traverseda
/
cpython
1
0
Fork 0
Code Issues Pull Requests Releases Wiki Activity
cpython/Lib/typing.py

2011 lines
67 KiB
Python
Raw Blame History

"""
The typing module: Support for gradual typing as defined by PEP 484.
At large scale, the structure of the module is following:
* Imports and exports, all public names should be explicitly added to __all__.
* Internal helper functions: these should never be used in code outside this module.
* _SpecialForm and its instances (special forms): Any, NoReturn, ClassVar, Union, Optional
* Two classes whose instances can be type arguments in addition to types: ForwardRef and TypeVar
* The core of internal generics API: _GenericAlias and _VariadicGenericAlias, the latter is
currently only used by Tuple and Callable. All subscripted types like X[int], Union[int, str],
etc., are instances of either of these classes.
* The public counterpart of the generics API consists of two classes: Generic and Protocol.
* Public helper functions: get_type_hints, overload, cast, no_type_check,
no_type_check_decorator.
* Generic aliases for collections.abc ABCs and few additional protocols.
* Special types: NewType, NamedTuple, TypedDict.
* Wrapper submodules for re and io related types.
"""
from abc import abstractmethod, ABCMeta
import collections
import collections.abc
import contextlib
import functools
import operator
import re as stdlib_re # Avoid confusion with the re we export.
import sys
import types
from types import WrapperDescriptorType, MethodWrapperType, MethodDescriptorType
# Please keep __all__ alphabetized within each category.
__all__ = [
# Super-special typing primitives.
'Any',
'Callable',
'ClassVar',
'Final',
'ForwardRef',
'Generic',
'Literal',
'Optional',
'Protocol',
'Tuple',
'Type',
'TypeVar',
'Union',
# ABCs (from collections.abc).
'AbstractSet', # collections.abc.Set.
'ByteString',
'Container',
'ContextManager',
'Hashable',
'ItemsView',
'Iterable',
'Iterator',
'KeysView',
'Mapping',
'MappingView',
'MutableMapping',
'MutableSequence',
'MutableSet',
'Sequence',
'Sized',
'ValuesView',
'Awaitable',
'AsyncIterator',
'AsyncIterable',
'Coroutine',
'Collection',
'AsyncGenerator',
'AsyncContextManager',
# Structural checks, a.k.a. protocols.
'Reversible',
'SupportsAbs',
'SupportsBytes',
'SupportsComplex',
'SupportsFloat',
'SupportsIndex',
'SupportsInt',
'SupportsRound',
# Concrete collection types.
'ChainMap',
'Counter',
'Deque',
'Dict',
'DefaultDict',
'List',
'OrderedDict',
'Set',
'FrozenSet',
'NamedTuple', # Not really a type.
'TypedDict', # Not really a type.
'Generator',
# One-off things.
'AnyStr',
'cast',
'final',
'get_args',
'get_origin',
'get_type_hints',
'NewType',
'no_type_check',
'no_type_check_decorator',
'NoReturn',
'overload',
'runtime_checkable',
'Text',
'TYPE_CHECKING',
]
# The pseudo-submodules 're' and 'io' are part of the public
# namespace, but excluded from __all__ because they might stomp on
# legitimate imports of those modules.
def _type_check(arg, msg, is_argument=True):
"""Check that the argument is a type, and return it (internal helper).
As a special case, accept None and return type(None) instead. Also wrap strings
into ForwardRef instances. Consider several corner cases, for example plain
special forms like Union are not valid, while Union[int, str] is OK, etc.
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).
"""
invalid_generic_forms = (Generic, Protocol)
if is_argument:
invalid_generic_forms = invalid_generic_forms + (ClassVar, Final)
if arg is None:
return type(None)
if isinstance(arg, str):
return ForwardRef(arg)
if (isinstance(arg, _GenericAlias) and
arg.__origin__ in invalid_generic_forms):
raise TypeError(f"{arg} is not valid as type argument")
if (isinstance(arg, _SpecialForm) and arg not in (Any, NoReturn) or
arg in (Generic, Protocol)):
raise TypeError(f"Plain {arg} is not valid as type argument")
if isinstance(arg, (type, TypeVar, ForwardRef)):
return arg
if not callable(arg):
raise TypeError(f"{msg} Got {arg!r:.100}.")
return arg
def _type_repr(obj):
"""Return the repr() of an object, special-casing types (internal helper).
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):
if obj.__module__ == 'builtins':
return obj.__qualname__
return f'{obj.__module__}.{obj.__qualname__}'
if obj is ...:
return('...')
if isinstance(obj, types.FunctionType):
return obj.__name__
return repr(obj)
def _collect_type_vars(types):
"""Collect all type variable contained in types in order of
first appearance (lexicographic order). For example::
_collect_type_vars((T, List[S, T])) == (T, S)
"""
tvars = []
for t in types:
if isinstance(t, TypeVar) and t not in tvars:
tvars.append(t)
if isinstance(t, _GenericAlias) and not t._special:
tvars.extend([t for t in t.__parameters__ if t not in tvars])
return tuple(tvars)
def _subs_tvars(tp, tvars, subs):
"""Substitute type variables 'tvars' with substitutions 'subs'.
These two must have the same length.
"""
if not isinstance(tp, _GenericAlias):
return tp
new_args = list(tp.__args__)
for a, arg in enumerate(tp.__args__):
if isinstance(arg, TypeVar):
for i, tvar in enumerate(tvars):
if arg == tvar:
new_args[a] = subs[i]
else:
new_args[a] = _subs_tvars(arg, tvars, subs)
if tp.__origin__ is Union:
return Union[tuple(new_args)]
return tp.copy_with(tuple(new_args))
def _check_generic(cls, parameters):
"""Check correct count for parameters of a generic cls (internal helper).
This gives a nice error message in case of count mismatch.
"""
if not cls.__parameters__:
raise TypeError(f"{cls} is not a generic class")
alen = len(parameters)
elen = len(cls.__parameters__)
if alen != elen:
raise TypeError(f"Too {'many' if alen > elen else 'few'} parameters for {cls};"
f" actual {alen}, expected {elen}")
def _remove_dups_flatten(parameters):
"""An internal helper for Union creation and substitution: flatten Unions
among parameters, then remove duplicates.
