PEP 696: Improve section "Using another TypeVarLike as the default" (#2777)
Co-authored-by: C.A.M. Gerlach <CAM.Gerlach@Gerlach.CAM> Co-authored-by: Eric Traut <eric@traut.com> Co-authored-by: Jelle Zijlstra <jelle.zijlstra@gmail.com>
This commit is contained in:
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pep-0696.rst
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pep-0696.rst
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@ -15,7 +15,8 @@ Abstract
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This PEP introduces the concept of type defaults for
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``TypeVarLike``\ s (``TypeVar``, ``ParamSpec`` and ``TypeVarTuple``),
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which act as defaults for a type parameter when none is specified.
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which act as defaults for a type parameter when one is not specified or
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the constraint solver isn't able to solve a type parameter to anything.
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Default type argument support is available in some popular languages
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such as C++, TypeScript, and Rust. A survey of type parameter syntax in
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@ -27,7 +28,7 @@ and can be found in its
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Motivation
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----------
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.. code:: py
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.. code-block:: py
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T = TypeVar("T", default=int) # This means that if no type is specified T = int
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@ -42,7 +43,7 @@ One place this `regularly comes
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up <https://github.com/python/typing/issues/975>`__ is ``Generator``. I
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propose changing the *stub definition* to something like:
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.. code:: py
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.. code-block:: py
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YieldT = TypeVar("YieldT")
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SendT = TypeVar("SendT", default=None)
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@ -54,7 +55,7 @@ propose changing the *stub definition* to something like:
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This is also useful for a ``Generic`` that is commonly over one type.
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.. code:: py
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.. code-block:: py
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class Bot: ...
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@ -73,20 +74,20 @@ also helps non-typing users who rely on auto-complete to speed up their
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development.
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This design pattern is common in projects like:
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- `discord.py <https://github.com/Rapptz/discord.py>`__ - where the
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- `discord.py <https://github.com/Rapptz/discord.py>`__ — where the
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example above was taken from.
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- `NumPy <https://github.com/numpy/numpy>`__ - the default for types
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- `NumPy <https://github.com/numpy/numpy>`__ — the default for types
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like ``ndarray``'s ``dtype`` would be ``float64``. Currently it's
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``Unknown`` or ``Any``.
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- `TensorFlow <https://github.com/tensorflow/tensorflow>`__ (this
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- `TensorFlow <https://github.com/tensorflow/tensorflow>`__ — this
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could be used for Tensor similarly to ``numpy.ndarray`` and would be
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useful to simplify the definition of ``Layer``).
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useful to simplify the definition of ``Layer``.
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Specification
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-------------
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Default ordering and subscription rules
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Default Ordering and Subscription Rules
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'''''''''''''''''''''''''''''''''''''''
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The order for defaults should follow the standard function parameter
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@ -95,7 +96,7 @@ a ``default`` value. Doing so should ideally raise a ``TypeError`` in
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``typing._GenericAlias``/``types.GenericAlias``, and a type checker
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should flag this an error.
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.. code:: py
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.. code-block:: py
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DefaultStrT = TypeVar("DefaultStrT", default=str)
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DefaultIntT = TypeVar("DefaultIntT", default=int)
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@ -141,7 +142,7 @@ future, this might be possible (see `Interaction with PEP
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``TypeVar`` \ s but use a ``list`` or ``tuple`` of types or an ellipsis
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literal "``...``".
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.. code:: py
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.. code-block:: py
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DefaultP = ParamSpec("DefaultP", default=(str, int))
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@ -156,44 +157,124 @@ literal "``...``".
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``TypeVarTuple`` defaults are defined using the same syntax as
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``TypeVar`` \ s but use an unpacked tuple of types instead of a single type.
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.. code:: py
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.. code-block:: py
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DefaultTs = TypeVarTuple("DefaultTs", default=Unpack[tuple[str, int]])
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class Foo(Generic[DefaultTs]): ...
