Expand documentation about type aliases and NewType in the typing module (merge 3.5 -> 3.6).

By Michael Lee.
This commit is contained in:
Guido van Rossum 2016-07-29 15:39:36 -07:00
commit e608709675

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@ -29,10 +29,105 @@ arguments.
Type aliases
------------
A type alias is defined by assigning the type to the alias::
A type alias is defined by assigning the type to the alias. In this example,
``Vector`` and ``List[float]`` will be treated as interchangeable synonyms::
from typing import List
Vector = List[float]
def scale(scalar: float, vector: Vector) -> Vector:
return [scalar * num for num in vector]
# typechecks; a list of floats qualifies as a Vector.
new_vector = scale(2.0, [1.0, -4.2, 5.4])
Type aliases are useful for simplifying complex type signatures. For example::
from typing import Dict, Tuple, List
ConnectionOptions = Dict[str, str]
Address = Tuple[str, int]
Server = Tuple[Address, ConnectionOptions]
def broadcast_message(message: str, servers: List[Server]) -> None:
...
# The static type checker will treat the previous type signature as
# being exactly equivalent to this one.
def broadcast_message(
message: str,
servers: List[Tuple[Tuple[str, int], Dict[str, str]]]) -> None:
...
NewType
-------
Use the ``NewType`` helper function to create distinct types::
from typing import NewType
UserId = NewType('UserId', int)
some_id = UserId(524313)
The static type checker will treat the new type as if it were a subclass
of the original type. This is useful in helping catch logical errors::
def get_user_name(user_id: UserId) -> str:
...
# typechecks
user_a = get_user_name(UserId(42351))
# does not typecheck; an int is not a UserId
user_b = get_user_name(-1)
You may still perform all ``int`` operations on a variable of type ``UserId``,
but the result will always be of type ``int``. This lets you pass in a
``UserId`` wherever an ``int`` might be expected, but will prevent you from
accidentally creating a ``UserId`` in an invalid way::
# `output` is of type `int`, not `UserId`
output = UserId(23413) + UserId(54341)
Note that these checks are enforced only by the static type checker. At runtime
the statement ``Derived = NewType('Derived', Base)`` will make ``Derived`` a
function that immediately returns whatever parameter you pass it. That means
the expression ``Derived(some_value)`` does not create a new class or introduce
any overhead beyond that of a regular function call.
More precisely, the expression ``some_value is Derived(some_value)`` is always
true at runtime.
This also means that it is not possible to create a subtype of ``Derived``
since it is an identity function at runtime, not an actual type. Similarly, it
is not possible to create another ``NewType`` based on a ``Derived`` type::
from typing import NewType
UserId = NewType('UserId', int)
# Fails at runtime and does not typecheck
class AdminUserId(UserId): pass
# Also does not typecheck
ProUserId = NewType('ProUserId', UserId)
See :pep:`484` for more details.
.. note::
Recall that the use of a type alias declares two types to be *equivalent* to
one another. Doing ``Alias = Original`` will make the static type checker
treat ``Alias`` as being *exactly equivalent* to ``Original`` in all cases.
This is useful when you want to simplify complex type signatures.
In contrast, ``NewType`` declares one type to be a *subtype* of another.
Doing ``Derived = NewType('Derived', Original)`` will make the static type
checker treat ``Derived`` as a *subclass* of ``Original``, which means a
value of type ``Original`` cannot be used in places where a value of type
``Derived`` is expected. This is useful when you want to prevent logic
errors with minimal runtime cost.
Callable
--------