"""
# Flatten out Union[Union[...], ...].
params = []
for p in parameters:
if isinstance(p, _GenericAlias) and p.__origin__ is Union:
params.extend(p.__args__)
elif isinstance(p, tuple) and len(p) > 0 and p[0] is Union:
params.extend(p[1:])
else:
params.append(p)
# 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
return tuple(params)
_cleanups = []
def _tp_cache(func):
"""Internal wrapper caching __getitem__ of generic types with a fallback to
original function for non-hashable arguments.
"""
cached = functools.lru_cache()(func)
_cleanups.append(cached.cache_clear)
@functools.wraps(func)
def inner(*args, **kwds):
try:
return cached(*args, **kwds)
except TypeError:
pass # All real errors (not unhashable args) are raised below.
return func(*args, **kwds)
return inner
def _eval_type(t, globalns, localns):
"""Evaluate all forward references in the given type t.
For use of globalns and localns see the docstring for get_type_hints().
"""
if isinstance(t, ForwardRef):
return t._evaluate(globalns, localns)
if isinstance(t, _GenericAlias):
ev_args = tuple(_eval_type(a, globalns, localns) for a in t.__args__)
if ev_args == t.__args__:
return t
res = t.copy_with(ev_args)
res._special = t._special
return res
return t
class _Final:
"""Mixin to prohibit subclassing"""
__slots__ = ('__weakref__',)
def __init_subclass__(self, /, *args, **kwds):
if '_root' not in kwds:
raise TypeError("Cannot subclass special typing classes")
class _Immutable:
"""Mixin to indicate that object should not be copied."""
def __copy__(self):
return self
def __deepcopy__(self, memo):
return self
class _SpecialForm(_Final, _Immutable, _root=True):
"""Internal indicator of special typing constructs.
See _doc instance attribute for specific docs.
"""
__slots__ = ('_name', '_doc')
def __new__(cls, *args, **kwds):
"""Constructor.
This only exists to give a better error message in case
someone tries to subclass a special typing object (not a good idea).
"""
if (len(args) == 3 and
isinstance(args[0], str) and
isinstance(args[1], tuple)):
# Close enough.
raise TypeError(f"Cannot subclass {cls!r}")
return super().__new__(cls)
def __init__(self, name, doc):
self._name = name
self._doc = doc
def __eq__(self, other):
if not isinstance(other, _SpecialForm):
return NotImplemented
return self._name == other._name
def __hash__(self):
return hash((self._name,))
def __repr__(self):
return 'typing.' + self._name
def __reduce__(self):
return self._name
def __call__(self, *args, **kwds):
raise TypeError(f"Cannot instantiate {self!r}")
def __instancecheck__(self, obj):
raise TypeError(f"{self} cannot be used with isinstance()")
def __subclasscheck__(self, cls):
raise TypeError(f"{self} cannot be used with issubclass()")
@_tp_cache
def __getitem__(self, parameters):
if self._name in ('ClassVar', 'Final'):
item = _type_check(parameters, f'{self._name} accepts only single type.')
return _GenericAlias(self, (item,))
if self._name == 'Union':
if parameters == ():
raise TypeError("Cannot take a Union of no types.")
if not isinstance(parameters, tuple):
parameters = (parameters,)
msg = "Union[arg, ...]: each arg must be a type."
parameters = tuple(_type_check(p, msg) for p in parameters)
parameters = _remove_dups_flatten(parameters)
if len(parameters) == 1:
return parameters[0]
return _GenericAlias(self, parameters)
if self._name == 'Optional':
arg = _type_check(parameters, "Optional[t] requires a single type.")
return Union[arg, type(None)]
if self._name == 'Literal':
# There is no '_type_check' call because arguments to Literal[...] are
# values, not types.
return _GenericAlias(self, parameters)
raise TypeError(f"{self} is not subscriptable")
Any = _SpecialForm('Any', doc=
"""Special type indicating an unconstrained type.
- Any is compatible with every type.
- Any assumed to have all methods.
- All values assumed to be instances of Any.
Note that all the above statements are true from the point of view of
static type checkers. At runtime, Any should not be used with instance
or class checks.
""")
NoReturn = _SpecialForm('NoReturn', doc=
"""Special type indicating functions that never return.
Example::
from typing import NoReturn
def stop() -> NoReturn:
raise Exception('no way')
This type is invalid in other positions, e.g., ``List[NoReturn]``
will fail in static type checkers.
""")
ClassVar = _SpecialForm('ClassVar', doc=
"""Special type construct to mark class variables.
An annotation wrapped in ClassVar indicates that a given
attribute is intended to be used as a class variable and
should not be set on instances of that class. Usage::
class Starship:
stats: ClassVar[Dict[str, int]] = {} # class variable
damage: int = 10 # instance variable
ClassVar accepts only types and cannot be further subscribed.
Note that ClassVar is not a class itself, and should not
be used with isinstance() or issubclass().
""")
Final = _SpecialForm('Final', doc=
"""Special typing construct to indicate final names to type checkers.
A final name cannot be re-assigned or overridden in a subclass.
For example:
MAX_SIZE: Final = 9000
MAX_SIZE += 1 # Error reported by type checker
class Connection:
TIMEOUT: Final[int] = 10
class FastConnector(Connection):
TIMEOUT = 1 # Error reported by type checker
There is no runtime checking of these properties.
""")
Union = _SpecialForm('Union', doc=
"""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]
- You cannot subclass or instantiate a union.
- You can use Optional[X] as a shorthand for Union[X, None].
""")
Optional = _SpecialForm('Optional', doc=
"""Optional type.
Optional[X] is equivalent to Union[X, None].
""")
Literal = _SpecialForm('Literal', doc=
"""Special typing form to define literal types (a.k.a. value types).
This form can be used to indicate to type checkers that the corresponding
variable or function parameter has a value equivalent to the provided
literal (or one of several literals):
def validate_simple(data: Any) -> Literal[True]: # always returns True
...
MODE = Literal['r', 'rb', 'w', 'wb']
def open_helper(file: str, mode: MODE) -> str:
...
open_helper('/some/path', 'r') # Passes type check
open_helper('/other/path', 'typo') # Error in type checker
Literal[...] cannot be subclassed. At runtime, an arbitrary value
is allowed as type argument to Literal[...], but type checkers may
impose restrictions.
""")
class ForwardRef(_Final, _root=True):
"""Internal wrapper to hold a forward reference."""
