
chooses the more compact grayscale mode, in all other cases a palette-based
image is written.
All :ref:`common keywords <common_keywords>` and :ref:`module colors <module_colors>`
are supported.
=============== ==============================================================
Name Description
=============== ==============================================================
out Filename or :py:class:`io.BytesIO`
kind "png"
scale integer
dark Default: "#000" (black)
``None`` is a valid value iff light is not ``None``.
If set to ``None``, the dark modules become transparent.
light Default value "#fff" (white)
See keyword "dark" for further details.
compresslevel Default: 9. Integer indicating the compression level
for the ``IDAT`` (data) chunk.
1 is fastest and produces the least compression, 9 is slowest
and produces the most. 0 is no compression.
dpi Default: ``None``. Specifies the DPI value for the image.
By default, the DPI value is unspecified. Please note
that the DPI value is converted into meters (maybe with
rounding errors) since PNG does not support the unit
"dots per inch".
=============== ==============================================================
.. _eps:
**Encapsulated PostScript (EPS)**
All :ref:`common keywords <common_keywords>` are supported.
============= ==============================================================
Name Description
============= ==============================================================
out Filename or :py:class:`io.StringIO`
kind "eps"
scale integer or float
dark Default: "#000" (black)
light Default value: ``None`` (transparent light modules)
============= ==============================================================
.. _pdf:
**Portable Document Format (PDF)**
All :ref:`common keywords <common_keywords>` are supported.
============= ==============================================================
Name Description
============= ==============================================================
out Filename or :py:class:`io.BytesIO`
kind "pdf"
scale integer or float
dark Default: "#000" (black)
light Default value: ``None`` (transparent light modules)
compresslevel Default: 9. Integer indicating the compression level.
1 is fastest and produces the least compression, 9 is slowest
and produces the most. 0 is no compression.
============= ==============================================================
.. _txt:
**Text (TXT)**
Aside of "scale", all :ref:`common keywords <common_keywords>` are supported.
============= ==============================================================
Name Description
============= ==============================================================
out Filename or :py:class:`io.StringIO`
kind "txt"
dark Default: "1"
light Default: "0"
============= ==============================================================
.. _ansi:
**ANSI escape code**
Supports the "border" keyword, only!
============= ==============================================================
Name Description
============= ==============================================================
out Filename or :py:class:`io.StringIO`
kind "ans"
============= ==============================================================
.. _pbm:
**Portable Bitmap (PBM)**
All :ref:`common keywords <common_keywords>` are supported.
============= ==============================================================
Name Description
============= ==============================================================
out Filename or :py:class:`io.BytesIO`
kind "pbm"
scale integer
plain Default: False. Boolean to switch between the P4 and P1 format.
If set to ``True``, the (outdated) P1 serialization format is
used.
============= ==============================================================
.. _pam:
**Portable Arbitrary Map (PAM)**
All :ref:`common keywords <common_keywords>` are supported.
============= ==============================================================
Name Description
============= ==============================================================
out Filename or :py:class:`io.BytesIO`
kind "pam"
scale integer
dark Default: "#000" (black).
light Default value "#fff" (white). Use ``None`` for transparent
light modules.
============= ==============================================================
.. _ppm:
**Portable Pixmap (PPM)**
All :ref:`common keywords <common_keywords>` and :ref:`module colors <module_colors>`
are supported.
============= ==============================================================
Name Description
============= ==============================================================
out Filename or :py:class:`io.BytesIO`
kind "ppm"
scale integer
dark Default: "#000" (black).
light Default value "#fff" (white).
============= ==============================================================
.. _latex:
**LaTeX / PGF/TikZ**
To use the output of this serializer, the ``PGF/TikZ`` (and optionally
``hyperref``) package is required in the LaTeX environment. The
serializer itself does not depend on any external packages.
All :ref:`common keywords <common_keywords>` are supported.
============= ==============================================================
Name Description
============= ==============================================================
out Filename or :py:class:`io.StringIO`
kind "tex"
scale integer or float
dark LaTeX color name (default: "black"). The color is written
"at it is", please ensure that the color is a standard color
or it has been defined in the enclosing LaTeX document.
url Default: ``None``. Optional URL where the QR code should
point to. Requires the ``hyperref`` package in the LaTeX
environment.
============= ==============================================================
.. _xbm:
**X BitMap (XBM)**
All :ref:`common keywords <common_keywords>` are supported.
============= ==============================================================
Name Description
============= ==============================================================
out Filename or :py:class:`io.StringIO`
kind "xbm"
scale integer
name Name of the variable (default: "img")
============= ==============================================================
.. _xpm:
**X PixMap (XPM)**
All :ref:`common keywords <common_keywords>` are supported.
============= ==============================================================
Name Description
============= ==============================================================
out Filename or :py:class:`io.StringIO`
kind "xpm"
scale integer
dark Default: "#000" (black).
``None`` indicates transparent dark modules.
light Default value "#fff" (white)
``None`` indicates transparent light modules.
name Name of the variable (default: "img")
============= ==============================================================
:param out: A filename or a writable file-like object with a
``name`` attribute. Use the :paramref:`kind <segno.QRCode.save.kind>`
parameter if `out` is a :py:class:`io.BytesIO` or
:py:class:`io.StringIO` stream which don't have a ``name``
attribute.
:param str kind: Default ``None``.
If the desired output format cannot be determined from
the :paramref:`out <segno.QRCode.save.out>` parameter, this
parameter can be used to indicate the serialization format
(i.e. "svg" to enforce SVG output). The value is case
insensitive.
:param kw: Any of the supported keywords by the specific serializer.
| def save(self, out, kind=None, **kw):
"""\
Serializes the QR code in one of the supported formats.
The serialization format depends on the filename extension.
.. _common_keywords:
**Common keywords**
========== ==============================================================
Name Description
========== ==============================================================
scale Integer or float indicating the size of a single module.
Default: 1. The interpretation of the scaling factor depends
on the serializer. For pixel-based output (like :ref:`PNG <png>`)
the scaling factor is interpreted as pixel-size (1 = 1 pixel).
:ref:`EPS <eps>` interprets ``1`` as 1 point (1/72 inch) per
module.
Some serializers (like :ref:`SVG <svg>`) accept float values.
If the serializer does not accept float values, the value will be
converted to an integer value (note: int(1.6) == 1).
border Integer indicating the size of the quiet zone.
If set to ``None`` (default), the recommended border size
will be used (``4`` for QR codes, ``2`` for a Micro QR codes).
A value of ``0`` indicates that border should be omitted.
dark A string or tuple representing a color value for the dark
modules. The default value is "black". The color can be
provided as ``(R, G, B)`` tuple, as web color name
(like "red") or in hexadecimal format (``#RGB`` or
``#RRGGBB``). Some serializers (i.e. :ref:`SVG <svg>` and
:ref:`PNG <png>`) accept an alpha transparency value like
``#RRGGBBAA``.
light A string or tuple representing a color for the light modules.
See `dark` for valid values.
The default value depends on the serializer. :ref:`SVG <svg>`
uses no color (``None``) for light modules by default, other
serializers, like :ref:`PNG <png>`, use "white" as default
light color.
========== ==============================================================
.. _module_colors:
**Module Colors**
=============== =======================================================
Name Description
=============== =======================================================
finder_dark Color of the dark modules of the finder patterns
Default: undefined, use value of "dark"
finder_light Color of the light modules of the finder patterns
Default: undefined, use value of "light"
data_dark Color of the dark data modules
Default: undefined, use value of "dark"
data_light Color of the light data modules.
Default: undefined, use value of "light".
version_dark Color of the dark modules of the version information.
Default: undefined, use value of "dark".
version_light Color of the light modules of the version information,
Default: undefined, use value of "light".
format_dark Color of the dark modules of the format information.
Default: undefined, use value of "dark".
format_light Color of the light modules of the format information.
Default: undefined, use value of "light".
alignment_dark Color of the dark modules of the alignment patterns.
Default: undefined, use value of "dark".
alignment_light Color of the light modules of the alignment patterns.
Default: undefined, use value of "light".
timing_dark Color of the dark modules of the timing patterns.
Default: undefined, use value of "dark".
timing_light Color of the light modules of the timing patterns.
Default: undefined, use value of "light".
separator Color of the separator.
Default: undefined, use value of "light".
dark_module Color of the dark module (a single dark module which
occurs in all QR Codes but not in Micro QR Codes.
Default: undefined, use value of "dark".
quiet_zone Color of the quiet zone / border.
Default: undefined, use value of "light".
=============== =======================================================
.. _svg:
**Scalable Vector Graphics (SVG)**
All :ref:`common keywords <common_keywords>` and :ref:`module colors <module_colors>`
are supported.
================ ==============================================================
Name Description
================ ==============================================================
out Filename or :py:class:`io.BytesIO`
kind "svg" or "svgz" (to create a gzip compressed SVG)
scale integer or float
dark Default: "#000" (black)
``None`` is a valid value. If set to ``None``, the resulting
path won't have a "stroke" attribute. The "stroke" attribute
may be defined via CSS (external).
If an alpha channel is defined, the output depends of the
used SVG version. For SVG versions >= 2.0, the "stroke"
attribute will have a value like "rgba(R, G, B, A)", otherwise
the path gets another attribute "stroke-opacity" to emulate
the alpha channel.
To minimize the document size, the SVG serializer uses
automatically the shortest color representation: If
a value like "#000000" is provided, the resulting
document will have a color value of "#000". If the color
is "#FF0000", the resulting color is not "#F00", but
the web color name "red".
light Default value ``None``. If this parameter is set to another
value, the resulting image will have another path which
is used to define the color of the light modules.
If an alpha channel is used, the resulting path may
have a "fill-opacity" attribute (for SVG version < 2.0)
or the "fill" attribute has a "rgba(R, G, B, A)" value.
xmldecl Boolean value (default: ``True``) indicating whether the
document should have an XML declaration header.
Set to ``False`` to omit the header.
svgns Boolean value (default: ``True``) indicating whether the
document should have an explicit SVG namespace declaration.
Set to ``False`` to omit the namespace declaration.
The latter might be useful if the document should be
embedded into a HTML 5 document where the SVG namespace
is implicitly defined.
title String (default: ``None``) Optional title of the generated
SVG document.
desc String (default: ``None``) Optional description of the
generated SVG document.
svgid A string indicating the ID of the SVG document
(if set to ``None`` (default), the SVG element won't have
an ID).
svgclass Default: "segno". The CSS class of the SVG document
(if set to ``None``, the SVG element won't have a class).
lineclass Default: "qrline". The CSS class of the path element
(which draws the dark modules (if set to ``None``, the path
won't have a class).
omitsize Indicates if width and height attr | (self, out, kind=None, **kw) | [
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|
39,250 | segno | show | Displays this QR code.
This method is mainly intended for debugging purposes.
This method saves the QR code as an image (by default with a scaling
factor of 10) to a temporary file and opens it with the standard PNG
viewer application or within the standard webbrowser.
The temporary file is deleted afterwards (unless
:paramref:`delete_after <segno.QRCode.show.delete_after>` is set to ``None``).
If this method does not show any result, try to increase the
:paramref:`delete_after <segno.QRCode.show.delete_after>` value or set
it to ``None``
:param delete_after: Time in seconds to wait till the temporary file is
deleted.
:type delete_after: int or None
:param int scale: Integer indicating the size of a single module.
:param border: Integer indicating the size of the quiet zone.
If set to ``None`` (default), the recommended border size
will be used.
:type border: int or None
:param dark: The color of the dark modules (default: black).
:param light: The color of the light modules (default: white).
| def show(self, delete_after=20, scale=10, border=None, dark='#000',
light='#fff'): # pragma: no cover
"""\
Displays this QR code.
This method is mainly intended for debugging purposes.
This method saves the QR code as an image (by default with a scaling
factor of 10) to a temporary file and opens it with the standard PNG
viewer application or within the standard webbrowser.
The temporary file is deleted afterwards (unless
:paramref:`delete_after <segno.QRCode.show.delete_after>` is set to ``None``).
If this method does not show any result, try to increase the
:paramref:`delete_after <segno.QRCode.show.delete_after>` value or set
it to ``None``
:param delete_after: Time in seconds to wait till the temporary file is
deleted.
:type delete_after: int or None
:param int scale: Integer indicating the size of a single module.
:param border: Integer indicating the size of the quiet zone.
If set to ``None`` (default), the recommended border size
will be used.
:type border: int or None
:param dark: The color of the dark modules (default: black).
:param light: The color of the light modules (default: white).
"""
import os
import time
import tempfile
import webbrowser
import threading
from urllib.parse import urljoin
from urllib.request import pathname2url
def delete_file(name):
time.sleep(delete_after)
try:
os.unlink(name)
except OSError:
pass
f = tempfile.NamedTemporaryFile('wb', suffix='.png', delete=False)
try:
self.save(f, scale=scale, dark=dark, light=light, border=border)
except: # noqa: E722
f.close()
os.unlink(f.name)
raise
f.close()
webbrowser.open_new_tab(urljoin('file:', pathname2url(f.name)))
if delete_after is not None:
t = threading.Thread(target=delete_file, args=(f.name,))
t.start()
| (self, delete_after=20, scale=10, border=None, dark='#000', light='#fff') | [
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|
39,251 | segno | svg_data_uri | Converts the QR code into an SVG data URI.
