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RustPython/Lib/types.py
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youknowdot fc9f4a9541 Update importlib to CPython 3.15 with native bootstrap callback (#9169)
* Refresh canonical importlib and preserve native import callback

Cache the original builtin __import__ callback so CPython 3.15 importlib's
hierarchical locking uses the existing native parent-initialization path.
Refresh the complete canonical importlib and related test/helper families
from CPython d220409a13b77de7a6c30abe16ea90db01528edc through update_lib.

Preserve both nondecorator importlib guards in the updater. Add explicit
hash-pinned removal of reviewed obsolete canonical files, with full
preflight, dry-run, idempotence and refusal tests. Preserve empty fixtures.

Assisted-by: OpenAI Codex:model version unavailable

* Complete canonical inspect and types closure for importlib metadata

Refresh whole canonical inspect/types production and related test families
through update_lib after hosted CI exposed stale __cached__ consumers.
Add coroutine and async-generator state getters, with closed-state priority
for reentrant frame-local finalizers, and expose the existing frame-locals
proxy type with its CPython class documentation.

Preserve the optional _datetime and unittest import blocks through a narrow
migration adapter. Retain canonical assertions and existing guards; record
the missing LazyImportType expectation before adding a conditional expected
failure, and capability-skip only the two absent-_testcapi CLI fixtures.

Assisted-by: OpenAI Codex:model version unavailable

* Reject canonical removal junctions and read UTF-8 manifests

Reject junctions alongside symlinks in the existing path-component preflight and revalidation. Decode removal manifests explicitly as UTF-8. Add regressions for whole-batch refusal, revalidation, and Unicode dry-run/apply/idempotence.