__slots__ = ('__forward_arg__', '__forward_code__',
'__forward_evaluated__', '__forward_value__',
'__forward_is_argument__')
def __init__(self, arg, is_argument=True):
if not isinstance(arg, str):
raise TypeError(f"Forward reference must be a string -- got {arg!r}")
try:
code = compile(arg, '<string>', 'eval')
except SyntaxError:
raise SyntaxError(f"Forward reference must be an expression -- got {arg!r}")
self.__forward_arg__ = arg
self.__forward_code__ = code
self.__forward_evaluated__ = False
self.__forward_value__ = None
self.__forward_is_argument__ = is_argument
def _evaluate(self, globalns, localns):
if not self.__forward_evaluated__ or localns is not globalns:
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.",
is_argument=self.__forward_is_argument__)
self.__forward_evaluated__ = True
return self.__forward_value__
def __eq__(self, other):
if not isinstance(other, ForwardRef):
return NotImplemented
if self.__forward_evaluated__ and other.__forward_evaluated__:
return (self.__forward_arg__ == other.__forward_arg__ and
self.__forward_value__ == other.__forward_value__)
return self.__forward_arg__ == other.__forward_arg__
def __hash__(self):
return hash(self.__forward_arg__)
def __repr__(self):
return f'ForwardRef({self.__forward_arg__!r})'
class TypeVar(_Final, _Immutable, _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) -> List[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) and issubclass(C, T) will raise TypeError.
Type variables defined with covariant=True or contravariant=True
can be used to declare covariant or contravariant generic types.
See PEP 484 for more details. By default generic types are invariant
in all type variables.
Type variables can be introspected. e.g.:
T.__name__ == 'T'
T.__constraints__ == ()
T.__covariant__ == False
T.__contravariant__ = False
A.__constraints__ == (str, bytes)
Note that only type variables defined in global scope can be pickled.
"""
__slots__ = ('__name__', '__bound__', '__constraints__',
'__covariant__', '__contravariant__')
def __init__(self, name, *constraints, bound=None,
covariant=False, contravariant=False):
self.__name__ = name
if covariant and contravariant:
raise ValueError("Bivariant types 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
try:
def_mod = sys._getframe(1).f_globals.get('__name__', '__main__') # for pickling
except (AttributeError, ValueError):
def_mod = None
if def_mod != 'typing':
self.__module__ = def_mod
def __repr__(self):
if self.__covariant__:
prefix = '+'
elif self.__contravariant__:
prefix = '-'
else:
prefix = '~'
return prefix + self.__name__
def __reduce__(self):
return self.__name__
# Special typing constructs Union, Optional, Generic, Callable and Tuple
# use three special attributes for internal bookkeeping of generic types:
# * __parameters__ is a tuple of unique free type parameters of a generic
# type, for example, Dict[T, T].__parameters__ == (T,);
# * __origin__ keeps a reference to a type that was subscripted,
# e.g., Union[T, int].__origin__ == Union, or the non-generic version of
# the type.
# * __args__ is a tuple of all arguments used in subscripting,
# e.g., Dict[T, int].__args__ == (T, int).
# Mapping from non-generic type names that have a generic alias in typing
# but with a different name.
_normalize_alias = {'list': 'List',
'tuple': 'Tuple',
'dict': 'Dict',
'set': 'Set',
'frozenset': 'FrozenSet',
'deque': 'Deque',
'defaultdict': 'DefaultDict',
'type': 'Type',
'Set': 'AbstractSet'}
def _is_dunder(attr):
return attr.startswith('__') and attr.endswith('__')
class _GenericAlias(_Final, _root=True):
"""The central part of internal API.
This represents a generic version of type 'origin' with type arguments 'params'.
There are two kind of these aliases: user defined and special. The special ones
are wrappers around builtin collections and ABCs in collections.abc. These must
have 'name' always set. If 'inst' is False, then the alias can't be instantiated,
this is used by e.g. typing.List and typing.Dict.
"""
def __init__(self, origin, params, *, inst=True, special=False, name=None):
self._inst = inst
self._special = special
if special and name is None:
orig_name = origin.__name__
name = _normalize_alias.get(orig_name, orig_name)
self._name = name
if not isinstance(params, tuple):
params = (params,)
self.__origin__ = origin
self.__args__ = tuple(... if a is _TypingEllipsis else
() if a is _TypingEmpty else
a for a in params)
self.__parameters__ = _collect_type_vars(params)
self.__slots__ = None # This is not documented.
if not name:
self.__module__ = origin.__module__
@_tp_cache
def __getitem__(self, params):
if self.__origin__ in (Generic, Protocol):
# Can't subscript Generic[...] or Protocol[...].
raise TypeError(f"Cannot subscript already-subscripted {self}")
if not isinstance(params, tuple):
params = (params,)
msg = "Parameters to generic types must be types."
params = tuple(_type_check(p, msg) for p in params)
_check_generic(self, params)
return _subs_tvars(self, self.__parameters__, params)
def copy_with(self, params):
# We don't copy self._special.
return _GenericAlias(self.__origin__, params, name=self._name, inst=self._inst)
def __repr__(self):
if (self._name != 'Callable' or
len(self.__args__) == 2 and self.__args__[0] is Ellipsis):
if self._name:
name = 'typing.' + self._name
else:
name = _type_repr(self.__origin__)
if not self._special:
args = f'[{", ".join([_type_repr(a) for a in self.__args__])}]'
else:
args = ''
return (f'{name}{args}')
if self._special:
return 'typing.Callable'
return (f'typing.Callable'
f'[[{", ".join([_type_repr(a) for a in self.__args__[:-1]])}], '
f'{_type_repr(self.__args__[-1])}]')
def __eq__(self, other):
if not isinstance(other, _GenericAlias):
return NotImplemented
if self.__origin__ != other.__origin__:
return False
if self.__origin__ is Union and other.__origin__ is Union:
return frozenset(self.__args__) == frozenset(other.__args__)
return self.__args__ == other.__args__
def __hash__(self):
if self.__origin__ is Union:
return hash((Union, frozenset(self.__args__)))
return hash((self.__origin__, self.__args__))
def __call__(self, *args, **kwargs):
if not self._inst:
raise TypeError(f"Type {self._name} cannot be instantiated; "
f"use {self._name.lower()}() instead")
result = self.__origin__(*args, **kwargs)
try:
result.__orig_class__ = self
except AttributeError:
pass
return result
def __mro_entries__(self, bases):
if self._name: # generic version of an ABC or built-in class
res = []
if self.__origin__ not in bases:
res.append(self.__origin__)
i = bases.index(self)
if not any(isinstance(b, _GenericAlias) or issubclass(b, Generic)
for b in bases[i+1:]):
res.append(Generic)
return tuple(res)
if self.__origin__ is Generic:
if Protocol in bases:
return ()
i = bases.index(self)
for b in bases[i+1:]:
if isinstance(b, _GenericAlias) and b is not self:
return ()
return (self.__origin__,)
def __getattr__(self, attr):
