| import abc |
| import collections |
| import collections.abc |
| import functools |
| import operator |
| import sys |
| import types as _types |
| import typing |
| |
| |
| __all__ = [ |
| # Super-special typing primitives. |
| 'Any', |
| 'ClassVar', |
| 'Concatenate', |
| 'Final', |
| 'LiteralString', |
| 'ParamSpec', |
| 'ParamSpecArgs', |
| 'ParamSpecKwargs', |
| 'Self', |
| 'Type', |
| 'TypeVar', |
| 'TypeVarTuple', |
| 'Unpack', |
| |
| # ABCs (from collections.abc). |
| 'Awaitable', |
| 'AsyncIterator', |
| 'AsyncIterable', |
| 'Coroutine', |
| 'AsyncGenerator', |
| 'AsyncContextManager', |
| 'ChainMap', |
| |
| # Concrete collection types. |
| 'ContextManager', |
| 'Counter', |
| 'Deque', |
| 'DefaultDict', |
| 'NamedTuple', |
| 'OrderedDict', |
| 'TypedDict', |
| |
| # Structural checks, a.k.a. protocols. |
| 'SupportsIndex', |
| |
| # One-off things. |
| 'Annotated', |
| 'assert_never', |
| 'assert_type', |
| 'clear_overloads', |
| 'dataclass_transform', |
| 'get_overloads', |
| 'final', |
| 'get_args', |
| 'get_origin', |
| 'get_type_hints', |
| 'IntVar', |
| 'is_typeddict', |
| 'Literal', |
| 'NewType', |
| 'overload', |
| 'override', |
| 'Protocol', |
| 'reveal_type', |
| 'runtime', |
| 'runtime_checkable', |
| 'Text', |
| 'TypeAlias', |
| 'TypeGuard', |
| 'TYPE_CHECKING', |
| 'Never', |
| 'NoReturn', |
| 'Required', |
| 'NotRequired', |
| ] |
| |
| # for backward compatibility |
| PEP_560 = True |
| GenericMeta = type |
| |
| # The functions below are modified copies of typing internal helpers. |
| # They are needed by _ProtocolMeta and they provide support for PEP 646. |
| |
| _marker = object() |
| |
| |
| def _check_generic(cls, parameters, elen=_marker): |
| """Check correct count for parameters of a generic cls (internal helper). |
| This gives a nice error message in case of count mismatch. |
| """ |
| if not elen: |
| raise TypeError(f"{cls} is not a generic class") |
| if elen is _marker: |
| if not hasattr(cls, "__parameters__") or not cls.__parameters__: |
| raise TypeError(f"{cls} is not a generic class") |
| elen = len(cls.__parameters__) |
| alen = len(parameters) |
| if alen != elen: |
| if hasattr(cls, "__parameters__"): |
| parameters = [p for p in cls.__parameters__ if not _is_unpack(p)] |
| num_tv_tuples = sum(isinstance(p, TypeVarTuple) for p in parameters) |
| if (num_tv_tuples > 0) and (alen >= elen - num_tv_tuples): |
| return |
| raise TypeError(f"Too {'many' if alen > elen else 'few'} parameters for {cls};" |
| f" actual {alen}, expected {elen}") |
| |
| |
| if sys.version_info >= (3, 10): |
| def _should_collect_from_parameters(t): |
| return isinstance( |
| t, (typing._GenericAlias, _types.GenericAlias, _types.UnionType) |
| ) |
| elif sys.version_info >= (3, 9): |
| def _should_collect_from_parameters(t): |
| return isinstance(t, (typing._GenericAlias, _types.GenericAlias)) |
| else: |
| def _should_collect_from_parameters(t): |
| return isinstance(t, typing._GenericAlias) and not t._special |
| |
| |
| def _collect_type_vars(types, typevar_types=None): |
| """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) |
| """ |
| if typevar_types is None: |
| typevar_types = typing.TypeVar |
| tvars = [] |
| for t in types: |
| if ( |
| isinstance(t, typevar_types) and |
| t not in tvars and |
| not _is_unpack(t) |
| ): |
| tvars.append(t) |
| if _should_collect_from_parameters(t): |
| tvars.extend([t for t in t.__parameters__ if t not in tvars]) |
| return tuple(tvars) |
| |
| |
| NoReturn = typing.NoReturn |
| |
| # Some unconstrained type variables. These are used by the container types. |
| # (These are not for export.) |
| T = typing.TypeVar('T') # Any type. |
| KT = typing.TypeVar('KT') # Key type. |
| VT = typing.TypeVar('VT') # Value type. |
| T_co = typing.TypeVar('T_co', covariant=True) # Any type covariant containers. |
| T_contra = typing.TypeVar('T_contra', contravariant=True) # Ditto contravariant. |
| |
| |
| if sys.version_info >= (3, 11): |
| from typing import Any |
| else: |
| |
| class _AnyMeta(type): |
| def __instancecheck__(self, obj): |
| if self is Any: |
| raise TypeError("typing_extensions.Any cannot be used with isinstance()") |
| return super().__instancecheck__(obj) |
| |
| def __repr__(self): |
| if self is Any: |
| return "typing_extensions.Any" |
| return super().__repr__() |
| |
| class Any(metaclass=_AnyMeta): |
| """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 |
| checks. |
| """ |
| def __new__(cls, *args, **kwargs): |
| if cls is Any: |
| raise TypeError("Any cannot be instantiated") |
| return super().__new__(cls, *args, **kwargs) |
| |
| |
| ClassVar = typing.ClassVar |
| |
| # On older versions of typing there is an internal class named "Final". |
| # 3.8+ |
| if hasattr(typing, 'Final') and sys.version_info[:2] >= (3, 7): |
| Final = typing.Final |
| # 3.7 |
| else: |
| class _FinalForm(typing._SpecialForm, _root=True): |
| |
| def __repr__(self): |
| return 'typing_extensions.' + self._name |
| |
| def __getitem__(self, parameters): |
| item = typing._type_check(parameters, |
| f'{self._name} accepts only a single type.') |
| return typing._GenericAlias(self, (item,)) |
| |
| Final = _FinalForm('Final', |
| doc="""A special typing construct to indicate that a 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.""") |
| |
| if sys.version_info >= (3, 11): |
| final = typing.final |
| else: |
| # @final exists in 3.8+, but we backport it for all versions |
| # before 3.11 to keep support for the __final__ attribute. |
| # See https://bugs.python.org/issue46342 |
| def final(f): |
| """This decorator can be used 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. The decorator |
| sets the ``__final__`` attribute to ``True`` on the decorated object |
| to allow runtime introspection. |
| """ |
| try: |
| f.__final__ = True |
| except (AttributeError, TypeError): |
| # Skip the attribute silently if it is not writable. |
| # AttributeError happens if the object has __slots__ or a |
| # read-only property, TypeError if it's a builtin class. |
| pass |
| return f |
| |
| |
| def IntVar(name): |
| return typing.TypeVar(name) |
| |
| |
| # 3.8+: |
| if hasattr(typing, 'Literal'): |
| Literal = typing.Literal |
| # 3.7: |
| else: |
| class _LiteralForm(typing._SpecialForm, _root=True): |
| |
| def __repr__(self): |
| return 'typing_extensions.' + self._name |
| |
| def __getitem__(self, parameters): |
| return typing._GenericAlias(self, parameters) |
| |
| Literal = _LiteralForm('Literal', |
| doc="""A type that can be used to indicate to type checkers |
| that the corresponding value has a value literally equivalent |
| to the provided parameter. For example: |
| |
| var: Literal[4] = 4 |
| |
| The type checker understands that 'var' is literally equal to |
| the value 4 and no other value. |
| |
| Literal[...] cannot be subclassed. There is no runtime |
| checking verifying that the parameter is actually a value |
| instead of a type.""") |
| |
| |
| _overload_dummy = typing._overload_dummy # noqa |
| |
| |
| if hasattr(typing, "get_overloads"): # 3.11+ |
| overload = typing.overload |
| get_overloads = typing.get_overloads |
| clear_overloads = typing.clear_overloads |
| else: |
| # {module: {qualname: {firstlineno: func}}} |
| _overload_registry = collections.defaultdict( |
| functools.partial(collections.defaultdict, dict) |
| ) |
| |
| 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 |
| |
| The overloads for a function can be retrieved at runtime using the |
| get_overloads() function. |
| """ |
| # classmethod and staticmethod |
| f = getattr(func, "__func__", func) |
| try: |
| _overload_registry[f.__module__][f.__qualname__][ |
| f.__code__.co_firstlineno |
| ] = func |
| except AttributeError: |
| # Not a normal function; ignore. |
| pass |
| return _overload_dummy |
| |
| def get_overloads(func): |
| """Return all defined overloads for *func* as a sequence.""" |
| # classmethod and staticmethod |
| f = getattr(func, "__func__", func) |
