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openmedialibrary_platform_d.../lib/python3.5/typing.py

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split platform
2016-02-06 09:36:57 +00:00
# TODO nits:
# Get rid of asserts that are the caller's fault.
# Docstrings (e.g. ABCs).
import abc
from abc import abstractmethod, abstractproperty
import collections
import functools
import re as stdlib_re # Avoid confusion with the re we export.
import sys
import types
try:
import collections.abc as collections_abc
except ImportError:
import collections as collections_abc # Fallback for PY3.2.
# Please keep __all__ alphabetized within each category.
__all__ = [
# Super-special typing primitives.
'Any',
'Callable',
'Generic',
'Optional',
'TypeVar',
'Union',
'Tuple',
# ABCs (from collections.abc).
'AbstractSet', # collections.abc.Set.
'ByteString',
'Container',
'Hashable',
'ItemsView',
'Iterable',
'Iterator',
'KeysView',
'Mapping',
'MappingView',
'MutableMapping',
'MutableSequence',
'MutableSet',
'Sequence',
'Sized',
'ValuesView',
# Structural checks, a.k.a. protocols.
'Reversible',
'SupportsAbs',
'SupportsFloat',
'SupportsInt',
'SupportsRound',
# Concrete collection types.
'Dict',
'List',
'Set',
'NamedTuple', # Not really a type.
'Generator',
# One-off things.
'AnyStr',
'cast',
'get_type_hints',
'no_type_check',
'no_type_check_decorator',
'overload',
# Submodules.
'io',
're',
]
def _qualname(x):
if sys.version_info[:2] >= (3, 3):
return x.__qualname__
else:
# Fall back to just name.
return x.__name__
class TypingMeta(type):
"""Metaclass for every type defined below.
This overrides __new__() to require an extra keyword parameter
'_root', which serves as a guard against naive subclassing of the
typing classes. Any legitimate class defined using a metaclass
derived from TypingMeta (including internal subclasses created by
e.g. Union[X, Y]) must pass _root=True.
This also defines a dummy constructor (all the work is done in
__new__) and a nicer repr().
"""
_is_protocol = False
def __new__(cls, name, bases, namespace, *, _root=False):
if not _root:
raise TypeError("Cannot subclass %s" %
(', '.join(map(_type_repr, bases)) or '()'))
return super().__new__(cls, name, bases, namespace)
def __init__(self, *args, **kwds):
pass
def _eval_type(self, globalns, localns):
"""Override this in subclasses to interpret forward references.
For example, Union['C'] is internally stored as
Union[_ForwardRef('C')], which should evaluate to _Union[C],
where C is an object found in globalns or localns (searching
localns first, of course).
"""
return self
def _has_type_var(self):
return False
def __repr__(self):
return '%s.%s' % (self.__module__, _qualname(self))
class Final:
"""Mix-in class to prevent instantiation."""
__slots__ = ()
def __new__(self, *args, **kwds):
raise TypeError("Cannot instantiate %r" % self.__class__)
class _ForwardRef(TypingMeta):
"""Wrapper to hold a forward reference."""
def __new__(cls, arg):
if not isinstance(arg, str):
raise TypeError('ForwardRef must be a string -- got %r' % (arg,))
try:
code = compile(arg, '<string>', 'eval')
except SyntaxError:
raise SyntaxError('ForwardRef must be an expression -- got %r' %
(arg,))
self = super().__new__(cls, arg, (), {}, _root=True)
self.__forward_arg__ = arg
self.__forward_code__ = code
self.__forward_evaluated__ = False
self.__forward_value__ = None
typing_globals = globals()
frame = sys._getframe(1)
while frame is not None and frame.f_globals is typing_globals:
frame = frame.f_back
assert frame is not None
self.__forward_frame__ = frame
return self
def _eval_type(self, globalns, localns):
if not isinstance(localns, dict):
raise TypeError('ForwardRef localns must be a dict -- got %r' %
(localns,))
if not isinstance(globalns, dict):
raise TypeError('ForwardRef globalns must be a dict -- got %r' %
(globalns,))
if not self.__forward_evaluated__:
if globalns is None and localns is None:
globalns = localns = {}
elif globalns is None:
globalns = localns
elif localns is None:
localns = globalns
self.__forward_value__ = _type_check(
eval(self.__forward_code__, globalns, localns),
"Forward references must evaluate to types.")
self.__forward_evaluated__ = True
return self.__forward_value__
def __instancecheck__(self, obj):
raise TypeError("Forward references cannot be used with isinstance().")
def __subclasscheck__(self, cls):
if not self.__forward_evaluated__:
globalns = self.__forward_frame__.f_globals
localns = self.__forward_frame__.f_locals
try:
self._eval_type(globalns, localns)
except NameError:
return False # Too early.
return issubclass(cls, self.__forward_value__)
def __repr__(self):
return '_ForwardRef(%r)' % (self.__forward_arg__,)
class _TypeAlias:
"""Internal helper class for defining generic variants of concrete types.
Note that this is not a type; let's call it a pseudo-type. It can
be used in instance and subclass checks, e.g. isinstance(m, Match)
or issubclass(type(m), Match). However, it cannot be itself the
target of an issubclass() call; e.g. issubclass(Match, C) (for
some arbitrary class C) raises TypeError rather than returning
False.
"""
__slots__ = ('name', 'type_var', 'impl_type', 'type_checker')
def __new__(cls, *args, **kwds):
"""Constructor.
This only exists to give a better error message in case
someone tries to subclass a type alias (not a good idea).