# We are careful for copy and pickle.
# Also for simplicity we just don't relay all dunder names
if '__origin__' in self.__dict__ and not _is_dunder(attr):
return getattr(self.__origin__, attr)
raise AttributeError(attr)
def __setattr__(self, attr, val):
if _is_dunder(attr) or attr in ('_name', '_inst', '_special'):
super().__setattr__(attr, val)
else:
setattr(self.__origin__, attr, val)
def __instancecheck__(self, obj):
return self.__subclasscheck__(type(obj))
def __subclasscheck__(self, cls):
if self._special:
if not isinstance(cls, _GenericAlias):
return issubclass(cls, self.__origin__)
if cls._special:
return issubclass(cls.__origin__, self.__origin__)
raise TypeError("Subscripted generics cannot be used with"
" class and instance checks")
def __reduce__(self):
if self._special:
return self._name
if self._name:
origin = globals()[self._name]
else:
origin = self.__origin__
if (origin is Callable and
not (len(self.__args__) == 2 and self.__args__[0] is Ellipsis)):
args = list(self.__args__[:-1]), self.__args__[-1]
else:
args = tuple(self.__args__)
if len(args) == 1 and not isinstance(args[0], tuple):
args, = args
return operator.getitem, (origin, args)
class _VariadicGenericAlias(_GenericAlias, _root=True):
"""Same as _GenericAlias above but for variadic aliases. Currently,
this is used only by special internal aliases: Tuple and Callable.
"""
def __getitem__(self, params):
if self._name != 'Callable' or not self._special:
return self.__getitem_inner__(params)
if not isinstance(params, tuple) or len(params) != 2:
raise TypeError("Callable must be used as "
"Callable[[arg, ...], result].")
args, result = params
if args is Ellipsis:
params = (Ellipsis, result)
else:
if not isinstance(args, list):
raise TypeError(f"Callable[args, result]: args must be a list."
f" Got {args}")
params = (tuple(args), result)
return self.__getitem_inner__(params)
@_tp_cache
def __getitem_inner__(self, params):
if self.__origin__ is tuple and self._special:
if params == ():
return self.copy_with((_TypingEmpty,))
if not isinstance(params, tuple):
params = (params,)
if len(params) == 2 and params[1] is ...:
msg = "Tuple[t, ...]: t must be a type."
p = _type_check(params[0], msg)
return self.copy_with((p, _TypingEllipsis))
msg = "Tuple[t0, t1, ...]: each t must be a type."
params = tuple(_type_check(p, msg) for p in params)
return self.copy_with(params)
if self.__origin__ is collections.abc.Callable and self._special:
args, result = params
msg = "Callable[args, result]: result must be a type."
result = _type_check(result, msg)
if args is Ellipsis:
return self.copy_with((_TypingEllipsis, result))
msg = "Callable[[arg, ...], result]: each arg must be a type."
args = tuple(_type_check(arg, msg) for arg in args)
params = args + (result,)
return self.copy_with(params)
return super().__getitem__(params)
class Generic:
"""Abstract base class for generic types.
A generic type is typically declared by inheriting from
this class parameterized 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[KT, VT], key: KT, default: VT) -> VT:
try:
return mapping[key]
except KeyError:
return default
"""
__slots__ = ()
_is_protocol = False
def __new__(cls, *args, **kwds):
if cls in (Generic, Protocol):
raise TypeError(f"Type {cls.__name__} cannot be instantiated; "
"it can be used only as a base class")
if super().__new__ is object.__new__ and cls.__init__ is not object.__init__:
obj = super().__new__(cls)
else:
obj = super().__new__(cls, *args, **kwds)
return obj
@_tp_cache
def __class_getitem__(cls, params):
if not isinstance(params, tuple):
params = (params,)
if not params and cls is not Tuple:
raise TypeError(
f"Parameter list to {cls.__qualname__}[...] cannot be empty")
msg = "Parameters to generic types must be types."
params = tuple(_type_check(p, msg) for p in params)
if cls in (Generic, Protocol):
# Generic and Protocol can only be subscripted with unique type variables.
if not all(isinstance(p, TypeVar) for p in params):
raise TypeError(
f"Parameters to {cls.__name__}[...] must all be type variables")
if len(set(params)) != len(params):
raise TypeError(
f"Parameters to {cls.__name__}[...] must all be unique")
else:
# Subscripting a regular Generic subclass.
_check_generic(cls, params)
return _GenericAlias(cls, params)
def __init_subclass__(cls, *args, **kwargs):
super().__init_subclass__(*args, **kwargs)
tvars = []
if '__orig_bases__' in cls.__dict__:
error = Generic in cls.__orig_bases__
else:
error = Generic in cls.__bases__ and cls.__name__ != 'Protocol'
if error:
raise TypeError("Cannot inherit from plain Generic")
if '__orig_bases__' in cls.__dict__:
tvars = _collect_type_vars(cls.__orig_bases__)
# Look for Generic[T1, ..., Tn].
# If found, tvars must be a subset of it.
# If not found, tvars is it.
# Also check for and reject plain Generic,
# and reject multiple Generic[...].
gvars = None
for base in cls.__orig_bases__:
if (isinstance(base, _GenericAlias) and
base.__origin__ is Generic):
if gvars is not None:
raise TypeError(
"Cannot inherit from Generic[...] multiple types.")
gvars = base.__parameters__
if gvars is not None:
tvarset = set(tvars)
gvarset = set(gvars)
if not tvarset <= gvarset:
s_vars = ', '.join(str(t) for t in tvars if t not in gvarset)
s_args = ', '.join(str(g) for g in gvars)
raise TypeError(f"Some type variables ({s_vars}) are"
f" not listed in Generic[{s_args}]")
tvars = gvars
cls.__parameters__ = tuple(tvars)
class _TypingEmpty:
"""Internal placeholder for () or []. Used by TupleMeta and CallableMeta
to allow empty list/tuple in specific places, without allowing them
to sneak in where prohibited.
"""
class _TypingEllipsis:
"""Internal placeholder for ... (ellipsis)."""