Assisted-by: OpenAI Codex:model version unavailable
2026-10-17 14:40:13 +09:00

356 lines
11 KiB
Python
Vendored

"""
Define names for built-in types that aren't directly accessible as a builtin.
"""
# Iterators in Python aren't a matter of type but of protocol. A large
# and changing number of builtin types implement *some* flavor of
# iterator. Don't check the type! Use hasattr to check for both
# "__iter__" and "__next__" attributes instead.
try:
from _types import *
except ImportError:
import sys
def _f(): pass
FunctionType = type(_f)
LambdaType = type(lambda: None) # Same as FunctionType
CodeType = type(_f.__code__)
MappingProxyType = type(type.__dict__)
SimpleNamespace = type(sys.implementation)
def _cell_factory():
a = 1
def f():
nonlocal a
return f.__closure__[0]
CellType = type(_cell_factory())
def _g():
yield 1
GeneratorType = type(_g())
async def _c(): pass
_c = _c()
CoroutineType = type(_c)
_c.close() # Prevent ResourceWarning
async def _ag():
yield
_ag = _ag()
AsyncGeneratorType = type(_ag)
class _C:
def _m(self): pass
MethodType = type(_C()._m)
BuiltinFunctionType = type(len)
BuiltinMethodType = type([].append) # Same as BuiltinFunctionType
WrapperDescriptorType = type(object.__init__)
MethodWrapperType = type(object().__str__)
MethodDescriptorType = type(str.join)
ClassMethodDescriptorType = type(dict.__dict__['fromkeys'])
ModuleType = type(sys)
try:
raise TypeError
except TypeError as exc:
TracebackType = type(exc.__traceback__)
_f = (lambda: sys._getframe())()
FrameType = type(_f)
FrameLocalsProxyType = type(_f.f_locals)
GetSetDescriptorType = type(FunctionType.__code__)
MemberDescriptorType = type(FunctionType.__globals__)
GenericAlias = type(list[int])
UnionType = type(int | str)
EllipsisType = type(Ellipsis)
NoneType = type(None)
NotImplementedType = type(NotImplemented)
# CapsuleType cannot be accessed from pure Python,
# so there is no fallback definition.
# LazyImportType in pure Python cannot be guaranteed
# without overriding the filter, so there is no fallback.
del sys, _f, _g, _C, _c, _ag, _cell_factory # Not for export
# Provide a PEP 3115 compliant mechanism for class creation
def new_class(name, bases=(), kwds=None, exec_body=None):
"""Create a class object dynamically using the appropriate metaclass."""
resolved_bases = resolve_bases(bases)
meta, ns, kwds = prepare_class(name, resolved_bases, kwds)
if exec_body is not None:
exec_body(ns)
if resolved_bases is not bases:
ns['__orig_bases__'] = bases
return meta(name, resolved_bases, ns, **kwds)
def resolve_bases(bases):
"""Resolve MRO entries dynamically as specified by PEP 560."""
new_bases = list(bases)
updated = False
shift = 0
for i, base in enumerate(bases):
if isinstance(base, type):
continue
if not hasattr(base, "__mro_entries__"):
continue
new_base = base.__mro_entries__(bases)
updated = True
if not isinstance(new_base, tuple):
raise TypeError("__mro_entries__ must return a tuple")
else:
new_bases[i+shift:i+shift+1] = new_base
shift += len(new_base) - 1
if not updated:
return bases
return tuple(new_bases)
def prepare_class(name, bases=(), kwds=None):
"""Call the __prepare__ method of the appropriate metaclass.
Returns (metaclass, namespace, kwds) as a 3-tuple
*metaclass* is the appropriate metaclass
*namespace* is the prepared class namespace
*kwds* is an updated copy of the passed in kwds argument with any
'metaclass' entry removed. If no kwds argument is passed in, this will
be an empty dict.
"""
if kwds is None:
kwds = {}
else:
kwds = dict(kwds) # Don't alter the provided mapping
if 'metaclass' in kwds:
meta = kwds.pop('metaclass')
else:
if bases:
meta = type(bases[0])
else:
meta = type
if isinstance(meta, type):
# when meta is a type, we first determine the most-derived metaclass
# instead of invoking the initial candidate directly
meta = _calculate_meta(meta, bases)
if hasattr(meta, '__prepare__'):
ns = meta.__prepare__(name, bases, **kwds)
else:
ns = {}
return meta, ns, kwds
def _calculate_meta(meta, bases):
"""Calculate the most derived metaclass."""
winner = meta
for base in bases:
base_meta = type(base)
if issubclass(winner, base_meta):
continue
if issubclass(base_meta, winner):
winner = base_meta
continue
# else:
raise TypeError("metaclass conflict: "
"the metaclass of a derived class "
"must be a (non-strict) subclass "
"of the metaclasses of all its bases")
return winner
def get_original_bases(cls, /):
"""Return the class's "original" bases prior to modification by `__mro_entries__`.
Examples::
from typing import TypeVar, Generic, NamedTuple, TypedDict
T = TypeVar("T")
class Foo(Generic[T]): ...
class Bar(Foo[int], float): ...
class Baz(list[str]): ...
Eggs = NamedTuple("Eggs", [("a", int), ("b", str)])
Spam = TypedDict("Spam", {"a": int, "b": str})
assert get_original_bases(Bar) == (Foo[int], float)
assert get_original_bases(Baz) == (list[str],)
assert get_original_bases(Eggs) == (NamedTuple,)
assert get_original_bases(Spam) == (TypedDict,)
assert get_original_bases(int) == (object,)