The XML declaration is omitted by default (set
:paramref:`xmldecl <segno.QRCode.svg_data_uri.xmldecl>` to ``True``
to enable it), further the newline is omitted by default (set ``nl`` to
``True`` to enable it).
Aside from the missing `out` parameter, the different `xmldecl` and
`nl` default values, and the additional parameters
:paramref:`encode_minimal <segno.QRCode.svg_data_uri.encode_minimal>`
and :paramref:`omit_charset <segno.QRCode.svg_data_uri.omit_charset>`,
this method uses the same parameters as the usual SVG serializer, see
:py:func:`save` and the available `SVG parameters <#svg>`_
.. note::
In order to embed a SVG image in HTML without generating a file, the
:py:func:`svg_inline` method could serve better results, as it
usually produces a smaller output.
:param bool xmldecl: Indicates if the XML declaration should be
serialized (default: ``False``)
:param bool encode_minimal: Indicates if the resulting data URI should
use minimal percent encoding (disabled by default).
:param bool omit_charset: Indicates if the ``;charset=...`` should be omitted
(disabled by default)
:param bool nl: Indicates if the document should have a trailing newline
(default: ``False``)
:rtype: str
| def svg_data_uri(self, xmldecl=False, encode_minimal=False,
omit_charset=False, nl=False, **kw):
"""\
Converts the QR code into an SVG data URI.
The XML declaration is omitted by default (set
:paramref:`xmldecl <segno.QRCode.svg_data_uri.xmldecl>` to ``True``
to enable it), further the newline is omitted by default (set ``nl`` to
``True`` to enable it).
Aside from the missing `out` parameter, the different `xmldecl` and
`nl` default values, and the additional parameters
:paramref:`encode_minimal <segno.QRCode.svg_data_uri.encode_minimal>`
and :paramref:`omit_charset <segno.QRCode.svg_data_uri.omit_charset>`,
this method uses the same parameters as the usual SVG serializer, see
:py:func:`save` and the available `SVG parameters <#svg>`_
.. note::
In order to embed a SVG image in HTML without generating a file, the
:py:func:`svg_inline` method could serve better results, as it
usually produces a smaller output.
:param bool xmldecl: Indicates if the XML declaration should be
serialized (default: ``False``)
:param bool encode_minimal: Indicates if the resulting data URI should
use minimal percent encoding (disabled by default).
:param bool omit_charset: Indicates if the ``;charset=...`` should be omitted
(disabled by default)
:param bool nl: Indicates if the document should have a trailing newline
(default: ``False``)
:rtype: str
"""
return writers.as_svg_data_uri(self.matrix, self._matrix_size,
xmldecl=xmldecl, nl=nl,
encode_minimal=encode_minimal,
omit_charset=omit_charset, **kw)
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|
39,252 | segno | svg_inline | Returns an SVG representation which is embeddable into HTML5 contexts.
Due to the fact that HTML5 directly supports SVG, various elements of
an SVG document can or should be suppressed (i.e. the XML declaration and
the SVG namespace).
This method returns a string that can be used in an HTML context.
This method uses the same parameters as the usual SVG serializer, see
:py:func:`save` and the available `SVG parameters <#svg>`_ (the ``out``
and ``kind`` parameters are not supported).
The returned string can be used directly in
`Jinja <https://jinja.palletsprojects.com/>`_ and
`Django <https://www.djangoproject.com/>`_ templates, provided the
``safe`` filter is used which marks a string as not requiring further
HTML escaping prior to output.
::
<div>{{ qr.svg_inline(dark='#228b22', scale=3) | safe }}</div>
:rtype: str
| def svg_inline(self, **kw):
"""\
Returns an SVG representation which is embeddable into HTML5 contexts.
Due to the fact that HTML5 directly supports SVG, various elements of
an SVG document can or should be suppressed (i.e. the XML declaration and
the SVG namespace).
This method returns a string that can be used in an HTML context.
This method uses the same parameters as the usual SVG serializer, see
:py:func:`save` and the available `SVG parameters <#svg>`_ (the ``out``
and ``kind`` parameters are not supported).
The returned string can be used directly in
`Jinja <https://jinja.palletsprojects.com/>`_ and
`Django <https://www.djangoproject.com/>`_ templates, provided the
``safe`` filter is used which marks a string as not requiring further
HTML escaping prior to output.
::
<div>{{ qr.svg_inline(dark='#228b22', scale=3) | safe }}</div>
:rtype: str
"""
buff = io.BytesIO()
self.save(buff, kind='svg', xmldecl=False, svgns=False, nl=False, **kw)
return buff.getvalue().decode(kw.get('encoding', 'utf-8'))
| (self, **kw) | [
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|
39,253 | segno | symbol_size | Returns the symbol size (width x height) with the provided border and
scaling factor.
:param scale: Indicates the size of a single module (default: 1).
The size of a module depends on the used output format; i.e.
in a PNG context, a scaling factor of 2 indicates that a module
has a size of 2 x 2 pixel. Some outputs (i.e. SVG) accept
floating point values.
:type scale: int or float
:param int border: The border size or ``None`` to specify the
default quiet zone (4 for QR Codes, 2 for Micro QR Codes).
:rtype: tuple (width, height)
| def symbol_size(self, scale=1, border=None):
"""\
Returns the symbol size (width x height) with the provided border and
scaling factor.
:param scale: Indicates the size of a single module (default: 1).
The size of a module depends on the used output format; i.e.
in a PNG context, a scaling factor of 2 indicates that a module
has a size of 2 x 2 pixel. Some outputs (i.e. SVG) accept
floating point values.
:type scale: int or float
:param int border: The border size or ``None`` to specify the
default quiet zone (4 for QR Codes, 2 for Micro QR Codes).
:rtype: tuple (width, height)
"""
return utils.get_symbol_size(self._matrix_size, scale=scale, border=border)
| (self, scale=1, border=None) | [
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|
39,254 | segno | terminal | Serializes the matrix as ANSI escape code or Unicode Block Elements
(if ``compact`` is ``True``).
Under Windows, no ANSI escape sequence is generated but the Windows
API is used *unless* :paramref:`out <segno.QRCode.terminal.out>`
is a writable object or using WinAPI fails or if ``compact`` is ``True``.
:param out: Filename or a file-like object supporting to write text.
If ``None`` (default), the matrix is written to :py:class:`sys.stdout`.
:param int border: Integer indicating the size of the quiet zone.
If set to ``None`` (default), the recommended border size
will be used (``4`` for QR Codes, ``2`` for Micro QR Codes).
:param bool compact: Indicates if a more compact QR code should be shown
(default: ``False``).
| def terminal(self, out=None, border=None, compact=False):
"""\
Serializes the matrix as ANSI escape code or Unicode Block Elements
(if ``compact`` is ``True``).
Under Windows, no ANSI escape sequence is generated but the Windows
API is used *unless* :paramref:`out <segno.QRCode.terminal.out>`
is a writable object or using WinAPI fails or if ``compact`` is ``True``.
:param out: Filename or a file-like object supporting to write text.
If ``None`` (default), the matrix is written to :py:class:`sys.stdout`.
:param int border: Integer indicating the size of the quiet zone.
If set to ``None`` (default), the recommended border size
will be used (``4`` for QR Codes, ``2`` for Micro QR Codes).
:param bool compact: Indicates if a more compact QR code should be shown
(default: ``False``).
"""
if compact:
writers.write_terminal_compact(self.matrix, self._matrix_size, out or sys.stdout, border)
elif out is None and sys.platform == 'win32': # pragma: no cover
# Windows < 10 does not support ANSI escape sequences, try to
# call the a Windows specific terminal output which uses the
# Windows API.
try:
writers.write_terminal_win(self.matrix, self._matrix_size, border)
except OSError:
# Use the standard output even if it may print garbage
writers.write_terminal(self.matrix, self._matrix_size, sys.stdout, border)
else:
writers.write_terminal(self.matrix, self._matrix_size, out or sys.stdout, border)
| (self, out=None, border=None, compact=False) | [
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|
39,255 | segno | QRCodeSequence | Represents a sequence of 1 .. n (max. n = 16) :py:class:`QRCode` instances.
Iff this sequence contains only one item, it behaves like :py:class:`QRCode`.
| class QRCodeSequence(tuple):
"""\
Represents a sequence of 1 .. n (max. n = 16) :py:class:`QRCode` instances.
Iff this sequence contains only one item, it behaves like :py:class:`QRCode`.
"""
__slots__ = ()
def __new__(cls, qrcodes):
return super(QRCodeSequence, cls).__new__(cls, qrcodes)
def terminal(self, out=None, border=None, compact=False):
"""\
Serializes the sequence of QR codes as ANSI escape code.
See :py:meth:`QRCode.terminal()` for details.
"""
for qrcode in self:
qrcode.terminal(out=out, border=border, compact=compact)
def save(self, out, kind=None, **kw):
"""\
Saves the sequence of QR codes to `out`.
If `out` is a filename, this method modifies the filename and adds
``<Number of QR codes>-<Current QR code>`` to it.
``structured-append.svg`` becomes (if the sequence contains two QR codes):
``structured-append-02-01.svg`` and ``structured-append-02-02.svg``
Please note that using a file or file-like object may result into an
invalid serialization format since all QR codes are written to the same
output.
See :py:meth:`QRCode.save()` for a detailed enumeration of options.
"""
filename = lambda o, n: o # noqa: E731
m = len(self)
if m > 1 and isinstance(out, str):
dot_idx = out.rfind('.')
if dot_idx > -1:
out = out[:dot_idx] + '-{0:02d}-{1:02d}' + out[dot_idx:]
filename = lambda o, n: o.format(m, n) # noqa: E731
for n, qrcode in enumerate(self, start=1):
qrcode.save(filename(out, n), kind=kind, **kw)
def __getattr__(self, item):
"""\
Behaves like :py:class:`QRCode` iff this sequence contains a single item.
"""
if len(self) == 1:
return getattr(self[0], item)
raise AttributeError("{0} object has no attribute '{1}'"
.format(self.__class__, item))
| (qrcodes) | [
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0.01715875416994095,
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|
39,256 | segno | __getattr__ | Behaves like :py:class:`QRCode` iff this sequence contains a single item.
| def __getattr__(self, item):
"""\
Behaves like :py:class:`QRCode` iff this sequence contains a single item.
"""
if len(self) == 1:
return getattr(self[0], item)
raise AttributeError("{0} object has no attribute '{1}'"
.format(self.__class__, item))
| (self, item) | [
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|
39,257 | segno | __new__ | null | def __new__(cls, qrcodes):
return super(QRCodeSequence, cls).__new__(cls, qrcodes)
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|
39,258 | segno | save | Saves the sequence of QR codes to `out`.
If `out` is a filename, this method modifies the filename and adds
``<Number of QR codes>-<Current QR code>`` to it.
``structured-append.svg`` becomes (if the sequence contains two QR codes):
``structured-append-02-01.svg`` and ``structured-append-02-02.svg``
Please note that using a file or file-like object may result into an
invalid serialization format since all QR codes are written to the same
output.
See :py:meth:`QRCode.save()` for a detailed enumeration of options.
| def save(self, out, kind=None, **kw):
"""\
Saves the sequence of QR codes to `out`.
If `out` is a filename, this method modifies the filename and adds
``<Number of QR codes>-<Current QR code>`` to it.
``structured-append.svg`` becomes (if the sequence contains two QR codes):
``structured-append-02-01.svg`` and ``structured-append-02-02.svg``
Please note that using a file or file-like object may result into an
invalid serialization format since all QR codes are written to the same
output.
See :py:meth:`QRCode.save()` for a detailed enumeration of options.
"""
filename = lambda o, n: o # noqa: E731
m = len(self)
if m > 1 and isinstance(out, str):
dot_idx = out.rfind('.')
if dot_idx > -1:
out = out[:dot_idx] + '-{0:02d}-{1:02d}' + out[dot_idx:]
filename = lambda o, n: o.format(m, n) # noqa: E731
for n, qrcode in enumerate(self, start=1):
qrcode.save(filename(out, n), kind=kind, **kw)
| (self, out, kind=None, **kw) | [
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|
39,259 | segno | terminal | Serializes the sequence of QR codes as ANSI escape code.
See :py:meth:`QRCode.terminal()` for details.
| def terminal(self, out=None, border=None, compact=False):
"""\
Serializes the sequence of QR codes as ANSI escape code.
See :py:meth:`QRCode.terminal()` for details.
"""
for qrcode in self:
qrcode.terminal(out=out, border=border, compact=compact)
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|
39,263 | segno | make | Creates a (Micro) QR Code.
This is main entry point to create QR Codes and Micro QR Codes.
Aside from `content`, all parameters are optional and an optimal (minimal)
(Micro) QR code with a maximal error correction level is generated.
:param content: The data to encode. Either a Unicode string, an integer or
bytes. If bytes are provided, the `encoding` parameter should be
used to specify the used encoding.
:type content: str, int, bytes
:param error: Error correction level. If ``None`` (default), error
correction level ``L`` is used (note: Micro QR Code version M1 does
not support any error correction. If an explicit error correction
level is used, a M1 QR code won't be generated).