_TYPING_INTERNALS = ['__parameters__', '__orig_bases__', '__orig_class__',
'_is_protocol', '_is_runtime_protocol']
_SPECIAL_NAMES = ['__abstractmethods__', '__annotations__', '__dict__', '__doc__',
'__init__', '__module__', '__new__', '__slots__',
'__subclasshook__', '__weakref__']
# These special attributes will be not collected as protocol members.
EXCLUDED_ATTRIBUTES = _TYPING_INTERNALS + _SPECIAL_NAMES + ['_MutableMapping__marker']
def _get_protocol_attrs(cls):
"""Collect protocol members from a protocol class objects.
This includes names actually defined in the class dictionary, as well
as names that appear in annotations. Special names (above) are skipped.
"""
attrs = set()
for base in cls.__mro__[:-1]: # without object
if base.__name__ in ('Protocol', 'Generic'):
continue
annotations = getattr(base, '__annotations__', {})
for attr in list(base.__dict__.keys()) + list(annotations.keys()):
if not attr.startswith('_abc_') and attr not in EXCLUDED_ATTRIBUTES:
attrs.add(attr)
return attrs
def _is_callable_members_only(cls):
# PEP 544 prohibits using issubclass() with protocols that have non-method members.
return all(callable(getattr(cls, attr, None)) for attr in _get_protocol_attrs(cls))
def _no_init(self, *args, **kwargs):
if type(self)._is_protocol:
raise TypeError('Protocols cannot be instantiated')
def _allow_reckless_class_cheks():
"""Allow instnance and class checks for special stdlib modules.
The abc and functools modules indiscriminately call isinstance() and
issubclass() on the whole MRO of a user class, which may contain protocols.
"""
try:
return sys._getframe(3).f_globals['__name__'] in ['abc', 'functools']
except (AttributeError, ValueError): # For platforms without _getframe().
return True
_PROTO_WHITELIST = {
'collections.abc': [
'Callable', 'Awaitable', 'Iterable', 'Iterator', 'AsyncIterable',
'Hashable', 'Sized', 'Container', 'Collection', 'Reversible',
],
'contextlib': ['AbstractContextManager', 'AbstractAsyncContextManager'],
}
class _ProtocolMeta(ABCMeta):
# This metaclass is really unfortunate and exists only because of
# the lack of __instancehook__.
def __instancecheck__(cls, instance):
# We need this method for situations where attributes are
# assigned in __init__.
if ((not getattr(cls, '_is_protocol', False) or
_is_callable_members_only(cls)) and
issubclass(instance.__class__, cls)):
return True
if cls._is_protocol:
if all(hasattr(instance, attr) and
# All *methods* can be blocked by setting them to None.
(not callable(getattr(cls, attr, None)) or
getattr(instance, attr) is not None)
for attr in _get_protocol_attrs(cls)):
return True
return super().__instancecheck__(instance)
class Protocol(Generic, metaclass=_ProtocolMeta):
"""Base class for protocol classes.
Protocol classes are defined as::
class Proto(Protocol):
def meth(self) -> int:
...
Such classes are primarily used with static type checkers that recognize
structural subtyping (static duck-typing), for example::
class C:
def meth(self) -> int:
return 0
def func(x: Proto) -> int:
return x.meth()
func(C()) # Passes static type check
See PEP 544 for details. Protocol classes decorated with
@typing.runtime_checkable act as simple-minded runtime protocols that check
only the presence of given attributes, ignoring their type signatures.
Protocol classes can be generic, they are defined as::
class GenProto(Protocol[T]):
def meth(self) -> T:
...
"""
__slots__ = ()
_is_protocol = True
_is_runtime_protocol = False
def __init_subclass__(cls, *args, **kwargs):
super().__init_subclass__(*args, **kwargs)
# Determine if this is a protocol or a concrete subclass.
if not cls.__dict__.get('_is_protocol', False):
cls._is_protocol = any(b is Protocol for b in cls.__bases__)
# Set (or override) the protocol subclass hook.
def _proto_hook(other):
if not cls.__dict__.get('_is_protocol', False):
return NotImplemented
# First, perform various sanity checks.
if not getattr(cls, '_is_runtime_protocol', False):
if _allow_reckless_class_cheks():
return NotImplemented
raise TypeError("Instance and class checks can only be used with"
" @runtime_checkable protocols")
if not _is_callable_members_only(cls):
if _allow_reckless_class_cheks():
return NotImplemented
raise TypeError("Protocols with non-method members"
" don't support issubclass()")
if not isinstance(other, type):
# Same error message as for issubclass(1, int).
raise TypeError('issubclass() arg 1 must be a class')
# Second, perform the actual structural compatibility check.
for attr in _get_protocol_attrs(cls):
for base in other.__mro__:
# Check if the members appears in the class dictionary...
if attr in base.__dict__:
if base.__dict__[attr] is None:
return NotImplemented
break
# ...or in annotations, if it is a sub-protocol.
annotations = getattr(base, '__annotations__', {})
if (isinstance(annotations, collections.abc.Mapping) and
attr in annotations and
issubclass(other, Generic) and other._is_protocol):
break
else:
return NotImplemented
return True
if '__subclasshook__' not in cls.__dict__:
cls.__subclasshook__ = _proto_hook
# We have nothing more to do for non-protocols...
if not cls._is_protocol:
return
# ... otherwise check consistency of bases, and prohibit instantiation.
for base in cls.__bases__:
if not (base in (object, Generic) or
base.__module__ in _PROTO_WHITELIST and
base.__name__ in _PROTO_WHITELIST[base.__module__] or
issubclass(base, Generic) and base._is_protocol):
raise TypeError('Protocols can only inherit from other'
' protocols, got %r' % base)
cls.__init__ = _no_init
def runtime_checkable(cls):
"""Mark a protocol class as a runtime protocol.
Such protocol can be used with isinstance() and issubclass().
Raise TypeError if applied to a non-protocol class.
This allows a simple-minded structural check very similar to
one trick ponies in collections.abc such as Iterable.
For example::
@runtime_checkable
class Closable(Protocol):
def close(self): ...
assert isinstance(open('/some/file'), Closable)
Warning: this will check only the presence of the required methods,
not their type signatures!
"""
if not issubclass(cls, Generic) or not cls._is_protocol:
raise TypeError('@runtime_checkable can be only applied to protocol classes,'
' got %r' % cls)
cls._is_runtime_protocol = True
return 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."""
try:
code = func.__code__
except AttributeError:
# Some built-in functions don't have __code__, __defaults__, etc.
return {}
pos_count = code.co_argcount
arg_names = code.co_varnames
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
_allowed_types = (types.FunctionType, types.BuiltinFunctionType,
types.MethodType, types.ModuleType,
WrapperDescriptorType, MethodWrapperType, MethodDescriptorType)
def get_type_hints(obj, globalns=None, localns=None):
"""Return type hints for an 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.