"""
try:
return cls.__dict__.get("__orig_bases__", cls.__bases__)
except AttributeError:
raise TypeError(
f"Expected an instance of type, not {type(cls).__name__!r}"
) from None
class DynamicClassAttribute:
"""Route attribute access on a class to __getattr__.
This is a descriptor, used to define attributes that act differently
when accessed through an instance and through a class. Instance access
remains normal, but access to an attribute through a class will be
routed to the class's __getattr__ method; this is done by raising
AttributeError.
This allows one to have properties active on an instance, and have
virtual attributes on the class with the same name. (Enum used this
between Python versions 3.4 - 3.9 .)
Subclass from this to use a different method of accessing virtual
attributes and still be treated properly by the inspect module. (Enum
uses this since Python 3.10 .)
"""
def __init__(self, fget=None, fset=None, fdel=None, doc=None):
self.fget = fget
self.fset = fset
self.fdel = fdel
# next two lines make DynamicClassAttribute act the same as property
self.__doc__ = doc or fget.__doc__
self.overwrite_doc = doc is None
# support for abstract methods
self.__isabstractmethod__ = bool(getattr(fget, '__isabstractmethod__', False))
def __get__(self, instance, ownerclass=None):
if instance is None:
if self.__isabstractmethod__:
return self
raise AttributeError()
elif self.fget is None:
raise AttributeError("unreadable attribute")
return self.fget(instance)
def __set__(self, instance, value):
if self.fset is None:
raise AttributeError("can't set attribute")
self.fset(instance, value)
def __delete__(self, instance):
if self.fdel is None:
raise AttributeError("can't delete attribute")
self.fdel(instance)
def getter(self, fget):
fdoc = fget.__doc__ if self.overwrite_doc else None
result = type(self)(fget, self.fset, self.fdel, fdoc or self.__doc__)
result.overwrite_doc = self.overwrite_doc
return result
def setter(self, fset):
result = type(self)(self.fget, fset, self.fdel, self.__doc__)
result.overwrite_doc = self.overwrite_doc
return result
def deleter(self, fdel):
result = type(self)(self.fget, self.fset, fdel, self.__doc__)
result.overwrite_doc = self.overwrite_doc
return result
class _GeneratorWrapper:
def __init__(self, gen):
self.__wrapped = gen
self.__isgen = gen.__class__ is GeneratorType
self.__name__ = getattr(gen, '__name__', None)
self.__qualname__ = getattr(gen, '__qualname__', None)
def send(self, val):
return self.__wrapped.send(val)
def throw(self, tp, *rest):
return self.__wrapped.throw(tp, *rest)
def close(self):
return self.__wrapped.close()
@property
def gi_code(self):
return self.__wrapped.gi_code
@property
def gi_frame(self):
return self.__wrapped.gi_frame
@property
def gi_running(self):
return self.__wrapped.gi_running
@property
def gi_yieldfrom(self):
return self.__wrapped.gi_yieldfrom
@property
def gi_suspended(self):
return self.__wrapped.gi_suspended
@property
def gi_state(self):
return self.__wrapped.gi_state
@property
def cr_state(self):
return self.__wrapped.gi_state.replace('GEN_', 'CORO_')
cr_code = gi_code
cr_frame = gi_frame
cr_running = gi_running
cr_await = gi_yieldfrom
cr_suspended = gi_suspended
def __next__(self):
return next(self.__wrapped)
def __iter__(self):
if self.__isgen:
return self.__wrapped
return self
__await__ = __iter__
def coroutine(func):
"""Convert regular generator function to a coroutine."""
if not callable(func):
raise TypeError('types.coroutine() expects a callable')
if (func.__class__ is FunctionType and
getattr(func, '__code__', None).__class__ is CodeType):
co_flags = func.__code__.co_flags
# Check if 'func' is a coroutine function.
# (0x180 == CO_COROUTINE | CO_ITERABLE_COROUTINE)
if co_flags & 0x180:
return func
# Check if 'func' is a generator function.
# (0x20 == CO_GENERATOR)
if co_flags & 0x20:
co = func.__code__
# 0x100 == CO_ITERABLE_COROUTINE
func.__code__ = co.replace(co_flags=co.co_flags | 0x100)
return func
# The following code is primarily to support functions that
# return generator-like objects (for instance generators
# compiled with Cython).
# Delay functools and _collections_abc import for speeding up types import.
import functools
import _collections_abc
@functools.wraps(func)
def wrapped(*args, **kwargs):
coro = func(*args, **kwargs)
if (coro.__class__ is CoroutineType or
coro.__class__ is GeneratorType and coro.gi_code.co_flags & 0x100):
# 'coro' is a native coroutine object or an iterable coroutine
return coro
if (isinstance(coro, _collections_abc.Generator) and
not isinstance(coro, _collections_abc.Coroutine)):
# 'coro' is either a pure Python generator iterator, or it
# implements collections.abc.Generator (and does not implement
# collections.abc.Coroutine).
return _GeneratorWrapper(coro)
# 'coro' is either an instance of collections.abc.Coroutine or
# some other object -- pass it through.
return coro
return wrapped
__all__ = [n for n in globals() if not n.startswith('_')] # for pydoc