Valid values: ``None`` (allowing generation of M1 codes or use error
correction level "L" or better see :paramref:`boost_error <segno.make.boost_error>`),
"L", "M", "Q", "H" (error correction level "H" isn't available for
Micro QR Codes).
===================================== ===========================
Error correction level Error correction capability
===================================== ===========================
L (Segno's default unless version M1) recovers 7% of data
M recovers 15% of data
Q recovers 25% of data
H (not available for Micro QR Codes) recovers 30% of data
===================================== ===========================
Higher error levels may require larger QR codes (see also
:paramref:`version <segno.make.version>` parameter).
The `error` parameter is case insensitive.
See also the :paramref:`boost_error <segno.make.boost_error>` parameter.
:type error: str or None
:param version: QR Code version. If the value is ``None`` (default), the
minimal version which fits for the input data will be used.
Valid values: "M1", "M2", "M3", "M4" (for Micro QR codes) or an
integer between 1 and 40 (for QR codes).
The `version` parameter is case insensitive.
:type version: int, str or None
:param mode: "numeric", "alphanumeric", "byte", "kanji" or "hanzi".
If the value is ``None`` (default) the appropriate mode will
automatically be determined.
If `version` refers to a Micro QR code, this function may raise a
:py:exc:`ValueError` if the provided `mode` is not supported.
The `mode` parameter is case insensitive.
============ =======================
Mode (Micro) QR Code Version
============ =======================
numeric 1 - 40, M1, M2, M3, M4
alphanumeric 1 - 40, M2, M3, M4
byte 1 - 40, M3, M4
kanji 1 - 40, M3, M4
hanzi 1 - 40
============ =======================
.. note::
The Hanzi mode may not be supported by all QR code readers since
it is not part of ISO/IEC 18004:2015(E).
For this reason, this mode must be specified explicitly by the
user::
import segno
qrcode = segno.make('书读百遍其义自现', mode='hanzi')
:type mode: str or None
:param mask: Data mask. If the value is ``None`` (default), the
appropriate data mask is chosen automatically. If the `mask`
parameter is provided, this function may raise a :py:exc:`ValueError`
if the mask is invalid.
:type mask: int or None
:param encoding: Indicates the encoding in mode "byte". By default
(`encoding` is ``None``) the implementation tries to use the
standard conform ISO/IEC 8859-1 encoding and if it does not fit, it
will use UTF-8. Note that no ECI mode indicator is inserted by
default (see :paramref:`eci <segno.make.eci>`).
The `encoding` parameter is case insensitive.
:type encoding: str or None
:param bool eci: Indicates if binary data which does not use the default
encoding (ISO/IEC 8859-1) should enforce the ECI mode. Since a lot
of QR code readers do not support the ECI mode, this feature is
disabled by default and the data is encoded in the provided
`encoding` using the usual "byte" mode. Set `eci` to ``True`` if
an ECI header should be inserted into the QR Code. Note that
the implementation may not know the ECI designator for the provided
`encoding` and may raise an exception if the ECI designator cannot
be found.
The ECI mode is not supported by Micro QR Codes.
:param micro: If :paramref:`version <segno.make.version>` is ``None`` (default)
this parameter can be used to allow the creation of a Micro QR code.
If set to ``False``, a QR code is generated. If set to
``None`` (default) a Micro QR code may be generated if applicable.
If set to ``True`` the algorithm generates a Micro QR Code or
raises an exception if the `mode` is not compatible or the `content`
is too large for Micro QR codes.
:type micro: bool or None
:param bool boost_error: Indicates if the error correction level may be
increased if it does not affect the version (default: ``True``).
If set to ``True``, the :paramref:`error <segno.make.error>`
parameter is interpreted as minimum error level. If set to ``False``,
the resulting (Micro) QR code uses the provided `error` level
(or the default error correction level, if error is ``None``)
:raises: :py:exc:`ValueError` or :py:exc:`DataOverflowError`: In case the
data does not fit into a (Micro) QR Code or it does not fit into
the provided :paramref:`version`.
:rtype: QRCode
| def make(content, error=None, version=None, mode=None, mask=None, encoding=None,
eci=False, micro=None, boost_error=True):
"""\
Creates a (Micro) QR Code.
This is main entry point to create QR Codes and Micro QR Codes.
Aside from `content`, all parameters are optional and an optimal (minimal)
(Micro) QR code with a maximal error correction level is generated.
:param content: The data to encode. Either a Unicode string, an integer or
bytes. If bytes are provided, the `encoding` parameter should be
used to specify the used encoding.
:type content: str, int, bytes
:param error: Error correction level. If ``None`` (default), error
correction level ``L`` is used (note: Micro QR Code version M1 does
not support any error correction. If an explicit error correction
level is used, a M1 QR code won't be generated).
Valid values: ``None`` (allowing generation of M1 codes or use error
correction level "L" or better see :paramref:`boost_error <segno.make.boost_error>`),
"L", "M", "Q", "H" (error correction level "H" isn't available for
Micro QR Codes).
===================================== ===========================
Error correction level Error correction capability
===================================== ===========================
L (Segno's default unless version M1) recovers 7% of data
M recovers 15% of data
Q recovers 25% of data
H (not available for Micro QR Codes) recovers 30% of data
===================================== ===========================
Higher error levels may require larger QR codes (see also
:paramref:`version <segno.make.version>` parameter).
The `error` parameter is case insensitive.
See also the :paramref:`boost_error <segno.make.boost_error>` parameter.
:type error: str or None
:param version: QR Code version. If the value is ``None`` (default), the
minimal version which fits for the input data will be used.
Valid values: "M1", "M2", "M3", "M4" (for Micro QR codes) or an
integer between 1 and 40 (for QR codes).
The `version` parameter is case insensitive.
:type version: int, str or None
:param mode: "numeric", "alphanumeric", "byte", "kanji" or "hanzi".
If the value is ``None`` (default) the appropriate mode will
automatically be determined.
If `version` refers to a Micro QR code, this function may raise a
:py:exc:`ValueError` if the provided `mode` is not supported.
The `mode` parameter is case insensitive.
============ =======================
Mode (Micro) QR Code Version
============ =======================
numeric 1 - 40, M1, M2, M3, M4
alphanumeric 1 - 40, M2, M3, M4
byte 1 - 40, M3, M4
kanji 1 - 40, M3, M4
hanzi 1 - 40
============ =======================
.. note::
The Hanzi mode may not be supported by all QR code readers since
it is not part of ISO/IEC 18004:2015(E).
For this reason, this mode must be specified explicitly by the
user::
import segno
qrcode = segno.make('书读百遍其义自现', mode='hanzi')
:type mode: str or None
:param mask: Data mask. If the value is ``None`` (default), the
appropriate data mask is chosen automatically. If the `mask`
parameter is provided, this function may raise a :py:exc:`ValueError`
if the mask is invalid.
:type mask: int or None
:param encoding: Indicates the encoding in mode "byte". By default
(`encoding` is ``None``) the implementation tries to use the
standard conform ISO/IEC 8859-1 encoding and if it does not fit, it
will use UTF-8. Note that no ECI mode indicator is inserted by
default (see :paramref:`eci <segno.make.eci>`).
The `encoding` parameter is case insensitive.
:type encoding: str or None
:param bool eci: Indicates if binary data which does not use the default
encoding (ISO/IEC 8859-1) should enforce the ECI mode. Since a lot
of QR code readers do not support the ECI mode, this feature is
disabled by default and the data is encoded in the provided
`encoding` using the usual "byte" mode. Set `eci` to ``True`` if
an ECI header should be inserted into the QR Code. Note that
the implementation may not know the ECI designator for the provided
`encoding` and may raise an exception if the ECI designator cannot
be found.
The ECI mode is not supported by Micro QR Codes.
:param micro: If :paramref:`version <segno.make.version>` is ``None`` (default)
this parameter can be used to allow the creation of a Micro QR code.
If set to ``False``, a QR code is generated. If set to
``None`` (default) a Micro QR code may be generated if applicable.
If set to ``True`` the algorithm generates a Micro QR Code or
raises an exception if the `mode` is not compatible or the `content`
is too large for Micro QR codes.
:type micro: bool or None
:param bool boost_error: Indicates if the error correction level may be
increased if it does not affect the version (default: ``True``).
If set to ``True``, the :paramref:`error <segno.make.error>`
parameter is interpreted as minimum error level. If set to ``False``,
the resulting (Micro) QR code uses the provided `error` level
(or the default error correction level, if error is ``None``)
:raises: :py:exc:`ValueError` or :py:exc:`DataOverflowError`: In case the
data does not fit into a (Micro) QR Code or it does not fit into
the provided :paramref:`version`.
:rtype: QRCode
"""
return QRCode(encoder.encode(content, error, version, mode, mask, encoding,
eci, micro, boost_error=boost_error))
| (content, error=None, version=None, mode=None, mask=None, encoding=None, eci=False, micro=None, boost_error=True) | [
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|
39,264 | segno | make_micro | Creates a Micro QR code.
See :py:func:`make` for a description of the parameters.
Note: Error correction level "H" isn't available for Micro QR codes. If
used, this function raises a :py:class:`segno.ErrorLevelError`.
:rtype: QRCode
| def make_micro(content, error=None, version=None, mode=None, mask=None,
encoding=None, boost_error=True):
"""\
Creates a Micro QR code.
See :py:func:`make` for a description of the parameters.
Note: Error correction level "H" isn't available for Micro QR codes. If
used, this function raises a :py:class:`segno.ErrorLevelError`.
:rtype: QRCode
"""
return make(content, error=error, version=version, mode=mode, mask=mask,
encoding=encoding, micro=True, boost_error=boost_error)
| (content, error=None, version=None, mode=None, mask=None, encoding=None, boost_error=True) | [
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|
39,265 | segno | make_qr | Creates a QR code (never a Micro QR code).
See :py:func:`make` for a description of the parameters.
:rtype: QRCode
| def make_qr(content, error=None, version=None, mode=None, mask=None,
encoding=None, eci=False, boost_error=True):
"""\
Creates a QR code (never a Micro QR code).
See :py:func:`make` for a description of the parameters.
:rtype: QRCode
"""
return make(content, error=error, version=version, mode=mode, mask=mask,
encoding=encoding, eci=eci, micro=False, boost_error=boost_error)
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|
39,266 | segno | make_sequence | Creates a sequence of QR codes using the Structured Append mode.
If the content fits into one QR code and neither ``version`` nor
``symbol_count`` is provided, this function may return a sequence with
one QR Code which does not use the Structured Append mode. Otherwise a
sequence of 2 .. n (max. n = 16) QR codes is returned which use the
Structured Append mode.
The Structured Append mode allows to split the content over a number
(max. 16) QR Codes.
The Structured Append mode isn't available for Micro QR Codes, therefor
the returned sequence contains QR codes, only.
Since this function returns an iterable object, it may be used as follows:
.. code-block:: python
for i, qrcode in enumerate(segno.make_sequence(data, symbol_count=2)):
qrcode.save('seq-%d.svg' % i, scale=10, color='darkblue')
The number of QR codes is determined by the `version` or `symbol_count`
parameter.
See :py:func:`make` for a description of the other parameters.
:param int symbol_count: Number of symbols.
:rtype: QRCodeSequence
| def make_sequence(content, error=None, version=None, mode=None, mask=None,
encoding=None, boost_error=True, symbol_count=None):
"""\
Creates a sequence of QR codes using the Structured Append mode.
If the content fits into one QR code and neither ``version`` nor
``symbol_count`` is provided, this function may return a sequence with
one QR Code which does not use the Structured Append mode. Otherwise a
sequence of 2 .. n (max. n = 16) QR codes is returned which use the
Structured Append mode.
The Structured Append mode allows to split the content over a number
(max. 16) QR Codes.
The Structured Append mode isn't available for Micro QR Codes, therefor
the returned sequence contains QR codes, only.
Since this function returns an iterable object, it may be used as follows:
.. code-block:: python
for i, qrcode in enumerate(segno.make_sequence(data, symbol_count=2)):
qrcode.save('seq-%d.svg' % i, scale=10, color='darkblue')
The number of QR codes is determined by the `version` or `symbol_count`
parameter.
See :py:func:`make` for a description of the other parameters.
:param int symbol_count: Number of symbols.
