libraries

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#!/usr/bin/env python3
# Copyright (c) 2005-2010 ActiveState Software Inc.
# Copyright (c) 2013 Eddy Petrișor
# flake8: noqa
"""
This file is directly from
https://github.com/ActiveState/appdirs/blob/3fe6a83776843a46f20c2e5587afcffe05e03b39/appdirs.py
The license of https://github.com/ActiveState/appdirs copied below:
# This is the MIT license
Copyright (c) 2010 ActiveState Software Inc.
Permission is hereby granted, free of charge, to any person obtaining a
copy of this software and associated documentation files (the
"Software"), to deal in the Software without restriction, including
without limitation the rights to use, copy, modify, merge, publish,
distribute, sublicense, and/or sell copies of the Software, and to
permit persons to whom the Software is furnished to do so, subject to
the following conditions:
The above copyright notice and this permission notice shall be included
in all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS
OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.
IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY
CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,
TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE
SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
"""
"""Utilities for determining application-specific dirs.
See <https://github.com/ActiveState/appdirs> for details and usage.
"""
# Dev Notes:
# - MSDN on where to store app data files:
# http://support.microsoft.com/default.aspx?scid=kb;en-us;310294#XSLTH3194121123120121120120
# - Mac OS X: http://developer.apple.com/documentation/MacOSX/Conceptual/BPFileSystem/index.html
# - XDG spec for Un*x: https://standards.freedesktop.org/basedir-spec/basedir-spec-latest.html
__version__ = "1.4.4"
__version_info__ = tuple(int(segment) for segment in __version__.split("."))
import sys
import os
unicode = str
if sys.platform.startswith('java'):
import platform
os_name = platform.java_ver()[3][0]
if os_name.startswith('Windows'): # "Windows XP", "Windows 7", etc.
system = 'win32'
elif os_name.startswith('Mac'): # "Mac OS X", etc.
system = 'darwin'
else: # "Linux", "SunOS", "FreeBSD", etc.
# Setting this to "linux2" is not ideal, but only Windows or Mac
# are actually checked for and the rest of the module expects
# *sys.platform* style strings.
system = 'linux2'
else:
system = sys.platform
def user_cache_dir(appname=None, appauthor=None, version=None, opinion=True):
r"""Return full path to the user-specific cache dir for this application.
"appname" is the name of application.
If None, just the system directory is returned.
"appauthor" (only used on Windows) is the name of the
appauthor or distributing body for this application. Typically
it is the owning company name. This falls back to appname. You may
pass False to disable it.
"version" is an optional version path element to append to the
path. You might want to use this if you want multiple versions
of your app to be able to run independently. If used, this
would typically be "<major>.<minor>".
Only applied when appname is present.
"opinion" (boolean) can be False to disable the appending of
"Cache" to the base app data dir for Windows. See
discussion below.
Typical user cache directories are:
Mac OS X: ~/Library/Caches/<AppName>
Unix: ~/.cache/<AppName> (XDG default)
Win XP: C:\Documents and Settings\<username>\Local Settings\Application Data\<AppAuthor>\<AppName>\Cache
Vista: C:\Users\<username>\AppData\Local\<AppAuthor>\<AppName>\Cache
On Windows the only suggestion in the MSDN docs is that local settings go in
the `CSIDL_LOCAL_APPDATA` directory. This is identical to the non-roaming
app data dir (the default returned by `user_data_dir` above). Apps typically
put cache data somewhere *under* the given dir here. Some examples:
...\Mozilla\Firefox\Profiles\<ProfileName>\Cache
...\Acme\SuperApp\Cache\1.0
OPINION: This function appends "Cache" to the `CSIDL_LOCAL_APPDATA` value.
This can be disabled with the `opinion=False` option.
"""
if system == "win32":
if appauthor is None:
appauthor = appname
path = os.path.normpath(_get_win_folder("CSIDL_LOCAL_APPDATA"))
if appname:
if appauthor is not False:
path = os.path.join(path, appauthor, appname)
else:
path = os.path.join(path, appname)
if opinion:
path = os.path.join(path, "Cache")
elif system == 'darwin':
path = os.path.expanduser('~/Library/Caches')
if appname:
path = os.path.join(path, appname)
else:
path = os.getenv('XDG_CACHE_HOME', os.path.expanduser('~/.cache'))
if appname:
path = os.path.join(path, appname)
if appname and version:
path = os.path.join(path, version)
return path
#---- internal support stuff
def _get_win_folder_from_registry(csidl_name):
"""This is a fallback technique at best. I'm not sure if using the
registry for this guarantees us the correct answer for all CSIDL_*
names.
"""
import winreg as _winreg
shell_folder_name = {
"CSIDL_APPDATA": "AppData",
"CSIDL_COMMON_APPDATA": "Common AppData",
"CSIDL_LOCAL_APPDATA": "Local AppData",
}[csidl_name]
key = _winreg.OpenKey(
_winreg.HKEY_CURRENT_USER,
r"Software\Microsoft\Windows\CurrentVersion\Explorer\Shell Folders"
)
dir, type = _winreg.QueryValueEx(key, shell_folder_name)
return dir
def _get_win_folder_with_pywin32(csidl_name):
from win32com.shell import shellcon, shell
dir = shell.SHGetFolderPath(0, getattr(shellcon, csidl_name), 0, 0)
# Try to make this a unicode path because SHGetFolderPath does
# not return unicode strings when there is unicode data in the
# path.
try:
dir = unicode(dir)
# Downgrade to short path name if have highbit chars. See
# <http://bugs.activestate.com/show_bug.cgi?id=85099>.
has_high_char = False
for c in dir:
if ord(c) > 255:
has_high_char = True
break
if has_high_char:
try:
import win32api
dir = win32api.GetShortPathName(dir)
except ImportError:
pass
except UnicodeError:
pass
return dir
def _get_win_folder_with_ctypes(csidl_name):
import ctypes
csidl_const = {
"CSIDL_APPDATA": 26,
"CSIDL_COMMON_APPDATA": 35,
"CSIDL_LOCAL_APPDATA": 28,
}[csidl_name]
buf = ctypes.create_unicode_buffer(1024)
ctypes.windll.shell32.SHGetFolderPathW(None, csidl_const, None, 0, buf)
# Downgrade to short path name if have highbit chars. See
# <http://bugs.activestate.com/show_bug.cgi?id=85099>.
has_high_char = False
for c in buf:
if ord(c) > 255:
has_high_char = True
break
if has_high_char:
buf2 = ctypes.create_unicode_buffer(1024)
if ctypes.windll.kernel32.GetShortPathNameW(buf.value, buf2, 1024):
buf = buf2
return buf.value
def _get_win_folder_with_jna(csidl_name):
import array
from com.sun import jna
from com.sun.jna.platform import win32
buf_size = win32.WinDef.MAX_PATH * 2
buf = array.zeros('c', buf_size)
shell = win32.Shell32.INSTANCE
shell.SHGetFolderPath(None, getattr(win32.ShlObj, csidl_name), None, win32.ShlObj.SHGFP_TYPE_CURRENT, buf)
dir = jna.Native.toString(buf.tostring()).rstrip("\0")
# Downgrade to short path name if have highbit chars. See
# <http://bugs.activestate.com/show_bug.cgi?id=85099>.
has_high_char = False
for c in dir:
if ord(c) > 255:
has_high_char = True
break
if has_high_char:
buf = array.zeros('c', buf_size)
kernel = win32.Kernel32.INSTANCE
if kernel.GetShortPathName(dir, buf, buf_size):
dir = jna.Native.toString(buf.tostring()).rstrip("\0")
return dir
if system == "win32":
try:
import win32com.shell
_get_win_folder = _get_win_folder_with_pywin32
except ImportError:
try:
from ctypes import windll
_get_win_folder = _get_win_folder_with_ctypes
except ImportError:
try:
import com.sun.jna
_get_win_folder = _get_win_folder_with_jna
except ImportError:
_get_win_folder = _get_win_folder_from_registry

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"""Extract reference documentation from the NumPy source tree.