"""
if (len(args) == 3 and
isinstance(args[0], str) and
isinstance(args[1], tuple)):
# Close enough.
raise TypeError("A type alias cannot be subclassed")
return object.__new__(cls)
def __init__(self, name, type_var, impl_type, type_checker):
"""Initializer.
Args:
name: The name, e.g. 'Pattern'.
type_var: The type parameter, e.g. AnyStr, or the
specific type, e.g. str.
impl_type: The implementation type.
type_checker: Function that takes an impl_type instance.
and returns a value that should be a type_var instance.
"""
assert isinstance(name, str), repr(name)
assert isinstance(type_var, type), repr(type_var)
assert isinstance(impl_type, type), repr(impl_type)
assert not isinstance(impl_type, TypingMeta), repr(impl_type)
self.name = name
self.type_var = type_var
self.impl_type = impl_type
self.type_checker = type_checker
def __repr__(self):
return "%s[%s]" % (self.name, _type_repr(self.type_var))
def __getitem__(self, parameter):
assert isinstance(parameter, type), repr(parameter)
if not isinstance(self.type_var, TypeVar):
raise TypeError("%s cannot be further parameterized." % self)
if self.type_var.__constraints__:
if not issubclass(parameter, Union[self.type_var.__constraints__]):
raise TypeError("%s is not a valid substitution for %s." %
(parameter, self.type_var))
return self.__class__(self.name, parameter,
self.impl_type, self.type_checker)
def __instancecheck__(self, obj):
raise TypeError("Type aliases cannot be used with isinstance().")
def __subclasscheck__(self, cls):
if cls is Any:
return True
if isinstance(cls, _TypeAlias):
# Covariance. For now, we compare by name.
return (cls.name == self.name and
issubclass(cls.type_var, self.type_var))
else:
# Note that this is too lenient, because the
# implementation type doesn't carry information about
# whether it is about bytes or str (for example).
return issubclass(cls, self.impl_type)
def _has_type_var(t):
return t is not None and isinstance(t, TypingMeta) and t._has_type_var()
def _eval_type(t, globalns, localns):
if isinstance(t, TypingMeta):
return t._eval_type(globalns, localns)
else:
return t
def _type_check(arg, msg):
"""Check that the argument is a type, and return it.
As a special case, accept None and return type(None) instead.
Also, _TypeAlias instances (e.g. Match, Pattern) are acceptable.
The msg argument is a human-readable error message, e.g.
"Union[arg, ...]: arg should be a type."
We append the repr() of the actual value (truncated to 100 chars).
"""
if arg is None:
return type(None)
if isinstance(arg, str):
arg = _ForwardRef(arg)
if not isinstance(arg, (type, _TypeAlias)):
raise TypeError(msg + " Got %.100r." % (arg,))
return arg
def _type_repr(obj):
"""Return the repr() of an object, special-casing types.
If obj is a type, we return a shorter version than the default
type.__repr__, based on the module and qualified name, which is
typically enough to uniquely identify a type. For everything
else, we fall back on repr(obj).
"""
if isinstance(obj, type) and not isinstance(obj, TypingMeta):
if obj.__module__ == 'builtins':
return _qualname(obj)
else:
return '%s.%s' % (obj.__module__, _qualname(obj))
else:
return repr(obj)
class AnyMeta(TypingMeta):
"""Metaclass for Any."""
def __new__(cls, name, bases, namespace, _root=False):
self = super().__new__(cls, name, bases, namespace, _root=_root)
return self
def __instancecheck__(self, obj):
raise TypeError("Any cannot be used with isinstance().")
def __subclasscheck__(self, cls):
if not isinstance(cls, type):
return super().__subclasscheck__(cls) # To TypeError.
return True
class Any(Final, metaclass=AnyMeta, _root=True):
"""Special type indicating an unconstrained type.
- Any object is an instance of Any.
- Any class is a subclass of Any.
- As a special case, Any and object are subclasses of each other.
"""
__slots__ = ()
class TypeVar(TypingMeta, metaclass=TypingMeta, _root=True):
"""Type variable.
Usage::
T = TypeVar('T') # Can be anything
A = TypeVar('A', str, bytes) # Must be str or bytes
Type variables exist primarily for the benefit of static type
checkers. They serve as the parameters for generic types as well
as for generic function definitions. See class Generic for more
information on generic types. Generic functions work as follows:
def repeat(x: T, n: int) -> Sequence[T]:
'''Return a list containing n references to x.'''
return [x]*n
def longest(x: A, y: A) -> A:
'''Return the longest of two strings.'''
return x if len(x) >= len(y) else y
The latter example's signature is essentially the overloading
of (str, str) -> str and (bytes, bytes) -> bytes. Also note
that if the arguments are instances of some subclass of str,
the return type is still plain str.
At runtime, isinstance(x, T) will raise TypeError. However,
issubclass(C, T) is true for any class C, and issubclass(str, A)
and issubclass(bytes, A) are true, and issubclass(int, A) is
false.
Type variables may be marked covariant or contravariant by passing
covariant=True or contravariant=True. See PEP 484 for more
details. By default type variables are invariant.