| if f.__module__ not in _overload_registry: |
| return [] |
| mod_dict = _overload_registry[f.__module__] |
| if f.__qualname__ not in mod_dict: |
| return [] |
| return list(mod_dict[f.__qualname__].values()) |
| |
| def clear_overloads(): |
| """Clear all overloads in the registry.""" |
| _overload_registry.clear() |
| |
| |
| # This is not a real generic class. Don't use outside annotations. |
| Type = typing.Type |
| |
| # Various ABCs mimicking those in collections.abc. |
| # A few are simply re-exported for completeness. |
| |
| |
| Awaitable = typing.Awaitable |
| Coroutine = typing.Coroutine |
| AsyncIterable = typing.AsyncIterable |
| AsyncIterator = typing.AsyncIterator |
| Deque = typing.Deque |
| ContextManager = typing.ContextManager |
| AsyncContextManager = typing.AsyncContextManager |
| DefaultDict = typing.DefaultDict |
| |
| # 3.7.2+ |
| if hasattr(typing, 'OrderedDict'): |
| OrderedDict = typing.OrderedDict |
| # 3.7.0-3.7.2 |
| else: |
| OrderedDict = typing._alias(collections.OrderedDict, (KT, VT)) |
| |
| Counter = typing.Counter |
| ChainMap = typing.ChainMap |
| AsyncGenerator = typing.AsyncGenerator |
| NewType = typing.NewType |
| Text = typing.Text |
| TYPE_CHECKING = typing.TYPE_CHECKING |
| |
| |
| _PROTO_WHITELIST = ['Callable', 'Awaitable', |
| 'Iterable', 'Iterator', 'AsyncIterable', 'AsyncIterator', |
| 'Hashable', 'Sized', 'Container', 'Collection', 'Reversible', |
| 'ContextManager', 'AsyncContextManager'] |
| |
| |
| def _get_protocol_attrs(cls): |
| 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 ( |
| '__abstractmethods__', '__annotations__', '__weakref__', |
| '_is_protocol', '_is_runtime_protocol', '__dict__', |
| '__args__', '__slots__', |
| '__next_in_mro__', '__parameters__', '__origin__', |
| '__orig_bases__', '__extra__', '__tree_hash__', |
| '__doc__', '__subclasshook__', '__init__', '__new__', |
| '__module__', '_MutableMapping__marker', '_gorg')): |
| attrs.add(attr) |
| return attrs |
| |
| |
| def _is_callable_members_only(cls): |
| return all(callable(getattr(cls, attr, None)) for attr in _get_protocol_attrs(cls)) |
| |
| |
| def _maybe_adjust_parameters(cls): |
| """Helper function used in Protocol.__init_subclass__ and _TypedDictMeta.__new__. |
| |
| The contents of this function are very similar |
| to logic found in typing.Generic.__init_subclass__ |
| on the CPython main branch. |
| """ |
| tvars = [] |
| if '__orig_bases__' in cls.__dict__: |
| tvars = typing._collect_type_vars(cls.__orig_bases__) |
| # Look for Generic[T1, ..., Tn] or Protocol[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[...] and/or Protocol[...]. |
| gvars = None |
| for base in cls.__orig_bases__: |
| if (isinstance(base, typing._GenericAlias) and |
| base.__origin__ in (typing.Generic, Protocol)): |
| # for error messages |
| the_base = base.__origin__.__name__ |
| if gvars is not None: |
| raise TypeError( |
| "Cannot inherit from Generic[...]" |
| " and/or Protocol[...] multiple types.") |
| gvars = base.__parameters__ |
| if gvars is None: |
| gvars = tvars |
| else: |
| 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 {the_base}[{s_args}]") |
| tvars = gvars |
| cls.__parameters__ = tuple(tvars) |
| |
| |
| # 3.8+ |
| if hasattr(typing, 'Protocol'): |
| Protocol = typing.Protocol |
| # 3.7 |
| else: |
| |
| def _no_init(self, *args, **kwargs): |
| if type(self)._is_protocol: |
| raise TypeError('Protocols cannot be instantiated') |
| |
| class _ProtocolMeta(abc.ABCMeta): # noqa: B024 |
| # This metaclass is a bit 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 |
| (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(metaclass=_ProtocolMeta): |
| # There is quite a lot of overlapping code with typing.Generic. |
| # Unfortunately it is hard to avoid this while these live in two different |
| # modules. The duplicated code will be removed when Protocol is moved to typing. |
| """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_extensions.runtime act as simple-minded runtime protocol that checks |
| 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 |
| |
| def __new__(cls, *args, **kwds): |
| if cls is Protocol: |
| raise TypeError("Type Protocol cannot be instantiated; " |
| "it can only be used as a base class") |
| return super().__new__(cls) |
| |
| @typing._tp_cache |
| def __class_getitem__(cls, params): |
| if not isinstance(params, tuple): |
| params = (params,) |
| if not params and cls is not typing.Tuple: |
| raise TypeError( |
| f"Parameter list to {cls.__qualname__}[...] cannot be empty") |
| msg = "Parameters to generic types must be types." |
| params = tuple(typing._type_check(p, msg) for p in params) # noqa |
| if cls is Protocol: |
| # Generic can only be subscripted with unique type variables. |
| if not all(isinstance(p, typing.TypeVar) for p in params): |
| i = 0 |
| while isinstance(params[i], typing.TypeVar): |
| i += 1 |
| raise TypeError( |
| "Parameters to Protocol[...] must all be type variables." |
| f" Parameter {i + 1} is {params[i]}") |
| if len(set(params)) != len(params): |
| raise TypeError( |
| "Parameters to Protocol[...] must all be unique") |
| else: |
| # Subscripting a regular Generic subclass. |
| _check_generic(cls, params, len(cls.__parameters__)) |
| return typing._GenericAlias(cls, params) |
| |
| def __init_subclass__(cls, *args, **kwargs): |
| if '__orig_bases__' in cls.__dict__: |
| error = typing.Generic in cls.__orig_bases__ |
| else: |
| error = typing.Generic in cls.__bases__ |
| if error: |
| raise TypeError("Cannot inherit from plain Generic") |
| _maybe_adjust_parameters(cls) |
| |
| # Determine if this is a protocol or a concrete subclass. |
| if not cls.__dict__.get('_is_protocol', None): |
| 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', None): |
| return NotImplemented |
| if not getattr(cls, '_is_runtime_protocol', False): |
| if sys._getframe(2).f_globals['__name__'] in ['abc', 'functools']: |
| return NotImplemented |
| raise TypeError("Instance and class checks can only be used with" |
| " @runtime protocols") |
| if not _is_callable_members_only(cls): |
| if sys._getframe(2).f_globals['__name__'] in ['abc', 'functools']: |
| return NotImplemented |
| raise TypeError("Protocols with non-method members" |
| " don't support issubclass()") |
| if not isinstance(other, type): |
| # Same error as for issubclass(1, int) |
| raise TypeError('issubclass() arg 1 must be a class') |
| for attr in _get_protocol_attrs(cls): |
| for base in other.__mro__: |
| if attr in base.__dict__: |
| if base.__dict__[attr] is None: |
| return NotImplemented |
| break |
| annotations = getattr(base, '__annotations__', {}) |
| if (isinstance(annotations, typing.Mapping) and |
| attr in annotations and |
| isinstance(other, _ProtocolMeta) 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 |
| |
| # Check consistency of bases. |
| for base in cls.__bases__: |
| if not (base in (object, typing.Generic) or |
| base.__module__ == 'collections.abc' and |
| base.__name__ in _PROTO_WHITELIST or |
| isinstance(base, _ProtocolMeta) and base._is_protocol): |
| raise TypeError('Protocols can only inherit from other' |
| f' protocols, got {repr(base)}') |
| cls.__init__ = _no_init |
| |
| |
| # 3.8+ |
| if hasattr(typing, 'runtime_checkable'): |
| runtime_checkable = typing.runtime_checkable |
| # 3.7 |
| else: |
| def runtime_checkable(cls): |
| """Mark a protocol class as a runtime protocol, so that it |
| 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 the |
| one-offs in collections.abc such as Hashable. |
| """ |
| if not isinstance(cls, _ProtocolMeta) or not cls._is_protocol: |
| raise TypeError('@runtime_checkable can be only applied to protocol classes,' |
| f' got {cls!r}') |
| cls._is_runtime_protocol = True |
| return cls |
| |
| |
| # Exists for backwards compatibility. |
| runtime = runtime_checkable |
| |
| |
| # 3.8+ |
| if hasattr(typing, 'SupportsIndex'): |
| SupportsIndex = typing.SupportsIndex |
| # 3.7 |
| else: |
| @runtime_checkable |