Copyright (C) 2008 Stefan van der Walt <stefan@mentat.za.net>, Pauli Virtanen <pav@iki.fi>
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are
met:
1. Redistributions of source code must retain the above copyright
notice, this list of conditions and the following disclaimer.
2. Redistributions in binary form must reproduce the above copyright
notice, this list of conditions and the following disclaimer in
the documentation and/or other materials provided with the
distribution.
THIS SOFTWARE IS PROVIDED BY THE AUTHOR ``AS IS'' AND ANY EXPRESS OR
IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
DISCLAIMED. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT,
INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION)
HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT,
STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING
IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
POSSIBILITY OF SUCH DAMAGE.
"""
import inspect
import textwrap
import re
import pydoc
from warnings import warn
from collections import namedtuple
from collections.abc import Callable, Mapping
import copy
import sys
def strip_blank_lines(l):
"Remove leading and trailing blank lines from a list of lines"
while l and not l[0].strip():
del l[0]
while l and not l[-1].strip():
del l[-1]
return l
class Reader:
"""A line-based string reader.
"""
def __init__(self, data):
"""
Parameters
----------
data : str
String with lines separated by '\n'.
"""
if isinstance(data, list):
self._str = data
else:
self._str = data.split('\n') # store string as list of lines
self.reset()
def __getitem__(self, n):
return self._str[n]
def reset(self):
self._l = 0 # current line nr
def read(self):
if not self.eof():
out = self[self._l]
self._l += 1
return out
else:
return ''
def seek_next_non_empty_line(self):
for l in self[self._l:]:
if l.strip():
break
else:
self._l += 1
def eof(self):
return self._l >= len(self._str)
def read_to_condition(self, condition_func):
start = self._l
for line in self[start:]:
if condition_func(line):
return self[start:self._l]
self._l += 1
if self.eof():
return self[start:self._l+1]
return []
def read_to_next_empty_line(self):
self.seek_next_non_empty_line()
def is_empty(line):
return not line.strip()
return self.read_to_condition(is_empty)
def read_to_next_unindented_line(self):
def is_unindented(line):
return (line.strip() and (len(line.lstrip()) == len(line)))
return self.read_to_condition(is_unindented)
def peek(self, n=0):
if self._l + n < len(self._str):
return self[self._l + n]
else:
return ''
def is_empty(self):
return not ''.join(self._str).strip()
class ParseError(Exception):
def __str__(self):
message = self.args[0]
if hasattr(self, 'docstring'):
message = f"{message} in {self.docstring!r}"
return message
Parameter = namedtuple('Parameter', ['name', 'type', 'desc'])
class NumpyDocString(Mapping):
"""Parses a numpydoc string to an abstract representation
Instances define a mapping from section title to structured data.
"""
sections = {
'Signature': '',
'Summary': [''],
'Extended Summary': [],
'Parameters': [],
'Returns': [],
'Yields': [],
'Receives': [],
'Raises': [],
'Warns': [],
'Other Parameters': [],
'Attributes': [],
'Methods': [],
'See Also': [],
'Notes': [],
'Warnings': [],
'References': '',
'Examples': '',
'index': {}
}
def __init__(self, docstring, config={}):
orig_docstring = docstring
docstring = textwrap.dedent(docstring).split('\n')
self._doc = Reader(docstring)
self._parsed_data = copy.deepcopy(self.sections)
try:
self._parse()
except ParseError as e:
e.docstring = orig_docstring
raise
def __getitem__(self, key):
return self._parsed_data[key]
def __setitem__(self, key, val):
if key not in self._parsed_data:
self._error_location(f"Unknown section {key}", error=False)
else:
self._parsed_data[key] = val
def __iter__(self):
return iter(self._parsed_data)
def __len__(self):
return len(self._parsed_data)
def _is_at_section(self):
self._doc.seek_next_non_empty_line()
if self._doc.eof():
return False
l1 = self._doc.peek().strip() # e.g. Parameters
if l1.startswith('.. index::'):
return True
l2 = self._doc.peek(1).strip() # ---------- or ==========
return l2.startswith('-'*len(l1)) or l2.startswith('='*len(l1))
def _strip(self, doc):
i = 0
j = 0
for i, line in enumerate(doc):
if line.strip():
break
for j, line in enumerate(doc[::-1]):
if line.strip():
break
return doc[i:len(doc)-j]
def _read_to_next_section(self):
section = self._doc.read_to_next_empty_line()
while not self._is_at_section() and not self._doc.eof():
if not self._doc.peek(-1).strip(): # previous line was empty
section += ['']
section += self._doc.read_to_next_empty_line()
return section
def _read_sections(self):
while not self._doc.eof():
data = self._read_to_next_section()
name = data[0].strip()
if name.startswith('..'): # index section
yield name, data[1:]
elif len(data) < 2:
yield StopIteration
else:
yield name, self._strip(data[2:])
def _parse_param_list(self, content, single_element_is_type=False):
r = Reader(content)
params = []
while not r.eof():
header = r.read().strip()
if ' : ' in header:
arg_name, arg_type = header.split(' : ')[:2]
else:
if single_element_is_type:
arg_name, arg_type = '', header
else:
arg_name, arg_type = header, ''
desc = r.read_to_next_unindented_line()
desc = dedent_lines(desc)
desc = strip_blank_lines(desc)
params.append(Parameter(arg_name, arg_type, desc))