The argument may be a module, class, method, or function. The annotations
are returned as a dictionary. For classes, annotations include also
inherited members.
TypeError is raised if the argument is not of a type that can contain
annotations, and an empty dictionary is returned if no annotations are
present.
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 (or the respective module's globals for classes),
and these are also used as the locals. If the object does not appear
to have globals, an empty dictionary is used.
- 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 {}
# Classes require a special treatment.
if isinstance(obj, type):
hints = {}
for base in reversed(obj.__mro__):
if globalns is None:
base_globals = sys.modules[base.__module__].__dict__
else:
base_globals = globalns
ann = base.__dict__.get('__annotations__', {})
for name, value in ann.items():
if value is None:
value = type(None)
if isinstance(value, str):
value = ForwardRef(value, is_argument=False)
value = _eval_type(value, base_globals, localns)
hints[name] = value
return hints
if globalns is None:
if isinstance(obj, types.ModuleType):
globalns = obj.__dict__
else:
nsobj = obj
# Find globalns for the unwrapped object.
while hasattr(nsobj, '__wrapped__'):
nsobj = nsobj.__wrapped__
globalns = getattr(nsobj, '__globals__', {})
if localns is None:
localns = globalns
elif localns is None:
localns = globalns
hints = getattr(obj, '__annotations__', None)
if hints is None:
# Return empty annotations for something that _could_ have them.
if isinstance(obj, _allowed_types):
return {}
else:
raise TypeError('{!r} is not a module, class, method, '
'or function.'.format(obj))
defaults = _get_defaults(obj)
hints = dict(hints)
for name, value in hints.items():
if value is None:
value = type(None)
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
def get_origin(tp):
"""Get the unsubscripted version of a type.
This supports generic types, Callable, Tuple, Union, Literal, Final and ClassVar.
Return None for unsupported types. Examples::
get_origin(Literal[42]) is Literal
get_origin(int) is None
get_origin(ClassVar[int]) is ClassVar
get_origin(Generic) is Generic
get_origin(Generic[T]) is Generic
get_origin(Union[T, int]) is Union
get_origin(List[Tuple[T, T]][int]) == list
"""
if isinstance(tp, _GenericAlias):
return tp.__origin__
if tp is Generic:
return Generic
return None
def get_args(tp):
"""Get type arguments with all substitutions performed.
For unions, basic simplifications used by Union constructor are performed.
Examples::
get_args(Dict[str, int]) == (str, int)
get_args(int) == ()
get_args(Union[int, Union[T, int], str][int]) == (int, str)
get_args(Union[int, Tuple[T, int]][str]) == (int, Tuple[str, int])
get_args(Callable[[], T][int]) == ([], int)
"""
if isinstance(tp, _GenericAlias) and not tp._special:
res = tp.__args__
if get_origin(tp) is collections.abc.Callable and res[0] is not Ellipsis:
res = (list(res[:-1]), res[-1])
return res
return ()
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 and classes defined in that class
(but not to methods defined in its superclasses or subclasses).
This mutates the function(s) or class(es) in place.
"""
if isinstance(arg, type):
arg_attrs = arg.__dict__.copy()
for attr, val in arg.__dict__.items():
if val in arg.__bases__ + (arg,):
arg_attrs.pop(attr)
for obj in arg_attrs.values():
if isinstance(obj, types.FunctionType):
obj.__no_type_check__ = True
if isinstance(obj, type):
no_type_check(obj)
try:
arg.__no_type_check__ = True
except TypeError: # built-in classes
pass
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_dummy(*args, **kwds):
"""Helper for @overload to raise when called."""
raise NotImplementedError(
"You should not call an overloaded function. "
"A series of @overload-decorated functions "
"outside a stub module should always be followed "
"by an implementation that is not @overload-ed.")
def overload(func):
"""Decorator for overloaded functions/methods.
In a stub file, place two or more stub definitions for the same
function in a row, each decorated with @overload. For example:
@overload
def utf8(value: None) -> None: ...
@overload
def utf8(value: bytes) -> bytes: ...
@overload
def utf8(value: str) -> bytes: ...
In a non-stub file (i.e. a regular .py file), do the same but
follow it with an implementation. The implementation should *not*
be decorated with @overload. For example:
@overload
def utf8(value: None) -> None: ...
@overload
def utf8(value: bytes) -> bytes: ...
@overload
def utf8(value: str) -> bytes: ...
def utf8(value):
# implementation goes here
"""
return _overload_dummy
def final(f):
"""A decorator to indicate final methods and final classes.
Use this decorator to indicate to type checkers that the decorated
method cannot be overridden, and decorated class cannot be subclassed.
For example:
class Base:
@final
def done(self) -> None:
...
class Sub(Base):
def done(self) -> None: # Error reported by type checker
...
@final
class Leaf:
...
class Other(Leaf): # Error reported by type checker
...
There is no runtime checking of these properties.
"""
return f
# Some unconstrained type variables. These are used by the container types.
# (These are not for export.)
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.
# Internal type variable used for Type[].
CT_co = TypeVar('CT_co', covariant=True, bound=type)
# A useful type variable with constraints. This represents string types.
# (This one *is* for export!)
AnyStr = TypeVar('AnyStr', bytes, str)
# Various ABCs mimicking those in collections.abc.
def _alias(origin, params, inst=True):
return _GenericAlias(origin, params, special=True, inst=inst)
Hashable = _alias(collections.abc.Hashable, ()) # Not generic.
Awaitable = _alias(collections.abc.Awaitable, T_co)
Coroutine = _alias(collections.abc.Coroutine, (T_co, T_contra, V_co))
AsyncIterable = _alias(collections.abc.AsyncIterable, T_co)
AsyncIterator = _alias(collections.abc.AsyncIterator, T_co)
Iterable = _alias(collections.abc.Iterable, T_co)
Iterator = _alias(collections.abc.Iterator, T_co)
Reversible = _alias(collections.abc.Reversible, T_co)
Sized = _alias(collections.abc.Sized, ()) # Not generic.