| class SupportsIndex(Protocol): |
| __slots__ = () |
| |
| @abc.abstractmethod |
| def __index__(self) -> int: |
| pass |
| |
| |
| if hasattr(typing, "Required"): |
| # The standard library TypedDict in Python 3.8 does not store runtime information |
| # about which (if any) keys are optional. See https://bugs.python.org/issue38834 |
| # The standard library TypedDict in Python 3.9.0/1 does not honour the "total" |
| # keyword with old-style TypedDict(). See https://bugs.python.org/issue42059 |
| # The standard library TypedDict below Python 3.11 does not store runtime |
| # information about optional and required keys when using Required or NotRequired. |
| # Generic TypedDicts are also impossible using typing.TypedDict on Python <3.11. |
| TypedDict = typing.TypedDict |
| _TypedDictMeta = typing._TypedDictMeta |
| is_typeddict = typing.is_typeddict |
| else: |
| def _check_fails(cls, other): |
| try: |
| if sys._getframe(1).f_globals['__name__'] not in ['abc', |
| 'functools', |
| 'typing']: |
| # Typed dicts are only for static structural subtyping. |
| raise TypeError('TypedDict does not support instance and class checks') |
| except (AttributeError, ValueError): |
| pass |
| return False |
| |
| def _dict_new(*args, **kwargs): |
| if not args: |
| raise TypeError('TypedDict.__new__(): not enough arguments') |
| _, args = args[0], args[1:] # allow the "cls" keyword be passed |
| return dict(*args, **kwargs) |
| |
| _dict_new.__text_signature__ = '($cls, _typename, _fields=None, /, **kwargs)' |
| |
| def _typeddict_new(*args, total=True, **kwargs): |
| if not args: |
| raise TypeError('TypedDict.__new__(): not enough arguments') |
| _, args = args[0], args[1:] # allow the "cls" keyword be passed |
| if args: |
| typename, args = args[0], args[1:] # allow the "_typename" keyword be passed |
| elif '_typename' in kwargs: |
| typename = kwargs.pop('_typename') |
| import warnings |
| warnings.warn("Passing '_typename' as keyword argument is deprecated", |
| DeprecationWarning, stacklevel=2) |
| else: |
| raise TypeError("TypedDict.__new__() missing 1 required positional " |
| "argument: '_typename'") |
| if args: |
| try: |
| fields, = args # allow the "_fields" keyword be passed |
| except ValueError: |
| raise TypeError('TypedDict.__new__() takes from 2 to 3 ' |
| f'positional arguments but {len(args) + 2} ' |
| 'were given') |
| elif '_fields' in kwargs and len(kwargs) == 1: |
| fields = kwargs.pop('_fields') |
| import warnings |
| warnings.warn("Passing '_fields' as keyword argument is deprecated", |
| DeprecationWarning, stacklevel=2) |
| else: |
| fields = None |
| |
| if fields is None: |
| fields = kwargs |
| elif kwargs: |
| raise TypeError("TypedDict takes either a dict or keyword arguments," |
| " but not both") |
| |
| ns = {'__annotations__': dict(fields)} |
| try: |
| # Setting correct module is necessary to make typed dict classes pickleable. |
| ns['__module__'] = sys._getframe(1).f_globals.get('__name__', '__main__') |
| except (AttributeError, ValueError): |
| pass |
| |
| return _TypedDictMeta(typename, (), ns, total=total) |
| |
| _typeddict_new.__text_signature__ = ('($cls, _typename, _fields=None,' |
| ' /, *, total=True, **kwargs)') |
| |
| class _TypedDictMeta(type): |
| def __init__(cls, name, bases, ns, total=True): |
| super().__init__(name, bases, ns) |
| |
| 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 syntaxes 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 |
| # Don't insert typing.Generic into __bases__ here, |
| # or Generic.__init_subclass__ will raise TypeError |
| # in the super().__new__() call. |
| # Instead, monkey-patch __bases__ onto the class after it's been created. |
| tp_dict = super().__new__(cls, name, (dict,), ns) |
| |
| if any(issubclass(base, typing.Generic) for base in bases): |
| tp_dict.__bases__ = (typing.Generic, dict) |
| _maybe_adjust_parameters(tp_dict) |
| |
| annotations = {} |
| own_annotations = ns.get('__annotations__', {}) |
| msg = "TypedDict('Name', {f0: t0, f1: t1, ...}); each t must be a type" |
| own_annotations = { |
| n: typing._type_check(tp, msg) for n, tp in own_annotations.items() |
| } |
| required_keys = set() |
| optional_keys = set() |
| |
| for base in bases: |
| annotations.update(base.__dict__.get('__annotations__', {})) |
| required_keys.update(base.__dict__.get('__required_keys__', ())) |
| optional_keys.update(base.__dict__.get('__optional_keys__', ())) |
| |
| annotations.update(own_annotations) |
| for annotation_key, annotation_type in own_annotations.items(): |
| annotation_origin = get_origin(annotation_type) |
| if annotation_origin is Annotated: |
| annotation_args = get_args(annotation_type) |
| if annotation_args: |
| annotation_type = annotation_args[0] |
| annotation_origin = get_origin(annotation_type) |
| |
| if annotation_origin is Required: |
| required_keys.add(annotation_key) |
| elif annotation_origin is NotRequired: |
| optional_keys.add(annotation_key) |
| elif total: |
| required_keys.add(annotation_key) |
| else: |
| optional_keys.add(annotation_key) |
| |
| tp_dict.__annotations__ = annotations |
| tp_dict.__required_keys__ = frozenset(required_keys) |
| tp_dict.__optional_keys__ = frozenset(optional_keys) |
| if not hasattr(tp_dict, '__total__'): |
| tp_dict.__total__ = total |
| return tp_dict |
| |
| __instancecheck__ = __subclasscheck__ = _check_fails |
| |
| TypedDict = _TypedDictMeta('TypedDict', (dict,), {}) |
| TypedDict.__module__ = __name__ |
| TypedDict.__doc__ = \ |
| """A simple typed name space. 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, with each key |
| 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 the Point2D.__annotations__ dict, and |
| the Point2D.__required_keys__ and Point2D.__optional_keys__ frozensets. |
| TypedDict supports two additional equivalent forms:: |
| |
| Point2D = TypedDict('Point2D', x=int, y=int, label=str) |
| Point2D = TypedDict('Point2D', {'x': int, 'y': int, 'label': str}) |
| |
| The class syntax is only supported in Python 3.6+, while two other |
| syntax forms work for Python 2.7 and 3.2+ |
| """ |
| |
| if hasattr(typing, "_TypedDictMeta"): |
| _TYPEDDICT_TYPES = (typing._TypedDictMeta, _TypedDictMeta) |
| else: |
| _TYPEDDICT_TYPES = (_TypedDictMeta,) |
| |
| def is_typeddict(tp): |
| """Check if an annotation is a TypedDict class |
| |
| For example:: |
| class Film(TypedDict): |
| title: str |
| year: int |
| |
| is_typeddict(Film) # => True |
| is_typeddict(Union[list, str]) # => False |
| """ |
| return isinstance(tp, tuple(_TYPEDDICT_TYPES)) |
| |
| |
| if hasattr(typing, "assert_type"): |
| assert_type = typing.assert_type |
| |
| else: |
| def assert_type(__val, __typ): |
| """Assert (to the type checker) that the value is of the given type. |
| |
| When the type checker encounters a call to assert_type(), it |
| emits an error if the value is not of the specified type:: |
| |
| def greet(name: str) -> None: |
| assert_type(name, str) # ok |
| assert_type(name, int) # type checker error |
| |
| At runtime this returns the first argument unchanged and otherwise |
| does nothing. |
| """ |
| return __val |
| |
| |
| if hasattr(typing, "Required"): |
| get_type_hints = typing.get_type_hints |
| else: |
| import functools |
| import types |
| |
| # replaces _strip_annotations() |
| def _strip_extras(t): |
| """Strips Annotated, Required and NotRequired from a given type.""" |
| if isinstance(t, _AnnotatedAlias): |
| return _strip_extras(t.__origin__) |
| if hasattr(t, "__origin__") and t.__origin__ in (Required, NotRequired): |
| return _strip_extras(t.__args__[0]) |
| if isinstance(t, typing._GenericAlias): |
| stripped_args = tuple(_strip_extras(a) for a in t.__args__) |
| if stripped_args == t.__args__: |
| return t |
| return t.copy_with(stripped_args) |
| if hasattr(types, "GenericAlias") and isinstance(t, types.GenericAlias): |
| stripped_args = tuple(_strip_extras(a) for a in t.__args__) |
| if stripped_args == t.__args__: |
| return t |