return params
# See also supports the following formats.
#
# <FUNCNAME>
# <FUNCNAME> SPACE* COLON SPACE+ <DESC> SPACE*
# <FUNCNAME> ( COMMA SPACE+ <FUNCNAME>)+ (COMMA | PERIOD)? SPACE*
# <FUNCNAME> ( COMMA SPACE+ <FUNCNAME>)* SPACE* COLON SPACE+ <DESC> SPACE*
# <FUNCNAME> is one of
# <PLAIN_FUNCNAME>
# COLON <ROLE> COLON BACKTICK <PLAIN_FUNCNAME> BACKTICK
# where
# <PLAIN_FUNCNAME> is a legal function name, and
# <ROLE> is any nonempty sequence of word characters.
# Examples: func_f1 :meth:`func_h1` :obj:`~baz.obj_r` :class:`class_j`
# <DESC> is a string describing the function.
_role = r":(?P<role>\w+):"
_funcbacktick = r"`(?P<name>(?:~\w+\.)?[a-zA-Z0-9_\.-]+)`"
_funcplain = r"(?P<name2>[a-zA-Z0-9_\.-]+)"
_funcname = r"(" + _role + _funcbacktick + r"|" + _funcplain + r")"
_funcnamenext = _funcname.replace('role', 'rolenext')
_funcnamenext = _funcnamenext.replace('name', 'namenext')
_description = r"(?P<description>\s*:(\s+(?P<desc>\S+.*))?)?\s*$"
_func_rgx = re.compile(r"^\s*" + _funcname + r"\s*")
_line_rgx = re.compile(
r"^\s*" +
r"(?P<allfuncs>" + # group for all function names
_funcname +
r"(?P<morefuncs>([,]\s+" + _funcnamenext + r")*)" +
r")" + # end of "allfuncs"
r"(?P<trailing>[,\.])?" + # Some function lists have a trailing comma (or period) '\s*'
_description)
# Empty <DESC> elements are replaced with '..'
empty_description = '..'
def _parse_see_also(self, content):
"""
func_name : Descriptive text
continued text
another_func_name : Descriptive text
func_name1, func_name2, :meth:`func_name`, func_name3
"""
items = []
def parse_item_name(text):
"""Match ':role:`name`' or 'name'."""
m = self._func_rgx.match(text)
if not m:
raise ParseError(f"{text} is not a item name")
role = m.group('role')
name = m.group('name') if role else m.group('name2')
return name, role, m.end()
rest = []
for line in content:
if not line.strip():
continue
line_match = self._line_rgx.match(line)
description = None
if line_match:
description = line_match.group('desc')
if line_match.group('trailing') and description:
self._error_location(
'Unexpected comma or period after function list at index %d of '
'line "%s"' % (line_match.end('trailing'), line),
error=False)
if not description and line.startswith(' '):
rest.append(line.strip())
elif line_match:
funcs = []
text = line_match.group('allfuncs')
while True:
if not text.strip():
break
name, role, match_end = parse_item_name(text)
funcs.append((name, role))
text = text[match_end:].strip()
if text and text[0] == ',':
text = text[1:].strip()
rest = list(filter(None, [description]))
items.append((funcs, rest))
else:
raise ParseError(f"{line} is not a item name")
return items
def _parse_index(self, section, content):
"""
.. index: default
:refguide: something, else, and more
"""
def strip_each_in(lst):
return [s.strip() for s in lst]
out = {}
section = section.split('::')
if len(section) > 1:
out['default'] = strip_each_in(section[1].split(','))[0]
for line in content:
line = line.split(':')
if len(line) > 2:
out[line[1]] = strip_each_in(line[2].split(','))
return out
def _parse_summary(self):
"""Grab signature (if given) and summary"""
if self._is_at_section():
return
# If several signatures present, take the last one
while True:
summary = self._doc.read_to_next_empty_line()
summary_str = " ".join([s.strip() for s in summary]).strip()
compiled = re.compile(r'^([\w., ]+=)?\s*[\w\.]+\(.*\)$')
if compiled.match(summary_str):
self['Signature'] = summary_str
if not self._is_at_section():
continue
break
if summary is not None:
self['Summary'] = summary
if not self._is_at_section():
self['Extended Summary'] = self._read_to_next_section()
def _parse(self):
self._doc.reset()
self._parse_summary()
sections = list(self._read_sections())
section_names = {section for section, content in sections}
has_returns = 'Returns' in section_names
has_yields = 'Yields' in section_names
# We could do more tests, but we are not. Arbitrarily.
if has_returns and has_yields:
msg = 'Docstring contains both a Returns and Yields section.'
raise ValueError(msg)
if not has_yields and 'Receives' in section_names:
msg = 'Docstring contains a Receives section but not Yields.'
raise ValueError(msg)
for (section, content) in sections:
if not section.startswith('..'):
section = (s.capitalize() for s in section.split(' '))
section = ' '.join(section)
if self.get(section):
self._error_location(f"The section {section} appears twice")
if section in ('Parameters', 'Other Parameters', 'Attributes',
'Methods'):
self[section] = self._parse_param_list(content)
elif section in ('Returns', 'Yields', 'Raises', 'Warns', 'Receives'):
self[section] = self._parse_param_list(
content, single_element_is_type=True)
elif section.startswith('.. index::'):
self['index'] = self._parse_index(section, content)
elif section == 'See Also':
self['See Also'] = self._parse_see_also(content)
else:
self[section] = content
def _error_location(self, msg, error=True):
if hasattr(self, '_obj'):
# we know where the docs came from:
try:
filename = inspect.getsourcefile(self._obj)
except TypeError:
filename = None
msg = msg + f" in the docstring of {self._obj} in {filename}."
