Issue #24272: Initial docs for typing.py (PEP 484). (Merge from 3.5.)

By Daniel Andrade Groppe and Ivan Levkivskyi.

Doc/library/typing.rst

@@ -13,3 +13,418 @@ fundamental support consists of the type :class:`Any`, :class:`Union`,
 :class:`Tuple`, :class:`Callable`, :class:`TypeVar`, and
 :class:`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.
+
+.. code-block:: python
+
+   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.
+
+.. code-block:: python
+
+   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.
+
+.. code-block:: python
+
+   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]):
+       ...
+
+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]
+
+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.
+
+Default argument values
+-----------------------
+
+Use a literal ellipsis `...` to declare an argument as having a default value::
+
+   from typing import AnyStr
+   
+   def foo(x: AnyStr, y: AnyStr = ...) -> AnyStr: ...
+
+
+Classes, functions, and decorators
+----------------------------------
+
+The module defines the following classes, functions and decorators:
+
+.. class:: 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:: 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:
+
+    .. code-block:: python
+
+       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.
+
+.. class:: 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:: Optional
+
+   Optional type.
+
+   `Optional[X]` is equivalent to `Union[X, type(None)]`.
+
+.. class:: 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:: 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:: 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:: Iterable(Generic[T_co])
+
+.. class:: Iterator(Iterable[T_co])
+
+.. class:: SupportsInt
+
+.. class:: SupportsFloat
+
+.. class:: SupportsAbs
+
+.. class:: SupportsRound
+
+.. class:: Reversible
+
+.. class:: Container(Generic[T_co])
+
+.. class:: AbstractSet(Sized, Iterable[T_co], Container[T_co])
+
+.. class:: MutableSet(AbstractSet[T])
+
+.. class:: Mapping(Sized, Iterable[KT_co], Container[KT_co], Generic[KT_co, VT_co])
+
+.. class:: MutableMapping(Mapping[KT, VT])
+
+.. class:: Sequence(Sized, Iterable[T_co], Container[T_co])
+
+.. class:: MutableSequence(Sequence[T])
+
+.. class:: ByteString(Sequence[int])
+
+.. class:: List(list, MutableSequence[T])
+
+.. class:: Set(set, MutableSet[T])
+
+.. class:: MappingView(Sized, Iterable[T_co])
+
+.. class:: KeysView(MappingView[KT_co], AbstractSet[KT_co])
+
+.. class:: ItemsView(MappingView, Generic[KT_co, VT_co])
+
+.. class:: ValuesView(MappingView[VT_co])
+
+.. class:: Dict(dict, MutableMapping[KT, VT])
+
+.. class:: Generator(Iterator[T_co], Generic[T_co, T_contra, V_co])
+
+.. class:: io
+
+   Wrapper namespace for IO generic classes.
+
+.. class:: re
+
+   Wrapper namespace for re type classes.
+
+.. function:: 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.)
+
+.. function:: 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).
+
+.. function:: 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.
+
+.. decorator:: 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.
+
+.. decorator:: 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.