| return types.GenericAlias(t.__origin__, stripped_args) |
| if hasattr(types, "UnionType") and isinstance(t, types.UnionType): |
| stripped_args = tuple(_strip_extras(a) for a in t.__args__) |
| if stripped_args == t.__args__: |
| return t |
| return functools.reduce(operator.or_, stripped_args) |
| |
| return t |
| |
| def get_type_hints(obj, globalns=None, localns=None, include_extras=False): |
| """Return type hints for an object. |
| |
| This is often the same as obj.__annotations__, but it handles |
| forward references encoded as string literals, adds Optional[t] if a |
| default value equal to None is set and recursively replaces all |
| 'Annotated[T, ...]', 'Required[T]' or 'NotRequired[T]' with 'T' |
| (unless 'include_extras=True'). |
| |
| 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 hasattr(typing, "Annotated"): |
| hint = typing.get_type_hints( |
| obj, globalns=globalns, localns=localns, include_extras=True |
| ) |
| else: |
| hint = typing.get_type_hints(obj, globalns=globalns, localns=localns) |
| if include_extras: |
| return hint |
| return {k: _strip_extras(t) for k, t in hint.items()} |
| |
| |
| # Python 3.9+ has PEP 593 (Annotated) |
| if hasattr(typing, 'Annotated'): |
| Annotated = typing.Annotated |
| # Not exported and not a public API, but needed for get_origin() and get_args() |
| # to work. |
| _AnnotatedAlias = typing._AnnotatedAlias |
| # 3.7-3.8 |
| else: |
| class _AnnotatedAlias(typing._GenericAlias, _root=True): |
| """Runtime representation of an annotated type. |
| |
| At its core 'Annotated[t, dec1, dec2, ...]' is an alias for the type 't' |
| with extra annotations. The alias behaves like a normal typing alias, |
| instantiating is the same as instantiating the underlying type, binding |
| it to types is also the same. |
| """ |
| def __init__(self, origin, metadata): |
| if isinstance(origin, _AnnotatedAlias): |
| metadata = origin.__metadata__ + metadata |
| origin = origin.__origin__ |
| super().__init__(origin, origin) |
| self.__metadata__ = metadata |
| |
| def copy_with(self, params): |
| assert len(params) == 1 |
| new_type = params[0] |
| return _AnnotatedAlias(new_type, self.__metadata__) |
| |
| def __repr__(self): |
| return (f"typing_extensions.Annotated[{typing._type_repr(self.__origin__)}, " |
| f"{', '.join(repr(a) for a in self.__metadata__)}]") |
| |
| def __reduce__(self): |
| return operator.getitem, ( |
| Annotated, (self.__origin__,) + self.__metadata__ |
| ) |
| |
| def __eq__(self, other): |
| if not isinstance(other, _AnnotatedAlias): |
| return NotImplemented |
| if self.__origin__ != other.__origin__: |
| return False |
| return self.__metadata__ == other.__metadata__ |
| |
| def __hash__(self): |
| return hash((self.__origin__, self.__metadata__)) |
| |
| class Annotated: |
| """Add context specific metadata to a type. |
| |
| Example: Annotated[int, runtime_check.Unsigned] indicates to the |
| hypothetical runtime_check module that this type is an unsigned int. |
| Every other consumer of this type can ignore this metadata and treat |
| this type as int. |
| |
| The first argument to Annotated must be a valid type (and will be in |
| the __origin__ field), the remaining arguments are kept as a tuple in |
| the __extra__ field. |
| |
| Details: |
| |
| - It's an error to call `Annotated` with less than two arguments. |
| - Nested Annotated are flattened:: |
| |
| Annotated[Annotated[T, Ann1, Ann2], Ann3] == Annotated[T, Ann1, Ann2, Ann3] |
| |
| - Instantiating an annotated type is equivalent to instantiating the |
| underlying type:: |
| |
| Annotated[C, Ann1](5) == C(5) |
| |
| - Annotated can be used as a generic type alias:: |
| |
| Optimized = Annotated[T, runtime.Optimize()] |
| Optimized[int] == Annotated[int, runtime.Optimize()] |
| |
| OptimizedList = Annotated[List[T], runtime.Optimize()] |
| OptimizedList[int] == Annotated[List[int], runtime.Optimize()] |
| """ |
| |
| __slots__ = () |
| |
| def __new__(cls, *args, **kwargs): |
| raise TypeError("Type Annotated cannot be instantiated.") |
| |
| @typing._tp_cache |
| def __class_getitem__(cls, params): |
| if not isinstance(params, tuple) or len(params) < 2: |
| raise TypeError("Annotated[...] should be used " |
| "with at least two arguments (a type and an " |
| "annotation).") |
| allowed_special_forms = (ClassVar, Final) |
| if get_origin(params[0]) in allowed_special_forms: |
| origin = params[0] |
| else: |
| msg = "Annotated[t, ...]: t must be a type." |
| origin = typing._type_check(params[0], msg) |
| metadata = tuple(params[1:]) |
| return _AnnotatedAlias(origin, metadata) |
| |
| def __init_subclass__(cls, *args, **kwargs): |
| raise TypeError( |
| f"Cannot subclass {cls.__module__}.Annotated" |
| ) |
| |
| # Python 3.8 has get_origin() and get_args() but those implementations aren't |
| # Annotated-aware, so we can't use those. Python 3.9's versions don't support |
| # ParamSpecArgs and ParamSpecKwargs, so only Python 3.10's versions will do. |
| if sys.version_info[:2] >= (3, 10): |
| get_origin = typing.get_origin |
| get_args = typing.get_args |
| # 3.7-3.9 |
| else: |
| try: |
| # 3.9+ |
| from typing import _BaseGenericAlias |
| except ImportError: |
| _BaseGenericAlias = typing._GenericAlias |
| try: |
| # 3.9+ |
| from typing import GenericAlias as _typing_GenericAlias |
| except ImportError: |
| _typing_GenericAlias = typing._GenericAlias |
| |
| def get_origin(tp): |
| """Get the unsubscripted version of a type. |
| |
| This supports generic types, Callable, Tuple, Union, Literal, Final, ClassVar |
| and Annotated. 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 |
| get_origin(P.args) is P |
| """ |
| if isinstance(tp, _AnnotatedAlias): |
| return Annotated |
| if isinstance(tp, (typing._GenericAlias, _typing_GenericAlias, _BaseGenericAlias, |
| ParamSpecArgs, ParamSpecKwargs)): |
| return tp.__origin__ |
| if tp is typing.Generic: |
| return typing.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, _AnnotatedAlias): |
| return (tp.__origin__,) + tp.__metadata__ |
| if isinstance(tp, (typing._GenericAlias, _typing_GenericAlias)): |
| if getattr(tp, "_special", False): |
| return () |
| 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 () |
| |
| |
| # 3.10+ |
| if hasattr(typing, 'TypeAlias'): |
| TypeAlias = typing.TypeAlias |
| # 3.9 |
| elif sys.version_info[:2] >= (3, 9): |
| class _TypeAliasForm(typing._SpecialForm, _root=True): |
| def __repr__(self): |
| return 'typing_extensions.' + self._name |
| |
| @_TypeAliasForm |
| def TypeAlias(self, parameters): |
| """Special marker indicating that an assignment should |
| be recognized as a proper type alias definition by type |
| checkers. |
| |
| For example:: |
| |
| Predicate: TypeAlias = Callable[..., bool] |
| |
| It's invalid when used anywhere except as in the example above. |
| """ |
| raise TypeError(f"{self} is not subscriptable") |
| # 3.7-3.8 |
| else: |
| class _TypeAliasForm(typing._SpecialForm, _root=True): |
| def __repr__(self): |
| return 'typing_extensions.' + self._name |
| |
| TypeAlias = _TypeAliasForm('TypeAlias', |
| doc="""Special marker indicating that an assignment should |
| be recognized as a proper type alias definition by type |
| checkers. |
| |
| For example:: |
| |
| Predicate: TypeAlias = Callable[..., bool] |
| |
| It's invalid when used anywhere except as in the example |
| above.""") |
| |
| |
| class _DefaultMixin: |
| """Mixin for TypeVarLike defaults.""" |
| |
| __slots__ = () |
| |
| def __init__(self, default): |
| if isinstance(default, (tuple, list)): |
| self.__default__ = tuple((typing._type_check(d, "Default must be a type") |
| for d in default)) |
| elif default: |
| self.__default__ = typing._type_check(default, "Default must be a type") |
| else: |
| self.__default__ = None |
| |
| |
| # Add default and infer_variance parameters from PEP 696 and 695 |
| class TypeVar(typing.TypeVar, _DefaultMixin, _root=True): |
| """Type variable.""" |
| |
| __module__ = 'typing' |
| |
| def __init__(self, name, *constraints, bound=None, |