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class Foo(Generic[*DefaultTs]): ...
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reveal_type(Foo()) # type is Foo[str, int]
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reveal_type(Foo[int, bool]()) # type is Foo[int, bool]
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Using another ``TypeVarLike`` as the default
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Using Another ``TypeVarLike`` as ``default``
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''''''''''''''''''''''''''''''''''''''''''''
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To use another ``TypeVarLike``\ s as the default they have to be of the
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same type. When using another ``TypeVarLike`` (T1) as the default, the default
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for the ``TypeVarLike`` (T2), T1 must be used before in the signature
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of the class it appears in before T2. T2's bound must be a subtype of
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T1's bound.
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This allows for a value to be used again when the constraints solver
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fails to solve a constraint for a type, or the type parameter to a
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generic is missing but another type parameter is specified.
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To use another ``TypeVarLike`` as a default the ``default`` and the
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``TypeVarLike`` must be the same type (a ``TypeVar``'s default must be
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a ``TypeVar``, etc.).
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`This could be used on builtins.slice <https://github.com/python/typing/issues/159>`__
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where the ``start`` parameter should default to ``int``, ``stop``
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default to the type of ``start`` and step default to ``int | None``.
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.. code:: py
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.. code-block:: py
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StartT = TypeVar("StartT", default=int)
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StopT = TypeVar("StopT", default=StartT)
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StepT = TypeVar("StepT", default=int | None)
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class slice(Generic[StartT, StopT, StepT]): ... # Valid
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class slice(Generic[StartT, StopT, StepT]): ...
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reveal_type(slice()) # type is slice[int, int, int | None]
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reveal_type(slice[str]()) # type is slice[str, str, int | None]
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reveal_type(slice[str, str, timedelta]()) # type is slice[str, str, timedelta]
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reveal_type(slice[str, bool, timedelta]()) # type is slice[str, bool, timedelta]
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StartT = TypeVar("StartT", default="StopT")
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When using a ``TypeVarLike`` as the default to another ``TypeVarLike``.
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Where ``T1`` is the default for ``T2`` the following rules apply.
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.. _scoping-rules:
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Scoping Rules
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~~~~~~~~~~~~~
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``T1`` must be used before ``T2`` in the parameter list of the generic,
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or be bound in an outer class or function scope.
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.. code-block:: py
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DefaultT = TypeVar("DefaultT", default=T)
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class Foo(Generic[T, DefaultT]): ... # Valid
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def bar(x: T, y: DefaultT): ... # Valid
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class Foo(Generic[T]):
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class Bar(Generic[DefaultT]): ... # Valid
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def outer(x: T):
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def inner(y: DefaultT): ... # Valid
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StartT = TypeVar("StartT", default="StopT") # Swapped defaults around from previous example
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StopT = TypeVar("StopT", default=int)
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class slice(Generic[StartT, StopT, StepT]): ...
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^^^^^^ # Invalid: ordering does not allow StopT to bound yet
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# ^^^^^^ Invalid: ordering does not allow StopT to be bound
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def baz(x: DefaultT, y: T): ...
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# ^^^^^^^^ Invalid: ordering does not allow DefaultT to be bound
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Bound Rules
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~~~~~~~~~~~
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``T2``'s bound must be a subtype of ``T1``'s bound.
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.. code-block:: py
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T = TypeVar("T", bound=float)
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TypeVar("Ok", default=T, bound=int) # Valid
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TypeVar("AlsoOk", default=T, bound=float) # Valid
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TypeVar("Invalid", default=T, bound=str) # Invalid: str is not a subtype of float
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Constraint Rules
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~~~~~~~~~~~~~~~~
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The constraints of ``T2`` must be a superset of the constraints of ``T1``.
