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Copy abc and dependent python files over from CPython 3.7 branch

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ben
2019-04-03 17:11:26 +13:00
parent c6e875f209
commit 39d4d64a4c
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147
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from _weakrefset import WeakSet
def get_cache_token():
"""Returns the current ABC cache token.
The token is an opaque object (supporting equality testing) identifying the
current version of the ABC cache for virtual subclasses. The token changes
with every call to ``register()`` on any ABC.
"""
return ABCMeta._abc_invalidation_counter
class ABCMeta(type):
"""Metaclass for defining Abstract Base Classes (ABCs).
Use this metaclass to create an ABC. An ABC can be subclassed
directly, and then acts as a mix-in class. You can also register
unrelated concrete classes (even built-in classes) and unrelated
ABCs as 'virtual subclasses' -- these and their descendants will
be considered subclasses of the registering ABC by the built-in
issubclass() function, but the registering ABC won't show up in
their MRO (Method Resolution Order) nor will method
implementations defined by the registering ABC be callable (not
even via super()).
"""
# A global counter that is incremented each time a class is
# registered as a virtual subclass of anything. It forces the
# negative cache to be cleared before its next use.
# Note: this counter is private. Use `abc.get_cache_token()` for
# external code.
_abc_invalidation_counter = 0
def __new__(mcls, name, bases, namespace, **kwargs):
cls = super().__new__(mcls, name, bases, namespace, **kwargs)
# Compute set of abstract method names
abstracts = {name
for name, value in namespace.items()
if getattr(value, "__isabstractmethod__", False)}
for base in bases:
for name in getattr(base, "__abstractmethods__", set()):
value = getattr(cls, name, None)
if getattr(value, "__isabstractmethod__", False):
abstracts.add(name)
cls.__abstractmethods__ = frozenset(abstracts)
# Set up inheritance registry
cls._abc_registry = WeakSet()
cls._abc_cache = WeakSet()
cls._abc_negative_cache = WeakSet()
cls._abc_negative_cache_version = ABCMeta._abc_invalidation_counter
return cls
def register(cls, subclass):
"""Register a virtual subclass of an ABC.
Returns the subclass, to allow usage as a class decorator.
"""
if not isinstance(subclass, type):
raise TypeError("Can only register classes")
if issubclass(subclass, cls):
return subclass # Already a subclass
# Subtle: test for cycles *after* testing for "already a subclass";
# this means we allow X.register(X) and interpret it as a no-op.
if issubclass(cls, subclass):
# This would create a cycle, which is bad for the algorithm below
raise RuntimeError("Refusing to create an inheritance cycle")
cls._abc_registry.add(subclass)
ABCMeta._abc_invalidation_counter += 1 # Invalidate negative cache
return subclass
def _dump_registry(cls, file=None):
"""Debug helper to print the ABC registry."""
print(f"Class: {cls.__module__}.{cls.__qualname__}", file=file)
print(f"Inv. counter: {get_cache_token()}", file=file)
for name in cls.__dict__:
if name.startswith("_abc_"):
value = getattr(cls, name)
if isinstance(value, WeakSet):
value = set(value)
print(f"{name}: {value!r}", file=file)
def _abc_registry_clear(cls):
"""Clear the registry (for debugging or testing)."""
cls._abc_registry.clear()
def _abc_caches_clear(cls):
"""Clear the caches (for debugging or testing)."""
cls._abc_cache.clear()
cls._abc_negative_cache.clear()
def __instancecheck__(cls, instance):
"""Override for isinstance(instance, cls)."""