Container = _alias(collections.abc.Container, T_co)
Collection = _alias(collections.abc.Collection, T_co)
Callable = _VariadicGenericAlias(collections.abc.Callable, (), special=True)
Callable.__doc__ = \
"""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 or ellipsis; 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.
"""
AbstractSet = _alias(collections.abc.Set, T_co)
MutableSet = _alias(collections.abc.MutableSet, T)
# NOTE: Mapping is only covariant in the value type.
Mapping = _alias(collections.abc.Mapping, (KT, VT_co))
MutableMapping = _alias(collections.abc.MutableMapping, (KT, VT))
Sequence = _alias(collections.abc.Sequence, T_co)
MutableSequence = _alias(collections.abc.MutableSequence, T)
ByteString = _alias(collections.abc.ByteString, ()) # Not generic
Tuple = _VariadicGenericAlias(tuple, (), inst=False, special=True)
Tuple.__doc__ = \
"""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 Tuple[T, ...].
"""
List = _alias(list, T, inst=False)
Deque = _alias(collections.deque, T)
Set = _alias(set, T, inst=False)
FrozenSet = _alias(frozenset, T_co, inst=False)
MappingView = _alias(collections.abc.MappingView, T_co)
KeysView = _alias(collections.abc.KeysView, KT)
ItemsView = _alias(collections.abc.ItemsView, (KT, VT_co))
ValuesView = _alias(collections.abc.ValuesView, VT_co)
ContextManager = _alias(contextlib.AbstractContextManager, T_co)
AsyncContextManager = _alias(contextlib.AbstractAsyncContextManager, T_co)
Dict = _alias(dict, (KT, VT), inst=False)
DefaultDict = _alias(collections.defaultdict, (KT, VT))
OrderedDict = _alias(collections.OrderedDict, (KT, VT))
Counter = _alias(collections.Counter, T)
ChainMap = _alias(collections.ChainMap, (KT, VT))
Generator = _alias(collections.abc.Generator, (T_co, T_contra, V_co))
AsyncGenerator = _alias(collections.abc.AsyncGenerator, (T_co, T_contra))
Type = _alias(type, CT_co, inst=False)
Type.__doc__ = \
"""A special construct usable to annotate class objects.
For example, suppose we have the following classes::
class User: ... # Abstract base for User classes
class BasicUser(User): ...
class ProUser(User): ...
class TeamUser(User): ...
And a function that takes a class argument that's a subclass of
User and returns an instance of the corresponding class::
U = TypeVar('U', bound=User)
def new_user(user_class: Type[U]) -> U:
user = user_class()
# (Here we could write the user object to a database)
return user
joe = new_user(BasicUser)
At this point the type checker knows that joe has type BasicUser.
"""
@runtime_checkable
class SupportsInt(Protocol):
"""An ABC with one abstract method __int__."""
__slots__ = ()
@abstractmethod
def __int__(self) -> int:
pass
@runtime_checkable
class SupportsFloat(Protocol):
"""An ABC with one abstract method __float__."""
__slots__ = ()
@abstractmethod
def __float__(self) -> float:
pass
@runtime_checkable
class SupportsComplex(Protocol):
"""An ABC with one abstract method __complex__."""
__slots__ = ()
@abstractmethod
def __complex__(self) -> complex:
pass
@runtime_checkable
class SupportsBytes(Protocol):
"""An ABC with one abstract method __bytes__."""
__slots__ = ()
@abstractmethod
def __bytes__(self) -> bytes:
pass
@runtime_checkable
class SupportsIndex(Protocol):
"""An ABC with one abstract method __index__."""
__slots__ = ()
@abstractmethod
def __index__(self) -> int:
pass
@runtime_checkable
class SupportsAbs(Protocol[T_co]):
"""An ABC with one abstract method __abs__ that is covariant in its return type."""
__slots__ = ()
@abstractmethod
def __abs__(self) -> T_co:
pass
@runtime_checkable
class SupportsRound(Protocol[T_co]):
"""An ABC with one abstract method __round__ that is covariant in its return type."""
__slots__ = ()
@abstractmethod
def __round__(self, ndigits: int = 0) -> T_co:
pass
def _make_nmtuple(name, types):
msg = "NamedTuple('Name', [(f0, t0), (f1, t1), ...]); each t must be a type"
types = [(n, _type_check(t, msg)) for n, t in types]
nm_tpl = collections.namedtuple(name, [n for n, t in types])
# Prior to PEP 526, only _field_types attribute was assigned.
# Now __annotations__ are used and _field_types is deprecated (remove in 3.9)
nm_tpl.__annotations__ = nm_tpl._field_types = dict(types)
try:
nm_tpl.__module__ = sys._getframe(2).f_globals.get('__name__', '__main__')
except (AttributeError, ValueError):
pass
return nm_tpl
# attributes prohibited to set in NamedTuple class syntax
_prohibited = ('__new__', '__init__', '__slots__', '__getnewargs__',
'_fields', '_field_defaults', '_field_types',
'_make', '_replace', '_asdict', '_source')
_special = ('__module__', '__name__', '__annotations__')
class NamedTupleMeta(type):
def __new__(cls, typename, bases, ns):
if ns.get('_root', False):
return super().__new__(cls, typename, bases, ns)
types = ns.get('__annotations__', {})
nm_tpl = _make_nmtuple(typename, types.items())
defaults = []
defaults_dict = {}
for field_name in types:
if field_name in ns:
default_value = ns[field_name]
defaults.append(default_value)
defaults_dict[field_name] = default_value
elif defaults:
raise TypeError("Non-default namedtuple field {field_name} cannot "
"follow default field(s) {default_names}"
.format(field_name=field_name,
default_names=', '.join(defaults_dict.keys())))
nm_tpl.__new__.__annotations__ = dict(types)
nm_tpl.__new__.__defaults__ = tuple(defaults)
nm_tpl._field_defaults = defaults_dict
# update from user namespace without overriding special namedtuple attributes
for key in ns:
if key in _prohibited:
raise AttributeError("Cannot overwrite NamedTuple attribute " + key)
elif key not in _special and key not in nm_tpl._fields:
setattr(nm_tpl, key, ns[key])
return nm_tpl
class NamedTuple(metaclass=NamedTupleMeta):
"""Typed version of namedtuple.
Usage in Python versions >= 3.6::
class Employee(NamedTuple):
name: str
id: int
This is equivalent to::
Employee = collections.namedtuple('Employee', ['name', 'id'])
The resulting class has an extra __annotations__ attribute, giving a
dict that maps field names to types. (The field names are also in
the _fields attribute, which is part of the namedtuple API.)