if error:
raise ValueError(msg)
else:
warn(msg)
# string conversion routines
def _str_header(self, name, symbol='-'):
return [name, len(name)*symbol]
def _str_indent(self, doc, indent=4):
out = []
for line in doc:
out += [' '*indent + line]
return out
def _str_signature(self):
if self['Signature']:
return [self['Signature'].replace('*', r'\*')] + ['']
else:
return ['']
def _str_summary(self):
if self['Summary']:
return self['Summary'] + ['']
else:
return []
def _str_extended_summary(self):
if self['Extended Summary']:
return self['Extended Summary'] + ['']
else:
return []
def _str_param_list(self, name):
out = []
if self[name]:
out += self._str_header(name)
for param in self[name]:
parts = []
if param.name:
parts.append(param.name)
if param.type:
parts.append(param.type)
out += [' : '.join(parts)]
if param.desc and ''.join(param.desc).strip():
out += self._str_indent(param.desc)
out += ['']
return out
def _str_section(self, name):
out = []
if self[name]:
out += self._str_header(name)
out += self[name]
out += ['']
return out
def _str_see_also(self, func_role):
if not self['See Also']:
return []
out = []
out += self._str_header("See Also")
out += ['']
last_had_desc = True
for funcs, desc in self['See Also']:
assert isinstance(funcs, list)
links = []
for func, role in funcs:
if role:
link = f':{role}:`{func}`'
elif func_role:
link = f':{func_role}:`{func}`'
else:
link = f"`{func}`_"
links.append(link)
link = ', '.join(links)
out += [link]
if desc:
out += self._str_indent([' '.join(desc)])
last_had_desc = True
else:
last_had_desc = False
out += self._str_indent([self.empty_description])
if last_had_desc:
out += ['']
out += ['']
return out
def _str_index(self):
idx = self['index']
out = []
output_index = False
default_index = idx.get('default', '')
if default_index:
output_index = True
out += [f'.. index:: {default_index}']
for section, references in idx.items():
if section == 'default':
continue
output_index = True
out += [f" :{section}: {', '.join(references)}"]
if output_index:
return out
else:
return ''
def __str__(self, func_role=''):
out = []
out += self._str_signature()
out += self._str_summary()
out += self._str_extended_summary()
for param_list in ('Parameters', 'Returns', 'Yields', 'Receives',
'Other Parameters', 'Raises', 'Warns'):
out += self._str_param_list(param_list)
out += self._str_section('Warnings')
out += self._str_see_also(func_role)
for s in ('Notes', 'References', 'Examples'):
out += self._str_section(s)
for param_list in ('Attributes', 'Methods'):
out += self._str_param_list(param_list)
out += self._str_index()
return '\n'.join(out)
def indent(str, indent=4):
indent_str = ' '*indent
if str is None:
return indent_str
lines = str.split('\n')
return '\n'.join(indent_str + l for l in lines)
def dedent_lines(lines):
"""Deindent a list of lines maximally"""
return textwrap.dedent("\n".join(lines)).split("\n")
def header(text, style='-'):
return text + '\n' + style*len(text) + '\n'
class FunctionDoc(NumpyDocString):
def __init__(self, func, role='func', doc=None, config={}):
self._f = func
self._role = role # e.g. "func" or "meth"
if doc is None:
if func is None:
raise ValueError("No function or docstring given")
doc = inspect.getdoc(func) or ''
NumpyDocString.__init__(self, doc, config)
if not self['Signature'] and func is not None:
func, func_name = self.get_func()
try:
try:
signature = str(inspect.signature(func))
except (AttributeError, ValueError):
# try to read signature, backward compat for older Python
if sys.version_info[0] >= 3:
argspec = inspect.getfullargspec(func)
else:
argspec = inspect.getargspec(func)
signature = inspect.formatargspec(*argspec)
signature = f'{func_name}{signature}'
except TypeError:
signature = f'{func_name}()'
self['Signature'] = signature
def get_func(self):
func_name = getattr(self._f, '__name__', self.__class__.__name__)
if inspect.isclass(self._f):
func = getattr(self._f, '__call__', self._f.__init__)
else:
func = self._f
return func, func_name
def __str__(self):
out = ''
func, func_name = self.get_func()
roles = {'func': 'function',
'meth': 'method'}
if self._role:
if self._role not in roles:
print(f"Warning: invalid role {self._role}")
out += f".. {roles.get(self._role, '')}:: {func_name}\n \n\n"
out += super().__str__(func_role=self._role)
return out
class ClassDoc(NumpyDocString):
extra_public_methods = ['__call__']
def __init__(self, cls, doc=None, modulename='', func_doc=FunctionDoc,
config={}):
if not inspect.isclass(cls) and cls is not None:
raise ValueError(f"Expected a class or None, but got {cls!r}")
self._cls = cls
if 'sphinx' in sys.modules:
from sphinx.ext.autodoc import ALL
else:
ALL = object()
self.show_inherited_members = config.get(
'show_inherited_class_members', True)
if modulename and not modulename.endswith('.'):
modulename += '.'
self._mod = modulename
if doc is None:
if cls is None:
raise ValueError("No class or documentation string given")
doc = pydoc.getdoc(cls)
NumpyDocString.__init__(self, doc)
_members = config.get('members', [])
if _members is ALL:
_members = None
_exclude = config.get('exclude-members', [])
if config.get('show_class_members', True) and _exclude is not ALL:
def splitlines_x(s):
if not s:
return []
else:
return s.splitlines()
for field, items in [('Methods', self.methods),
('Attributes', self.properties)]:
if not self[field]:
doc_list = []
for name in sorted(items):
if (name in _exclude or
(_members and name not in _members)):
continue
try:
doc_item = pydoc.getdoc(getattr(self._cls, name))
doc_list.append(
Parameter(name, '', splitlines_x(doc_item)))
except AttributeError:
pass # method doesn't exist
self[field] = doc_list
@property
def methods(self):
if self._cls is None:
return []
return [name for name, func in inspect.getmembers(self._cls)
if ((not name.startswith('_')
or name in self.extra_public_methods)
and isinstance(func, Callable)
and self._is_show_member(name))]
@property
def properties(self):
if self._cls is None:
return []
return [name for name, func in inspect.getmembers(self._cls)
if (not name.startswith('_') and
(func is None or isinstance(func, property) or
inspect.isdatadescriptor(func))
and self._is_show_member(name))]
def _is_show_member(self, name):
if self.show_inherited_members:
return True # show all class members
if name not in self._cls.__dict__:
return False # class member is inherited, we do not show it
return True

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@@ -0,0 +1,313 @@
import operator
import math
__version__ = "2.1.0"
m = [
[3.2406, -1.5372, -0.4986],
[-0.9689, 1.8758, 0.0415],
[0.0557, -0.2040, 1.0570]
]
m_inv = [
[0.4124, 0.3576, 0.1805],
[0.2126, 0.7152, 0.0722],
[0.0193, 0.1192, 0.9505]
]
# Hard-coded D65 illuminant
refX = 0.95047
refY = 1.00000
refZ = 1.08883
refU = 0.19784
refV = 0.46834
lab_e = 0.008856
lab_k = 903.3
# Public API
def husl_to_rgb(h, s, l):
return lch_to_rgb(*husl_to_lch([h, s, l]))
def husl_to_hex(h, s, l):
return rgb_to_hex(husl_to_rgb(h, s, l))
def rgb_to_husl(r, g, b):
return lch_to_husl(rgb_to_lch(r, g, b))
def hex_to_husl(hex):
return rgb_to_husl(*hex_to_rgb(hex))
def huslp_to_rgb(h, s, l):