Type variables can be introspected. e.g.:
T.__name__ == 'T'
T.__constraints__ == ()
T.__covariant__ == False
T.__contravariant__ = False
A.__constraints__ == (str, bytes)
"""
def __new__(cls, name, *constraints, bound=None,
covariant=False, contravariant=False):
self = super().__new__(cls, name, (Final,), {}, _root=True)
if covariant and contravariant:
raise ValueError("Bivariant type variables are not supported.")
self.__covariant__ = bool(covariant)
self.__contravariant__ = bool(contravariant)
if constraints and bound is not None:
raise TypeError("Constraints cannot be combined with bound=...")
if constraints and len(constraints) == 1:
raise TypeError("A single constraint is not allowed")
msg = "TypeVar(name, constraint, ...): constraints must be types."
self.__constraints__ = tuple(_type_check(t, msg) for t in constraints)
if bound:
self.__bound__ = _type_check(bound, "Bound must be a type.")
else:
self.__bound__ = None
return self
def _has_type_var(self):
return True
def __repr__(self):
if self.__covariant__:
prefix = '+'
elif self.__contravariant__:
prefix = '-'
else:
prefix = '~'
return prefix + self.__name__
def __instancecheck__(self, instance):
raise TypeError("Type variables cannot be used with isinstance().")
def __subclasscheck__(self, cls):
# TODO: Make this raise TypeError too?
if cls is self:
return True
if cls is Any:
return True
if self.__bound__ is not None:
return issubclass(cls, self.__bound__)
if self.__constraints__:
return any(issubclass(cls, c) for c in self.__constraints__)
return True
# Some unconstrained type variables. These are used by the container types.
T = TypeVar('T') # Any type.
KT = TypeVar('KT') # Key type.
VT = TypeVar('VT') # Value type.
T_co = TypeVar('T_co', covariant=True) # Any type covariant containers.
V_co = TypeVar('V_co', covariant=True) # Any type covariant containers.
VT_co = TypeVar('VT_co', covariant=True) # Value type covariant containers.
T_contra = TypeVar('T_contra', contravariant=True) # Ditto contravariant.
# A useful type variable with constraints. This represents string types.
# TODO: What about bytearray, memoryview?
AnyStr = TypeVar('AnyStr', bytes, str)
class UnionMeta(TypingMeta):
"""Metaclass for Union."""
def __new__(cls, name, bases, namespace, parameters=None, _root=False):
if parameters is None:
return super().__new__(cls, name, bases, namespace, _root=_root)
if not isinstance(parameters, tuple):
raise TypeError("Expected parameters=<tuple>")
# Flatten out Union[Union[...], ...] and type-check non-Union args.
params = []
msg = "Union[arg, ...]: each arg must be a type."
for p in parameters:
if isinstance(p, UnionMeta):
params.extend(p.__union_params__)
else:
params.append(_type_check(p, msg))
# Weed out strict duplicates, preserving the first of each occurrence.
all_params = set(params)
if len(all_params) < len(params):
new_params = []
for t in params:
if t in all_params:
new_params.append(t)
all_params.remove(t)
params = new_params
assert not all_params, all_params
# Weed out subclasses.
# E.g. Union[int, Employee, Manager] == Union[int, Employee].
# If Any or object is present it will be the sole survivor.
# If both Any and object are present, Any wins.
# Never discard type variables, except against Any.
# (In particular, Union[str, AnyStr] != AnyStr.)
all_params = set(params)
for t1 in params:
if t1 is Any:
return Any
if isinstance(t1, TypeVar):
continue
if any(issubclass(t1, t2)
for t2 in all_params - {t1} if not isinstance(t2, TypeVar)):
all_params.remove(t1)
# It's not a union if there's only one type left.
if len(all_params) == 1:
return all_params.pop()
# Create a new class with these params.
self = super().__new__(cls, name, bases, {}, _root=True)
self.__union_params__ = tuple(t for t in params if t in all_params)
self.__union_set_params__ = frozenset(self.__union_params__)
return self
def _eval_type(self, globalns, localns):
p = tuple(_eval_type(t, globalns, localns)
for t in self.__union_params__)
if p == self.__union_params__:
return self
else:
return self.__class__(self.__name__, self.__bases__, {},
p, _root=True)
def _has_type_var(self):
if self.__union_params__:
for t in self.__union_params__:
if _has_type_var(t):
return True
return False
def __repr__(self):
r = super().__repr__()
if self.__union_params__:
r += '[%s]' % (', '.join(_type_repr(t)
for t in self.__union_params__))
return r
def __getitem__(self, parameters):
if self.__union_params__ is not None:
raise TypeError(
"Cannot subscript an existing Union. Use Union[u, t] instead.")
if parameters == ():
raise TypeError("Cannot take a Union of no types.")
if not isinstance(parameters, tuple):
parameters = (parameters,)
return self.__class__(self.__name__, self.__bases__,
dict(self.__dict__), parameters, _root=True)
def __eq__(self, other):
if not isinstance(other, UnionMeta):
return NotImplemented
return self.__union_set_params__ == other.__union_set_params__
def __hash__(self):
return hash(self.__union_set_params__)
def __instancecheck__(self, obj):
raise TypeError("Unions cannot be used with isinstance().")
def __subclasscheck__(self, cls):
if cls is Any:
return True
if self.__union_params__ is None:
return isinstance(cls, UnionMeta)
elif isinstance(cls, UnionMeta):
if cls.__union_params__ is None:
return False
return all(issubclass(c, self) for c in (cls.__union_params__))
elif isinstance(cls, TypeVar):
if cls in self.__union_params__:
return True
if cls.__constraints__:
return issubclass(Union[cls.__constraints__], self)
return False
else:
return any(issubclass(cls, t) for t in self.__union_params__)
class Union(Final, metaclass=UnionMeta, _root=True):
"""Union type; Union[X, Y] means either X or Y.
To define a union, use e.g. Union[int, str]. Details:
- The arguments must be types and there must be at least one.
- None as an argument is a special case and is replaced by
type(None).