:rtype: QRCodeSequence
"""
return QRCodeSequence(map(QRCode,
encoder.encode_sequence(content, error=error,
version=version,
mode=mode, mask=mask,
encoding=encoding,
boost_error=boost_error,
symbol_count=symbol_count)))
| (content, error=None, version=None, mode=None, mask=None, encoding=None, boost_error=True, symbol_count=None) | [
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|
39,270 | sparkypandy._column | Columny | null | class Columny(Column): # type: ignore
def __init__(self, jc: JavaObject, df_sparky: DataFrame):
super().__init__(jc=jc)
self.df_sparky = df_sparky
@property
def _name(self) -> str:
return cast(str, self._jc.toString())
@classmethod
def from_spark(cls, col: Column, df_sparky: DataFramy) -> Columny:
# noinspection PyProtectedMember
return cls(jc=col._jc, df_sparky=df_sparky)
def to_pandas(self) -> pd.Series:
# noinspection PyTypeChecker
df: pd.DataFrame = self.df_sparky.select(self._name).toPandas()
return df[self._name]
# def mean(self) -> float:
# r = df_spark.select(F.mean("a").alias("result")).collect()[0].result
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|
39,271 | pyspark.sql.column | _ | binary operator | def _bin_op(
name: str,
doc: str = "binary operator",
) -> Callable[
["Column", Union["Column", "LiteralType", "DecimalLiteral", "DateTimeLiteral"]], "Column"
]:
"""Create a method for given binary operator"""
def _(
self: "Column",
other: Union["Column", "LiteralType", "DecimalLiteral", "DateTimeLiteral"],
) -> "Column":
jc = other._jc if isinstance(other, Column) else other
njc = getattr(self._jc, name)(jc)
return Column(njc)
_.__doc__ = doc
return _
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|
39,273 | pyspark.sql.column | __nonzero__ | null | def __nonzero__(self) -> None:
raise PySparkValueError(
error_class="CANNOT_CONVERT_COLUMN_INTO_BOOL",
message_parameters={},
)
| (self) -> NoneType | [
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|
39,274 | pyspark.sql.column | __contains__ | null | def __contains__(self, item: Any) -> None:
raise PySparkValueError(
error_class="CANNOT_APPLY_IN_FOR_COLUMN",
message_parameters={},
)
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|
39,276 | pyspark.sql.column | __eq__ | binary function | def __eq__( # type: ignore[override]
self,
other: Union["Column", "LiteralType", "DecimalLiteral", "DateTimeLiteral"],
) -> "Column":
"""binary function"""
return _bin_op("equalTo")(self, other)
| (self, other: Union[ForwardRef('Column'), ForwardRef('LiteralType'), ForwardRef('DecimalLiteral'), ForwardRef('DateTimeLiteral')]) -> 'Column' | [
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|
39,278 | pyspark.sql.column | __getattr__ |
An expression that gets an item at position ``ordinal`` out of a list,
or gets an item by key out of a dict.
.. versionadded:: 1.3.0
.. versionchanged:: 3.4.0
Supports Spark Connect.
Parameters
----------
item
a literal value.
Returns
-------
:class:`Column`
Column representing the item got by key out of a dict.
Examples
--------
>>> df = spark.createDataFrame([('abcedfg', {"key": "value"})], ["l", "d"])
>>> df.select(df.d.key).show()
+------+
|d[key]|
+------+
| value|
+------+
| def __getattr__(self, item: Any) -> "Column":
"""
An expression that gets an item at position ``ordinal`` out of a list,
or gets an item by key out of a dict.
.. versionadded:: 1.3.0
.. versionchanged:: 3.4.0
Supports Spark Connect.
Parameters
----------
item
a literal value.
Returns
-------
:class:`Column`
Column representing the item got by key out of a dict.
Examples
--------
>>> df = spark.createDataFrame([('abcedfg', {"key": "value"})], ["l", "d"])
>>> df.select(df.d.key).show()
+------+
|d[key]|
+------+
| value|
+------+
"""
if item.startswith("__"):
raise PySparkAttributeError(
error_class="CANNOT_ACCESS_TO_DUNDER",
message_parameters={},
)
return self[item]
| (self, item: Any) -> pyspark.sql.column.Column | [
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|
39,279 | pyspark.sql.column | __getitem__ |
An expression that gets an item at position ``ordinal`` out of a list,
or gets an item by key out of a dict.
.. versionadded:: 1.3.0
.. versionchanged:: 3.4.0
Supports Spark Connect.
Parameters
----------
k
a literal value, or a slice object without step.
Returns
-------
:class:`Column`
Column representing the item got by key out of a dict, or substrings sliced by
the given slice object.
Examples
--------
>>> df = spark.createDataFrame([('abcedfg', {"key": "value"})], ["l", "d"])
>>> df.select(df.l[slice(1, 3)], df.d['key']).show()
+------------------+------+
|substring(l, 1, 3)|d[key]|
+------------------+------+
| abc| value|
+------------------+------+
| def __getitem__(self, k: Any) -> "Column":
"""
An expression that gets an item at position ``ordinal`` out of a list,
or gets an item by key out of a dict.
.. versionadded:: 1.3.0
.. versionchanged:: 3.4.0
Supports Spark Connect.
Parameters
----------
k
a literal value, or a slice object without step.
Returns
-------
:class:`Column`
Column representing the item got by key out of a dict, or substrings sliced by
the given slice object.
Examples
--------
>>> df = spark.createDataFrame([('abcedfg', {"key": "value"})], ["l", "d"])
>>> df.select(df.l[slice(1, 3)], df.d['key']).show()
+------------------+------+
|substring(l, 1, 3)|d[key]|
+------------------+------+
| abc| value|
+------------------+------+
"""
if isinstance(k, slice):
if k.step is not None:
raise PySparkValueError(
error_class="SLICE_WITH_STEP",
message_parameters={},
)
return self.substr(k.start, k.stop)
else:
return _bin_op("apply")(self, k)
| (self, k: Any) -> pyspark.sql.column.Column | [
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|
39,281 | sparkypandy._column | __init__ | null | def __init__(self, jc: JavaObject, df_sparky: DataFrame):
super().__init__(jc=jc)
self.df_sparky = df_sparky
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|
39,282 | pyspark.sql.column | _ | def _func_op(name: str, doc: str = "") -> Callable[["Column"], "Column"]:
def _(self: "Column") -> "Column":
sc = get_active_spark_context()
jc = getattr(cast(JVMView, sc._jvm).functions, name)(self._jc)
return Column(jc)
_.__doc__ = doc
return _
| (self: pyspark.sql.column.Column) -> pyspark.sql.column.Column | [
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|
|
39,283 | pyspark.sql.column | __iter__ | null | def __iter__(self) -> None:
raise PySparkTypeError(
error_class="NOT_ITERABLE", message_parameters={"objectName": "Column"}
)
| (self) -> NoneType | [
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|
39,288 | pyspark.sql.column | __ne__ | binary function | def __ne__( # type: ignore[override]
self,
other: Any,
) -> "Column":
"""binary function"""
return _bin_op("notEqual")(self, other)
| (self, other: Any) -> pyspark.sql.column.Column | [
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|
39,292 | pyspark.sql.column | _ | binary function | def _bin_func_op(
name: str,
reverse: bool = False,
doc: str = "binary function",
) -> Callable[["Column", Union["Column", "LiteralType", "DecimalLiteral"]], "Column"]:
def _(self: "Column", other: Union["Column", "LiteralType", "DecimalLiteral"]) -> "Column":
sc = get_active_spark_context()
fn = getattr(cast(JVMView, sc._jvm).functions, name)
jc = other._jc if isinstance(other, Column) else _create_column_from_literal(other)
njc = fn(self._jc, jc) if not reverse else fn(jc, self._jc)
return Column(njc)
_.__doc__ = doc
return _
| (self: 'Column', other: Union[ForwardRef('Column'), ForwardRef('LiteralType'), ForwardRef('DecimalLiteral')]) -> 'Column' | [
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|
39,295 | pyspark.sql.column | _ | binary operator | def _reverse_op(
name: str,
doc: str = "binary operator",
) -> Callable[["Column", Union["LiteralType", "DecimalLiteral"]], "Column"]:
"""Create a method for binary operator (this object is on right side)"""
def _(self: "Column", other: Union["LiteralType", "DecimalLiteral"]) -> "Column":
jother = _create_column_from_literal(other)
jc = getattr(jother, name)(self._jc)
return Column(jc)
_.__doc__ = doc
return _
| (self: 'Column', other: Union[ForwardRef('LiteralType'), ForwardRef('DecimalLiteral')]) -> 'Column' | [
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|
39,296 | pyspark.sql.column | __repr__ | null | def __repr__(self) -> str:
return "Column<'%s'>" % self._jc.toString()
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|
39,305 | pyspark.sql.column | alias |
Returns this column aliased with a new name or names (in the case of expressions that
return more than one column, such as explode).
.. versionadded:: 1.3.0
.. versionchanged:: 3.4.0
Supports Spark Connect.
Parameters
----------
alias : str
desired column names (collects all positional arguments passed)
Other Parameters
----------------
metadata: dict
a dict of information to be stored in ``metadata`` attribute of the
corresponding :class:`StructField <pyspark.sql.types.StructField>` (optional, keyword
only argument)
.. versionchanged:: 2.2.0
Added optional ``metadata`` argument.
Returns
-------
:class:`Column`
Column representing whether each element of Column is aliased with new name or names.
Examples
--------
>>> df = spark.createDataFrame(
... [(2, "Alice"), (5, "Bob")], ["age", "name"])
>>> df.select(df.age.alias("age2")).collect()
[Row(age2=2), Row(age2=5)]
>>> df.select(df.age.alias("age3", metadata={'max': 99})).schema['age3'].metadata['max']
99
| def alias(self, *alias: str, **kwargs: Any) -> "Column":
"""
Returns this column aliased with a new name or names (in the case of expressions that
return more than one column, such as explode).
.. versionadded:: 1.3.0
.. versionchanged:: 3.4.0
Supports Spark Connect.
Parameters
----------
alias : str
desired column names (collects all positional arguments passed)
Other Parameters
----------------
metadata: dict
a dict of information to be stored in ``metadata`` attribute of the
corresponding :class:`StructField <pyspark.sql.types.StructField>` (optional, keyword
only argument)
.. versionchanged:: 2.2.0
Added optional ``metadata`` argument.
Returns
-------
:class:`Column`
Column representing whether each element of Column is aliased with new name or names.
Examples
--------
>>> df = spark.createDataFrame(
... [(2, "Alice"), (5, "Bob")], ["age", "name"])
>>> df.select(df.age.alias("age2")).collect()
[Row(age2=2), Row(age2=5)]
>>> df.select(df.age.alias("age3", metadata={'max': 99})).schema['age3'].metadata['max']
99
"""
metadata = kwargs.pop("metadata", None)
assert not kwargs, "Unexpected kwargs where passed: %s" % kwargs
sc = get_active_spark_context()
if len(alias) == 1:
if metadata:
assert sc._jvm is not None
jmeta = sc._jvm.org.apache.spark.sql.types.Metadata.fromJson(json.dumps(metadata))
return Column(getattr(self._jc, "as")(alias[0], jmeta))
else:
return Column(getattr(self._jc, "as")(alias[0]))
else:
if metadata:
raise PySparkValueError(
error_class="ONLY_ALLOWED_FOR_SINGLE_COLUMN",
message_parameters={"arg_name": "metadata"},
)
return Column(getattr(self._jc, "as")(_to_seq(sc, list(alias))))
| (self, *alias: str, **kwargs: Any) -> pyspark.sql.column.Column | [
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|
39,306 | pyspark.sql.column | _ |
Returns a sort expression based on the ascending order of the column.
.. versionchanged:: 3.4.0
Supports Spark Connect.
Examples
--------
>>> from pyspark.sql import Row
>>> df = spark.createDataFrame([('Tom', 80), ('Alice', None)], ["name", "height"])
>>> df.select(df.name).orderBy(df.name.asc()).collect()
[Row(name='Alice'), Row(name='Tom')]
| def _unary_op(
name: str,
doc: str = "unary operator",
) -> Callable[["Column"], "Column"]:
"""Create a method for given unary operator"""
def _(self: "Column") -> "Column":
jc = getattr(self._jc, name)()
return Column(jc)
_.__doc__ = doc
return _
| (self: pyspark.sql.column.Column) -> pyspark.sql.column.Column | [
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|
39,307 | pyspark.sql.column | _ |
Returns a sort expression based on ascending order of the column, and null values
return before non-null values.
.. versionadded:: 2.4.0
.. versionchanged:: 3.4.0
Supports Spark Connect.
Examples
--------
>>> from pyspark.sql import Row
>>> df = spark.createDataFrame([('Tom', 80), (None, 60), ('Alice', None)], ["name", "height"])
>>> df.select(df.name).orderBy(df.name.asc_nulls_first()).collect()
[Row(name=None), Row(name='Alice'), Row(name='Tom')]
| def _unary_op(
name: str,
doc: str = "unary operator",
) -> Callable[["Column"], "Column"]:
"""Create a method for given unary operator"""
def _(self: "Column") -> "Column":
jc = getattr(self._jc, name)()
return Column(jc)
_.__doc__ = doc
return _
| (self: pyspark.sql.column.Column) -> pyspark.sql.column.Column | [
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|
39,308 | pyspark.sql.column | _ |
Returns a sort expression based on ascending order of the column, and null values
appear after non-null values.
.. versionadded:: 2.4.0
.. versionchanged:: 3.4.0
Supports Spark Connect.
Examples
--------
>>> from pyspark.sql import Row
>>> df = spark.createDataFrame([('Tom', 80), (None, 60), ('Alice', None)], ["name", "height"])
>>> df.select(df.name).orderBy(df.name.asc_nulls_last()).collect()
[Row(name='Alice'), Row(name='Tom'), Row(name=None)]
| def _unary_op(
name: str,
doc: str = "unary operator",
) -> Callable[["Column"], "Column"]:
"""Create a method for given unary operator"""
def _(self: "Column") -> "Column":
jc = getattr(self._jc, name)()
return Column(jc)
_.__doc__ = doc
return _
| (self: pyspark.sql.column.Column) -> pyspark.sql.column.Column | [
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|
39,309 | pyspark.sql.column | cast | :func:`astype` is an alias for :func:`cast`.
