
"typing" --- Support for type hints
***********************************

**Source code:** Lib/typing.py

======================================================================

This module supports type hints as specified by **PEP 484**.  The most
fundamental support consists of the type "Any", "Union", "Tuple",
"Callable", "TypeVar", and "Generic".  For full specification please
see **PEP 484**.  For a simplified introduction to type hints see
**PEP 483**.

The function below takes and returns a string and is annotated as
follows:

   def greeting(name: str) -> str:
       return 'Hello ' + name

In the function "greeting", the argument "name" is expected to by of
type "str" and the return type "str". Subtypes are accepted as
arguments.


Type aliases
============

A type alias is defined by assigning the type to the alias:

   Vector = List[float]


Callable
========

Frameworks expecting callback functions of specific signatures might
be type hinted using *Callable[[Arg1Type, Arg2Type], ReturnType]*.

For example:

   from typing import Callable

   def feeder(get_next_item: Callable[[], str]) -> None:
       # Body

   def async_query(on_success: Callable[[int], None],
                   on_error: Callable[[int, Exception], None]) -> None:
       # Body

It is possible to declare the return type of a callable without
specifying the call signature by substituting a literal ellipsis for
the list of arguments in the type hint: "Callable[..., ReturnType]".
"None" as a type hint is a special case and is replaced by
"type(None)".


Generics
========

Since type information about objects kept in containers cannot be
statically inferred in a generic way, abstract base classes have been
extended to support subscription to denote expected types for
container elements.

   from typing import Mapping, Sequence

   def notify_by_email(employees: Sequence[Employee],
                       overrides: Mapping[str, str]) -> None: ...

Generics can be parametrized by using a new factory available in
typing called "TypeVar".

   from typing import Sequence, TypeVar

   T = TypeVar('T')      # Declare type variable

   def first(l: Sequence[T]) -> T:   # Generic function
       return l[0]


User-defined generic types
==========================

A user-defined class can be defined as a generic class.

   from typing import TypeVar, Generic
   from logging import Logger

   T = TypeVar('T')

   class LoggedVar(Generic[T]):
       def __init__(self, value: T, name: str, logger: Logger) -> None:
           self.name = name
           self.logger = logger
           self.value = value

       def set(self, new: T) -> None:
           self.log('Set ' + repr(self.value))
           self.value = new

       def get(self) -> T:
           self.log('Get ' + repr(self.value))
           return self.value

       def log(self, message: str) -> None:
           self.logger.info('{}: {}'.format(self.name, message))

"Generic[T]" as a base class defines that the class "LoggedVar" takes
a single type parameter "T" . This also makes "T" valid as a type
within the class body.

The "Generic" base class uses a metaclass that defines "__getitem__()"
so that "LoggedVar[t]" is valid as a type:

   from typing import Iterable

   def zero_all_vars(vars: Iterable[LoggedVar[int]]) -> None:
       for var in vars:
           var.set(0)

A generic type can have any number of type variables, and type
variables may be constrained:

   from typing import TypeVar, Generic
   ...

   T = TypeVar('T')
   S = TypeVar('S', int, str)

   class StrangePair(Generic[T, S]):
       ...

Each type variable argument to "Generic" must be distinct. This is
thus invalid:

   from typing import TypeVar, Generic
   ...

   T = TypeVar('T')

   class Pair(Generic[T, T]):   # INVALID
       ...

You can use multiple inheritance with "Generic":

   from typing import TypeVar, Generic, Sized

   T = TypeVar('T')

   class LinkedList(Sized, Generic[T]):
       ...

When inheriting from generic classes, some type variables could fixed:

   from typing import TypeVar, Mapping

   T = TypeVar('T')

   class MyDict(Mapping[str, T]):
       ...

In this case "MyDict" has a single parameter, "T".

Subclassing a generic class without specifying type parameters assumes
"Any" for each position. In the following example, "MyIterable" is not
generic but implicitly inherits from "Iterable[Any]":

   from typing import Iterable

   class MyIterable(Iterable): # Same as Iterable[Any]

The metaclass used by "Generic" is a subclass of "abc.ABCMeta". A
generic class can be an ABC by including abstract methods or
properties, and generic classes can also have ABCs as base classes
without a metaclass conflict.  Generic metaclasses are not supported.