# Inline the cache checking
subclass = instance.__class__
if subclass in cls._abc_cache:
return True
subtype = type(instance)
if subtype is subclass:
if (cls._abc_negative_cache_version ==
ABCMeta._abc_invalidation_counter and
subclass in cls._abc_negative_cache):
return False
# Fall back to the subclass check.
return cls.__subclasscheck__(subclass)
return any(cls.__subclasscheck__(c) for c in (subclass, subtype))
def __subclasscheck__(cls, subclass):
"""Override for issubclass(subclass, cls)."""
if not isinstance(subclass, type):
raise TypeError('issubclass() arg 1 must be a class')
# Check cache
if subclass in cls._abc_cache:
return True
# Check negative cache; may have to invalidate
if cls._abc_negative_cache_version < ABCMeta._abc_invalidation_counter:
# Invalidate the negative cache
cls._abc_negative_cache = WeakSet()
cls._abc_negative_cache_version = ABCMeta._abc_invalidation_counter
elif subclass in cls._abc_negative_cache:
return False
# Check the subclass hook
ok = cls.__subclasshook__(subclass)
if ok is not NotImplemented:
assert isinstance(ok, bool)
if ok:
cls._abc_cache.add(subclass)
else:
cls._abc_negative_cache.add(subclass)
return ok
# Check if it's a direct subclass
if cls in getattr(subclass, '__mro__', ()):
cls._abc_cache.add(subclass)
return True
# Check if it's a subclass of a registered class (recursive)
for rcls in cls._abc_registry:
if issubclass(subclass, rcls):
cls._abc_cache.add(subclass)
return True
# Check if it's a subclass of a subclass (recursive)
for scls in cls.__subclasses__():
if issubclass(subclass, scls):
cls._abc_cache.add(subclass)
return True
# No dice; update negative cache
cls._abc_negative_cache.add(subclass)
return False

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# Access WeakSet through the weakref module.
# This code is separated-out because it is needed
# by abc.py to load everything else at startup.
from _weakref import ref
__all__ = ['WeakSet']
class _IterationGuard:
# This context manager registers itself in the current iterators of the
# weak container, such as to delay all removals until the context manager
# exits.
# This technique should be relatively thread-safe (since sets are).
def __init__(self, weakcontainer):
# Don't create cycles
self.weakcontainer = ref(weakcontainer)
def __enter__(self):
w = self.weakcontainer()
if w is not None:
w._iterating.add(self)
return self
def __exit__(self, e, t, b):
w = self.weakcontainer()
if w is not None:
s = w._iterating
s.remove(self)
if not s:
w._commit_removals()
class WeakSet:
def __init__(self, data=None):
self.data = set()
def _remove(item, selfref=ref(self)):
self = selfref()
if self is not None:
if self._iterating:
self._pending_removals.append(item)
else:
self.data.discard(item)
self._remove = _remove
# A list of keys to be removed
self._pending_removals = []
self._iterating = set()
if data is not None:
self.update(data)
def _commit_removals(self):
l = self._pending_removals
discard = self.data.discard
while l:
discard(l.pop())
def __iter__(self):
with _IterationGuard(self):
for itemref in self.data:
item = itemref()
if item is not None:
# Caveat: the iterator will keep a strong reference to
# `item` until it is resumed or closed.
yield item
def __len__(self):
return len(self.data) - len(self._pending_removals)
def __contains__(self, item):
try:
wr = ref(item)
except TypeError:
return False
return wr in self.data
def __reduce__(self):
return (self.__class__, (list(self),),
getattr(self, '__dict__', None))
def add(self, item):
if self._pending_removals:
self._commit_removals()
self.data.add(ref(item, self._remove))
def clear(self):
if self._pending_removals:
self._commit_removals()
self.data.clear()
def copy(self):
return self.__class__(self)
def pop(self):
if self._pending_removals:
self._commit_removals()
while True:
try:
itemref = self.data.pop()
except KeyError:
raise KeyError('pop from empty WeakSet') from None
item = itemref()
if item is not None:
return item
def remove(self, item):
if self._pending_removals:
self._commit_removals()
self.data.remove(ref(item))
def discard(self, item):
if self._pending_removals:
self._commit_removals()
self.data.discard(ref(item))
def update(self, other):
if self._pending_removals:
self._commit_removals()
for element in other:
self.add(element)
def __ior__(self, other):
self.update(other)
return self
def difference(self, other):
newset = self.copy()
newset.difference_update(other)
return newset
__sub__ = difference
def difference_update(self, other):
self.__isub__(other)
def __isub__(self, other):
if self._pending_removals:
self._commit_removals()
if self is other:
self.data.clear()
else:
self.data.difference_update(ref(item) for item in other)
return self
def intersection(self, other):
return self.__class__(item for item in other if item in self)
__and__ = intersection
def intersection_update(self, other):
self.__iand__(other)
def __iand__(self, other):
if self._pending_removals:
self._commit_removals()
self.data.intersection_update(ref(item) for item in other)
return self
def issubset(self, other):
return self.data.issubset(ref(item) for item in other)
__le__ = issubset
def __lt__(self, other):
return self.data < set(map(ref, other))
def issuperset(self, other):
return self.data.issuperset(ref(item) for item in other)
__ge__ = issuperset
def __gt__(self, other):
return self.data > set(map(ref, other))
def __eq__(self, other):
if not isinstance(other, self.__class__):
return NotImplemented
return self.data == set(map(ref, other))
def symmetric_difference(self, other):
newset = self.copy()
newset.symmetric_difference_update(other)
return newset
__xor__ = symmetric_difference
def symmetric_difference_update(self, other):
self.__ixor__(other)
def __ixor__(self, other):
if self._pending_removals:
self._commit_removals()
if self is other:
self.data.clear()
else:
self.data.symmetric_difference_update(ref(item, self._remove) for item in other)
return self
def union(self, other):
return self.__class__(e for s in (self, other) for e in s)
__or__ = union
def isdisjoint(self, other):
return len(self.intersection(other)) == 0

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# Copyright 2007 Google, Inc. All Rights Reserved.
# Licensed to PSF under a Contributor Agreement.
"""Abstract Base Classes (ABCs) according to PEP 3119."""
def abstractmethod(funcobj):
"""A decorator indicating abstract methods.
Requires that the metaclass is ABCMeta or derived from it. A
class that has a metaclass derived from ABCMeta cannot be
instantiated unless all of its abstract methods are overridden.
The abstract methods can be called using any of the normal
'super' call mechanisms.
Usage:
class C(metaclass=ABCMeta):
@abstractmethod
def my_abstract_method(self, ...):
...
"""
funcobj.__isabstractmethod__ = True
return funcobj
class abstractclassmethod(classmethod):
"""A decorator indicating abstract classmethods.
Similar to abstractmethod.
Usage:
class C(metaclass=ABCMeta):
@abstractclassmethod
def my_abstract_classmethod(cls, ...):
...
'abstractclassmethod' is deprecated. Use 'classmethod' with
'abstractmethod' instead.
"""
__isabstractmethod__ = True
def __init__(self, callable):
callable.__isabstractmethod__ = True
super().__init__(callable)
class abstractstaticmethod(staticmethod):
"""A decorator indicating abstract staticmethods.
Similar to abstractmethod.
Usage:
class C(metaclass=ABCMeta):
@abstractstaticmethod
def my_abstract_staticmethod(...):
...
'abstractstaticmethod' is deprecated. Use 'staticmethod' with
'abstractmethod' instead.
"""
__isabstractmethod__ = True
def __init__(self, callable):
callable.__isabstractmethod__ = True
super().__init__(callable)
class abstractproperty(property):
"""A decorator indicating abstract properties.
Requires that the metaclass is ABCMeta or derived from it. A
class that has a metaclass derived from ABCMeta cannot be
instantiated unless all of its abstract properties are overridden.
The abstract properties can be called using any of the normal
'super' call mechanisms.
Usage:
class C(metaclass=ABCMeta):
@abstractproperty
def my_abstract_property(self):
...