return lch_to_rgb(*huslp_to_lch([h, s, l]))
def huslp_to_hex(h, s, l):
return rgb_to_hex(huslp_to_rgb(h, s, l))
def rgb_to_huslp(r, g, b):
return lch_to_huslp(rgb_to_lch(r, g, b))
def hex_to_huslp(hex):
return rgb_to_huslp(*hex_to_rgb(hex))
def lch_to_rgb(l, c, h):
return xyz_to_rgb(luv_to_xyz(lch_to_luv([l, c, h])))
def rgb_to_lch(r, g, b):
return luv_to_lch(xyz_to_luv(rgb_to_xyz([r, g, b])))
def max_chroma(L, H):
hrad = math.radians(H)
sinH = (math.sin(hrad))
cosH = (math.cos(hrad))
sub1 = (math.pow(L + 16, 3.0) / 1560896.0)
sub2 = sub1 if sub1 > 0.008856 else (L / 903.3)
result = float("inf")
for row in m:
m1 = row[0]
m2 = row[1]
m3 = row[2]
top = ((0.99915 * m1 + 1.05122 * m2 + 1.14460 * m3) * sub2)
rbottom = (0.86330 * m3 - 0.17266 * m2)
lbottom = (0.12949 * m3 - 0.38848 * m1)
bottom = (rbottom * sinH + lbottom * cosH) * sub2
for t in (0.0, 1.0):
C = (L * (top - 1.05122 * t) / (bottom + 0.17266 * sinH * t))
if C > 0.0 and C < result:
result = C
return result
def _hrad_extremum(L):
lhs = (math.pow(L, 3.0) + 48.0 * math.pow(L, 2.0) + 768.0 * L + 4096.0) / 1560896.0
rhs = 1107.0 / 125000.0
sub = lhs if lhs > rhs else 10.0 * L / 9033.0
chroma = float("inf")
result = None
for row in m:
for limit in (0.0, 1.0):
[m1, m2, m3] = row
top = -3015466475.0 * m3 * sub + 603093295.0 * m2 * sub - 603093295.0 * limit
bottom = 1356959916.0 * m1 * sub - 452319972.0 * m3 * sub
hrad = math.atan2(top, bottom)
# This is a math hack to deal with tan quadrants, I'm too lazy to figure
# out how to do this properly
if limit == 0.0:
hrad += math.pi
test = max_chroma(L, math.degrees(hrad))
if test < chroma:
chroma = test
result = hrad
return result
def max_chroma_pastel(L):
H = math.degrees(_hrad_extremum(L))
return max_chroma(L, H)
def dot_product(a, b):
return sum(map(operator.mul, a, b))
def f(t):
if t > lab_e:
return (math.pow(t, 1.0 / 3.0))
else:
return (7.787 * t + 16.0 / 116.0)
def f_inv(t):
if math.pow(t, 3.0) > lab_e:
return (math.pow(t, 3.0))
else:
return (116.0 * t - 16.0) / lab_k
def from_linear(c):
if c <= 0.0031308:
return 12.92 * c
else:
return (1.055 * math.pow(c, 1.0 / 2.4) - 0.055)
def to_linear(c):
a = 0.055
if c > 0.04045:
return (math.pow((c + a) / (1.0 + a), 2.4))
else:
return (c / 12.92)
def rgb_prepare(triple):
ret = []
for ch in triple:
ch = round(ch, 3)
if ch < -0.0001 or ch > 1.0001:
raise Exception(f"Illegal RGB value {ch:f}")
if ch < 0:
ch = 0
if ch > 1:
ch = 1
# Fix for Python 3 which by default rounds 4.5 down to 4.0
# instead of Python 2 which is rounded to 5.0 which caused
# a couple off by one errors in the tests. Tests now all pass
# in Python 2 and Python 3
ret.append(int(round(ch * 255 + 0.001, 0)))
return ret
def hex_to_rgb(hex):
if hex.startswith('#'):
hex = hex[1:]
r = int(hex[0:2], 16) / 255.0
g = int(hex[2:4], 16) / 255.0
b = int(hex[4:6], 16) / 255.0
return [r, g, b]
def rgb_to_hex(triple):
[r, g, b] = triple
return '#%02x%02x%02x' % tuple(rgb_prepare([r, g, b]))
def xyz_to_rgb(triple):
xyz = map(lambda row: dot_product(row, triple), m)
return list(map(from_linear, xyz))
def rgb_to_xyz(triple):
rgbl = list(map(to_linear, triple))
return list(map(lambda row: dot_product(row, rgbl), m_inv))
def xyz_to_luv(triple):
X, Y, Z = triple
if X == Y == Z == 0.0:
return [0.0, 0.0, 0.0]
varU = (4.0 * X) / (X + (15.0 * Y) + (3.0 * Z))
varV = (9.0 * Y) / (X + (15.0 * Y) + (3.0 * Z))
L = 116.0 * f(Y / refY) - 16.0
# Black will create a divide-by-zero error
if L == 0.0:
return [0.0, 0.0, 0.0]
U = 13.0 * L * (varU - refU)
V = 13.0 * L * (varV - refV)
return [L, U, V]
def luv_to_xyz(triple):
L, U, V = triple
if L == 0:
return [0.0, 0.0, 0.0]
varY = f_inv((L + 16.0) / 116.0)
varU = U / (13.0 * L) + refU
varV = V / (13.0 * L) + refV
Y = varY * refY
X = 0.0 - (9.0 * Y * varU) / ((varU - 4.0) * varV - varU * varV)
Z = (9.0 * Y - (15.0 * varV * Y) - (varV * X)) / (3.0 * varV)
return [X, Y, Z]
def luv_to_lch(triple):
L, U, V = triple
C = (math.pow(math.pow(U, 2) + math.pow(V, 2), (1.0 / 2.0)))
hrad = (math.atan2(V, U))
H = math.degrees(hrad)
if H < 0.0:
H = 360.0 + H
return [L, C, H]
def lch_to_luv(triple):
L, C, H = triple
Hrad = math.radians(H)
U = (math.cos(Hrad) * C)
V = (math.sin(Hrad) * C)
return [L, U, V]
def husl_to_lch(triple):
H, S, L = triple
if L > 99.9999999:
return [100, 0.0, H]
if L < 0.00000001:
return [0.0, 0.0, H]
mx = max_chroma(L, H)
C = mx / 100.0 * S
return [L, C, H]
def lch_to_husl(triple):
L, C, H = triple
if L > 99.9999999:
return [H, 0.0, 100.0]
if L < 0.00000001:
return [H, 0.0, 0.0]
mx = max_chroma(L, H)
S = C / mx * 100.0
return [H, S, L]
def huslp_to_lch(triple):
H, S, L = triple
if L > 99.9999999:
return [100, 0.0, H]
if L < 0.00000001:
return [0.0, 0.0, H]
mx = max_chroma_pastel(L)
C = mx / 100.0 * S
return [L, C, H]
def lch_to_huslp(triple):
L, C, H = triple
if L > 99.9999999:
return [H, 0.0, 100.0]
if L < 0.00000001:
return [H, 0.0, 0.0]
mx = max_chroma_pastel(L)
S = C / mx * 100.0
return [H, S, L]

View File

@@ -0,0 +1,380 @@
"""
This module was copied from the scipy project.
In the process of copying, some methods were removed because they depended on
other parts of scipy (especially on compiled components), allowing seaborn to
have a simple and pure Python implementation. These include:
- integrate_gaussian
- integrate_box
- integrate_box_1d
- integrate_kde
- logpdf
- resample
Additionally, the numpy.linalg module was substituted for scipy.linalg,
and the examples section (with doctests) was removed from the docstring
The original scipy license is copied below:
Copyright (c) 2001-2002 Enthought, Inc. 2003-2019, SciPy Developers.
All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions
are met:
1. Redistributions of source code must retain the above copyright
notice, this list of conditions and the following disclaimer.
2. Redistributions in binary form must reproduce the above
copyright notice, this list of conditions and the following
disclaimer in the documentation and/or other materials provided
with the distribution.
3. Neither the name of the copyright holder nor the names of its
contributors may be used to endorse or promote products derived
from this software without specific prior written permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
"AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
"""
# -------------------------------------------------------------------------------
#
# Define classes for (uni/multi)-variate kernel density estimation.
#
# Currently, only Gaussian kernels are implemented.
#
# Written by: Robert Kern
#
# Date: 2004-08-09
#
# Modified: 2005-02-10 by Robert Kern.
# Contributed to SciPy
# 2005-10-07 by Robert Kern.
# Some fixes to match the new scipy_core
#
# Copyright 2004-2005 by Enthought, Inc.
#
# -------------------------------------------------------------------------------
import numpy as np
from numpy import (asarray, atleast_2d, reshape, zeros, newaxis, dot, exp, pi,
sqrt, power, atleast_1d, sum, ones, cov)
from numpy import linalg
__all__ = ['gaussian_kde']
class gaussian_kde:
"""Representation of a kernel-density estimate using Gaussian kernels.