| covariant=False, contravariant=False, |
| default=None, infer_variance=False): |
| super().__init__(name, *constraints, bound=bound, covariant=covariant, |
| contravariant=contravariant) |
| _DefaultMixin.__init__(self, default) |
| self.__infer_variance__ = infer_variance |
| |
| # for pickling: |
| try: |
| def_mod = sys._getframe(1).f_globals.get('__name__', '__main__') |
| except (AttributeError, ValueError): |
| def_mod = None |
| if def_mod != 'typing_extensions': |
| self.__module__ = def_mod |
| |
| |
| # Python 3.10+ has PEP 612 |
| if hasattr(typing, 'ParamSpecArgs'): |
| ParamSpecArgs = typing.ParamSpecArgs |
| ParamSpecKwargs = typing.ParamSpecKwargs |
| # 3.7-3.9 |
| else: |
| class _Immutable: |
| """Mixin to indicate that object should not be copied.""" |
| __slots__ = () |
| |
| def __copy__(self): |
| return self |
| |
| def __deepcopy__(self, memo): |
| return self |
| |
| class ParamSpecArgs(_Immutable): |
| """The args for a ParamSpec object. |
| |
| Given a ParamSpec object P, P.args is an instance of ParamSpecArgs. |
| |
| ParamSpecArgs objects have a reference back to their ParamSpec: |
| |
| P.args.__origin__ is P |
| |
| This type is meant for runtime introspection and has no special meaning to |
| static type checkers. |
| """ |
| def __init__(self, origin): |
| self.__origin__ = origin |
| |
| def __repr__(self): |
| return f"{self.__origin__.__name__}.args" |
| |
| def __eq__(self, other): |
| if not isinstance(other, ParamSpecArgs): |
| return NotImplemented |
| return self.__origin__ == other.__origin__ |
| |
| class ParamSpecKwargs(_Immutable): |
| """The kwargs for a ParamSpec object. |
| |
| Given a ParamSpec object P, P.kwargs is an instance of ParamSpecKwargs. |
| |
| ParamSpecKwargs objects have a reference back to their ParamSpec: |
| |
| P.kwargs.__origin__ is P |
| |
| This type is meant for runtime introspection and has no special meaning to |
| static type checkers. |
| """ |
| def __init__(self, origin): |
| self.__origin__ = origin |
| |
| def __repr__(self): |
| return f"{self.__origin__.__name__}.kwargs" |
| |
| def __eq__(self, other): |
| if not isinstance(other, ParamSpecKwargs): |
| return NotImplemented |
| return self.__origin__ == other.__origin__ |
| |
| # 3.10+ |
| if hasattr(typing, 'ParamSpec'): |
| |
| # Add default Parameter - PEP 696 |
| class ParamSpec(typing.ParamSpec, _DefaultMixin, _root=True): |
| """Parameter specification variable.""" |
| |
| __module__ = 'typing' |
| |
| def __init__(self, name, *, bound=None, covariant=False, contravariant=False, |
| default=None): |
| super().__init__(name, bound=bound, covariant=covariant, |
| contravariant=contravariant) |
| _DefaultMixin.__init__(self, default) |
| |
| # for pickling: |
| try: |
| def_mod = sys._getframe(1).f_globals.get('__name__', '__main__') |
| except (AttributeError, ValueError): |
| def_mod = None |
| if def_mod != 'typing_extensions': |
| self.__module__ = def_mod |
| |
| # 3.7-3.9 |
| else: |
| |
| # Inherits from list as a workaround for Callable checks in Python < 3.9.2. |
| class ParamSpec(list, _DefaultMixin): |
| """Parameter specification variable. |
| |
| Usage:: |
| |
| P = ParamSpec('P') |
| |
| Parameter specification variables exist primarily for the benefit of static |
| type checkers. They are used to forward the parameter types of one |
| callable to another callable, a pattern commonly found in higher order |
| functions and decorators. They are only valid when used in ``Concatenate``, |
| or s the first argument to ``Callable``. In Python 3.10 and higher, |
| they are also supported in user-defined Generics at runtime. |
| See class Generic for more information on generic types. An |
| example for annotating a decorator:: |
| |
| T = TypeVar('T') |
| P = ParamSpec('P') |
| |
| def add_logging(f: Callable[P, T]) -> Callable[P, T]: |
| '''A type-safe decorator to add logging to a function.''' |
| def inner(*args: P.args, **kwargs: P.kwargs) -> T: |
| logging.info(f'{f.__name__} was called') |
| return f(*args, **kwargs) |
| return inner |
| |
| @add_logging |
| def add_two(x: float, y: float) -> float: |
| '''Add two numbers together.''' |
| return x + y |
| |
| Parameter specification variables defined with covariant=True or |
| contravariant=True can be used to declare covariant or contravariant |
| generic types. These keyword arguments are valid, but their actual semantics |
| are yet to be decided. See PEP 612 for details. |
| |
| Parameter specification variables can be introspected. e.g.: |
| |
| P.__name__ == 'T' |
| P.__bound__ == None |
| P.__covariant__ == False |
| P.__contravariant__ == False |
| |
| Note that only parameter specification variables defined in global scope can |
| be pickled. |
| """ |
| |
| # Trick Generic __parameters__. |
| __class__ = typing.TypeVar |
| |
| @property |
| def args(self): |
| return ParamSpecArgs(self) |
| |
| @property |
| def kwargs(self): |
| return ParamSpecKwargs(self) |
| |
| def __init__(self, name, *, bound=None, covariant=False, contravariant=False, |
| default=None): |
| super().__init__([self]) |
| self.__name__ = name |
| self.__covariant__ = bool(covariant) |
| self.__contravariant__ = bool(contravariant) |
| if bound: |
| self.__bound__ = typing._type_check(bound, 'Bound must be a type.') |
| else: |
| self.__bound__ = None |
| _DefaultMixin.__init__(self, default) |
| |
| # for pickling: |
| try: |
| def_mod = sys._getframe(1).f_globals.get('__name__', '__main__') |
| except (AttributeError, ValueError): |
| def_mod = None |
| if def_mod != 'typing_extensions': |
| self.__module__ = def_mod |
| |
| def __repr__(self): |
| if self.__covariant__: |
| prefix = '+' |
| elif self.__contravariant__: |
| prefix = '-' |
| else: |
| prefix = '~' |
| return prefix + self.__name__ |
| |
| def __hash__(self): |
| return object.__hash__(self) |
| |
| def __eq__(self, other): |
| return self is other |
| |
| def __reduce__(self): |
| return self.__name__ |
| |
| # Hack to get typing._type_check to pass. |
| def __call__(self, *args, **kwargs): |
| pass |
| |
| |
| # 3.7-3.9 |
| if not hasattr(typing, 'Concatenate'): |
| # Inherits from list as a workaround for Callable checks in Python < 3.9.2. |
| class _ConcatenateGenericAlias(list): |
| |
| # Trick Generic into looking into this for __parameters__. |
| __class__ = typing._GenericAlias |
| |
| # Flag in 3.8. |
| _special = False |
| |
| def __init__(self, origin, args): |
| super().__init__(args) |
| self.__origin__ = origin |
| self.__args__ = args |
| |
| def __repr__(self): |
| _type_repr = typing._type_repr |
| return (f'{_type_repr(self.__origin__)}' |
| f'[{", ".join(_type_repr(arg) for arg in self.__args__)}]') |
| |
| def __hash__(self): |
| return hash((self.__origin__, self.__args__)) |
| |
| # Hack to get typing._type_check to pass in Generic. |
| def __call__(self, *args, **kwargs): |
| pass |
| |
| @property |
| def __parameters__(self): |
| return tuple( |
| tp for tp in self.__args__ if isinstance(tp, (typing.TypeVar, ParamSpec)) |
| ) |
| |
| |
| # 3.7-3.9 |
| @typing._tp_cache |
| def _concatenate_getitem(self, parameters): |
| if parameters == (): |
| raise TypeError("Cannot take a Concatenate of no types.") |
| if not isinstance(parameters, tuple): |
| parameters = (parameters,) |
| if not isinstance(parameters[-1], ParamSpec): |
| raise TypeError("The last parameter to Concatenate should be a " |
| "ParamSpec variable.") |
| msg = "Concatenate[arg, ...]: each arg must be a type." |
| parameters = tuple(typing._type_check(p, msg) for p in parameters) |
| return _ConcatenateGenericAlias(self, parameters) |
| |
| |
| # 3.10+ |
| if hasattr(typing, 'Concatenate'): |
| Concatenate = typing.Concatenate |
| _ConcatenateGenericAlias = typing._ConcatenateGenericAlias # noqa |
| # 3.9 |
| elif sys.version_info[:2] >= (3, 9): |
| @_TypeAliasForm |
| def Concatenate(self, parameters): |
| """Used in conjunction with ``ParamSpec`` and ``Callable`` to represent a |