This defines a read-only property; you can also define a read-write
abstract property using the 'long' form of property declaration:
class C(metaclass=ABCMeta):
def getx(self): ...
def setx(self, value): ...
x = abstractproperty(getx, setx)
'abstractproperty' is deprecated. Use 'property' with 'abstractmethod'
instead.
"""
__isabstractmethod__ = True
try:
from _abc import (get_cache_token, _abc_init, _abc_register,
_abc_instancecheck, _abc_subclasscheck, _get_dump,
_reset_registry, _reset_caches)
except ImportError:
from _py_abc import ABCMeta, get_cache_token
ABCMeta.__module__ = 'abc'
else:
class ABCMeta(type):
"""Metaclass for defining Abstract Base Classes (ABCs).
Use this metaclass to create an ABC. An ABC can be subclassed
directly, and then acts as a mix-in class. You can also register
unrelated concrete classes (even built-in classes) and unrelated
ABCs as 'virtual subclasses' -- these and their descendants will
be considered subclasses of the registering ABC by the built-in
issubclass() function, but the registering ABC won't show up in
their MRO (Method Resolution Order) nor will method
implementations defined by the registering ABC be callable (not
even via super()).
"""
def __new__(mcls, name, bases, namespace, **kwargs):
cls = super().__new__(mcls, name, bases, namespace, **kwargs)
_abc_init(cls)
return cls
def register(cls, subclass):
"""Register a virtual subclass of an ABC.
Returns the subclass, to allow usage as a class decorator.
"""
return _abc_register(cls, subclass)
def __instancecheck__(cls, instance):
"""Override for isinstance(instance, cls)."""
return _abc_instancecheck(cls, instance)
def __subclasscheck__(cls, subclass):
"""Override for issubclass(subclass, cls)."""
return _abc_subclasscheck(cls, subclass)
def _dump_registry(cls, file=None):
"""Debug helper to print the ABC registry."""
print(f"Class: {cls.__module__}.{cls.__qualname__}", file=file)
print(f"Inv. counter: {get_cache_token()}", file=file)
(_abc_registry, _abc_cache, _abc_negative_cache,
_abc_negative_cache_version) = _get_dump(cls)
print(f"_abc_registry: {_abc_registry!r}", file=file)
print(f"_abc_cache: {_abc_cache!r}", file=file)
print(f"_abc_negative_cache: {_abc_negative_cache!r}", file=file)
print(f"_abc_negative_cache_version: {_abc_negative_cache_version!r}",
file=file)
def _abc_registry_clear(cls):
"""Clear the registry (for debugging or testing)."""
_reset_registry(cls)
def _abc_caches_clear(cls):
"""Clear the caches (for debugging or testing)."""
_reset_caches(cls)
class ABC(metaclass=ABCMeta):
"""Helper class that provides a standard way to create an ABC using
inheritance.
"""
__slots__ = ()

254
PSF-LICENSE Normal file
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A. HISTORY OF THE SOFTWARE
==========================
Python was created in the early 1990s by Guido van Rossum at Stichting
Mathematisch Centrum (CWI, see http://www.cwi.nl) in the Netherlands
as a successor of a language called ABC. Guido remains Python's
principal author, although it includes many contributions from others.
In 1995, Guido continued his work on Python at the Corporation for
National Research Initiatives (CNRI, see http://www.cnri.reston.va.us)
in Reston, Virginia where he released several versions of the
software.
In May 2000, Guido and the Python core development team moved to
BeOpen.com to form the BeOpen PythonLabs team. In October of the same
year, the PythonLabs team moved to Digital Creations, which became
Zope Corporation. In 2001, the Python Software Foundation (PSF, see
https://www.python.org/psf/) was formed, a non-profit organization
created specifically to own Python-related Intellectual Property.
Zope Corporation was a sponsoring member of the PSF.