.. versionadded:: 1.4 | def cast(self, dataType: Union[DataType, str]) -> "Column":
"""
Casts the column into type ``dataType``.
.. versionadded:: 1.3.0
.. versionchanged:: 3.4.0
Supports Spark Connect.
Parameters
----------
dataType : :class:`DataType` or str
a DataType or Python string literal with a DDL-formatted string
to use when parsing the column to the same type.
Returns
-------
:class:`Column`
Column representing whether each element of Column is cast into new type.
Examples
--------
>>> from pyspark.sql.types import StringType
>>> df = spark.createDataFrame(
... [(2, "Alice"), (5, "Bob")], ["age", "name"])
>>> df.select(df.age.cast("string").alias('ages')).collect()
[Row(ages='2'), Row(ages='5')]
>>> df.select(df.age.cast(StringType()).alias('ages')).collect()
[Row(ages='2'), Row(ages='5')]
"""
if isinstance(dataType, str):
jc = self._jc.cast(dataType)
elif isinstance(dataType, DataType):
from pyspark.sql import SparkSession
spark = SparkSession._getActiveSessionOrCreate()
jdt = spark._jsparkSession.parseDataType(dataType.json())
jc = self._jc.cast(jdt)
else:
raise PySparkTypeError(
error_class="NOT_DATATYPE_OR_STR",
message_parameters={"arg_name": "dataType", "arg_type": type(dataType).__name__},
)
return Column(jc)
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|
39,310 | pyspark.sql.column | between |
True if the current column is between the lower bound and upper bound, inclusive.
.. versionadded:: 1.3.0
.. versionchanged:: 3.4.0
Supports Spark Connect.
Parameters
----------
lowerBound : :class:`Column`, int, float, string, bool, datetime, date or Decimal
a boolean expression that boundary start, inclusive.
upperBound : :class:`Column`, int, float, string, bool, datetime, date or Decimal
a boolean expression that boundary end, inclusive.
Returns
-------
:class:`Column`
Column of booleans showing whether each element of Column
is between left and right (inclusive).
Examples
--------
>>> df = spark.createDataFrame(
... [(2, "Alice"), (5, "Bob")], ["age", "name"])
>>> df.select(df.name, df.age.between(2, 4)).show()
+-----+---------------------------+
| name|((age >= 2) AND (age <= 4))|
+-----+---------------------------+
|Alice| true|
| Bob| false|
+-----+---------------------------+
| def between(
self,
lowerBound: Union["Column", "LiteralType", "DateTimeLiteral", "DecimalLiteral"],
upperBound: Union["Column", "LiteralType", "DateTimeLiteral", "DecimalLiteral"],
) -> "Column":
"""
True if the current column is between the lower bound and upper bound, inclusive.
.. versionadded:: 1.3.0
.. versionchanged:: 3.4.0
Supports Spark Connect.
Parameters
----------
lowerBound : :class:`Column`, int, float, string, bool, datetime, date or Decimal
a boolean expression that boundary start, inclusive.
upperBound : :class:`Column`, int, float, string, bool, datetime, date or Decimal
a boolean expression that boundary end, inclusive.
Returns
-------
:class:`Column`
Column of booleans showing whether each element of Column
is between left and right (inclusive).
Examples
--------
>>> df = spark.createDataFrame(
... [(2, "Alice"), (5, "Bob")], ["age", "name"])
>>> df.select(df.name, df.age.between(2, 4)).show()
+-----+---------------------------+
| name|((age >= 2) AND (age <= 4))|
+-----+---------------------------+
|Alice| true|
| Bob| false|
+-----+---------------------------+
"""
return (self >= lowerBound) & (self <= upperBound)
| (self, lowerBound: Union[ForwardRef('Column'), ForwardRef('LiteralType'), ForwardRef('DateTimeLiteral'), ForwardRef('DecimalLiteral')], upperBound: Union[ForwardRef('Column'), ForwardRef('LiteralType'), ForwardRef('DateTimeLiteral'), ForwardRef('DecimalLiteral')]) -> 'Column' | [
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|
39,311 | pyspark.sql.column | _ |
Compute bitwise AND of this expression with another expression.
.. versionchanged:: 3.4.0
Supports Spark Connect.
Parameters
----------
other
a value or :class:`Column` to calculate bitwise and(&) with
this :class:`Column`.
Examples
--------
>>> from pyspark.sql import Row
>>> df = spark.createDataFrame([Row(a=170, b=75)])
>>> df.select(df.a.bitwiseAND(df.b)).collect()
[Row((a & b)=10)]
| def _bin_op(
name: str,
doc: str = "binary operator",
) -> Callable[
["Column", Union["Column", "LiteralType", "DecimalLiteral", "DateTimeLiteral"]], "Column"
]:
"""Create a method for given binary operator"""
def _(
self: "Column",
other: Union["Column", "LiteralType", "DecimalLiteral", "DateTimeLiteral"],
) -> "Column":
jc = other._jc if isinstance(other, Column) else other
njc = getattr(self._jc, name)(jc)
return Column(njc)
_.__doc__ = doc
return _
| (self: 'Column', other: Union[ForwardRef('Column'), ForwardRef('LiteralType'), ForwardRef('DecimalLiteral'), ForwardRef('DateTimeLiteral')]) -> 'Column' | [
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|
39,312 | pyspark.sql.column | _ |
Compute bitwise OR of this expression with another expression.
.. versionchanged:: 3.4.0
Supports Spark Connect.
Parameters
----------
other
a value or :class:`Column` to calculate bitwise or(|) with
this :class:`Column`.
Examples
--------
>>> from pyspark.sql import Row
>>> df = spark.createDataFrame([Row(a=170, b=75)])
>>> df.select(df.a.bitwiseOR(df.b)).collect()
[Row((a | b)=235)]
| def _bin_op(
name: str,
doc: str = "binary operator",
) -> Callable[
["Column", Union["Column", "LiteralType", "DecimalLiteral", "DateTimeLiteral"]], "Column"
]:
"""Create a method for given binary operator"""
def _(
self: "Column",
other: Union["Column", "LiteralType", "DecimalLiteral", "DateTimeLiteral"],
) -> "Column":
jc = other._jc if isinstance(other, Column) else other
njc = getattr(self._jc, name)(jc)
return Column(njc)
_.__doc__ = doc
return _
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|
39,313 | pyspark.sql.column | _ |
Compute bitwise XOR of this expression with another expression.
.. versionchanged:: 3.4.0
Supports Spark Connect.
Parameters
----------
other
a value or :class:`Column` to calculate bitwise xor(^) with
this :class:`Column`.
Examples
--------
>>> from pyspark.sql import Row
>>> df = spark.createDataFrame([Row(a=170, b=75)])
>>> df.select(df.a.bitwiseXOR(df.b)).collect()
[Row((a ^ b)=225)]
| def _bin_op(
name: str,
doc: str = "binary operator",
) -> Callable[
["Column", Union["Column", "LiteralType", "DecimalLiteral", "DateTimeLiteral"]], "Column"
]:
"""Create a method for given binary operator"""
def _(
self: "Column",
other: Union["Column", "LiteralType", "DecimalLiteral", "DateTimeLiteral"],
) -> "Column":
jc = other._jc if isinstance(other, Column) else other
njc = getattr(self._jc, name)(jc)
return Column(njc)
_.__doc__ = doc
return _
| (self: 'Column', other: Union[ForwardRef('Column'), ForwardRef('LiteralType'), ForwardRef('DecimalLiteral'), ForwardRef('DateTimeLiteral')]) -> 'Column' | [
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|
39,314 | pyspark.sql.column | cast |
Casts the column into type ``dataType``.
.. versionadded:: 1.3.0
.. versionchanged:: 3.4.0
Supports Spark Connect.
Parameters
----------
dataType : :class:`DataType` or str
a DataType or Python string literal with a DDL-formatted string
to use when parsing the column to the same type.
Returns
-------
:class:`Column`
Column representing whether each element of Column is cast into new type.
Examples
--------
>>> from pyspark.sql.types import StringType
>>> df = spark.createDataFrame(
... [(2, "Alice"), (5, "Bob")], ["age", "name"])
>>> df.select(df.age.cast("string").alias('ages')).collect()
[Row(ages='2'), Row(ages='5')]
>>> df.select(df.age.cast(StringType()).alias('ages')).collect()
[Row(ages='2'), Row(ages='5')]
| def cast(self, dataType: Union[DataType, str]) -> "Column":
"""
Casts the column into type ``dataType``.
.. versionadded:: 1.3.0
.. versionchanged:: 3.4.0
Supports Spark Connect.
Parameters
----------
dataType : :class:`DataType` or str
a DataType or Python string literal with a DDL-formatted string
to use when parsing the column to the same type.
Returns
-------
:class:`Column`
Column representing whether each element of Column is cast into new type.
Examples
--------
>>> from pyspark.sql.types import StringType
>>> df = spark.createDataFrame(
... [(2, "Alice"), (5, "Bob")], ["age", "name"])
>>> df.select(df.age.cast("string").alias('ages')).collect()
[Row(ages='2'), Row(ages='5')]
>>> df.select(df.age.cast(StringType()).alias('ages')).collect()
[Row(ages='2'), Row(ages='5')]
"""
if isinstance(dataType, str):
jc = self._jc.cast(dataType)
elif isinstance(dataType, DataType):
from pyspark.sql import SparkSession
spark = SparkSession._getActiveSessionOrCreate()
jdt = spark._jsparkSession.parseDataType(dataType.json())
jc = self._jc.cast(jdt)
else:
raise PySparkTypeError(
error_class="NOT_DATATYPE_OR_STR",
message_parameters={"arg_name": "dataType", "arg_type": type(dataType).__name__},
)
return Column(jc)
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|
39,315 | pyspark.sql.column | _ |
Contains the other element. Returns a boolean :class:`Column` based on a string match.
.. versionchanged:: 3.4.0
Supports Spark Connect.
Parameters
----------
other
string in line. A value as a literal or a :class:`Column`.
Examples
--------
>>> df = spark.createDataFrame(
... [(2, "Alice"), (5, "Bob")], ["age", "name"])
>>> df.filter(df.name.contains('o')).collect()
[Row(age=5, name='Bob')]
| def _bin_op(
name: str,
doc: str = "binary operator",
) -> Callable[
["Column", Union["Column", "LiteralType", "DecimalLiteral", "DateTimeLiteral"]], "Column"
]:
"""Create a method for given binary operator"""
def _(
self: "Column",
other: Union["Column", "LiteralType", "DecimalLiteral", "DateTimeLiteral"],
) -> "Column":
jc = other._jc if isinstance(other, Column) else other
njc = getattr(self._jc, name)(jc)
return Column(njc)
_.__doc__ = doc
return _
| (self: 'Column', other: Union[ForwardRef('Column'), ForwardRef('LiteralType'), ForwardRef('DecimalLiteral'), ForwardRef('DateTimeLiteral')]) -> 'Column' | [
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|
39,316 | pyspark.sql.column | _ |
Returns a sort expression based on the descending order of the column.
.. versionadded:: 2.4.0
.. versionchanged:: 3.4.0
Supports Spark Connect.
Examples
--------
>>> from pyspark.sql import Row
>>> df = spark.createDataFrame([('Tom', 80), ('Alice', None)], ["name", "height"])
>>> df.select(df.name).orderBy(df.name.desc()).collect()
[Row(name='Tom'), Row(name='Alice')]
| def _unary_op(
name: str,
doc: str = "unary operator",
) -> Callable[["Column"], "Column"]:
"""Create a method for given unary operator"""
def _(self: "Column") -> "Column":
jc = getattr(self._jc, name)()
return Column(jc)
_.__doc__ = doc
return _
| (self: pyspark.sql.column.Column) -> pyspark.sql.column.Column | [
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|
39,317 | pyspark.sql.column | _ |
Returns a sort expression based on the descending order of the column, and null values
appear before non-null values.
.. versionadded:: 2.4.0
.. versionchanged:: 3.4.0
Supports Spark Connect.
Examples
--------
>>> from pyspark.sql import Row
>>> df = spark.createDataFrame([('Tom', 80), (None, 60), ('Alice', None)], ["name", "height"])
>>> df.select(df.name).orderBy(df.name.desc_nulls_first()).collect()
[Row(name=None), Row(name='Tom'), Row(name='Alice')]
| def _unary_op(
name: str,
doc: str = "unary operator",
) -> Callable[["Column"], "Column"]:
"""Create a method for given unary operator"""
def _(self: "Column") -> "Column":
jc = getattr(self._jc, name)()
return Column(jc)
_.__doc__ = doc
return _
| (self: pyspark.sql.column.Column) -> pyspark.sql.column.Column | [
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|
39,318 | pyspark.sql.column | _ |
Returns a sort expression based on the descending order of the column, and null values
appear after non-null values.
.. versionadded:: 2.4.0
.. versionchanged:: 3.4.0
Supports Spark Connect.