| higher order function which adds, removes or transforms parameters of a |
| callable. |
| |
| For example:: |
| |
| Callable[Concatenate[int, P], int] |
| |
| See PEP 612 for detailed information. |
| """ |
| return _concatenate_getitem(self, parameters) |
| # 3.7-8 |
| else: |
| class _ConcatenateForm(typing._SpecialForm, _root=True): |
| def __repr__(self): |
| return 'typing_extensions.' + self._name |
| |
| def __getitem__(self, parameters): |
| return _concatenate_getitem(self, parameters) |
| |
| Concatenate = _ConcatenateForm( |
| 'Concatenate', |
| doc="""Used in conjunction with ``ParamSpec`` and ``Callable`` to represent a |
| higher order function which adds, removes or transforms parameters of a |
| callable. |
| |
| For example:: |
| |
| Callable[Concatenate[int, P], int] |
| |
| See PEP 612 for detailed information. |
| """) |
| |
| # 3.10+ |
| if hasattr(typing, 'TypeGuard'): |
| TypeGuard = typing.TypeGuard |
| # 3.9 |
| elif sys.version_info[:2] >= (3, 9): |
| class _TypeGuardForm(typing._SpecialForm, _root=True): |
| def __repr__(self): |
| return 'typing_extensions.' + self._name |
| |
| @_TypeGuardForm |
| def TypeGuard(self, parameters): |
| """Special typing form used to annotate the return type of a user-defined |
| type guard function. ``TypeGuard`` only accepts a single type argument. |
| At runtime, functions marked this way should return a boolean. |
| |
| ``TypeGuard`` aims to benefit *type narrowing* -- a technique used by static |
| type checkers to determine a more precise type of an expression within a |
| program's code flow. Usually type narrowing is done by analyzing |
| conditional code flow and applying the narrowing to a block of code. The |
| conditional expression here is sometimes referred to as a "type guard". |
| |
| Sometimes it would be convenient to use a user-defined boolean function |
| as a type guard. Such a function should use ``TypeGuard[...]`` as its |
| return type to alert static type checkers to this intention. |
| |
| Using ``-> TypeGuard`` tells the static type checker that for a given |
| function: |
| |
| 1. The return value is a boolean. |
| 2. If the return value is ``True``, the type of its argument |
| is the type inside ``TypeGuard``. |
| |
| For example:: |
| |
| def is_str(val: Union[str, float]): |
| # "isinstance" type guard |
| if isinstance(val, str): |
| # Type of ``val`` is narrowed to ``str`` |
| ... |
| else: |
| # Else, type of ``val`` is narrowed to ``float``. |
| ... |
| |
| Strict type narrowing is not enforced -- ``TypeB`` need not be a narrower |
| form of ``TypeA`` (it can even be a wider form) and this may lead to |
| type-unsafe results. The main reason is to allow for things like |
| narrowing ``List[object]`` to ``List[str]`` even though the latter is not |
| a subtype of the former, since ``List`` is invariant. The responsibility of |
| writing type-safe type guards is left to the user. |
| |
| ``TypeGuard`` also works with type variables. For more information, see |
| PEP 647 (User-Defined Type Guards). |
| """ |
| item = typing._type_check(parameters, f'{self} accepts only a single type.') |
| return typing._GenericAlias(self, (item,)) |
| # 3.7-3.8 |
| else: |
| class _TypeGuardForm(typing._SpecialForm, _root=True): |
| |
| def __repr__(self): |
| return 'typing_extensions.' + self._name |
| |
| def __getitem__(self, parameters): |
| item = typing._type_check(parameters, |
| f'{self._name} accepts only a single type') |
| return typing._GenericAlias(self, (item,)) |
| |
| TypeGuard = _TypeGuardForm( |
| 'TypeGuard', |
| doc="""Special typing form used to annotate the return type of a user-defined |
| type guard function. ``TypeGuard`` only accepts a single type argument. |
| At runtime, functions marked this way should return a boolean. |
| |
| ``TypeGuard`` aims to benefit *type narrowing* -- a technique used by static |
| type checkers to determine a more precise type of an expression within a |
| program's code flow. Usually type narrowing is done by analyzing |
| conditional code flow and applying the narrowing to a block of code. The |
| conditional expression here is sometimes referred to as a "type guard". |
| |
| Sometimes it would be convenient to use a user-defined boolean function |
| as a type guard. Such a function should use ``TypeGuard[...]`` as its |
| return type to alert static type checkers to this intention. |
| |
| Using ``-> TypeGuard`` tells the static type checker that for a given |
| function: |
| |
| 1. The return value is a boolean. |
| 2. If the return value is ``True``, the type of its argument |
| is the type inside ``TypeGuard``. |
| |
| For example:: |
| |
| def is_str(val: Union[str, float]): |
| # "isinstance" type guard |
| if isinstance(val, str): |
| # Type of ``val`` is narrowed to ``str`` |
| ... |
| else: |
| # Else, type of ``val`` is narrowed to ``float``. |
| ... |
| |
| Strict type narrowing is not enforced -- ``TypeB`` need not be a narrower |
| form of ``TypeA`` (it can even be a wider form) and this may lead to |
| type-unsafe results. The main reason is to allow for things like |
| narrowing ``List[object]`` to ``List[str]`` even though the latter is not |
| a subtype of the former, since ``List`` is invariant. The responsibility of |
| writing type-safe type guards is left to the user. |
| |
| ``TypeGuard`` also works with type variables. For more information, see |
| PEP 647 (User-Defined Type Guards). |
| """) |
| |
| |
| # Vendored from cpython typing._SpecialFrom |
| class _SpecialForm(typing._Final, _root=True): |
| __slots__ = ('_name', '__doc__', '_getitem') |
| |
| def __init__(self, getitem): |
| self._getitem = getitem |
| self._name = getitem.__name__ |
| self.__doc__ = getitem.__doc__ |
| |
| def __getattr__(self, item): |
| if item in {'__name__', '__qualname__'}: |
| return self._name |
| |
| raise AttributeError(item) |
| |
| def __mro_entries__(self, bases): |
| raise TypeError(f"Cannot subclass {self!r}") |
| |
| def __repr__(self): |
| return f'typing_extensions.{self._name}' |
| |
| def __reduce__(self): |
| return self._name |
| |
| def __call__(self, *args, **kwds): |
| raise TypeError(f"Cannot instantiate {self!r}") |
| |
| def __or__(self, other): |
| return typing.Union[self, other] |
| |
| def __ror__(self, other): |
| return typing.Union[other, self] |
| |
| 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()") |
| |
| @typing._tp_cache |
| def __getitem__(self, parameters): |
| return self._getitem(self, parameters) |
| |
| |
| if hasattr(typing, "LiteralString"): |
| LiteralString = typing.LiteralString |
| else: |
| @_SpecialForm |
| def LiteralString(self, params): |
| """Represents an arbitrary literal string. |
| |
| Example:: |
| |
| from pip._vendor.typing_extensions import LiteralString |
| |
| def query(sql: LiteralString) -> ...: |
| ... |
| |
| query("SELECT * FROM table") # ok |
| query(f"SELECT * FROM {input()}") # not ok |
| |
| See PEP 675 for details. |
| |
| """ |
| raise TypeError(f"{self} is not subscriptable") |
| |
| |
| if hasattr(typing, "Self"): |
| Self = typing.Self |
| else: |
| @_SpecialForm |
| def Self(self, params): |
| """Used to spell the type of "self" in classes. |
| |
| Example:: |
| |
| from typing import Self |
| |
| class ReturnsSelf: |
| def parse(self, data: bytes) -> Self: |
| ... |
| return self |
| |
| """ |
| |
| raise TypeError(f"{self} is not subscriptable") |
| |
| |
| if hasattr(typing, "Never"): |
| Never = typing.Never |
| else: |
| @_SpecialForm |
| def Never(self, params): |
| """The bottom type, a type that has no members. |
| |
| This can be used to define a function that should never be |
| called, or a function that never returns:: |
| |
| from pip._vendor.typing_extensions import Never |
| |
| def never_call_me(arg: Never) -> None: |
| pass |
| |
| def int_or_str(arg: int | str) -> None: |
| never_call_me(arg) # type checker error |
| match arg: |
| case int(): |
| print("It's an int") |
| case str(): |
| print("It's a str") |
| case _: |
