python-peps/pep-0612.rst

PEP: 612
Title: Parameter Specification Variables
Author: Mark Mendoza <mendoza.mark.a@gmail.com>
Sponsor: Guido van Rossum <guido@python.org>
Discussions-To: Typing-Sig <typing-sig@python.org>
Status: Draft
Type: Standards Track
Content-Type: text/x-rst
Created: 18-Dec-2019
Python-Version: 3.9
Post-History: 18-Dec-2019

Parameter Specification Variables
=================================

Abstract
--------

There currently are two ways to specify the type of a callable, the
``Callable[[int, str], bool]`` syntax defined in  `PEP 484
<https://www.python.org/dev/peps/pep-0484>`_\ , and callback protocols from `PEP
544 <https://www.python.org/dev/peps/pep-0544/#callback-protocols>`_. Neither of
these support forwarding the parameter types of one callable over to another
callable, making it difficult to annotate function decorators. This PEP proposes
``typing.ParamSpec`` and ``typing.type_variable_operators.Concatenate`` to
support expressing these kinds of relationships.

Motivation
----------

The existing standards for annotating higher order functions don’t give us the
tools to annotate the following common decorator pattern satisfactorily:

.. code-block::

   from typing import Awaitable, Callable, TypeVar

   R = TypeVar("R")

   def add_logging(f: Callable[..., R]) -> Callable[..., Awaitable[R]]:
       async def inner(*args: object, **kwargs: object) -> R:
           await log_to_database()
           return f(*args, **kwargs)
       return inner

   @add_logging
   def takes_int_str(x: int, y: str) -> int:
       return x + 7

   await takes_int_str(1, "A")
   await takes_int_str("B", 2) # fails at runtime

``add_logging``\ , a decorator which logs before each entry into the decorated
function, is an instance of the Python idiom of one function passing all
arguments given to it over to another function.  This is done through the
combination of the ``*args`` and ``**kwargs`` features in both parameters and in
arguments. When one defines a function (like ``inner``\ ) that takes ``(*args,
**kwargs)`` and goes on to call another function with ``(*args, **kwargs)``\
, the wrapping function can only be safely called in all of the ways that the
wrapped function could be safely called. To type this decorator, we’d like to be
able to place a dependency between the parameters of the callable ``f`` and the
parameters of the returned function. `PEP 484
<https://www.python.org/dev/peps/pep-0484>`_ supports dependencies between
single types, as in ``def append(l: typing.List[T], e: T) -> typing.List[T]:
...``\ , but there is no existing way to do so with a complicated entity like
the parameters of a function.

Due to the limitations of the status quo, the ``add_logging`` example will type
check but will fail at runtime. ``inner`` will pass the string “B” into
``takes_int_str``\, which will try to add 7 to it, triggering a type error.
This was not caught by the type checker because the decorated ``takes_int_str``
was given the type ``Callable[..., Awaitable[int]]`` (an ellipsis in place of
parameter types is specified to mean that we do no validation on arguments).

Without the ability to define dependencies between the parameters of different
callable types, there is no way, at present, to make ``add_logging`` compatible
with all functions, while still preserving the enforcement of the parameters of
the decorated function.

With the addition of the ``ParamSpec`` variables proposed by this
PEP, we can rewrite the previous example in a way that keeps the flexibility of
the decorator and the parameter enforcement of the decorated function.

.. code-block::

   from typing import Awaitable, Callable, ParamSpec, TypeVar

   P = ParamSpec("P")
   R = TypeVar("R")

   def add_logging(f: Callable[P, R]) -> Callable[P, Awaitable[R]]:
       async def inner(*args: P.args, **kwargs: P.kwargs) -> R:
           await log_to_database()
           return f(*args, **kwargs)
       return inner

   @add_logging
   def takes_int_str(x: int, y: str) -> int:
       return x + 7

   await takes_int_str(1, "A") # Accepted
   await takes_int_str("B", 2) # Correctly rejected by the type checker

Another common decorator pattern that has previously been impossible to type is
the practice of adding or removing arguments from the decorated function.  For
example:

.. code-block::

   class Request:
    ...

   def with_request(f: Callable[..., R]) -> Callable[..., R]:
      def inner(*args: object, **kwargs: object) -> R:
          return f(Request(), *args, **kwargs)
      return inner

   @with_request
   def takes_int_str(request: Request, x: int, y: str) -> int:
    # use request
    return x + 7

   takes_int_str(1, "A")
   takes_int_str("B", 2) # fails at runtime


With the addition of the ``Concatenate`` operator from this PEP, we can even
type this more complex decorator.