Alternative equivalent keyword syntax is also accepted::
Employee = NamedTuple('Employee', name=str, id=int)
In Python versions <= 3.5 use::
Employee = NamedTuple('Employee', [('name', str), ('id', int)])
"""
_root = True
def __new__(*args, **kwargs):
if not args:
raise TypeError('NamedTuple.__new__(): not enough arguments')
cls, *args = args # allow the "cls" keyword be passed
if args:
typename, *args = args # allow the "typename" keyword be passed
elif 'typename' in kwargs:
typename = kwargs.pop('typename')
import warnings
warnings.warn("Passing 'typename' as keyword argument is deprecated",
DeprecationWarning, stacklevel=2)
else:
raise TypeError("NamedTuple.__new__() missing 1 required positional "
"argument: 'typename'")
if args:
try:
fields, = args # allow the "fields" keyword be passed
except ValueError:
raise TypeError(f'NamedTuple.__new__() takes from 2 to 3 '
f'positional arguments but {len(args) + 2} '
f'were given') from None
elif 'fields' in kwargs and len(kwargs) == 1:
fields = kwargs.pop('fields')
import warnings
warnings.warn("Passing 'fields' as keyword argument is deprecated",
DeprecationWarning, stacklevel=2)
else:
fields = None
if fields is None:
fields = kwargs.items()
elif kwargs:
raise TypeError("Either list of fields or keywords"
" can be provided to NamedTuple, not both")
return _make_nmtuple(typename, fields)
__new__.__text_signature__ = '($cls, typename, fields=None, /, **kwargs)'
def _dict_new(cls, /, *args, **kwargs):
return dict(*args, **kwargs)
def _typeddict_new(cls, typename, fields=None, /, *, total=True, **kwargs):
if fields is None:
fields = kwargs
elif kwargs:
raise TypeError("TypedDict takes either a dict or keyword arguments,"
" but not both")
ns = {'__annotations__': dict(fields), '__total__': total}
try:
# Setting correct module is necessary to make typed dict classes pickleable.
ns['__module__'] = sys._getframe(1).f_globals.get('__name__', '__main__')
except (AttributeError, ValueError):
pass
return _TypedDictMeta(typename, (), ns)
def _check_fails(cls, other):
# Typed dicts are only for static structural subtyping.
raise TypeError('TypedDict does not support instance and class checks')
class _TypedDictMeta(type):
def __new__(cls, name, bases, ns, total=True):
"""Create new typed dict class object.
This method is called directly when TypedDict is subclassed,
or via _typeddict_new when TypedDict is instantiated. This way
TypedDict supports all three syntax forms described in its docstring.
Subclasses and instances of TypedDict return actual dictionaries
via _dict_new.
"""
ns['__new__'] = _typeddict_new if name == 'TypedDict' else _dict_new
tp_dict = super(_TypedDictMeta, cls).__new__(cls, name, (dict,), ns)
anns = ns.get('__annotations__', {})
msg = "TypedDict('Name', {f0: t0, f1: t1, ...}); each t must be a type"
anns = {n: _type_check(tp, msg) for n, tp in anns.items()}
for base in bases:
anns.update(base.__dict__.get('__annotations__', {}))
tp_dict.__annotations__ = anns
if not hasattr(tp_dict, '__total__'):
tp_dict.__total__ = total
return tp_dict
__instancecheck__ = __subclasscheck__ = _check_fails
class TypedDict(dict, metaclass=_TypedDictMeta):
"""A simple typed namespace. At runtime it is equivalent to a plain dict.
TypedDict creates a dictionary type that expects all of its
instances to have a certain set of keys, where each key is
associated with a value of a consistent type. This expectation
is not checked at runtime but is only enforced by type checkers.
Usage::
class Point2D(TypedDict):
x: int
y: int
label: str
a: Point2D = {'x': 1, 'y': 2, 'label': 'good'} # OK
b: Point2D = {'z': 3, 'label': 'bad'} # Fails type check
assert Point2D(x=1, y=2, label='first') == dict(x=1, y=2, label='first')
The type info can be accessed via Point2D.__annotations__. TypedDict
supports two additional equivalent forms::
Point2D = TypedDict('Point2D', x=int, y=int, label=str)
Point2D = TypedDict('Point2D', {'x': int, 'y': int, 'label': str})
By default, all keys must be present in a TypedDict. It is possible
to override this by specifying totality.
Usage::
class point2D(TypedDict, total=False):
x: int
y: int
This means that a point2D TypedDict can have any of the keys omitted.A type
checker is only expected to support a literal False or True as the value of
the total argument. True is the default, and makes all items defined in the
class body be required.
The class syntax is only supported in Python 3.6+, while two other
syntax forms work for Python 2.7 and 3.2+
"""
def NewType(name, tp):
"""NewType creates simple unique types with almost zero
runtime overhead. NewType(name, tp) is considered a subtype of tp
by static type checkers. At runtime, NewType(name, tp) returns
a dummy function that simply returns its argument. Usage::
UserId = NewType('UserId', int)
def name_by_id(user_id: UserId) -> str:
...
UserId('user') # Fails type check
name_by_id(42) # Fails type check
name_by_id(UserId(42)) # OK
num = UserId(5) + 1 # type: int
"""
def new_type(x):
return x
new_type.__name__ = name
new_type.__supertype__ = tp
return new_type
# Python-version-specific alias (Python 2: unicode; Python 3: str)
Text = str
# Constant that's True when type checking, but False here.
TYPE_CHECKING = False
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__ = ()
@property
@abstractmethod
def mode(self) -> str:
pass
@property
@abstractmethod
def name(self) -> str:
pass
@abstractmethod
def close(self) -> None:
pass
@property
@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__ = ()
@property
@abstractmethod
def buffer(self) -> BinaryIO:
pass
@property
@abstractmethod
def encoding(self) -> str:
pass
@property
@abstractmethod
def errors(self) -> Optional[str]:
pass
@property
@abstractmethod
def line_buffering(self) -> bool:
pass
@property
@abstractmethod
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 = _alias(stdlib_re.Pattern, AnyStr)
Match = _alias(stdlib_re.Match, AnyStr)
class re:
"""Wrapper namespace for re type aliases."""
__all__ = ['Pattern', 'Match']
Pattern = Pattern
Match = Match
re.__name__ = __name__ + '.re'
sys.modules[re.__name__] = re
Reference in New Issue View Git Blame Copy Permalink