Kernel density estimation is a way to estimate the probability density
function (PDF) of a random variable in a non-parametric way.
`gaussian_kde` works for both uni-variate and multi-variate data. It
includes automatic bandwidth determination. The estimation works best for
a unimodal distribution; bimodal or multi-modal distributions tend to be
oversmoothed.
Parameters
----------
dataset : array_like
Datapoints to estimate from. In case of univariate data this is a 1-D
array, otherwise a 2-D array with shape (# of dims, # of data).
bw_method : str, scalar or callable, optional
The method used to calculate the estimator bandwidth. This can be
'scott', 'silverman', a scalar constant or a callable. If a scalar,
this will be used directly as `kde.factor`. If a callable, it should
take a `gaussian_kde` instance as only parameter and return a scalar.
If None (default), 'scott' is used. See Notes for more details.
weights : array_like, optional
weights of datapoints. This must be the same shape as dataset.
If None (default), the samples are assumed to be equally weighted
Attributes
----------
dataset : ndarray
The dataset with which `gaussian_kde` was initialized.
d : int
Number of dimensions.
n : int
Number of datapoints.
neff : int
Effective number of datapoints.
.. versionadded:: 1.2.0
factor : float
The bandwidth factor, obtained from `kde.covariance_factor`, with which
the covariance matrix is multiplied.
covariance : ndarray
The covariance matrix of `dataset`, scaled by the calculated bandwidth
(`kde.factor`).
inv_cov : ndarray
The inverse of `covariance`.
Methods
-------
evaluate
__call__
integrate_gaussian
integrate_box_1d
integrate_box
integrate_kde
pdf
logpdf
resample
set_bandwidth
covariance_factor
Notes
-----
Bandwidth selection strongly influences the estimate obtained from the KDE
(much more so than the actual shape of the kernel). Bandwidth selection
can be done by a "rule of thumb", by cross-validation, by "plug-in
methods" or by other means; see [3]_, [4]_ for reviews. `gaussian_kde`
uses a rule of thumb, the default is Scott's Rule.
Scott's Rule [1]_, implemented as `scotts_factor`, is::
n**(-1./(d+4)),
with ``n`` the number of data points and ``d`` the number of dimensions.
In the case of unequally weighted points, `scotts_factor` becomes::
neff**(-1./(d+4)),
with ``neff`` the effective number of datapoints.
Silverman's Rule [2]_, implemented as `silverman_factor`, is::
(n * (d + 2) / 4.)**(-1. / (d + 4)).
or in the case of unequally weighted points::
(neff * (d + 2) / 4.)**(-1. / (d + 4)).
Good general descriptions of kernel density estimation can be found in [1]_
and [2]_, the mathematics for this multi-dimensional implementation can be
found in [1]_.
With a set of weighted samples, the effective number of datapoints ``neff``
is defined by::
neff = sum(weights)^2 / sum(weights^2)
as detailed in [5]_.
References
----------
.. [1] D.W. Scott, "Multivariate Density Estimation: Theory, Practice, and
Visualization", John Wiley & Sons, New York, Chicester, 1992.
.. [2] B.W. Silverman, "Density Estimation for Statistics and Data
Analysis", Vol. 26, Monographs on Statistics and Applied Probability,
Chapman and Hall, London, 1986.
.. [3] B.A. Turlach, "Bandwidth Selection in Kernel Density Estimation: A
Review", CORE and Institut de Statistique, Vol. 19, pp. 1-33, 1993.
.. [4] D.M. Bashtannyk and R.J. Hyndman, "Bandwidth selection for kernel
conditional density estimation", Computational Statistics & Data
Analysis, Vol. 36, pp. 279-298, 2001.
.. [5] Gray P. G., 1969, Journal of the Royal Statistical Society.
Series A (General), 132, 272
"""
def __init__(self, dataset, bw_method=None, weights=None):
self.dataset = atleast_2d(asarray(dataset))
if not self.dataset.size > 1:
raise ValueError("`dataset` input should have multiple elements.")
self.d, self.n = self.dataset.shape
if weights is not None:
self._weights = atleast_1d(weights).astype(float)
self._weights /= sum(self._weights)
if self.weights.ndim != 1:
raise ValueError("`weights` input should be one-dimensional.")
if len(self._weights) != self.n:
raise ValueError("`weights` input should be of length n")
self._neff = 1/sum(self._weights**2)
self.set_bandwidth(bw_method=bw_method)
def evaluate(self, points):
"""Evaluate the estimated pdf on a set of points.
Parameters
----------
points : (# of dimensions, # of points)-array
Alternatively, a (# of dimensions,) vector can be passed in and
treated as a single point.
Returns
-------
values : (# of points,)-array
The values at each point.
Raises
------
ValueError : if the dimensionality of the input points is different than
the dimensionality of the KDE.
"""
points = atleast_2d(asarray(points))
d, m = points.shape
if d != self.d:
if d == 1 and m == self.d:
# points was passed in as a row vector
points = reshape(points, (self.d, 1))
m = 1
else:
msg = f"points have dimension {d}, dataset has dimension {self.d}"
raise ValueError(msg)
output_dtype = np.common_type(self.covariance, points)
result = zeros((m,), dtype=output_dtype)
whitening = linalg.cholesky(self.inv_cov)
scaled_dataset = dot(whitening, self.dataset)
scaled_points = dot(whitening, points)
if m >= self.n:
# there are more points than data, so loop over data
for i in range(self.n):
diff = scaled_dataset[:, i, newaxis] - scaled_points
energy = sum(diff * diff, axis=0) / 2.0
result += self.weights[i]*exp(-energy)
else:
# loop over points
for i in range(m):
diff = scaled_dataset - scaled_points[:, i, newaxis]
energy = sum(diff * diff, axis=0) / 2.0
result[i] = sum(exp(-energy)*self.weights, axis=0)
result = result / self._norm_factor
return result
__call__ = evaluate
def scotts_factor(self):
"""Compute Scott's factor.
Returns
-------
s : float
Scott's factor.
"""
return power(self.neff, -1./(self.d+4))
def silverman_factor(self):
"""Compute the Silverman factor.
Returns
-------
s : float
The silverman factor.
"""
return power(self.neff*(self.d+2.0)/4.0, -1./(self.d+4))
# Default method to calculate bandwidth, can be overwritten by subclass
covariance_factor = scotts_factor
covariance_factor.__doc__ = """Computes the coefficient (`kde.factor`) that
multiplies the data covariance matrix to obtain the kernel covariance
matrix. The default is `scotts_factor`. A subclass can overwrite this
method to provide a different method, or set it through a call to
`kde.set_bandwidth`."""
def set_bandwidth(self, bw_method=None):
"""Compute the estimator bandwidth with given method.