.. code-block::

   from typing.type_variable_operators import Concatenate

   def with_request(f: Callable[Concatenate[Request, P], R]) -> Callable[P, R]:
       def inner(*args: P.args, **kwargs: P.kwargs) -> R:
           return f(Request(), *args, **kwargs)
       return inner

   @with_request
   def takes_int_str(request: Request, x: int, y: str) -> int:
       # use request
       return x + 7

   takes_int_str(1, "A") # Accepted
   takes_int_str("B", 2) # Correctly rejected by the type checker


Specification
-------------

ParamSpec Declarations
^^^^^^^^^^^^^^^^^^^^^^

A parameter specification variable is defined in a similar manner to how a
normal type variable is defined with ``typing.TypeVar``.

.. code-block::

   from typing import ParamSpec
   P = ParamSpec("P")         # Accepted
   P = ParamSpec("WrongName") # Rejected because P =/= WrongName

The runtime should accept ``bound``\ s and ``covariant`` and ``contravariant``
arguments in the declaration just as ``typing.TypeVar`` does, but for now we
will defer the standardization of the semantics of those options to a later PEP.

Valid use locations
^^^^^^^^^^^^^^^^^^^

Previously only a list of parameter arguments (``[A, B, C]``) or an ellipsis
(signifying "undefined parameters") were acceptable as the first "argument" to
``typing.Callable`` .  We now augment that with two new options: a parameter
specification variable (``Callable[P, int]``\ ) or a concatenation on a
parameter specification variable (``Callable[Concatenate[int, P], int]``\ ).

.. code-block::

   callable ::= Callable "[" parameters_expression, type_expression "]"

   parameters_expression ::=
     | "..."
     | "[" [ type_expression ("," type_expression)\* ] "]"
     | parameter_specification_variable
     | concatenate "["
                      type_expression ("," type_expression)\* ","
                      parameter_specification_variable
                   "]"

where ``parameter_specification_variable`` is a ``typing.ParamSpec`` variable,
declared in the manner as defined above, and ``concatenate`` is
``typing.type_variable_operators.Concatenate``.

As before, ``parameters_expression``\ s by themselves are not acceptable in
places where a type is expected

.. code-block::

   def foo(x: P) -> P: ...                           # Rejected
   def foo(x: Concatenate[int, P]) -> int: ...       # Rejected
   def foo(x: typing.List[P]) -> None: ...           # Rejected
   def foo(x: Callable[[int, str], P]) -> None: ...  # Rejected