- Unions of unions are flattened, e.g.::
Union[Union[int, str], float] == Union[int, str, float]
- Unions of a single argument vanish, e.g.::
Union[int] == int # The constructor actually returns int
- Redundant arguments are skipped, e.g.::
Union[int, str, int] == Union[int, str]
- When comparing unions, the argument order is ignored, e.g.::
Union[int, str] == Union[str, int]
- When two arguments have a subclass relationship, the least
derived argument is kept, e.g.::
class Employee: pass
class Manager(Employee): pass
Union[int, Employee, Manager] == Union[int, Employee]
Union[Manager, int, Employee] == Union[int, Employee]
Union[Employee, Manager] == Employee
- Corollary: if Any is present it is the sole survivor, e.g.::
Union[int, Any] == Any
- Similar for object::
Union[int, object] == object
- To cut a tie: Union[object, Any] == Union[Any, object] == Any.
- You cannot subclass or instantiate a union.
- You cannot write Union[X][Y] (what would it mean?).
- You can use Optional[X] as a shorthand for Union[X, None].
"""
# Unsubscripted Union type has params set to None.
__union_params__ = None
__union_set_params__ = None
class OptionalMeta(TypingMeta):
"""Metaclass for Optional."""
def __new__(cls, name, bases, namespace, _root=False):
return super().__new__(cls, name, bases, namespace, _root=_root)
def __getitem__(self, arg):
arg = _type_check(arg, "Optional[t] requires a single type.")
return Union[arg, type(None)]
class Optional(Final, metaclass=OptionalMeta, _root=True):
"""Optional type.
Optional[X] is equivalent to Union[X, type(None)].
"""
__slots__ = ()
class TupleMeta(TypingMeta):
"""Metaclass for Tuple."""
def __new__(cls, name, bases, namespace, parameters=None,
use_ellipsis=False, _root=False):
self = super().__new__(cls, name, bases, namespace, _root=_root)
self.__tuple_params__ = parameters
self.__tuple_use_ellipsis__ = use_ellipsis
return self
def _has_type_var(self):
if self.__tuple_params__:
for t in self.__tuple_params__:
if _has_type_var(t):
return True
return False
def _eval_type(self, globalns, localns):
tp = self.__tuple_params__
if tp is None:
return self
p = tuple(_eval_type(t, globalns, localns) for t in tp)
if p == self.__tuple_params__:
return self
else:
return self.__class__(self.__name__, self.__bases__, {},
p, _root=True)
def __repr__(self):
r = super().__repr__()
if self.__tuple_params__ is not None:
params = [_type_repr(p) for p in self.__tuple_params__]
if self.__tuple_use_ellipsis__:
params.append('...')
r += '[%s]' % (
', '.join(params))
return r
def __getitem__(self, parameters):
if self.__tuple_params__ is not None:
raise TypeError("Cannot re-parameterize %r" % (self,))
if not isinstance(parameters, tuple):
parameters = (parameters,)
if len(parameters) == 2 and parameters[1] == Ellipsis:
parameters = parameters[:1]
use_ellipsis = True
msg = "Tuple[t, ...]: t must be a type."
else:
use_ellipsis = False
msg = "Tuple[t0, t1, ...]: each t must be a type."
parameters = tuple(_type_check(p, msg) for p in parameters)
return self.__class__(self.__name__, self.__bases__,
dict(self.__dict__), parameters,
use_ellipsis=use_ellipsis, _root=True)
def __eq__(self, other):
if not isinstance(other, TupleMeta):
return NotImplemented
return self.__tuple_params__ == other.__tuple_params__
def __hash__(self):
return hash(self.__tuple_params__)
def __instancecheck__(self, obj):
raise TypeError("Tuples cannot be used with isinstance().")
def __subclasscheck__(self, cls):
if cls is Any:
return True
if not isinstance(cls, type):
return super().__subclasscheck__(cls) # To TypeError.
if issubclass(cls, tuple):
return True # Special case.
if not isinstance(cls, TupleMeta):
return super().__subclasscheck__(cls) # False.
if self.__tuple_params__ is None:
return True
if cls.__tuple_params__ is None:
return False # ???
if cls.__tuple_use_ellipsis__ != self.__tuple_use_ellipsis__:
return False
# Covariance.
return (len(self.__tuple_params__) == len(cls.__tuple_params__) and
all(issubclass(x, p)
for x, p in zip(cls.__tuple_params__,
self.__tuple_params__)))
class Tuple(Final, metaclass=TupleMeta, _root=True):
"""Tuple type; Tuple[X, Y] is the cross-product type of X and Y.
Example: Tuple[T1, T2] is a tuple of two elements corresponding
to type variables T1 and T2. Tuple[int, float, str] is a tuple
of an int, a float and a string.
To specify a variable-length tuple of homogeneous type, use Sequence[T].
"""
__slots__ = ()
class CallableMeta(TypingMeta):
"""Metaclass for Callable."""
def __new__(cls, name, bases, namespace, _root=False,
args=None, result=None):
if args is None and result is None:
pass # Must be 'class Callable'.
else:
if args is not Ellipsis:
if not isinstance(args, list):
raise TypeError("Callable[args, result]: "
"args must be a list."