The "Any" type
==============

A special kind of type is "Any". Every type is a subtype of "Any".
This is also true for the builtin type object. However, to the static
type checker these are completely different.

When the type of a value is "object", the type checker will reject
almost all operations on it, and assigning it to a variable (or using
it as a return value) of a more specialized type is a type error. On
the other hand, when a value has type "Any", the type checker will
allow all operations on it, and a value of type "Any" can be assigned
to a variable (or used as a return value) of a more constrained type.


Classes, functions, and decorators
==================================

The module defines the following classes, functions and decorators:

class class typing.Any

   Special type indicating an unconstrained type.

   * Any object is an instance of "Any".

   * Any class is a subclass of "Any".

   * As a special case, "Any" and "object" are subclasses of each
     other.

class class typing.TypeVar

   Type variable.

   Usage:

      T = TypeVar('T')  # Can be anything
      A = TypeVar('A', str, bytes)  # Must be str or bytes

   Type variables exist primarily for the benefit of static type
   checkers.  They serve as the parameters for generic types as well
   as for generic function definitions.  See class Generic for more
   information on generic types.  Generic functions work as follows:

      def repeat(x: T, n: int) -> Sequence[T]:
          """Return a list containing n references to x."""
          return [x]*n

      def longest(x: A, y: A) -> A:
          """Return the longest of two strings."""
          return x if len(x) >= len(y) else y

   The latter example's signature is essentially the overloading of
   "(str, str) -> str" and "(bytes, bytes) -> bytes".  Also note that
   if the arguments are instances of some subclass of "str", the
   return type is still plain "str".

   At runtime, "isinstance(x, T)" will raise "TypeError".  In general,
   "isinstance()" and "issublass()" should not be used with types.

   Type variables may be marked covariant or contravariant by passing
   "covariant=True" or "contravariant=True".  See **PEP 484** for more
   details.  By default type variables are invariant.  Alternatively,
   a type variable may specify an upper bound using "bound=<type>".
   This means that an actual type substituted (explicitly or
   implictly) for the type variable must be a subclass of the boundary
   type, see **PEP 484**.

class class typing.Union

   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.

   * 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]

   * If "Any" is present it is the sole survivor, e.g.:

        Union[int, Any] == Any

   * You cannot subclass or instantiate a union.

   * You cannot write "Union[X][Y]"

   * You can use "Optional[X]" as a shorthand for "Union[X, None]".

class class typing.Optional

   Optional type.

   "Optional[X]" is equivalent to "Union[X, type(None)]".

class class typing.Tuple

   Tuple type; "Tuple[X, Y]" is the is the type of a tuple of two
   items with the first item of type X and the second of type 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 literal
   ellipsis, e.g. "Tuple[int, ...]".

class class typing.Callable

   Callable type; "Callable[[int], str]" is a function of (int) ->
   str.

   The subscription syntax must always be used with exactly two
   values: the argument list and the return type.  The argument list
   must be a list of types; the return type must be a single type.

   There is no syntax to indicate optional or keyword arguments, such
   function types are rarely used as callback types. "Callable[...,
   ReturnType]" could be used to type hint a callable taking any
   number of arguments and returning "ReturnType". A plain "Callable"
   is equivalent to "Callable[..., Any]".

class class typing.Generic

   Abstract base class for generic types.

   A generic type is typically declared by inheriting from an
   instantiation of this class with one or more type variables. For
   example, a generic mapping type might be defined as:

      class Mapping(Generic[KT, VT]):
          def __getitem__(self, key: KT) -> VT:
              ...
              # Etc.

   This class can then be used as follows:

      X = TypeVar('X')
      Y = TypeVar('Y')
      def lookup_name(mapping: Mapping[X, Y], key: X, default: Y) -> Y:
          try:
              return mapping[key]
          except KeyError:
              return default

class class typing.Iterable(Generic[T_co])

   A generic version of the "collections.abc.Iterable".

class class typing.Iterator(Iterable[T_co])

   A generic version of the "collections.abc.Iterator".

class class typing.SupportsInt

   An ABC with one abstract method *__int__*.

class class typing.SupportsFloat

   An ABC with one abstract method *__float__*.

class class typing.SupportsAbs

   An ABC with one abstract method *__abs__* that is covariant in its
   return type.