Examples
--------
>>> from pyspark.sql import Row
>>> df = spark.createDataFrame([('Tom', 80), (None, 60), ('Alice', None)], ["name", "height"])
>>> df.select(df.name).orderBy(df.name.desc_nulls_last()).collect()
[Row(name='Tom'), Row(name='Alice'), Row(name=None)]
| def _unary_op(
name: str,
doc: str = "unary operator",
) -> Callable[["Column"], "Column"]:
"""Create a method for given unary operator"""
def _(self: "Column") -> "Column":
jc = getattr(self._jc, name)()
return Column(jc)
_.__doc__ = doc
return _
| (self: pyspark.sql.column.Column) -> pyspark.sql.column.Column | [
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|
39,319 | pyspark.sql.column | dropFields |
An expression that drops fields in :class:`StructType` by name.
This is a no-op if the schema doesn't contain field name(s).
.. versionadded:: 3.1.0
.. versionchanged:: 3.4.0
Supports Spark Connect.
Parameters
----------
fieldNames : str
Desired field names (collects all positional arguments passed)
The result will drop at a location if any field matches in the Column.
Returns
-------
:class:`Column`
Column representing whether each element of Column with field dropped by fieldName.
Examples
--------
>>> from pyspark.sql import Row
>>> from pyspark.sql.functions import col, lit
>>> df = spark.createDataFrame([
... Row(a=Row(b=1, c=2, d=3, e=Row(f=4, g=5, h=6)))])
>>> df.withColumn('a', df['a'].dropFields('b')).show()
+-----------------+
| a|
+-----------------+
|{2, 3, {4, 5, 6}}|
+-----------------+
>>> df.withColumn('a', df['a'].dropFields('b', 'c')).show()
+--------------+
| a|
+--------------+
|{3, {4, 5, 6}}|
+--------------+
This method supports dropping multiple nested fields directly e.g.
>>> df.withColumn("a", col("a").dropFields("e.g", "e.h")).show()
+--------------+
| a|
+--------------+
|{1, 2, 3, {4}}|
+--------------+
However, if you are going to add/replace multiple nested fields,
it is preferred to extract out the nested struct before
adding/replacing multiple fields e.g.
>>> df.select(col("a").withField(
... "e", col("a.e").dropFields("g", "h")).alias("a")
... ).show()
+--------------+
| a|
+--------------+
|{1, 2, 3, {4}}|
+--------------+
| def dropFields(self, *fieldNames: str) -> "Column":
"""
An expression that drops fields in :class:`StructType` by name.
This is a no-op if the schema doesn't contain field name(s).
.. versionadded:: 3.1.0
.. versionchanged:: 3.4.0
Supports Spark Connect.
Parameters
----------
fieldNames : str
Desired field names (collects all positional arguments passed)
The result will drop at a location if any field matches in the Column.
Returns
-------
:class:`Column`
Column representing whether each element of Column with field dropped by fieldName.
Examples
--------
>>> from pyspark.sql import Row
>>> from pyspark.sql.functions import col, lit
>>> df = spark.createDataFrame([
... Row(a=Row(b=1, c=2, d=3, e=Row(f=4, g=5, h=6)))])
>>> df.withColumn('a', df['a'].dropFields('b')).show()
+-----------------+
| a|
+-----------------+
|{2, 3, {4, 5, 6}}|
+-----------------+
>>> df.withColumn('a', df['a'].dropFields('b', 'c')).show()
+--------------+
| a|
+--------------+
|{3, {4, 5, 6}}|
+--------------+
This method supports dropping multiple nested fields directly e.g.
>>> df.withColumn("a", col("a").dropFields("e.g", "e.h")).show()
+--------------+
| a|
+--------------+
|{1, 2, 3, {4}}|
+--------------+
However, if you are going to add/replace multiple nested fields,
it is preferred to extract out the nested struct before
adding/replacing multiple fields e.g.
>>> df.select(col("a").withField(
... "e", col("a.e").dropFields("g", "h")).alias("a")
... ).show()
+--------------+
| a|
+--------------+
|{1, 2, 3, {4}}|
+--------------+
"""
sc = get_active_spark_context()
jc = self._jc.dropFields(_to_seq(sc, fieldNames))
return Column(jc)
| (self, *fieldNames: str) -> pyspark.sql.column.Column | [
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|
39,320 | pyspark.sql.column | _ |
String ends with. Returns a boolean :class:`Column` based on a string match.
.. versionchanged:: 3.4.0
Supports Spark Connect.
Parameters
----------
other : :class:`Column` or str
string at end of line (do not use a regex `$`)
Examples
--------
>>> df = spark.createDataFrame(
... [(2, "Alice"), (5, "Bob")], ["age", "name"])
>>> df.filter(df.name.endswith('ice')).collect()
[Row(age=2, name='Alice')]
>>> df.filter(df.name.endswith('ice$')).collect()
[]
| def _bin_op(
name: str,
doc: str = "binary operator",
) -> Callable[
["Column", Union["Column", "LiteralType", "DecimalLiteral", "DateTimeLiteral"]], "Column"
]:
"""Create a method for given binary operator"""
def _(
self: "Column",
other: Union["Column", "LiteralType", "DecimalLiteral", "DateTimeLiteral"],
) -> "Column":
jc = other._jc if isinstance(other, Column) else other
njc = getattr(self._jc, name)(jc)
return Column(njc)
_.__doc__ = doc
return _
| (self: 'Column', other: Union[ForwardRef('Column'), ForwardRef('LiteralType'), ForwardRef('DecimalLiteral'), ForwardRef('DateTimeLiteral')]) -> 'Column' | [
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|
39,321 | pyspark.sql.column | _ |
Equality test that is safe for null values.
.. versionadded:: 2.3.0
.. versionchanged:: 3.4.0
Supports Spark Connect.
Parameters
----------
other
a value or :class:`Column`
Examples
--------
>>> from pyspark.sql import Row
>>> df1 = spark.createDataFrame([
... Row(id=1, value='foo'),
... Row(id=2, value=None)
... ])
>>> df1.select(
... df1['value'] == 'foo',
... df1['value'].eqNullSafe('foo'),
... df1['value'].eqNullSafe(None)
... ).show()
+-------------+---------------+----------------+
|(value = foo)|(value <=> foo)|(value <=> NULL)|
+-------------+---------------+----------------+
| true| true| false|
| NULL| false| true|
+-------------+---------------+----------------+
>>> df2 = spark.createDataFrame([
... Row(value = 'bar'),
... Row(value = None)
... ])
>>> df1.join(df2, df1["value"] == df2["value"]).count()
0
>>> df1.join(df2, df1["value"].eqNullSafe(df2["value"])).count()
1
>>> df2 = spark.createDataFrame([
... Row(id=1, value=float('NaN')),
... Row(id=2, value=42.0),
... Row(id=3, value=None)
... ])
>>> df2.select(
... df2['value'].eqNullSafe(None),
... df2['value'].eqNullSafe(float('NaN')),
... df2['value'].eqNullSafe(42.0)
... ).show()
+----------------+---------------+----------------+
|(value <=> NULL)|(value <=> NaN)|(value <=> 42.0)|
+----------------+---------------+----------------+
| false| true| false|
| false| false| true|
| true| false| false|
+----------------+---------------+----------------+
Notes
-----
Unlike Pandas, PySpark doesn't consider NaN values to be NULL. See the
`NaN Semantics <https://spark.apache.org/docs/latest/sql-ref-datatypes.html#nan-semantics>`_
for details.
| def _bin_op(
name: str,
doc: str = "binary operator",
) -> Callable[
["Column", Union["Column", "LiteralType", "DecimalLiteral", "DateTimeLiteral"]], "Column"
]:
"""Create a method for given binary operator"""
def _(
self: "Column",
other: Union["Column", "LiteralType", "DecimalLiteral", "DateTimeLiteral"],
) -> "Column":
jc = other._jc if isinstance(other, Column) else other
njc = getattr(self._jc, name)(jc)
return Column(njc)
_.__doc__ = doc
return _
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|
39,322 | pyspark.sql.column | getField |
An expression that gets a field by name in a :class:`StructType`.
.. versionadded:: 1.3.0
.. versionchanged:: 3.4.0
Supports Spark Connect.
Parameters
----------
name
a literal value, or a :class:`Column` expression.
The result will only be true at a location if the field matches in the Column.
.. deprecated:: 3.0.0
:class:`Column` as a parameter is deprecated.
Returns
-------
:class:`Column`
Column representing whether each element of Column got by name.
Examples
--------
>>> from pyspark.sql import Row
>>> df = spark.createDataFrame([Row(r=Row(a=1, b="b"))])
>>> df.select(df.r.getField("b")).show()
+---+
|r.b|
+---+
| b|
+---+
>>> df.select(df.r.a).show()
+---+
|r.a|
+---+
| 1|
+---+
| def getField(self, name: Any) -> "Column":
"""
An expression that gets a field by name in a :class:`StructType`.
.. versionadded:: 1.3.0
.. versionchanged:: 3.4.0
Supports Spark Connect.
Parameters
----------
name
a literal value, or a :class:`Column` expression.
The result will only be true at a location if the field matches in the Column.
.. deprecated:: 3.0.0
:class:`Column` as a parameter is deprecated.
Returns
-------
:class:`Column`
Column representing whether each element of Column got by name.
Examples
--------
>>> from pyspark.sql import Row
>>> df = spark.createDataFrame([Row(r=Row(a=1, b="b"))])
>>> df.select(df.r.getField("b")).show()
+---+
|r.b|
+---+
| b|
+---+
>>> df.select(df.r.a).show()
+---+
|r.a|
+---+
| 1|
+---+
"""
if isinstance(name, Column):
warnings.warn(
"A column as 'name' in getField is deprecated as of Spark 3.0, and will not "
"be supported in the future release. Use `column[name]` or `column.name` syntax "
"instead.",
FutureWarning,
)
return self[name]
| (self, name: Any) -> pyspark.sql.column.Column | [
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|
39,323 | pyspark.sql.column | getItem |
An expression that gets an item at position ``ordinal`` out of a list,
or gets an item by key out of a dict.
.. versionadded:: 1.3.0
.. versionchanged:: 3.4.0
Supports Spark Connect.
Parameters
----------
key
a literal value, or a :class:`Column` expression.
The result will only be true at a location if the item matches in the column.
.. deprecated:: 3.0.0
:class:`Column` as a parameter is deprecated.
Returns
-------
:class:`Column`
Column representing the item(s) got at position out of a list or by key out of a dict.
Examples
--------
>>> df = spark.createDataFrame([([1, 2], {"key": "value"})], ["l", "d"])
>>> df.select(df.l.getItem(0), df.d.getItem("key")).show()
+----+------+
|l[0]|d[key]|
+----+------+
| 1| value|
+----+------+
| def getItem(self, key: Any) -> "Column":
"""
An expression that gets an item at position ``ordinal`` out of a list,
or gets an item by key out of a dict.
.. versionadded:: 1.3.0
.. versionchanged:: 3.4.0
Supports Spark Connect.
Parameters
----------
key
a literal value, or a :class:`Column` expression.
The result will only be true at a location if the item matches in the column.
.. deprecated:: 3.0.0
:class:`Column` as a parameter is deprecated.
Returns
-------
:class:`Column`
Column representing the item(s) got at position out of a list or by key out of a dict.
Examples
--------
>>> df = spark.createDataFrame([([1, 2], {"key": "value"})], ["l", "d"])
>>> df.select(df.l.getItem(0), df.d.getItem("key")).show()
+----+------+
|l[0]|d[key]|
+----+------+
| 1| value|
+----+------+
"""
if isinstance(key, Column):
warnings.warn(
"A column as 'key' in getItem is deprecated as of Spark 3.0, and will not "
"be supported in the future release. Use `column[key]` or `column.key` syntax "
"instead.",
FutureWarning,
)
return self[key]
| (self, key: Any) -> pyspark.sql.column.Column | [
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|
39,324 | pyspark.sql.column | ilike |
SQL ILIKE expression (case insensitive LIKE). Returns a boolean :class:`Column`
based on a case insensitive match.
.. versionadded:: 3.3.0
.. versionchanged:: 3.4.0
Supports Spark Connect.
Parameters
----------
other : str
a SQL LIKE pattern
See Also
--------
pyspark.sql.Column.rlike
Returns
-------
:class:`Column`
Column of booleans showing whether each element
in the Column is matched by SQL LIKE pattern.
Examples
--------
>>> df = spark.createDataFrame(
... [(2, "Alice"), (5, "Bob")], ["age", "name"])
>>> df.filter(df.name.ilike('%Ice')).collect()
[Row(age=2, name='Alice')]
| def ilike(self: "Column", other: str) -> "Column":
"""
SQL ILIKE expression (case insensitive LIKE). Returns a boolean :class:`Column`
based on a case insensitive match.
.. versionadded:: 3.3.0
.. versionchanged:: 3.4.0
Supports Spark Connect.
Parameters
----------
other : str
a SQL LIKE pattern
See Also
--------
pyspark.sql.Column.rlike
Returns
-------
:class:`Column`
Column of booleans showing whether each element
in the Column is matched by SQL LIKE pattern.