" Got %.100r." % (args,))
msg = "Callable[[arg, ...], result]: each arg must be a type."
args = tuple(_type_check(arg, msg) for arg in args)
msg = "Callable[args, result]: result must be a type."
result = _type_check(result, msg)
self = super().__new__(cls, name, bases, namespace, _root=_root)
self.__args__ = args
self.__result__ = result
return self
def _has_type_var(self):
if self.__args__:
for t in self.__args__:
if _has_type_var(t):
return True
return _has_type_var(self.__result__)
def _eval_type(self, globalns, localns):
if self.__args__ is None and self.__result__ is None:
return self
if self.__args__ is Ellipsis:
args = self.__args__
else:
args = [_eval_type(t, globalns, localns) for t in self.__args__]
result = _eval_type(self.__result__, globalns, localns)
if args == self.__args__ and result == self.__result__:
return self
else:
return self.__class__(self.__name__, self.__bases__, {},
args=args, result=result, _root=True)
def __repr__(self):
r = super().__repr__()
if self.__args__ is not None or self.__result__ is not None:
if self.__args__ is Ellipsis:
args_r = '...'
else:
args_r = '[%s]' % ', '.join(_type_repr(t)
for t in self.__args__)
r += '[%s, %s]' % (args_r, _type_repr(self.__result__))
return r
def __getitem__(self, parameters):
if self.__args__ is not None or self.__result__ is not None:
raise TypeError("This Callable type is already parameterized.")
if not isinstance(parameters, tuple) or len(parameters) != 2:
raise TypeError(
"Callable must be used as Callable[[arg, ...], result].")
args, result = parameters
return self.__class__(self.__name__, self.__bases__,
dict(self.__dict__), _root=True,
args=args, result=result)
def __eq__(self, other):
if not isinstance(other, CallableMeta):
return NotImplemented
return (self.__args__ == other.__args__ and
self.__result__ == other.__result__)
def __hash__(self):
return hash(self.__args__) ^ hash(self.__result__)
def __instancecheck__(self, obj):
# For unparametrized Callable we allow this, because
# typing.Callable should be equivalent to
# collections.abc.Callable.
if self.__args__ is None and self.__result__ is None:
return isinstance(obj, collections_abc.Callable)
else:
raise TypeError("Callable[] cannot be used with isinstance().")
def __subclasscheck__(self, cls):
if cls is Any:
return True
if not isinstance(cls, CallableMeta):
return super().__subclasscheck__(cls)
if self.__args__ is None and self.__result__ is None:
return True
# We're not doing covariance or contravariance -- this is *invariance*.
return self == cls
class Callable(Final, metaclass=CallableMeta, _root=True):
"""Callable type; Callable[[int], str] is a function of (int) -> str.
The subscription syntax must always be used with exactly two
values: the argument list and the return type. The argument list
must be a list of types; the return type must be a single type.
There is no syntax to indicate optional or keyword arguments,
such function types are rarely used as callback types.
"""
__slots__ = ()
def _gorg(a):
"""Return the farthest origin of a generic class."""
assert isinstance(a, GenericMeta)
while a.__origin__ is not None:
a = a.__origin__
return a
def _geqv(a, b):
"""Return whether two generic classes are equivalent.
The intention is to consider generic class X and any of its
parameterized forms (X[T], X[int], etc.) as equivalent.
However, X is not equivalent to a subclass of X.
The relation is reflexive, symmetric and transitive.
"""
assert isinstance(a, GenericMeta) and isinstance(b, GenericMeta)
# Reduce each to its origin.
return _gorg(a) is _gorg(b)
class GenericMeta(TypingMeta, abc.ABCMeta):
"""Metaclass for generic types."""
# TODO: Constrain more how Generic is used; only a few
# standard patterns should be allowed.
# TODO: Use a more precise rule than matching __name__ to decide
# whether two classes are the same. Also, save the formal
# parameters. (These things are related! A solution lies in
# using origin.)
__extra__ = None
def __new__(cls, name, bases, namespace,
parameters=None, origin=None, extra=None):
if parameters is None:
# Extract parameters from direct base classes. Only
# direct bases are considered and only those that are
# themselves generic, and parameterized with type
# variables. Don't use bases like Any, Union, Tuple,
# Callable or type variables.
params = None
for base in bases:
if isinstance(base, TypingMeta):
if not isinstance(base, GenericMeta):
raise TypeError(
"You cannot inherit from magic class %s" %
repr(base))
if base.__parameters__ is None:
continue # The base is unparameterized.
for bp in base.__parameters__:
if _has_type_var(bp) and not isinstance(bp, TypeVar):
raise TypeError(
"Cannot inherit from a generic class "
"parameterized with "
"non-type-variable %s" % bp)
if params is None:
params = []
if bp not in params:
params.append(bp)
if params is not None:
parameters = tuple(params)
self = super().__new__(cls, name, bases, namespace, _root=True)
self.__parameters__ = parameters
if extra is not None:
self.__extra__ = extra
# Else __extra__ is inherited, eventually from the
# (meta-)class default above.
self.__origin__ = origin
return self
def _has_type_var(self):
if self.__parameters__:
for t in self.__parameters__:
if _has_type_var(t):
return True
return False
def __repr__(self):
r = super().__repr__()
if self.__parameters__ is not None:
r += '[%s]' % (
', '.join(_type_repr(p) for p in self.__parameters__))
return r
def __eq__(self, other):
if not isinstance(other, GenericMeta):
return NotImplemented
return (_geqv(self, other) and
self.__parameters__ == other.__parameters__)
def __hash__(self):
return hash((self.__name__, self.__parameters__))
def __getitem__(self, params):
if not isinstance(params, tuple):
params = (params,)
if not params:
raise TypeError("Cannot have empty parameter list")
msg = "Parameters to generic types must be types."
params = tuple(_type_check(p, msg) for p in params)
if self.__parameters__ is None:
for p in params:
if not isinstance(p, TypeVar):
raise TypeError("Initial parameters must be "
"type variables; got %s" % p)
if len(set(params)) != len(params):
raise TypeError(
"All type variables in Generic[...] must be distinct.")