class class typing.SupportsRound

   An ABC with one abstract method *__round__* that is covariant in
   its return type.

class class typing.Reversible

   An ABC with one abstract method *__reversed__* returning an
   *Iterator[T_co]*.

class class typing.Container(Generic[T_co])

   A generic version of "collections.abc.Container".

class class typing.AbstractSet(Sized, Iterable[T_co], Container[T_co])

   A generic version of "collections.abc.Set".

class class typing.MutableSet(AbstractSet[T])

   A generic version of "collections.abc.MutableSet".

class class typing.Mapping(Sized, Iterable[KT], Container[KT], Generic[VT_co])

   A generic version of "collections.abc.Mapping".

class class typing.MutableMapping(Mapping[KT, VT])

   A generic version of "collections.abc.MutableMapping".

class class typing.Sequence(Sized, Iterable[T_co], Container[T_co])

   A generic version of "collections.abc.Sequence".

class class typing.MutableSequence(Sequence[T])

   A generic version of "collections.abc.MutableSequence".

class class typing.ByteString(Sequence[int])

   A generic version of "collections.abc.ByteString".

   This type represents the types "bytes", "bytearray", and
   "memoryview".

   As a shorthand for this type, "bytes" can be used to annotate
   arguments of any of the types mentioned above.

class class typing.List(list, MutableSequence[T])

   Generic version of "list". Useful for annotating return types. To
   annotate arguments it is preferred to use abstract collection types
   such as "Mapping", "Sequence", or "AbstractSet".

   This type may be used as follows:

      T = TypeVar('T', int, float)

      def vec2(x: T, y: T) -> List[T]:
          return [x, y]

      def slice__to_4(vector: Sequence[T]) -> List[T]:
          return vector[0:4]

class class typing.AbstractSet(set, MutableSet[T])

   A generic version of "collections.abc.Set".

class class typing.MappingView(Sized, Iterable[T_co])

   A generic version of "collections.abc.MappingView".

class class typing.KeysView(MappingView[KT_co], AbstractSet[KT_co])

   A generic version of "collections.abc.KeysView".

class class typing.ItemsView(MappingView, Generic[KT_co, VT_co])

   A generic version of "collections.abc.ItemsView".

class class typing.ValuesView(MappingView[VT_co])

   A generic version of "collections.abc.ValuesView".

class class typing.Dict(dict, MutableMapping[KT, VT])

   A generic version of "dict". The usage of this type is as follows:

      def get_position_in_index(word_list: Dict[str, int], word: str) -> int:
          return word_list[word]

class class typing.Generator(Iterator[T_co], Generic[T_co, T_contra, V_co])

class class typing.io

   Wrapper namespace for I/O stream types.

   This defines the generic type "IO[AnyStr]" and aliases "TextIO" and
   "BinaryIO" for respectively "IO[str]" and "IO[bytes]". These
   representing the types of I/O streams such as returned by "open()".

class class typing.re

   Wrapper namespace for regular expression matching types.

   This defines the type aliases "Pattern" and "Match" which
   correspond to the return types from "re.compile()" and
   "re.match()".  These types (and the corresponding functions) are
   generic in "AnyStr" and can be made specific by writing
   "Pattern[str]", "Pattern[bytes]", "Match[str]", or "Match[bytes]".

typing.NamedTuple(typename, fields)

   Typed version of namedtuple.

   Usage:

      Employee = typing.NamedTuple('Employee', [('name', str), 'id', int)])

   This is equivalent to:

      Employee = collections.namedtuple('Employee', ['name', 'id'])

   The resulting class has one extra attribute: _field_types, giving a
   dict mapping field names to types.  (The field names are in the
   _fields attribute, which is part of the namedtuple API.)

typing.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).

typing.get_type_hints(obj)

   Return type hints for a function or method object.

   This is often the same as obj.__annotations__, but it handles
   forward references encoded as string literals, and if necessary
   adds Optional[t] if a default value equal to None is set.

@typing.no_type_check(arg)

   Decorator to indicate that annotations are not type hints.

   The argument must be a class or function; if it is a class, it
   applies recursively to all methods defined in that class (but not
   to methods defined in its superclasses or subclasses).

   This mutates the function(s) in place.

@typing.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.