Examples
--------
>>> df = spark.createDataFrame(
... [(2, "Alice"), (5, "Bob")], ["age", "name"])
>>> df.filter(df.name.ilike('%Ice')).collect()
[Row(age=2, name='Alice')]
"""
njc = getattr(self._jc, "ilike")(other)
return Column(njc)
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|
39,325 | pyspark.sql.column | _ |
True if the current expression is NOT null.
.. versionchanged:: 3.4.0
Supports Spark Connect.
Examples
--------
>>> from pyspark.sql import Row
>>> df = spark.createDataFrame([Row(name='Tom', height=80), Row(name='Alice', height=None)])
>>> df.filter(df.height.isNotNull()).collect()
[Row(name='Tom', height=80)]
| def _unary_op(
name: str,
doc: str = "unary operator",
) -> Callable[["Column"], "Column"]:
"""Create a method for given unary operator"""
def _(self: "Column") -> "Column":
jc = getattr(self._jc, name)()
return Column(jc)
_.__doc__ = doc
return _
| (self: pyspark.sql.column.Column) -> pyspark.sql.column.Column | [
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|
39,326 | pyspark.sql.column | _ |
True if the current expression is null.
.. versionchanged:: 3.4.0
Supports Spark Connect.
Examples
--------
>>> from pyspark.sql import Row
>>> df = spark.createDataFrame([Row(name='Tom', height=80), Row(name='Alice', height=None)])
>>> df.filter(df.height.isNull()).collect()
[Row(name='Alice', height=None)]
| def _unary_op(
name: str,
doc: str = "unary operator",
) -> Callable[["Column"], "Column"]:
"""Create a method for given unary operator"""
def _(self: "Column") -> "Column":
jc = getattr(self._jc, name)()
return Column(jc)
_.__doc__ = doc
return _
| (self: pyspark.sql.column.Column) -> pyspark.sql.column.Column | [
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|
39,327 | pyspark.sql.column | isin |
A boolean expression that is evaluated to true if the value of this
expression is contained by the evaluated values of the arguments.
.. versionadded:: 1.5.0
.. versionchanged:: 3.4.0
Supports Spark Connect.
Parameters
----------
cols
The result will only be true at a location if any value matches in the Column.
Returns
-------
:class:`Column`
Column of booleans showing whether each element in the Column is contained in cols.
Examples
--------
>>> df = spark.createDataFrame(
... [(2, "Alice"), (5, "Bob")], ["age", "name"])
>>> df[df.name.isin("Bob", "Mike")].collect()
[Row(age=5, name='Bob')]
>>> df[df.age.isin([1, 2, 3])].collect()
[Row(age=2, name='Alice')]
| def isin(self, *cols: Any) -> "Column":
"""
A boolean expression that is evaluated to true if the value of this
expression is contained by the evaluated values of the arguments.
.. versionadded:: 1.5.0
.. versionchanged:: 3.4.0
Supports Spark Connect.
Parameters
----------
cols
The result will only be true at a location if any value matches in the Column.
Returns
-------
:class:`Column`
Column of booleans showing whether each element in the Column is contained in cols.
Examples
--------
>>> df = spark.createDataFrame(
... [(2, "Alice"), (5, "Bob")], ["age", "name"])
>>> df[df.name.isin("Bob", "Mike")].collect()
[Row(age=5, name='Bob')]
>>> df[df.age.isin([1, 2, 3])].collect()
[Row(age=2, name='Alice')]
"""
if len(cols) == 1 and isinstance(cols[0], (list, set)):
cols = cast(Tuple, cols[0])
cols = cast(
Tuple,
[c._jc if isinstance(c, Column) else _create_column_from_literal(c) for c in cols],
)
sc = get_active_spark_context()
jc = getattr(self._jc, "isin")(_to_seq(sc, cols))
return Column(jc)
| (self, *cols: Any) -> pyspark.sql.column.Column | [
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|
39,328 | pyspark.sql.column | like |
SQL like expression. Returns a boolean :class:`Column` based on a SQL LIKE match.
.. versionchanged:: 3.4.0
Supports Spark Connect.
Parameters
----------
other : str
a SQL LIKE pattern
See Also
--------
pyspark.sql.Column.rlike
Returns
-------
:class:`Column`
Column of booleans showing whether each element
in the Column is matched by SQL LIKE pattern.
Examples
--------
>>> df = spark.createDataFrame(
... [(2, "Alice"), (5, "Bob")], ["age", "name"])
>>> df.filter(df.name.like('Al%')).collect()
[Row(age=2, name='Alice')]
| def like(self: "Column", other: str) -> "Column":
"""
SQL like expression. Returns a boolean :class:`Column` based on a SQL LIKE match.
.. versionchanged:: 3.4.0
Supports Spark Connect.
Parameters
----------
other : str
a SQL LIKE pattern
See Also
--------
pyspark.sql.Column.rlike
Returns
-------
:class:`Column`
Column of booleans showing whether each element
in the Column is matched by SQL LIKE pattern.
Examples
--------
>>> df = spark.createDataFrame(
... [(2, "Alice"), (5, "Bob")], ["age", "name"])
>>> df.filter(df.name.like('Al%')).collect()
[Row(age=2, name='Alice')]
"""
njc = getattr(self._jc, "like")(other)
return Column(njc)
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|
39,329 | pyspark.sql.column | alias | :func:`name` is an alias for :func:`alias`.
.. versionadded:: 2.0 | def alias(self, *alias: str, **kwargs: Any) -> "Column":
"""
Returns this column aliased with a new name or names (in the case of expressions that
return more than one column, such as explode).
.. versionadded:: 1.3.0
.. versionchanged:: 3.4.0
Supports Spark Connect.
Parameters
----------
alias : str
desired column names (collects all positional arguments passed)
Other Parameters
----------------
metadata: dict
a dict of information to be stored in ``metadata`` attribute of the
corresponding :class:`StructField <pyspark.sql.types.StructField>` (optional, keyword
only argument)
.. versionchanged:: 2.2.0
Added optional ``metadata`` argument.
Returns
-------
:class:`Column`
Column representing whether each element of Column is aliased with new name or names.
Examples
--------
>>> df = spark.createDataFrame(
... [(2, "Alice"), (5, "Bob")], ["age", "name"])
>>> df.select(df.age.alias("age2")).collect()
[Row(age2=2), Row(age2=5)]
>>> df.select(df.age.alias("age3", metadata={'max': 99})).schema['age3'].metadata['max']
99
"""
metadata = kwargs.pop("metadata", None)
assert not kwargs, "Unexpected kwargs where passed: %s" % kwargs
sc = get_active_spark_context()
if len(alias) == 1:
if metadata:
assert sc._jvm is not None
jmeta = sc._jvm.org.apache.spark.sql.types.Metadata.fromJson(json.dumps(metadata))
return Column(getattr(self._jc, "as")(alias[0], jmeta))
else:
return Column(getattr(self._jc, "as")(alias[0]))
else:
if metadata:
raise PySparkValueError(
error_class="ONLY_ALLOWED_FOR_SINGLE_COLUMN",
message_parameters={"arg_name": "metadata"},
)
return Column(getattr(self._jc, "as")(_to_seq(sc, list(alias))))
| (self, *alias, **kwargs) | [
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|
39,330 | pyspark.sql.column | otherwise |
Evaluates a list of conditions and returns one of multiple possible result expressions.
If :func:`Column.otherwise` is not invoked, None is returned for unmatched conditions.
.. versionadded:: 1.4.0
.. versionchanged:: 3.4.0
Supports Spark Connect.
Parameters
----------
value
a literal value, or a :class:`Column` expression.
Returns
-------
:class:`Column`
Column representing whether each element of Column is unmatched conditions.
Examples
--------
>>> from pyspark.sql import functions as sf
>>> df = spark.createDataFrame(
... [(2, "Alice"), (5, "Bob")], ["age", "name"])
>>> df.select(df.name, sf.when(df.age > 3, 1).otherwise(0)).show()
+-----+-------------------------------------+
| name|CASE WHEN (age > 3) THEN 1 ELSE 0 END|
+-----+-------------------------------------+
|Alice| 0|
| Bob| 1|
+-----+-------------------------------------+
See Also
--------
pyspark.sql.functions.when
| def otherwise(self, value: Any) -> "Column":
"""
Evaluates a list of conditions and returns one of multiple possible result expressions.
If :func:`Column.otherwise` is not invoked, None is returned for unmatched conditions.
.. versionadded:: 1.4.0
.. versionchanged:: 3.4.0
Supports Spark Connect.
Parameters
----------
value
a literal value, or a :class:`Column` expression.
Returns
-------
:class:`Column`
Column representing whether each element of Column is unmatched conditions.
Examples
--------
>>> from pyspark.sql import functions as sf
>>> df = spark.createDataFrame(
... [(2, "Alice"), (5, "Bob")], ["age", "name"])
>>> df.select(df.name, sf.when(df.age > 3, 1).otherwise(0)).show()
+-----+-------------------------------------+
| name|CASE WHEN (age > 3) THEN 1 ELSE 0 END|
+-----+-------------------------------------+
|Alice| 0|
| Bob| 1|
+-----+-------------------------------------+
See Also
--------
pyspark.sql.functions.when
"""
v = value._jc if isinstance(value, Column) else value
jc = self._jc.otherwise(v)
return Column(jc)
| (self, value: Any) -> pyspark.sql.column.Column | [
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|
39,331 | pyspark.sql.column | over |
Define a windowing column.
.. versionadded:: 1.4.0
.. versionchanged:: 3.4.0
Supports Spark Connect.
Parameters
----------
window : :class:`WindowSpec`
Returns
-------
:class:`Column`
Examples
--------
>>> from pyspark.sql import Window
>>> window = (
... Window.partitionBy("name")
... .orderBy("age")
... .rowsBetween(Window.unboundedPreceding, Window.currentRow)
... )
>>> from pyspark.sql.functions import rank, min, desc
>>> df = spark.createDataFrame(
... [(2, "Alice"), (5, "Bob")], ["age", "name"])
>>> df.withColumn(
... "rank", rank().over(window)
... ).withColumn(
... "min", min('age').over(window)
... ).sort(desc("age")).show()
+---+-----+----+---+
|age| name|rank|min|
+---+-----+----+---+
| 5| Bob| 1| 5|
| 2|Alice| 1| 2|
+---+-----+----+---+
| def over(self, window: "WindowSpec") -> "Column":
"""
Define a windowing column.
.. versionadded:: 1.4.0
.. versionchanged:: 3.4.0
Supports Spark Connect.
Parameters
----------
window : :class:`WindowSpec`
Returns
-------
:class:`Column`
Examples
--------
>>> from pyspark.sql import Window
>>> window = (
... Window.partitionBy("name")
... .orderBy("age")
... .rowsBetween(Window.unboundedPreceding, Window.currentRow)
... )
>>> from pyspark.sql.functions import rank, min, desc
>>> df = spark.createDataFrame(
... [(2, "Alice"), (5, "Bob")], ["age", "name"])
>>> df.withColumn(
... "rank", rank().over(window)
... ).withColumn(
... "min", min('age').over(window)
... ).sort(desc("age")).show()
+---+-----+----+---+
|age| name|rank|min|
+---+-----+----+---+
| 5| Bob| 1| 5|
| 2|Alice| 1| 2|
+---+-----+----+---+
"""
from pyspark.sql.window import WindowSpec
if not isinstance(window, WindowSpec):
raise PySparkTypeError(
error_class="NOT_WINDOWSPEC",
message_parameters={"arg_name": "window", "arg_type": type(window).__name__},
)
jc = self._jc.over(window._jspec)
return Column(jc)
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|
39,332 | pyspark.sql.column | rlike |
SQL RLIKE expression (LIKE with Regex). Returns a boolean :class:`Column` based on a regex
match.
.. versionchanged:: 3.4.0
Supports Spark Connect.
Parameters
----------
other : str
an extended regex expression
Returns
-------
:class:`Column`
Column of booleans showing whether each element
in the Column is matched by extended regex expression.
Examples
--------
>>> df = spark.createDataFrame(
... [(2, "Alice"), (5, "Bob")], ["age", "name"])
>>> df.filter(df.name.rlike('ice$')).collect()
[Row(age=2, name='Alice')]
| def rlike(self: "Column", other: str) -> "Column":
"""
SQL RLIKE expression (LIKE with Regex). Returns a boolean :class:`Column` based on a regex
match.
.. versionchanged:: 3.4.0
Supports Spark Connect.
Parameters
----------
other : str
an extended regex expression
Returns
-------
:class:`Column`
Column of booleans showing whether each element
in the Column is matched by extended regex expression.
Examples
--------
>>> df = spark.createDataFrame(
... [(2, "Alice"), (5, "Bob")], ["age", "name"])
>>> df.filter(df.name.rlike('ice$')).collect()
[Row(age=2, name='Alice')]
"""
njc = getattr(self._jc, "rlike")(other)
return Column(njc)
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]
|
39,333 | pyspark.sql.column | _ |
String starts with. Returns a boolean :class:`Column` based on a string match.
.. versionchanged:: 3.4.0
Supports Spark Connect.