else:
if len(params) != len(self.__parameters__):
raise TypeError("Cannot change parameter count from %d to %d" %
(len(self.__parameters__), len(params)))
for new, old in zip(params, self.__parameters__):
if isinstance(old, TypeVar):
if not old.__constraints__:
# Substituting for an unconstrained TypeVar is OK.
continue
if issubclass(new, Union[old.__constraints__]):
# Specializing a constrained type variable is OK.
continue
if not issubclass(new, old):
raise TypeError(
"Cannot substitute %s for %s in %s" %
(_type_repr(new), _type_repr(old), self))
return self.__class__(self.__name__, self.__bases__,
dict(self.__dict__),
parameters=params,
origin=self,
extra=self.__extra__)
def __instancecheck__(self, instance):
# Since we extend ABC.__subclasscheck__ and
# ABC.__instancecheck__ inlines the cache checking done by the
# latter, we must extend __instancecheck__ too. For simplicity
# we just skip the cache check -- instance checks for generic
# classes are supposed to be rare anyways.
return self.__subclasscheck__(instance.__class__)
def __subclasscheck__(self, cls):
if cls is Any:
return True
if isinstance(cls, GenericMeta):
# For a class C(Generic[T]) where T is co-variant,
# C[X] is a subclass of C[Y] iff X is a subclass of Y.
origin = self.__origin__
if origin is not None and origin is cls.__origin__:
assert len(self.__parameters__) == len(origin.__parameters__)
assert len(cls.__parameters__) == len(origin.__parameters__)
for p_self, p_cls, p_origin in zip(self.__parameters__,
cls.__parameters__,
origin.__parameters__):
if isinstance(p_origin, TypeVar):
if p_origin.__covariant__:
# Covariant -- p_cls must be a subclass of p_self.
if not issubclass(p_cls, p_self):
break
elif p_origin.__contravariant__:
# Contravariant. I think it's the opposite. :-)
if not issubclass(p_self, p_cls):
break
else:
# Invariant -- p_cls and p_self must equal.
if p_self != p_cls:
break
else:
# If the origin's parameter is not a typevar,
# insist on invariance.
if p_self != p_cls:
break
else:
return True
# If we break out of the loop, the superclass gets a chance.
if super().__subclasscheck__(cls):
return True
if self.__extra__ is None or isinstance(cls, GenericMeta):
return False
return issubclass(cls, self.__extra__)
class Generic(metaclass=GenericMeta):
"""Abstract base class for generic types.
A generic type is typically declared by inheriting from an
instantiation of this class with one or more type variables.
For example, a generic mapping type might be defined as::
class Mapping(Generic[KT, VT]):
def __getitem__(self, key: KT) -> VT:
...
# Etc.
This class can then be used as follows::
def lookup_name(mapping: Mapping, key: KT, default: VT) -> VT:
try:
return mapping[key]
except KeyError:
return default
For clarity the type variables may be redefined, e.g.::
X = TypeVar('X')
Y = TypeVar('Y')
def lookup_name(mapping: Mapping[X, Y], key: X, default: Y) -> Y:
# Same body as above.
"""
__slots__ = ()
def __new__(cls, *args, **kwds):
next_in_mro = object
# Look for the last occurrence of Generic or Generic[...].
for i, c in enumerate(cls.__mro__[:-1]):
if isinstance(c, GenericMeta) and _gorg(c) is Generic:
next_in_mro = cls.__mro__[i+1]
return next_in_mro.__new__(_gorg(cls))
def cast(typ, val):
"""Cast a value to a type.
This returns the value unchanged. To the type checker this
signals that the return value has the designated type, but at
runtime we intentionally don't check anything (we want this
to be as fast as possible).
"""
return val
def _get_defaults(func):
"""Internal helper to extract the default arguments, by name."""
code = func.__code__
pos_count = code.co_argcount
kw_count = code.co_kwonlyargcount
arg_names = code.co_varnames
kwarg_names = arg_names[pos_count:pos_count + kw_count]
arg_names = arg_names[:pos_count]
defaults = func.__defaults__ or ()
kwdefaults = func.__kwdefaults__
res = dict(kwdefaults) if kwdefaults else {}
pos_offset = pos_count - len(defaults)
for name, value in zip(arg_names[pos_offset:], defaults):
assert name not in res
res[name] = value
return res
def get_type_hints(obj, globalns=None, localns=None):
"""Return type hints for a function or method object.
This is often the same as obj.__annotations__, but it handles
forward references encoded as string literals, and if necessary
adds Optional[t] if a default value equal to None is set.
BEWARE -- the behavior of globalns and localns is counterintuitive
(unless you are familiar with how eval() and exec() work). The
search order is locals first, then globals.
- If no dict arguments are passed, an attempt is made to use the
globals from obj, and these are also used as the locals. If the
object does not appear to have globals, an exception is raised.
- If one dict argument is passed, it is used for both globals and
locals.
- If two dict arguments are passed, they specify globals and
locals, respectively.
"""
if getattr(obj, '__no_type_check__', None):
return {}
if globalns is None:
globalns = getattr(obj, '__globals__', {})
if localns is None:
localns = globalns
elif localns is None:
localns = globalns
defaults = _get_defaults(obj)
hints = dict(obj.__annotations__)
for name, value in hints.items():
if isinstance(value, str):
value = _ForwardRef(value)
value = _eval_type(value, globalns, localns)
if name in defaults and defaults[name] is None:
value = Optional[value]
hints[name] = value
return hints
# TODO: Also support this as a class decorator.
def no_type_check(arg):
"""Decorator to indicate that annotations are not type hints.
The argument must be a class or function; if it is a class, it
applies recursively to all methods defined in that class (but not
to methods defined in its superclasses or subclasses).