All Python releases are Open Source (see http://www.opensource.org for
the Open Source Definition). Historically, most, but not all, Python
releases have also been GPL-compatible; the table below summarizes
the various releases.
Release Derived Year Owner GPL-
from compatible? (1)
0.9.0 thru 1.2 1991-1995 CWI yes
1.3 thru 1.5.2 1.2 1995-1999 CNRI yes
1.6 1.5.2 2000 CNRI no
2.0 1.6 2000 BeOpen.com no
1.6.1 1.6 2001 CNRI yes (2)
2.1 2.0+1.6.1 2001 PSF no
2.0.1 2.0+1.6.1 2001 PSF yes
2.1.1 2.1+2.0.1 2001 PSF yes
2.1.2 2.1.1 2002 PSF yes
2.1.3 2.1.2 2002 PSF yes
2.2 and above 2.1.1 2001-now PSF yes
Footnotes:
(1) GPL-compatible doesn't mean that we're distributing Python under
the GPL. All Python licenses, unlike the GPL, let you distribute
a modified version without making your changes open source. The
GPL-compatible licenses make it possible to combine Python with
other software that is released under the GPL; the others don't.
(2) According to Richard Stallman, 1.6.1 is not GPL-compatible,
because its license has a choice of law clause. According to
CNRI, however, Stallman's lawyer has told CNRI's lawyer that 1.6.1
is "not incompatible" with the GPL.
Thanks to the many outside volunteers who have worked under Guido's
direction to make these releases possible.
B. TERMS AND CONDITIONS FOR ACCESSING OR OTHERWISE USING PYTHON
===============================================================
PYTHON SOFTWARE FOUNDATION LICENSE VERSION 2
--------------------------------------------
1. This LICENSE AGREEMENT is between the Python Software Foundation
("PSF"), and the Individual or Organization ("Licensee") accessing and
otherwise using this software ("Python") in source or binary form and
its associated documentation.
2. Subject to the terms and conditions of this License Agreement, PSF hereby
grants Licensee a nonexclusive, royalty-free, world-wide license to reproduce,
analyze, test, perform and/or display publicly, prepare derivative works,
distribute, and otherwise use Python alone or in any derivative version,
provided, however, that PSF's License Agreement and PSF's notice of copyright,
i.e., "Copyright (c) 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010,
2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018 Python Software Foundation; All
Rights Reserved" are retained in Python alone or in any derivative version
prepared by Licensee.
3. In the event Licensee prepares a derivative work that is based on
or incorporates Python or any part thereof, and wants to make
the derivative work available to others as provided herein, then
Licensee hereby agrees to include in any such work a brief summary of
the changes made to Python.
4. PSF is making Python available to Licensee on an "AS IS"
basis. PSF MAKES NO REPRESENTATIONS OR WARRANTIES, EXPRESS OR
IMPLIED. BY WAY OF EXAMPLE, BUT NOT LIMITATION, PSF MAKES NO AND
DISCLAIMS ANY REPRESENTATION OR WARRANTY OF MERCHANTABILITY OR FITNESS
FOR ANY PARTICULAR PURPOSE OR THAT THE USE OF PYTHON WILL NOT
INFRINGE ANY THIRD PARTY RIGHTS.
5. PSF SHALL NOT BE LIABLE TO LICENSEE OR ANY OTHER USERS OF PYTHON
FOR ANY INCIDENTAL, SPECIAL, OR CONSEQUENTIAL DAMAGES OR LOSS AS
A RESULT OF MODIFYING, DISTRIBUTING, OR OTHERWISE USING PYTHON,
OR ANY DERIVATIVE THEREOF, EVEN IF ADVISED OF THE POSSIBILITY THEREOF.
6. This License Agreement will automatically terminate upon a material
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7. Nothing in this License Agreement shall be deemed to create any
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trademarks or trade name in a trademark sense to endorse or promote
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8. By copying, installing or otherwise using Python, Licensee
agrees to be bound by the terms and conditions of this License
Agreement.