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.. code-block:: py
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T1 = TypeVar("T1", bound=int)
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TypeVar("Invalid", float, str, default=T1) # Invalid: upper bound int is incompatible with constraints float or str
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T1 = TypeVar("T1", int, str)
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TypeVar("AlsoOk", int, str, bool, default=T1) # Valid
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TypeVar("AlsoInvalid", bool, complex, default=T1) # Invalid: {bool, complex} is not a superset of {int, str}
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``TypeVarLike``\s as Parameters to Generics
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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``TypeVarLike``\ s are valid as parameters to generics inside of a
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``default`` when the first parameter is in scope as determined by the
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:ref:`previous section <scoping-rules>`.
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.. code-block:: py
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T = TypeVar("T")
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ListDefaultT = TypeVar("ListDefaultT", default=list[T])
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class Bar(Generic[T, ListDefaultT]):
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def __init__(self, x: T, y: ListDefaultT): ...
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reveal_type(Bar[int]) # type is Bar[int, list[int]]
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reveal_type(Bar[int, list[str]]) # type is Bar[int, list[str]]
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reveal_type(Bar[int, str]) # type is Bar[int, str]
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Specialisation Rules
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~~~~~~~~~~~~~~~~~~~~
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``TypeVarLike``\ s currently cannot be further subscripted. This might
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change if `Higher Kinded TypeVars <https://github.com/python/typing/issues/548>`__
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are implemented.
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``Generic`` ``TypeAlias``\ es
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'''''''''''''''''''''''''''''
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@ -204,11 +285,11 @@ that hasn't been overridden it should be treated like it was
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substituted into the ``TypeAlias``. However, it can be specialised
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further down the line.
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.. code:: py
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.. code-block:: py
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class SomethingWithNoDefaults(Generic[T, T2]): ...
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MyAlias: TypeAlias = SomethingWithNoDefaults[int, DefaultStrT] # valid
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MyAlias: TypeAlias = SomethingWithNoDefaults[int, DefaultStrT] # Valid
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reveal_type(MyAlias()) # type is SomethingWithNoDefaults[int, str]
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reveal_type(MyAlias[bool]()) # type is SomethingWithNoDefaults[int, bool]
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@ -220,17 +301,18 @@ Subclassing
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Subclasses of ``Generic``\ s with ``TypeVarLike``\ s that have defaults
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behave similarly to ``Generic`` ``TypeAlias``\ es.
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.. code:: py
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.. code-block:: py
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class SubclassMe(Generic[T, DefaultStrT]): ...
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class SubclassMe(Generic[T, DefaultStrT]):
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x: DefaultStrT
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class Bar(SubclassMe[int, DefaultStrT]): ...
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reveal_type(Bar()) # type is Bar[str]
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reveal_type(Bar[bool]()) # type is Bar[bool]
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class Foo(SubclassMe[int]): ...
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class Foo(SubclassMe[float]): ...
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reveal_type(Foo()) # type is <subclass of SubclassMe[int, int]>
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reveal_type(Foo().x) # type is str
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Foo[str] # Invalid: Foo cannot be further subscripted
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@ -239,14 +321,14 @@ behave similarly to ``Generic`` ``TypeAlias``\ es.
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class Spam(Baz): ...
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reveal_type(Spam()) # type is <subclass of Baz[int, str]>
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Using bound and default
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'''''''''''''''''''''''
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Using ``bound`` and ``default``
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'''''''''''''''''''''''''''''''
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If both ``bound`` and ``default`` are passed ``default`` must be a
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subtype of ``bound``. Otherwise the type checker should generate an
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error.
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.. code:: py
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.. code-block:: py
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TypeVar("Ok", bound=float, default=int) # Valid
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TypeVar("Invalid", bound=str, default=int) # Invalid: the bound and default are incompatible
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@ -258,7 +340,7 @@ For constrained ``TypeVar``\ s, the default needs to be one of the
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constraints. A type checker should generate an error even if it is a
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subtype of one of the constraints.