| never_call_me(arg) # ok, arg is of type Never |
| |
| """ |
| |
| raise TypeError(f"{self} is not subscriptable") |
| |
| |
| if hasattr(typing, 'Required'): |
| Required = typing.Required |
| NotRequired = typing.NotRequired |
| elif sys.version_info[:2] >= (3, 9): |
| class _ExtensionsSpecialForm(typing._SpecialForm, _root=True): |
| def __repr__(self): |
| return 'typing_extensions.' + self._name |
| |
| @_ExtensionsSpecialForm |
| def Required(self, parameters): |
| """A special typing construct to mark a key of a total=False TypedDict |
| as required. For example: |
| |
| class Movie(TypedDict, total=False): |
| title: Required[str] |
| year: int |
| |
| m = Movie( |
| title='The Matrix', # typechecker error if key is omitted |
| year=1999, |
| ) |
| |
| There is no runtime checking that a required key is actually provided |
| when instantiating a related TypedDict. |
| """ |
| item = typing._type_check(parameters, f'{self._name} accepts only a single type.') |
| return typing._GenericAlias(self, (item,)) |
| |
| @_ExtensionsSpecialForm |
| def NotRequired(self, parameters): |
| """A special typing construct to mark a key of a TypedDict as |
| potentially missing. For example: |
| |
| class Movie(TypedDict): |
| title: str |
| year: NotRequired[int] |
| |
| m = Movie( |
| title='The Matrix', # typechecker error if key is omitted |
| year=1999, |
| ) |
| """ |
| item = typing._type_check(parameters, f'{self._name} accepts only a single type.') |
| return typing._GenericAlias(self, (item,)) |
| |
| else: |
| class _RequiredForm(typing._SpecialForm, _root=True): |
| def __repr__(self): |
| return 'typing_extensions.' + self._name |
| |
| def __getitem__(self, parameters): |
| item = typing._type_check(parameters, |
| f'{self._name} accepts only a single type.') |
| return typing._GenericAlias(self, (item,)) |
| |
| Required = _RequiredForm( |
| 'Required', |
| doc="""A special typing construct to mark a key of a total=False TypedDict |
| as required. For example: |
| |
| class Movie(TypedDict, total=False): |
| title: Required[str] |
| year: int |
| |
| m = Movie( |
| title='The Matrix', # typechecker error if key is omitted |
| year=1999, |
| ) |
| |
| There is no runtime checking that a required key is actually provided |
| when instantiating a related TypedDict. |
| """) |
| NotRequired = _RequiredForm( |
| 'NotRequired', |
| doc="""A special typing construct to mark a key of a TypedDict as |
| potentially missing. For example: |
| |
| class Movie(TypedDict): |
| title: str |
| year: NotRequired[int] |
| |
| m = Movie( |
| title='The Matrix', # typechecker error if key is omitted |
| year=1999, |
| ) |
| """) |
| |
| |
| if hasattr(typing, "Unpack"): # 3.11+ |
| Unpack = typing.Unpack |
| elif sys.version_info[:2] >= (3, 9): |
| class _UnpackSpecialForm(typing._SpecialForm, _root=True): |
| def __repr__(self): |
| return 'typing_extensions.' + self._name |
| |
| class _UnpackAlias(typing._GenericAlias, _root=True): |
| __class__ = typing.TypeVar |
| |
| @_UnpackSpecialForm |
| def Unpack(self, parameters): |
| """A special typing construct to unpack a variadic type. For example: |
| |
| Shape = TypeVarTuple('Shape') |
| Batch = NewType('Batch', int) |
| |
| def add_batch_axis( |
| x: Array[Unpack[Shape]] |
| ) -> Array[Batch, Unpack[Shape]]: ... |
| |
| """ |
| item = typing._type_check(parameters, f'{self._name} accepts only a single type.') |
| return _UnpackAlias(self, (item,)) |
| |
| def _is_unpack(obj): |
| return isinstance(obj, _UnpackAlias) |
| |
| else: |
| class _UnpackAlias(typing._GenericAlias, _root=True): |
| __class__ = typing.TypeVar |
| |
| class _UnpackForm(typing._SpecialForm, _root=True): |
| def __repr__(self): |
| return 'typing_extensions.' + self._name |
| |
| def __getitem__(self, parameters): |
| item = typing._type_check(parameters, |
| f'{self._name} accepts only a single type.') |
| return _UnpackAlias(self, (item,)) |
| |
| Unpack = _UnpackForm( |
| 'Unpack', |
| doc="""A special typing construct to unpack a variadic type. For example: |
| |
| Shape = TypeVarTuple('Shape') |
| Batch = NewType('Batch', int) |
| |
| def add_batch_axis( |
| x: Array[Unpack[Shape]] |
| ) -> Array[Batch, Unpack[Shape]]: ... |
| |
| """) |
| |
| def _is_unpack(obj): |
| return isinstance(obj, _UnpackAlias) |
| |
| |
| if hasattr(typing, "TypeVarTuple"): # 3.11+ |
| |
| # Add default Parameter - PEP 696 |
| class TypeVarTuple(typing.TypeVarTuple, _DefaultMixin, _root=True): |
| """Type variable tuple.""" |
| |
| def __init__(self, name, *, default=None): |
| super().__init__(name) |
| _DefaultMixin.__init__(self, default) |
| |
| # for pickling: |
| try: |
| def_mod = sys._getframe(1).f_globals.get('__name__', '__main__') |
| except (AttributeError, ValueError): |
| def_mod = None |
| if def_mod != 'typing_extensions': |
| self.__module__ = def_mod |
| |
| else: |
| class TypeVarTuple(_DefaultMixin): |
| """Type variable tuple. |
| |
| Usage:: |
| |
| Ts = TypeVarTuple('Ts') |
| |
| In the same way that a normal type variable is a stand-in for a single |
| type such as ``int``, a type variable *tuple* is a stand-in for a *tuple* |
| type such as ``Tuple[int, str]``. |
| |
| Type variable tuples can be used in ``Generic`` declarations. |
| Consider the following example:: |
| |
| class Array(Generic[*Ts]): ... |
| |
| The ``Ts`` type variable tuple here behaves like ``tuple[T1, T2]``, |
| where ``T1`` and ``T2`` are type variables. To use these type variables |
| as type parameters of ``Array``, we must *unpack* the type variable tuple using |
| the star operator: ``*Ts``. The signature of ``Array`` then behaves |
| as if we had simply written ``class Array(Generic[T1, T2]): ...``. |
| In contrast to ``Generic[T1, T2]``, however, ``Generic[*Shape]`` allows |
| us to parameterise the class with an *arbitrary* number of type parameters. |
| |
| Type variable tuples can be used anywhere a normal ``TypeVar`` can. |
| This includes class definitions, as shown above, as well as function |
| signatures and variable annotations:: |
| |
| class Array(Generic[*Ts]): |
| |
| def __init__(self, shape: Tuple[*Ts]): |
| self._shape: Tuple[*Ts] = shape |
| |
| def get_shape(self) -> Tuple[*Ts]: |
| return self._shape |
| |
| shape = (Height(480), Width(640)) |
| x: Array[Height, Width] = Array(shape) |
| y = abs(x) # Inferred type is Array[Height, Width] |
| z = x + x # ... is Array[Height, Width] |
| x.get_shape() # ... is tuple[Height, Width] |
| |
| """ |
| |
| # Trick Generic __parameters__. |
| __class__ = typing.TypeVar |
| |
| def __iter__(self): |
| yield self.__unpacked__ |
| |
| def __init__(self, name, *, default=None): |
| self.__name__ = name |
| _DefaultMixin.__init__(self, default) |
| |
| # for pickling: |
| try: |
| def_mod = sys._getframe(1).f_globals.get('__name__', '__main__') |
| except (AttributeError, ValueError): |
| def_mod = None |
| if def_mod != 'typing_extensions': |
| self.__module__ = def_mod |
| |
| self.__unpacked__ = Unpack[self] |
| |
| def __repr__(self): |
| return self.__name__ |
| |
| def __hash__(self): |
| return object.__hash__(self) |
| |
| def __eq__(self, other): |
| return self is other |
| |
| def __reduce__(self): |
| return self.__name__ |
| |
| def __init_subclass__(self, *args, **kwds): |
| if '_root' not in kwds: |
| raise TypeError("Cannot subclass special typing classes") |
| |
| |
| if hasattr(typing, "reveal_type"): |
| reveal_type = typing.reveal_type |
| else: |
| def reveal_type(__obj: T) -> T: |
| """Reveal the inferred type of a variable. |
| |
| When a static type checker encounters a call to ``reveal_type()``, |
| it will emit the inferred type of the argument:: |
| |
| x: int = 1 |
| reveal_type(x) |
| |
| Running a static type checker (e.g., ``mypy``) on this example |
| will produce output similar to 'Revealed type is "builtins.int"'. |
| |
| At runtime, the function prints the runtime type of the |
| argument and returns it unchanged. |
| |
| """ |
| print(f"Runtime type is {type(__obj).__name__!r}", file=sys.stderr) |