This mutates the function(s) in place.
"""
if isinstance(arg, type):
for obj in arg.__dict__.values():
if isinstance(obj, types.FunctionType):
obj.__no_type_check__ = True
else:
arg.__no_type_check__ = True
return arg
def no_type_check_decorator(decorator):
"""Decorator to give another decorator the @no_type_check effect.
This wraps the decorator with something that wraps the decorated
function in @no_type_check.
"""
@functools.wraps(decorator)
def wrapped_decorator(*args, **kwds):
func = decorator(*args, **kwds)
func = no_type_check(func)
return func
return wrapped_decorator
def overload(func):
raise RuntimeError("Overloading is only supported in library stubs")
class _ProtocolMeta(GenericMeta):
"""Internal metaclass for _Protocol.
This exists so _Protocol classes can be generic without deriving
from Generic.
"""
def __instancecheck__(self, obj):
raise TypeError("Protocols cannot be used with isinstance().")
def __subclasscheck__(self, cls):
if not self._is_protocol:
# No structural checks since this isn't a protocol.
return NotImplemented
if self is _Protocol:
# Every class is a subclass of the empty protocol.
return True
# Find all attributes defined in the protocol.
attrs = self._get_protocol_attrs()
for attr in attrs:
if not any(attr in d.__dict__ for d in cls.__mro__):
return False
return True
def _get_protocol_attrs(self):
# Get all Protocol base classes.
protocol_bases = []
for c in self.__mro__:
if getattr(c, '_is_protocol', False) and c.__name__ != '_Protocol':
protocol_bases.append(c)
# Get attributes included in protocol.
attrs = set()
for base in protocol_bases:
for attr in base.__dict__.keys():
# Include attributes not defined in any non-protocol bases.
for c in self.__mro__:
if (c is not base and attr in c.__dict__ and
not getattr(c, '_is_protocol', False)):
break
else:
if (not attr.startswith('_abc_') and
attr != '__abstractmethods__' and
attr != '_is_protocol' and
attr != '__dict__' and
attr != '__slots__' and
attr != '_get_protocol_attrs' and
attr != '__parameters__' and
attr != '__origin__' and
attr != '__module__'):
attrs.add(attr)
return attrs
class _Protocol(metaclass=_ProtocolMeta):
"""Internal base class for protocol classes.
This implements a simple-minded structural isinstance check
(similar but more general than the one-offs in collections.abc
such as Hashable).
"""
__slots__ = ()
_is_protocol = True
# Various ABCs mimicking those in collections.abc.
# A few are simply re-exported for completeness.
Hashable = collections_abc.Hashable # Not generic.
class Iterable(Generic[T_co], extra=collections_abc.Iterable):
__slots__ = ()
class Iterator(Iterable[T_co], extra=collections_abc.Iterator):
__slots__ = ()
class SupportsInt(_Protocol):
__slots__ = ()
@abstractmethod
def __int__(self) -> int:
pass
class SupportsFloat(_Protocol):
__slots__ = ()
@abstractmethod
def __float__(self) -> float:
pass
class SupportsComplex(_Protocol):
__slots__ = ()
@abstractmethod
def __complex__(self) -> complex:
pass
class SupportsBytes(_Protocol):
__slots__ = ()
@abstractmethod
def __bytes__(self) -> bytes:
pass
class SupportsAbs(_Protocol[T_co]):
__slots__ = ()
@abstractmethod
def __abs__(self) -> T_co:
pass
class SupportsRound(_Protocol[T_co]):
__slots__ = ()
@abstractmethod
def __round__(self, ndigits: int = 0) -> T_co:
pass
class Reversible(_Protocol[T_co]):
__slots__ = ()
@abstractmethod
def __reversed__(self) -> 'Iterator[T_co]':
pass
Sized = collections_abc.Sized # Not generic.
class Container(Generic[T_co], extra=collections_abc.Container):
__slots__ = ()
# Callable was defined earlier.
class AbstractSet(Sized, Iterable[T_co], Container[T_co],
extra=collections_abc.Set):
pass
class MutableSet(AbstractSet[T], extra=collections_abc.MutableSet):
pass
# NOTE: Only the value type is covariant.
class Mapping(Sized, Iterable[KT], Container[KT], Generic[VT_co],
extra=collections_abc.Mapping):
pass
class MutableMapping(Mapping[KT, VT], extra=collections_abc.MutableMapping):
pass
class Sequence(Sized, Iterable[T_co], Container[T_co],
extra=collections_abc.Sequence):
pass
class MutableSequence(Sequence[T], extra=collections_abc.MutableSequence):
pass
class ByteString(Sequence[int], extra=collections_abc.ByteString):
pass
ByteString.register(type(memoryview(b'')))
class List(list, MutableSequence[T]):
def __new__(cls, *args, **kwds):
if _geqv(cls, List):
raise TypeError("Type List cannot be instantiated; "
"use list() instead")
return list.__new__(cls, *args, **kwds)
class Set(set, MutableSet[T]):
def __new__(cls, *args, **kwds):
if _geqv(cls, Set):
raise TypeError("Type Set cannot be instantiated; "
"use set() instead")
return set.__new__(cls, *args, **kwds)
class _FrozenSetMeta(GenericMeta):
"""This metaclass ensures set is not a subclass of FrozenSet.
Without this metaclass, set would be considered a subclass of
FrozenSet, because FrozenSet.__extra__ is collections.abc.Set, and
set is a subclass of that.