The new bandwidth calculated after a call to `set_bandwidth` is used
for subsequent evaluations of the estimated density.
Parameters
----------
bw_method : str, scalar or callable, optional
The method used to calculate the estimator bandwidth. This can be
'scott', 'silverman', a scalar constant or a callable. If a
scalar, this will be used directly as `kde.factor`. If a callable,
it should take a `gaussian_kde` instance as only parameter and
return a scalar. If None (default), nothing happens; the current
`kde.covariance_factor` method is kept.
Notes
-----
.. versionadded:: 0.11
"""
if bw_method is None:
pass
elif bw_method == 'scott':
self.covariance_factor = self.scotts_factor
elif bw_method == 'silverman':
self.covariance_factor = self.silverman_factor
elif np.isscalar(bw_method) and not isinstance(bw_method, str):
self._bw_method = 'use constant'
self.covariance_factor = lambda: bw_method
elif callable(bw_method):
self._bw_method = bw_method
self.covariance_factor = lambda: self._bw_method(self)
else:
msg = "`bw_method` should be 'scott', 'silverman', a scalar " \
"or a callable."
raise ValueError(msg)
self._compute_covariance()
def _compute_covariance(self):
"""Computes the covariance matrix for each Gaussian kernel using
covariance_factor().
"""
self.factor = self.covariance_factor()
# Cache covariance and inverse covariance of the data
if not hasattr(self, '_data_inv_cov'):
self._data_covariance = atleast_2d(cov(self.dataset, rowvar=1,
bias=False,
aweights=self.weights))
self._data_inv_cov = linalg.inv(self._data_covariance)
self.covariance = self._data_covariance * self.factor**2
self.inv_cov = self._data_inv_cov / self.factor**2
self._norm_factor = sqrt(linalg.det(2*pi*self.covariance))
def pdf(self, x):
"""
Evaluate the estimated pdf on a provided set of points.
Notes
-----
This is an alias for `gaussian_kde.evaluate`. See the ``evaluate``
docstring for more details.
"""
return self.evaluate(x)
@property
def weights(self):
try:
return self._weights
except AttributeError:
self._weights = ones(self.n)/self.n
return self._weights
@property
def neff(self):
try:
return self._neff
except AttributeError:
self._neff = 1/sum(self.weights**2)
return self._neff

View File

@@ -0,0 +1,461 @@
"""Extract reference documentation from the pypa/packaging source tree.
In the process of copying, some unused methods / classes were removed.
These include:
- parse()
- anything involving LegacyVersion
This software is made available under the terms of *either* of the licenses
found in LICENSE.APACHE or LICENSE.BSD. Contributions to this software is made
under the terms of *both* these licenses.
Vendored from:
- https://github.com/pypa/packaging/
- commit ba07d8287b4554754ac7178d177033ea3f75d489 (09/09/2021)
"""
# This file is dual licensed under the terms of the Apache License, Version
# 2.0, and the BSD License. See the LICENSE file in the root of this repository
# for complete details.
import collections
import itertools
import re
from typing import Callable, Optional, SupportsInt, Tuple, Union
__all__ = ["Version", "InvalidVersion", "VERSION_PATTERN"]
# Vendored from https://github.com/pypa/packaging/blob/main/packaging/_structures.py
class InfinityType:
def __repr__(self) -> str:
return "Infinity"
def __hash__(self) -> int:
return hash(repr(self))
def __lt__(self, other: object) -> bool:
return False
def __le__(self, other: object) -> bool:
return False
def __eq__(self, other: object) -> bool:
return isinstance(other, self.__class__)
def __ne__(self, other: object) -> bool:
return not isinstance(other, self.__class__)
def __gt__(self, other: object) -> bool:
return True
def __ge__(self, other: object) -> bool:
return True
def __neg__(self: object) -> "NegativeInfinityType":
return NegativeInfinity
Infinity = InfinityType()
class NegativeInfinityType:
def __repr__(self) -> str:
return "-Infinity"
def __hash__(self) -> int:
return hash(repr(self))
def __lt__(self, other: object) -> bool:
return True
def __le__(self, other: object) -> bool:
return True
def __eq__(self, other: object) -> bool:
return isinstance(other, self.__class__)
def __ne__(self, other: object) -> bool:
return not isinstance(other, self.__class__)
def __gt__(self, other: object) -> bool:
return False
def __ge__(self, other: object) -> bool:
return False
def __neg__(self: object) -> InfinityType:
return Infinity
NegativeInfinity = NegativeInfinityType()
# Vendored from https://github.com/pypa/packaging/blob/main/packaging/version.py
InfiniteTypes = Union[InfinityType, NegativeInfinityType]
PrePostDevType = Union[InfiniteTypes, Tuple[str, int]]
SubLocalType = Union[InfiniteTypes, int, str]
LocalType = Union[
NegativeInfinityType,
Tuple[
Union[
SubLocalType,
Tuple[SubLocalType, str],
Tuple[NegativeInfinityType, SubLocalType],
],
...,
],
]
CmpKey = Tuple[
int, Tuple[int, ...], PrePostDevType, PrePostDevType, PrePostDevType, LocalType
]
LegacyCmpKey = Tuple[int, Tuple[str, ...]]
VersionComparisonMethod = Callable[
[Union[CmpKey, LegacyCmpKey], Union[CmpKey, LegacyCmpKey]], bool
]
_Version = collections.namedtuple(
"_Version", ["epoch", "release", "dev", "pre", "post", "local"]
)
class InvalidVersion(ValueError):
"""
An invalid version was found, users should refer to PEP 440.
"""
class _BaseVersion:
_key: Union[CmpKey, LegacyCmpKey]
def __hash__(self) -> int:
return hash(self._key)
# Please keep the duplicated `isinstance` check
# in the six comparisons hereunder
# unless you find a way to avoid adding overhead function calls.
def __lt__(self, other: "_BaseVersion") -> bool:
if not isinstance(other, _BaseVersion):
return NotImplemented
return self._key < other._key
def __le__(self, other: "_BaseVersion") -> bool:
if not isinstance(other, _BaseVersion):
return NotImplemented
return self._key <= other._key
def __eq__(self, other: object) -> bool:
if not isinstance(other, _BaseVersion):
return NotImplemented
return self._key == other._key
def __ge__(self, other: "_BaseVersion") -> bool:
if not isinstance(other, _BaseVersion):
return NotImplemented
return self._key >= other._key
def __gt__(self, other: "_BaseVersion") -> bool:
if not isinstance(other, _BaseVersion):
return NotImplemented
return self._key > other._key
def __ne__(self, other: object) -> bool:
if not isinstance(other, _BaseVersion):
return NotImplemented
return self._key != other._key
# Deliberately not anchored to the start and end of the string, to make it
# easier for 3rd party code to reuse
VERSION_PATTERN = r"""
v?