| return __obj |
| |
| |
| if hasattr(typing, "assert_never"): |
| assert_never = typing.assert_never |
| else: |
| def assert_never(__arg: Never) -> Never: |
| """Assert to the type checker that a line of code is unreachable. |
| |
| Example:: |
| |
| def int_or_str(arg: int | str) -> None: |
| match arg: |
| case int(): |
| print("It's an int") |
| case str(): |
| print("It's a str") |
| case _: |
| assert_never(arg) |
| |
| If a type checker finds that a call to assert_never() is |
| reachable, it will emit an error. |
| |
| At runtime, this throws an exception when called. |
| |
| """ |
| raise AssertionError("Expected code to be unreachable") |
| |
| |
| if hasattr(typing, 'dataclass_transform'): |
| dataclass_transform = typing.dataclass_transform |
| else: |
| def dataclass_transform( |
| *, |
| eq_default: bool = True, |
| order_default: bool = False, |
| kw_only_default: bool = False, |
| field_specifiers: typing.Tuple[ |
| typing.Union[typing.Type[typing.Any], typing.Callable[..., typing.Any]], |
| ... |
| ] = (), |
| **kwargs: typing.Any, |
| ) -> typing.Callable[[T], T]: |
| """Decorator that marks a function, class, or metaclass as providing |
| dataclass-like behavior. |
| |
| Example: |
| |
| from pip._vendor.typing_extensions import dataclass_transform |
| |
| _T = TypeVar("_T") |
| |
| # Used on a decorator function |
| @dataclass_transform() |
| def create_model(cls: type[_T]) -> type[_T]: |
| ... |
| return cls |
| |
| @create_model |
| class CustomerModel: |
| id: int |
| name: str |
| |
| # Used on a base class |
| @dataclass_transform() |
| class ModelBase: ... |
| |
| class CustomerModel(ModelBase): |
| id: int |
| name: str |
| |
| # Used on a metaclass |
| @dataclass_transform() |
| class ModelMeta(type): ... |
| |
| class ModelBase(metaclass=ModelMeta): ... |
| |
| class CustomerModel(ModelBase): |
| id: int |
| name: str |
| |
| Each of the ``CustomerModel`` classes defined in this example will now |
| behave similarly to a dataclass created with the ``@dataclasses.dataclass`` |
| decorator. For example, the type checker will synthesize an ``__init__`` |
| method. |
| |
| The arguments to this decorator can be used to customize this behavior: |
| - ``eq_default`` indicates whether the ``eq`` parameter is assumed to be |
| True or False if it is omitted by the caller. |
| - ``order_default`` indicates whether the ``order`` parameter is |
| assumed to be True or False if it is omitted by the caller. |
| - ``kw_only_default`` indicates whether the ``kw_only`` parameter is |
| assumed to be True or False if it is omitted by the caller. |
| - ``field_specifiers`` specifies a static list of supported classes |
| or functions that describe fields, similar to ``dataclasses.field()``. |
| |
| At runtime, this decorator records its arguments in the |
| ``__dataclass_transform__`` attribute on the decorated object. |
| |
| See PEP 681 for details. |
| |
| """ |
| def decorator(cls_or_fn): |
| cls_or_fn.__dataclass_transform__ = { |
| "eq_default": eq_default, |
| "order_default": order_default, |
| "kw_only_default": kw_only_default, |
| "field_specifiers": field_specifiers, |
| "kwargs": kwargs, |
| } |
| return cls_or_fn |
| return decorator |
| |
| |
| if hasattr(typing, "override"): |
| override = typing.override |
| else: |
| _F = typing.TypeVar("_F", bound=typing.Callable[..., typing.Any]) |
| |
| def override(__arg: _F) -> _F: |
| """Indicate that a method is intended to override a method in a base class. |
| |
| Usage: |
| |
| class Base: |
| def method(self) -> None: ... |
| pass |
| |
| class Child(Base): |
| @override |
| def method(self) -> None: |
| super().method() |
| |
| When this decorator is applied to a method, the type checker will |
| validate that it overrides a method with the same name on a base class. |
| This helps prevent bugs that may occur when a base class is changed |
| without an equivalent change to a child class. |
| |
| See PEP 698 for details. |
| |
| """ |
| return __arg |
| |
| |
| # We have to do some monkey patching to deal with the dual nature of |
| # Unpack/TypeVarTuple: |
| # - We want Unpack to be a kind of TypeVar so it gets accepted in |
| # Generic[Unpack[Ts]] |
| # - We want it to *not* be treated as a TypeVar for the purposes of |
| # counting generic parameters, so that when we subscript a generic, |
| # the runtime doesn't try to substitute the Unpack with the subscripted type. |
| if not hasattr(typing, "TypeVarTuple"): |
| typing._collect_type_vars = _collect_type_vars |
| typing._check_generic = _check_generic |
| |
| |
| # Backport typing.NamedTuple as it exists in Python 3.11. |
| # In 3.11, the ability to define generic `NamedTuple`s was supported. |
| # This was explicitly disallowed in 3.9-3.10, and only half-worked in <=3.8. |
| if sys.version_info >= (3, 11): |
| NamedTuple = typing.NamedTuple |
| else: |
| def _caller(): |
| try: |
| return sys._getframe(2).f_globals.get('__name__', '__main__') |
| except (AttributeError, ValueError): # For platforms without _getframe() |
| return None |
| |
| def _make_nmtuple(name, types, module, defaults=()): |
| fields = [n for n, t in types] |
| annotations = {n: typing._type_check(t, f"field {n} annotation must be a type") |
| for n, t in types} |
| nm_tpl = collections.namedtuple(name, fields, |
| defaults=defaults, module=module) |
| nm_tpl.__annotations__ = nm_tpl.__new__.__annotations__ = annotations |
| # The `_field_types` attribute was removed in 3.9; |
| # in earlier versions, it is the same as the `__annotations__` attribute |
| if sys.version_info < (3, 9): |
| nm_tpl._field_types = annotations |
| return nm_tpl |
| |
| _prohibited_namedtuple_fields = typing._prohibited |
| _special_namedtuple_fields = frozenset({'__module__', '__name__', '__annotations__'}) |
| |
| class _NamedTupleMeta(type): |
| def __new__(cls, typename, bases, ns): |
| assert _NamedTuple in bases |
| for base in bases: |
| if base is not _NamedTuple and base is not typing.Generic: |
| raise TypeError( |
| 'can only inherit from a NamedTuple type and Generic') |
| bases = tuple(tuple if base is _NamedTuple else base for base in bases) |
| types = ns.get('__annotations__', {}) |
| default_names = [] |
| for field_name in types: |
| if field_name in ns: |
| default_names.append(field_name) |
| elif default_names: |
| raise TypeError(f"Non-default namedtuple field {field_name} " |
| f"cannot follow default field" |
| f"{'s' if len(default_names) > 1 else ''} " |
| f"{', '.join(default_names)}") |
| nm_tpl = _make_nmtuple( |
| typename, types.items(), |
| defaults=[ns[n] for n in default_names], |
| module=ns['__module__'] |
| ) |
| nm_tpl.__bases__ = bases |
| if typing.Generic in bases: |
| class_getitem = typing.Generic.__class_getitem__.__func__ |
| nm_tpl.__class_getitem__ = classmethod(class_getitem) |
| # update from user namespace without overriding special namedtuple attributes |
| for key in ns: |
| if key in _prohibited_namedtuple_fields: |
| raise AttributeError("Cannot overwrite NamedTuple attribute " + key) |
| elif key not in _special_namedtuple_fields and key not in nm_tpl._fields: |
| setattr(nm_tpl, key, ns[key]) |
| if typing.Generic in bases: |
| nm_tpl.__init_subclass__() |
| return nm_tpl |
| |
| def NamedTuple(__typename, __fields=None, **kwargs): |
| 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, module=_caller()) |
| |
| NamedTuple.__doc__ = typing.NamedTuple.__doc__ |
| _NamedTuple = type.__new__(_NamedTupleMeta, 'NamedTuple', (), {}) |
| |
| # On 3.8+, alter the signature so that it matches typing.NamedTuple. |
| # The signature of typing.NamedTuple on >=3.8 is invalid syntax in Python 3.7, |
| # so just leave the signature as it is on 3.7. |
| if sys.version_info >= (3, 8): |
| NamedTuple.__text_signature__ = '(typename, fields=None, /, **kwargs)' |
| |
| def _namedtuple_mro_entries(bases): |
| assert NamedTuple in bases |
| return (_NamedTuple,) |
| |
| NamedTuple.__mro_entries__ = _namedtuple_mro_entries |