Parameters
----------
other : :class:`Column` or str
string at start of line (do not use a regex `^`)
Examples
--------
>>> df = spark.createDataFrame(
... [(2, "Alice"), (5, "Bob")], ["age", "name"])
>>> df.filter(df.name.startswith('Al')).collect()
[Row(age=2, name='Alice')]
>>> df.filter(df.name.startswith('^Al')).collect()
[]
| def _bin_op(
name: str,
doc: str = "binary operator",
) -> Callable[
["Column", Union["Column", "LiteralType", "DecimalLiteral", "DateTimeLiteral"]], "Column"
]:
"""Create a method for given binary operator"""
def _(
self: "Column",
other: Union["Column", "LiteralType", "DecimalLiteral", "DateTimeLiteral"],
) -> "Column":
jc = other._jc if isinstance(other, Column) else other
njc = getattr(self._jc, name)(jc)
return Column(njc)
_.__doc__ = doc
return _
| (self: 'Column', other: Union[ForwardRef('Column'), ForwardRef('LiteralType'), ForwardRef('DecimalLiteral'), ForwardRef('DateTimeLiteral')]) -> 'Column' | [
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|
39,334 | pyspark.sql.column | substr |
Return a :class:`Column` which is a substring of the column.
.. versionadded:: 1.3.0
.. versionchanged:: 3.4.0
Supports Spark Connect.
Parameters
----------
startPos : :class:`Column` or int
start position
length : :class:`Column` or int
length of the substring
Returns
-------
:class:`Column`
Column representing whether each element of Column is substr of origin Column.
Examples
--------
>>> df = spark.createDataFrame(
... [(2, "Alice"), (5, "Bob")], ["age", "name"])
>>> df.select(df.name.substr(1, 3).alias("col")).collect()
[Row(col='Ali'), Row(col='Bob')]
| def substr(self, startPos: Union[int, "Column"], length: Union[int, "Column"]) -> "Column":
"""
Return a :class:`Column` which is a substring of the column.
.. versionadded:: 1.3.0
.. versionchanged:: 3.4.0
Supports Spark Connect.
Parameters
----------
startPos : :class:`Column` or int
start position
length : :class:`Column` or int
length of the substring
Returns
-------
:class:`Column`
Column representing whether each element of Column is substr of origin Column.
Examples
--------
>>> df = spark.createDataFrame(
... [(2, "Alice"), (5, "Bob")], ["age", "name"])
>>> df.select(df.name.substr(1, 3).alias("col")).collect()
[Row(col='Ali'), Row(col='Bob')]
"""
if type(startPos) != type(length):
raise PySparkTypeError(
error_class="NOT_SAME_TYPE",
message_parameters={
"arg_name1": "startPos",
"arg_name2": "length",
"arg_type1": type(startPos).__name__,
"arg_type2": type(length).__name__,
},
)
if isinstance(startPos, int):
jc = self._jc.substr(startPos, length)
elif isinstance(startPos, Column):
jc = self._jc.substr(startPos._jc, cast("Column", length)._jc)
else:
raise PySparkTypeError(
error_class="NOT_COLUMN_OR_INT",
message_parameters={"arg_name": "startPos", "arg_type": type(startPos).__name__},
)
return Column(jc)
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|
39,335 | sparkypandy._column | to_pandas | null | def to_pandas(self) -> pd.Series:
# noinspection PyTypeChecker
df: pd.DataFrame = self.df_sparky.select(self._name).toPandas()
return df[self._name]
| (self) -> pandas.core.series.Series | [
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|
39,336 | pyspark.sql.column | when |
Evaluates a list of conditions and returns one of multiple possible result expressions.
If :func:`Column.otherwise` is not invoked, None is returned for unmatched conditions.
.. versionadded:: 1.4.0
.. versionchanged:: 3.4.0
Supports Spark Connect.
Parameters
----------
condition : :class:`Column`
a boolean :class:`Column` expression.
value
a literal value, or a :class:`Column` expression.
Returns
-------
:class:`Column`
Column representing whether each element of Column is in conditions.
Examples
--------
>>> from pyspark.sql import functions as sf
>>> df = spark.createDataFrame(
... [(2, "Alice"), (5, "Bob")], ["age", "name"])
>>> df.select(df.name, sf.when(df.age > 4, 1).when(df.age < 3, -1).otherwise(0)).show()
+-----+------------------------------------------------------------+
| name|CASE WHEN (age > 4) THEN 1 WHEN (age < 3) THEN -1 ELSE 0 END|
+-----+------------------------------------------------------------+
|Alice| -1|
| Bob| 1|
+-----+------------------------------------------------------------+
See Also
--------
pyspark.sql.functions.when
| def when(self, condition: "Column", value: Any) -> "Column":
"""
Evaluates a list of conditions and returns one of multiple possible result expressions.
If :func:`Column.otherwise` is not invoked, None is returned for unmatched conditions.
.. versionadded:: 1.4.0
.. versionchanged:: 3.4.0
Supports Spark Connect.
Parameters
----------
condition : :class:`Column`
a boolean :class:`Column` expression.
value
a literal value, or a :class:`Column` expression.
Returns
-------
:class:`Column`
Column representing whether each element of Column is in conditions.
Examples
--------
>>> from pyspark.sql import functions as sf
>>> df = spark.createDataFrame(
... [(2, "Alice"), (5, "Bob")], ["age", "name"])
>>> df.select(df.name, sf.when(df.age > 4, 1).when(df.age < 3, -1).otherwise(0)).show()
+-----+------------------------------------------------------------+
| name|CASE WHEN (age > 4) THEN 1 WHEN (age < 3) THEN -1 ELSE 0 END|
+-----+------------------------------------------------------------+
|Alice| -1|
| Bob| 1|
+-----+------------------------------------------------------------+
See Also
--------
pyspark.sql.functions.when
"""
if not isinstance(condition, Column):
raise PySparkTypeError(
error_class="NOT_COLUMN",
message_parameters={"arg_name": "condition", "arg_type": type(condition).__name__},
)
v = value._jc if isinstance(value, Column) else value
jc = self._jc.when(condition._jc, v)
return Column(jc)
| (self, condition: pyspark.sql.column.Column, value: Any) -> pyspark.sql.column.Column | [
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|
39,337 | pyspark.sql.column | withField |
An expression that adds/replaces a field in :class:`StructType` by name.
.. versionadded:: 3.1.0
.. versionchanged:: 3.4.0
Supports Spark Connect.
Parameters
----------
fieldName : str
a literal value.
The result will only be true at a location if any field matches in the Column.
col : :class:`Column`
A :class:`Column` expression for the column with `fieldName`.
Returns
-------
:class:`Column`
Column representing whether each element of Column
which field was added/replaced by fieldName.
Examples
--------
>>> from pyspark.sql import Row
>>> from pyspark.sql.functions import lit
>>> df = spark.createDataFrame([Row(a=Row(b=1, c=2))])
>>> df.withColumn('a', df['a'].withField('b', lit(3))).select('a.b').show()
+---+
| b|
+---+
| 3|
+---+
>>> df.withColumn('a', df['a'].withField('d', lit(4))).select('a.d').show()
+---+
| d|
+---+
| 4|
+---+
| def withField(self, fieldName: str, col: "Column") -> "Column":
"""
An expression that adds/replaces a field in :class:`StructType` by name.
.. versionadded:: 3.1.0
.. versionchanged:: 3.4.0
Supports Spark Connect.
Parameters
----------
fieldName : str
a literal value.
The result will only be true at a location if any field matches in the Column.
col : :class:`Column`
A :class:`Column` expression for the column with `fieldName`.
Returns
-------
:class:`Column`
Column representing whether each element of Column
which field was added/replaced by fieldName.
Examples
--------
>>> from pyspark.sql import Row
>>> from pyspark.sql.functions import lit
>>> df = spark.createDataFrame([Row(a=Row(b=1, c=2))])
>>> df.withColumn('a', df['a'].withField('b', lit(3))).select('a.b').show()
+---+
| b|
+---+
| 3|
+---+
>>> df.withColumn('a', df['a'].withField('d', lit(4))).select('a.d').show()
+---+
| d|
+---+
| 4|
+---+
"""
if not isinstance(fieldName, str):
raise PySparkTypeError(
error_class="NOT_STR",
message_parameters={"arg_name": "fieldName", "arg_type": type(fieldName).__name__},
)
if not isinstance(col, Column):
raise PySparkTypeError(
error_class="NOT_COLUMN",
message_parameters={"arg_name": "col", "arg_type": type(col).__name__},
)
return Column(self._jc.withField(fieldName, col._jc))
| (self, fieldName: str, col: pyspark.sql.column.Column) -> pyspark.sql.column.Column | [
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|
39,338 | sparkypandy._dataframe | DataFramy | null | class DataFramy(DataFrame): # type: ignore
@classmethod
def from_spark(cls, df_spark: DataFrame) -> DataFramy:
# noinspection PyProtectedMember
return cls(jdf=df_spark._jdf, sql_ctx=df_spark.sql_ctx)
@classmethod
def from_pandas(cls, spark_session: SparkSession, df_pandas: pd.DataFrame) -> DataFramy:
df_spark = spark_session.createDataFrame(df_pandas)
return cls.from_spark(df_spark)
def to_pandas(self) -> pd.DataFrame:
"""PEP8-compliant alias to toPandas()"""
# noinspection PyTypeChecker
return super().toPandas()
def __getitem__(self, item: str) -> Columny:
if not isinstance(item, str):
raise TypeError(f"Expected a string key, not {item}")
col = super().__getitem__(item=item)
return Columny.from_spark(col=col, df_sparky=self)
| (jdf: py4j.java_gateway.JavaObject, sql_ctx: Union[ForwardRef('SQLContext'), ForwardRef('SparkSession')]) | [
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|
39,339 | pyspark.sql.dataframe | __dir__ |
Examples
--------
>>> from pyspark.sql.functions import lit
Create a dataframe with a column named 'id'.
>>> df = spark.range(3)
>>> [attr for attr in dir(df) if attr[0] == 'i'][:7] # Includes column id
['id', 'inputFiles', 'intersect', 'intersectAll', 'isEmpty', 'isLocal', 'isStreaming']
Add a column named 'i_like_pancakes'.
>>> df = df.withColumn('i_like_pancakes', lit(1))
>>> [attr for attr in dir(df) if attr[0] == 'i'][:7] # Includes columns i_like_pancakes, id
['i_like_pancakes', 'id', 'inputFiles', 'intersect', 'intersectAll', 'isEmpty', 'isLocal']
Try to add an existed column 'inputFiles'.
>>> df = df.withColumn('inputFiles', lit(2))
>>> [attr for attr in dir(df) if attr[0] == 'i'][:7] # Doesn't duplicate inputFiles
['i_like_pancakes', 'id', 'inputFiles', 'intersect', 'intersectAll', 'isEmpty', 'isLocal']
Try to add a column named 'id2'.
>>> df = df.withColumn('id2', lit(3))
>>> [attr for attr in dir(df) if attr[0] == 'i'][:7] # result includes id2 and sorted
['i_like_pancakes', 'id', 'id2', 'inputFiles', 'intersect', 'intersectAll', 'isEmpty']
Don't include columns that are not valid python identifiers.
>>> df = df.withColumn('1', lit(4))
>>> df = df.withColumn('name 1', lit(5))
>>> [attr for attr in dir(df) if attr[0] == 'i'][:7] # Doesn't include 1 or name 1
['i_like_pancakes', 'id', 'id2', 'inputFiles', 'intersect', 'intersectAll', 'isEmpty']
| def __dir__(self) -> List[str]:
"""
Examples
--------
>>> from pyspark.sql.functions import lit
Create a dataframe with a column named 'id'.
>>> df = spark.range(3)
>>> [attr for attr in dir(df) if attr[0] == 'i'][:7] # Includes column id
['id', 'inputFiles', 'intersect', 'intersectAll', 'isEmpty', 'isLocal', 'isStreaming']
Add a column named 'i_like_pancakes'.
>>> df = df.withColumn('i_like_pancakes', lit(1))
>>> [attr for attr in dir(df) if attr[0] == 'i'][:7] # Includes columns i_like_pancakes, id
['i_like_pancakes', 'id', 'inputFiles', 'intersect', 'intersectAll', 'isEmpty', 'isLocal']
Try to add an existed column 'inputFiles'.
>>> df = df.withColumn('inputFiles', lit(2))
>>> [attr for attr in dir(df) if attr[0] == 'i'][:7] # Doesn't duplicate inputFiles
['i_like_pancakes', 'id', 'inputFiles', 'intersect', 'intersectAll', 'isEmpty', 'isLocal']
Try to add a column named 'id2'.
>>> df = df.withColumn('id2', lit(3))
>>> [attr for attr in dir(df) if attr[0] == 'i'][:7] # result includes id2 and sorted
['i_like_pancakes', 'id', 'id2', 'inputFiles', 'intersect', 'intersectAll', 'isEmpty']
Don't include columns that are not valid python identifiers.
>>> df = df.withColumn('1', lit(4))
>>> df = df.withColumn('name 1', lit(5))
>>> [attr for attr in dir(df) if attr[0] == 'i'][:7] # Doesn't include 1 or name 1
['i_like_pancakes', 'id', 'id2', 'inputFiles', 'intersect', 'intersectAll', 'isEmpty']
"""
attrs = set(super().__dir__())
attrs.update(filter(lambda s: s.isidentifier(), self.columns))
return sorted(attrs)
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|
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