(?:
(?:(?P<epoch>[0-9]+)!)? # epoch
(?P<release>[0-9]+(?:\.[0-9]+)*) # release segment
(?P<pre> # pre-release
[-_\.]?
(?P<pre_l>(a|b|c|rc|alpha|beta|pre|preview))
[-_\.]?
(?P<pre_n>[0-9]+)?
)?
(?P<post> # post release
(?:-(?P<post_n1>[0-9]+))
|
(?:
[-_\.]?
(?P<post_l>post|rev|r)
[-_\.]?
(?P<post_n2>[0-9]+)?
)
)?
(?P<dev> # dev release
[-_\.]?
(?P<dev_l>dev)
[-_\.]?
(?P<dev_n>[0-9]+)?
)?
)
(?:\+(?P<local>[a-z0-9]+(?:[-_\.][a-z0-9]+)*))? # local version
"""
class Version(_BaseVersion):
_regex = re.compile(r"^\s*" + VERSION_PATTERN + r"\s*$", re.VERBOSE | re.IGNORECASE)
def __init__(self, version: str) -> None:
# Validate the version and parse it into pieces
match = self._regex.search(version)
if not match:
raise InvalidVersion(f"Invalid version: '{version}'")
# Store the parsed out pieces of the version
self._version = _Version(
epoch=int(match.group("epoch")) if match.group("epoch") else 0,
release=tuple(int(i) for i in match.group("release").split(".")),
pre=_parse_letter_version(match.group("pre_l"), match.group("pre_n")),
post=_parse_letter_version(
match.group("post_l"), match.group("post_n1") or match.group("post_n2")
),
dev=_parse_letter_version(match.group("dev_l"), match.group("dev_n")),
local=_parse_local_version(match.group("local")),
)
# Generate a key which will be used for sorting
self._key = _cmpkey(
self._version.epoch,
self._version.release,
self._version.pre,
self._version.post,
self._version.dev,
self._version.local,
)
def __repr__(self) -> str:
return f"<Version('{self}')>"
def __str__(self) -> str:
parts = []
# Epoch
if self.epoch != 0:
parts.append(f"{self.epoch}!")
# Release segment
parts.append(".".join(str(x) for x in self.release))
# Pre-release
if self.pre is not None:
parts.append("".join(str(x) for x in self.pre))
# Post-release
if self.post is not None:
parts.append(f".post{self.post}")
# Development release
if self.dev is not None:
parts.append(f".dev{self.dev}")
# Local version segment
if self.local is not None:
parts.append(f"+{self.local}")
return "".join(parts)
@property
def epoch(self) -> int:
_epoch: int = self._version.epoch
return _epoch
@property
def release(self) -> Tuple[int, ...]:
_release: Tuple[int, ...] = self._version.release
return _release
@property
def pre(self) -> Optional[Tuple[str, int]]:
_pre: Optional[Tuple[str, int]] = self._version.pre
return _pre
@property
def post(self) -> Optional[int]:
return self._version.post[1] if self._version.post else None
@property
def dev(self) -> Optional[int]:
return self._version.dev[1] if self._version.dev else None
@property
def local(self) -> Optional[str]:
if self._version.local:
return ".".join(str(x) for x in self._version.local)
else:
return None
@property
def public(self) -> str:
return str(self).split("+", 1)[0]
@property
def base_version(self) -> str:
parts = []
# Epoch
if self.epoch != 0:
parts.append(f"{self.epoch}!")
# Release segment
parts.append(".".join(str(x) for x in self.release))
return "".join(parts)
@property
def is_prerelease(self) -> bool:
return self.dev is not None or self.pre is not None
@property
def is_postrelease(self) -> bool:
return self.post is not None
@property
def is_devrelease(self) -> bool:
return self.dev is not None
@property
def major(self) -> int:
return self.release[0] if len(self.release) >= 1 else 0
@property
def minor(self) -> int:
return self.release[1] if len(self.release) >= 2 else 0
@property
def micro(self) -> int:
return self.release[2] if len(self.release) >= 3 else 0
def _parse_letter_version(
letter: str, number: Union[str, bytes, SupportsInt]
) -> Optional[Tuple[str, int]]:
if letter:
# We consider there to be an implicit 0 in a pre-release if there is
# not a numeral associated with it.
if number is None:
number = 0
# We normalize any letters to their lower case form
letter = letter.lower()
# We consider some words to be alternate spellings of other words and
# in those cases we want to normalize the spellings to our preferred
# spelling.
if letter == "alpha":
letter = "a"
elif letter == "beta":
letter = "b"
elif letter in ["c", "pre", "preview"]:
letter = "rc"
elif letter in ["rev", "r"]:
letter = "post"
return letter, int(number)
if not letter and number:
# We assume if we are given a number, but we are not given a letter
# then this is using the implicit post release syntax (e.g. 1.0-1)
letter = "post"
return letter, int(number)
return None
_local_version_separators = re.compile(r"[\._-]")
def _parse_local_version(local: str) -> Optional[LocalType]:
"""
Takes a string like abc.1.twelve and turns it into ("abc", 1, "twelve").
"""
if local is not None:
return tuple(
part.lower() if not part.isdigit() else int(part)
for part in _local_version_separators.split(local)
)
return None
def _cmpkey(
epoch: int,
release: Tuple[int, ...],
pre: Optional[Tuple[str, int]],
post: Optional[Tuple[str, int]],
dev: Optional[Tuple[str, int]],
local: Optional[Tuple[SubLocalType]],
) -> CmpKey:
# When we compare a release version, we want to compare it with all of the
# trailing zeros removed. So we'll use a reverse the list, drop all the now
# leading zeros until we come to something non zero, then take the rest
# re-reverse it back into the correct order and make it a tuple and use
# that for our sorting key.
_release = tuple(
reversed(list(itertools.dropwhile(lambda x: x == 0, reversed(release))))
)
# We need to "trick" the sorting algorithm to put 1.0.dev0 before 1.0a0.
# We'll do this by abusing the pre segment, but we _only_ want to do this
# if there is not a pre or a post segment. If we have one of those then
# the normal sorting rules will handle this case correctly.
if pre is None and post is None and dev is not None:
_pre: PrePostDevType = NegativeInfinity
# Versions without a pre-release (except as noted above) should sort after
# those with one.
elif pre is None:
_pre = Infinity
else:
_pre = pre
# Versions without a post segment should sort before those with one.
if post is None:
_post: PrePostDevType = NegativeInfinity
else:
_post = post
# Versions without a development segment should sort after those with one.
if dev is None:
_dev: PrePostDevType = Infinity
else:
_dev = dev
if local is None:
# Versions without a local segment should sort before those with one.
_local: LocalType = NegativeInfinity
else:
# Versions with a local segment need that segment parsed to implement
# the sorting rules in PEP440.
# - Alpha numeric segments sort before numeric segments
# - Alpha numeric segments sort lexicographically
# - Numeric segments sort numerically
# - Shorter versions sort before longer versions when the prefixes
# match exactly
_local = tuple(
(i, "") if isinstance(i, int) else (NegativeInfinity, i) for i in local
)
return epoch, _release, _pre, _post, _dev, _local