BEOPEN.COM LICENSE AGREEMENT FOR PYTHON 2.0
-------------------------------------------
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1. This LICENSE AGREEMENT is between BeOpen.com ("BeOpen"), having an
office at 160 Saratoga Avenue, Santa Clara, CA 95051, and the
Individual or Organization ("Licensee") accessing and otherwise using
this software in source or binary form and its associated
documentation ("the Software").
2. Subject to the terms and conditions of this BeOpen Python License
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royalty-free, world-wide license to reproduce, analyze, test, perform
and/or display publicly, prepare derivative works, distribute, and
otherwise use the Software alone or in any derivative version,
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basis. BEOPEN MAKES NO REPRESENTATIONS OR WARRANTIES, EXPRESS OR
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DISCLAIMS ANY REPRESENTATION OR WARRANTY OF MERCHANTABILITY OR FITNESS
FOR ANY PARTICULAR PURPOSE OR THAT THE USE OF THE SOFTWARE WILL NOT
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4. BEOPEN SHALL NOT BE LIABLE TO LICENSEE OR ANY OTHER USERS OF THE
SOFTWARE FOR ANY INCIDENTAL, SPECIAL, OR CONSEQUENTIAL DAMAGES OR LOSS
AS A RESULT OF USING, MODIFYING OR DISTRIBUTING THE SOFTWARE, OR ANY
DERIVATIVE THEREOF, EVEN IF ADVISED OF THE POSSIBILITY THEREOF.
5. This License Agreement will automatically terminate upon a material
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6. This License Agreement shall be governed by and interpreted in all
respects by the law of the State of California, excluding conflict of
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7. By copying, installing or otherwise using the software, Licensee
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CNRI LICENSE AGREEMENT FOR PYTHON 1.6.1
---------------------------------------
1. This LICENSE AGREEMENT is between the Corporation for National
Research Initiatives, having an office at 1895 Preston White Drive,
Reston, VA 20191 ("CNRI"), and the Individual or Organization
("Licensee") accessing and otherwise using Python 1.6.1 software in
source or binary form and its associated documentation.
2. Subject to the terms and conditions of this License Agreement, CNRI
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license to reproduce, analyze, test, perform and/or display publicly,
prepare derivative works, distribute, and otherwise use Python 1.6.1
alone or in any derivative version, provided, however, that CNRI's
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3. In the event Licensee prepares a derivative work that is based on
or incorporates Python 1.6.1 or any part thereof, and wants to make
the derivative work available to others as provided herein, then
Licensee hereby agrees to include in any such work a brief summary of
the changes made to Python 1.6.1.
4. CNRI is making Python 1.6.1 available to Licensee on an "AS IS"
basis. CNRI MAKES NO REPRESENTATIONS OR WARRANTIES, EXPRESS OR
IMPLIED. BY WAY OF EXAMPLE, BUT NOT LIMITATION, CNRI MAKES NO AND
DISCLAIMS ANY REPRESENTATION OR WARRANTY OF MERCHANTABILITY OR FITNESS
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INFRINGE ANY THIRD PARTY RIGHTS.
5. CNRI SHALL NOT BE LIABLE TO LICENSEE OR ANY OTHER USERS OF PYTHON
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ACCEPT
CWI LICENSE AGREEMENT FOR PYTHON 0.9.0 THROUGH 1.2
--------------------------------------------------
Copyright (c) 1991 - 1995, Stichting Mathematisch Centrum Amsterdam,
The Netherlands. All rights reserved.
Permission to use, copy, modify, and distribute this software and its
documentation for any purpose and without fee is hereby granted,
provided that the above copyright notice appear in all copies and that
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ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION, ARISING OUT
OF OR IN CONNECTION WITH THE USE OR PERFORMANCE OF THIS SOFTWARE.

4
tests/snippets/abc_test.py Normal file
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import sys
sys.path.append('Lib')
import abc