"""
def __subclasscheck__(self, cls):
if issubclass(cls, Set):
return False
return super().__subclasscheck__(cls)
class FrozenSet(frozenset, AbstractSet[T_co], metaclass=_FrozenSetMeta):
__slots__ = ()
def __new__(cls, *args, **kwds):
if _geqv(cls, FrozenSet):
raise TypeError("Type FrozenSet cannot be instantiated; "
"use frozenset() instead")
return frozenset.__new__(cls, *args, **kwds)
class MappingView(Sized, Iterable[T_co], extra=collections_abc.MappingView):
pass
class KeysView(MappingView[KT], AbstractSet[KT],
extra=collections_abc.KeysView):
pass
# TODO: Enable Set[Tuple[KT, VT_co]] instead of Generic[KT, VT_co].
class ItemsView(MappingView, Generic[KT, VT_co],
extra=collections_abc.ItemsView):
pass
class ValuesView(MappingView[VT_co], extra=collections_abc.ValuesView):
pass
class Dict(dict, MutableMapping[KT, VT]):
def __new__(cls, *args, **kwds):
if _geqv(cls, Dict):
raise TypeError("Type Dict cannot be instantiated; "
"use dict() instead")
return dict.__new__(cls, *args, **kwds)
# Determine what base class to use for Generator.
if hasattr(collections_abc, 'Generator'):
# Sufficiently recent versions of 3.5 have a Generator ABC.
_G_base = collections_abc.Generator
else:
# Fall back on the exact type.
_G_base = types.GeneratorType
class Generator(Iterator[T_co], Generic[T_co, T_contra, V_co],
extra=_G_base):
__slots__ = ()
def __new__(cls, *args, **kwds):
if _geqv(cls, Generator):
raise TypeError("Type Generator cannot be instantiated; "
"create a subclass instead")
return super().__new__(cls, *args, **kwds)
def NamedTuple(typename, fields):
"""Typed version of namedtuple.
Usage::
Employee = typing.NamedTuple('Employee', [('name', str), 'id', int)])
This is equivalent to::
Employee = collections.namedtuple('Employee', ['name', 'id'])
The resulting class has one extra attribute: _field_types,
giving a dict mapping field names to types. (The field names
are in the _fields attribute, which is part of the namedtuple
API.)
"""
fields = [(n, t) for n, t in fields]
cls = collections.namedtuple(typename, [n for n, t in fields])
cls._field_types = dict(fields)
return cls
class IO(Generic[AnyStr]):
"""Generic base class for TextIO and BinaryIO.
This is an abstract, generic version of the return of open().
NOTE: This does not distinguish between the different possible
classes (text vs. binary, read vs. write vs. read/write,
append-only, unbuffered). The TextIO and BinaryIO subclasses
below capture the distinctions between text vs. binary, which is
pervasive in the interface; however we currently do not offer a
way to track the other distinctions in the type system.
"""
__slots__ = ()
@abstractproperty
def mode(self) -> str:
pass
@abstractproperty
def name(self) -> str:
pass
@abstractmethod
def close(self) -> None:
pass
@abstractmethod
def closed(self) -> bool:
pass
@abstractmethod
def fileno(self) -> int:
pass
@abstractmethod
def flush(self) -> None:
pass
@abstractmethod
def isatty(self) -> bool:
pass
@abstractmethod
def read(self, n: int = -1) -> AnyStr:
pass
@abstractmethod
def readable(self) -> bool:
pass
@abstractmethod
def readline(self, limit: int = -1) -> AnyStr:
pass
@abstractmethod
def readlines(self, hint: int = -1) -> List[AnyStr]:
pass
@abstractmethod
def seek(self, offset: int, whence: int = 0) -> int:
pass
@abstractmethod
def seekable(self) -> bool:
pass
@abstractmethod
def tell(self) -> int:
pass
@abstractmethod
def truncate(self, size: int = None) -> int:
pass
@abstractmethod
def writable(self) -> bool:
pass
@abstractmethod
def write(self, s: AnyStr) -> int:
pass
@abstractmethod
def writelines(self, lines: List[AnyStr]) -> None:
pass
@abstractmethod
def __enter__(self) -> 'IO[AnyStr]':
pass
@abstractmethod
def __exit__(self, type, value, traceback) -> None:
pass
class BinaryIO(IO[bytes]):
"""Typed version of the return of open() in binary mode."""
__slots__ = ()
@abstractmethod
def write(self, s: Union[bytes, bytearray]) -> int:
pass
@abstractmethod
def __enter__(self) -> 'BinaryIO':
pass
class TextIO(IO[str]):
"""Typed version of the return of open() in text mode."""
__slots__ = ()
@abstractproperty
def buffer(self) -> BinaryIO:
pass
@abstractproperty
def encoding(self) -> str:
pass
@abstractproperty
def errors(self) -> str:
pass
@abstractproperty
def line_buffering(self) -> bool:
pass
@abstractproperty
def newlines(self) -> Any:
pass
@abstractmethod
def __enter__(self) -> 'TextIO':
pass
class io:
"""Wrapper namespace for IO generic classes."""
__all__ = ['IO', 'TextIO', 'BinaryIO']
IO = IO
TextIO = TextIO
BinaryIO = BinaryIO
io.__name__ = __name__ + '.io'
sys.modules[io.__name__] = io
Pattern = _TypeAlias('Pattern', AnyStr, type(stdlib_re.compile('')),
lambda p: p.pattern)
Match = _TypeAlias('Match', AnyStr, type(stdlib_re.match('', '')),
lambda m: m.re.pattern)
class re:
"""Wrapper namespace for re type aliases."""
__all__ = ['Pattern', 'Match']
Pattern = Pattern
Match = Match
re.__name__ = __name__ + '.re'
sys.modules[re.__name__] = re
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