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.. code:: py
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.. code-block:: py
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TypeVar("Ok", float, str, default=float) # Valid
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TypeVar("Invalid", float, str, default=int) # Invalid: expected one of float or str got int
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@ -268,7 +350,7 @@ Function Defaults
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``TypeVarLike``\ s currently can only be used where a parameter can go unsolved.
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.. code:: py
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.. code-block:: py
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def foo(a: DefaultStrT | None = None) -> DefaultStrT: ...
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@ -289,7 +371,8 @@ module.
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of ``TypeVar``, ``ParamSpec``, and ``TypeVarTuple``.
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- the type passed to default would be available as a ``__default__``
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attribute.
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attribute and a sentinel would need to be added that can be
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checked against to see if it was supplied.
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The following changes would be required to both ``GenericAlias``\ es:
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@ -308,7 +391,7 @@ If this PEP is accepted, the syntax proposed in :pep:`695` will be
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extended to introduce a way to specify defaults for type parameters
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using the "=" operator inside of the square brackets like so:
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.. code:: py
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.. code-block:: py
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# TypeVars
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class Foo[T = str]: ...
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@ -322,6 +405,12 @@ using the "=" operator inside of the square brackets like so:
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class Qux[*Ts = *tuple[int, bool]]: ...
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def ham[*Us = *tuple[str]](): ...
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# TypeAliases
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type Foo[T, U = str] = Bar[T, U]
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type Baz[**P = (int, str)] = Spam[**P]
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type Qux[*Ts = *tuple[str]] = Ham[*Ts]
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type Rab[U, T = str] = Bar[T, U]
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This functionality was included in the initial draft of :pep:`695` but
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was removed due to scope creep.
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@ -336,7 +425,9 @@ Grammar Changes
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| '*' a=NAME d=[type_param_default]
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| '**' a=NAME d=[type_param_default]
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type_param_default: '=' e=expression
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type_param_default:
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| '=' e=expression
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| '=' e=starred_expression
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This would mean that ``TypeVarLike``\ s with defaults proceeding those
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with non-defaults can be checked at compile time.
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@ -345,10 +436,10 @@ with non-defaults can be checked at compile time.
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Rejected Alternatives
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---------------------
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Allowing the ``TypeVarLike``\ s defaults to be passed to ``type.__new__``'s ``**kwargs``
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''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''
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Allowing the ``TypeVarLike``\s Defaults to Be Passed to ``type.__new__``'s ``**kwargs``
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'''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''
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.. code:: py
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.. code-block:: py
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T = TypeVar("T")
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@ -365,7 +456,7 @@ at runtime.
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Ideally, if :pep:`637` wasn't rejected, the following would be acceptable:
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.. code:: py
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.. code-block:: py
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T = TypeVar("T")
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class Box(Generic[T = int]):
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value: T | None = None
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Allowing non-defaults to follow defaults
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Allowing Non-defaults to Follow Defaults
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''''''''''''''''''''''''''''''''''''''''
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.. code:: py
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.. code-block:: py
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YieldT = TypeVar("YieldT", default=Any)
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SendT = TypeVar("SendT", default=Any)
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@ -394,12 +485,12 @@ above two forms were valid. Changing the argument order now would also
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break a lot of codebases. This is also solvable in most cases using a
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``TypeAlias``.
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.. code:: py
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.. code-block:: py
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Coro: TypeAlias = Coroutine[Any, Any, T]
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Coro[int] == Coroutine[Any, Any, int]
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Having ``default`` implicitly be ``bound``
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Having ``default`` Implicitly Be ``bound``
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''''''''''''''''''''''''''''''''''''''''''
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In an earlier version of this PEP, the ``default`` was implicitly set
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@ -407,7 +498,7 @@ to ``bound`` if no value was passed for ``default``. This while
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convenient, could have a ``TypeVarLike`` with no default follow a
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``TypeVarLike`` with a default. Consider:
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.. code:: py
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.. code-block:: py
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T = TypeVar("T", bound=int) # default is implicitly int
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U = TypeVar("U")
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