User-Defined Generic Classes
````````````````````````````

Just as defining a class as inheriting from ``Generic[T]`` makes a class generic
for a single parameter (when ``T`` is a ``TypeVar``\ ), defining a class as
inheriting from ``Generic[P]`` makes a class generic on
``parameters_expression``\ s (when ``P`` is a ``ParamSpec``).

.. code-block::

   T = TypeVar("T")
   S = TypeVar("S")
   P_2 = ParamSpec("P_2")

   class X(Generic[T, P]):
     ...

   def f(x: X[int, P_2]) -> str: ...                    # Accepted
   def f(x: X[int, Concatenate[int, P_2]]) -> str: ...  # Accepted
   def f(x: X[int, [int, bool]]) -> str: ...            # Accepted
   def f(x: X[int, ...]) -> str: ...                    # Accepted
   def f(x: X[int, int]) -> str: ...                    # Rejected

By the rules defined above, spelling an concrete instance of a class generic
with respect to only a single ``ParamSpec`` would require unsightly double
brackets.  For aesthetic purposes we allow these to be omitted.

.. code-block::

   class Z(Generic[P]):
     ...

   def f(x: Z[[int, str, bool]]) -> str: ...   # Accepted
   def f(x: Z[int, str, bool]) -> str: ...     # Equivalent

Semantics
^^^^^^^^^

The inference rules for the return type of a function invocation whose signature
contains a ``ParamSpec`` variable are analogous to those around
evaluating ones with ``TypeVar``\ s.

.. code-block::

   def changes_return_type_to_str(x: Callable[P, int]) -> Callable[P, str]: ...

   def returns_int(a: str, b: bool) -> int: ...

   f = changes_return_type_to_str(returns_int) # f should have the type:
                                               # (a: str, b: bool) -> str

   f("A", True)               # Accepted
   f(a="A", b=True)           # Accepted
   f("A", "A")                # Rejected

   expects_str(f("A", True))  # Accepted
   expects_int(f("A", True))  # Rejected

Just as with traditional ``TypeVars``\ , a user may include the same
``ParamSpec`` multiple times in the arguments of the same function,
to indicate a dependency between multiple arguments.  In these cases a type
checker may choose to solve to a common behavioral supertype (i.e. a set of
parameters for which all of the valid calls are valid in both of the subtypes),
but is not obligated to do so.

.. code-block::

   P = ParamSpec("P")

   def foo(x: Callable[P, int], y: Callable[P, int]) -> Callable[P, bool]: ...

   def x_int_y_str(x: int, y: str) -> int: ...
   def y_int_x_str(y: int, x: str) -> int: ...

   foo(x_int_y_str, x_int_y_str) # Should return (x: int, y: str) -> bool

   foo(x_int_y_str, y_int_x_str) # Could return (__a: int, __b: str) -> bool
                                 # This works because both callables have types
                                 # that are behavioral subtypes of
                                 # Callable[[int, str], object]

   def keyword_only_x(*, x: int) -> int: ...
   def keyword_only_y(*, y: int) -> int: ...
   foo(keyword_only_x, keyword_only_y) # Rejected

The semantics of ``Concatenate[X, Y, P]`` are that it represents the parameters
represented by ``P`` with two positional-only parameters prepended.  This means
that we can use it to represent higher order functions that add, remove or
transform a finite number of parameters of a callable.

.. code-block::

   def bar(x: int, *args: bool) -> int: ...

   def add(x: Callable[P, int]) -> Callable[Concatenate[str, P], bool]: ...

   add(bar)       # Should return (__a: str, x: int, *args: bool) -> bool

   def remove(x: Callable[Concatenate[int, P], int]) -> Callable[P, bool]: ...

   remove(bar)    # Should return (*args: bool) -> bool

   def transform(
     x: Callable[Concatenate[int, P], int]
   ) -> Callable[Concatenate[str, P], bool]: ...

   transform(bar) # Should return (__a: str, *args: bool) -> bool

This also means that while any function that returns an ``R`` can satisfy
``typing.Callable[P, R]``, only functions that can be called positionally in
their first position with a ``X`` can satisfy
``typing.Callable[Concatenate[X, P], R]``.

.. code-block::

   def expects_int_first(x: Callable[Concatenate[int, P], int]) -> None: ...

   @expects_int_first # Rejected
   def one(x: str) -> int: ...

   @expects_int_first # Rejected
   def two(*, x: int) -> int: ...

   @expects_int_first # Rejected
   def three(**kwargs: int) -> int: ...

   @expects_int_first # Accepted
   def four(*args: int) -> int: ...

There are still some classes of decorators still not supported with these
features:

* those that add/remove/change a **variable** number of parameters (for
  example, ``functools.partial`` will remain untypable even after this PEP)
* those that add/remove/change keyword-only parameters (See
  `Concatenating Keyword Parameters`_ for more details).

The components of a ``ParamSpec``
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

A ``ParamSpec`` captures both positional and keyword accessible
parameters, but there unfortunately is no object in the runtime that captures
both of these together. Instead, we are forced to separate them into ``*args``
and ``**kwargs``\ , respectively. This means we need to be able to split apart
a single ``ParamSpec`` into these two components, and then bring
them back together into a call.  To do this, we introduce ``P.args`` to
represent the tuple of positional arguments in a given call and
``P.kwargs`` to represent the corresponding ``Mapping`` of keywords to
values.

Valid use locations
```````````````````

These "properties" can only be used as the annotated types for
``*args`` and ``**kwargs``\ , accessed from a ParamSpec already in scope.

.. code-block::

   def puts_p_into_scope(f: Callable[P, int]) -> None:

     def inner(*args: P.args, **kwargs: P.kwargs) -> None:      # Accepted
       pass

     def mixed_up(*args: P.kwargs, **kwargs: P.args) -> None:   # Rejected
       pass

     def misplaced(x: P.args) -> None:                          # Rejected
       pass

   def out_of_scope(*args: P.args, **kwargs: P.kwargs) -> None: # Rejected
      pass


Furthermore, because the default kind of parameter in Python (\ ``(x: int)``\ )
may be addressed both positionally and through its name, two valid invocations
of a ``(*args: P.args, **kwargs: P.kwargs)`` function may give different
partitions of the same set of parameters. Therefore we need to make sure that
these special types are only brought into the world together, and are used
together, so that our usage is valid for all possible partitions.

.. code-block::

   def puts_p_into_scope(f: Callable[P, int]) -> None:

     stored_args: P.args                      # Rejected

     stored_kwargs: P.args                    # Rejected

     def just_args(*args: P.args) -> None:    # Rejected
       pass

     def just_kwargs(*args: P.args) -> None:  # Rejected
       pass


Semantics
`````````

With those requirements met, we can now take advantage of the unique properties
afforded to us by this set up:


* Inside the function, ``args`` has the type ``P.args``\ , not
  ``Tuple[P.args, ...]`` as would be with a normal annotation
  (and likewise with the ``**kwargs``\ )
* A function of type ``Callable[P, R]`` can be called with ``(*args, **kwargs)``
  if and only if ``args`` has the type ``P.args`` and ``kwargs`` has the type
  ``P.kwargs``\ , and that those types both originated from the same function
  declaration.
* A function declared as ``def inner(*args: P.args, **kwargs: P.kwargs) -> X``
  has type ``Callable[P, X]``.

With these three properties, we now have the ability to fully type check
parameter preserving decorators.

.. code-block::

   def decorator(f: Callable[P, int]) -> Callable[P, None]:

     def foo(*args: P.args, **kwargs: P.kwargs) -> None:

       f(*args, **kwargs)    # Accepted, should resolve to int

       f(*kwargs, **args)    # Rejected

       f(1, *args, **kwargs) # Rejected

     return foo              # Accepted

To extend this to include ``Concatenate``, we declare the following properties:

* A function of type ``Callable[Concatenate[A, B, P], R]`` can only be
  called with ``(a, b, *args, **kwargs)`` when ``args`` and ``kwargs`` are the
  respective components of ``P``, ``a`` is of type ``A`` and ``b`` is of
  type ``B``.
* A function declared as
  ``def inner(a: A, b: B, *args: P.args, **kwargs: P.kwargs) -> R``
  has type ``Callable[Concatenate[A, B, P], R]``. Placing keyword-only
  parameters beterrn the ``*args`` and ``**kwargs`` is forbidden.

.. code-block::

   def add(f: Callable[P, int]) -> Callable[Concatenate[str, P], None]:

     def foo(s: str, *args: P.args, **kwargs: P.kwargs) -> None:  # Accepted
       pass

     def bar(*args: P.args, s: str, **kwargs: P.kwargs) -> None:  # Rejected
       pass

     return foo                                                   # Accepted


   def remove(x: Callable[Concatenate[int, P], int]) -> Callable[P, None]:

     def foo(*args: P.args, **kwargs: P.kwargs) -> None:
       f(1, *args, **kwargs) # Accepted

       f(*args, 1, **kwargs) # Rejected

       f(*args, **kwargs)    # Rejected

     return foo

Note that the names of the parameters preceding the ``ParamSpec``
components are not mentioned in the resulting ``Concatenate``.  This means that
these parameters can not be addressed via a named argument:

.. code-block::

   def outer(f: Callable[P, None]) -> Callable[P, None]:
     def foo(x: int, *args: P.args, **kwargs: P.kwargs) -> None:
       f(*args, **kwargs)

     def bar(*args: P.args, **kwargs: P.kwargs) -> None:
       foo(1, *args, **kwargs)   # Accepted
       foo(x=1, *args, **kwargs) # Rejected

     return bar

.. _above:

This is not an implementation convenience, but a soundness requirement.  If we
were to allow that second calling style, then the following snippet would be
problematic.

.. code-block::

   @outer
   def problem(*, x: object) -> None:
     pass

   problem(x="uh-oh")

Inside of ``bar``, we would get
``TypeError: foo() got multiple values for argument 'x'``.  Requiring these
concatenated arguments to be addressed positionally avoids this kind of problem,
and simplifies the syntax for spelling these types. Note that this also why we
have to reject signatures of the form
``(*args: P.args, s: str, **kwargs: P.kwargs)`` (See
`Concatenating Keyword Parameters`_ for more details).

If one of these prepended positional parameters contains a free ``ParamSpec``\ ,
we consider that variable in scope for the purposes of extracting the components
of that ``ParamSpec``.  That allows us to spell things like this:

.. code-block::

   def twice(f: Callable[P, int], *args: P.args, **kwargs: P.kwargs) -> int:
       return f(*args, **kwargs) + f(*args, **kwargs)

The type of ``twice`` in the above example is
``Callable[Concatenate[Callable[P, int], P], int]``, where ``P`` is bound by the
outer ``Callable``.  This has the following semantics:

.. code-block::

   def a_int_b_str(a: int, b: str) -> int:
     pass

   twice(a_int_b_str, 1, "A")       # Accepted

   twice(a_int_b_str, b="A", a=1)   # Accepted

   twice(a_int_b_str, "A", 1)       # Rejected


Backwards Compatibility
-----------------------

The only changes necessary to existing features in ``typing`` is allowing these
``ParamSpec`` and ``Concatenate`` objects to be the first parameter to
``Callable`` and to be a parameter to ``Generic``. Currently ``Callable``
expects a list of types there and ``Generic`` expects single types, so they are
currently mutually exclusive. Otherwise, existing code that doesn't reference
the new interfaces will be unaffected.

Reference Implementation
------------------------

The `Pyre <https://pyre-check.org/>`_ type checker supports all of the behavior
described above.  A reference implementation of the runtime components needed
for those uses is provided in the ``pyre_extensions`` module.

Rejected Alternatives
---------------------

Using List Variadics and Map Variadics
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

We considered just trying to make something like this with a callback protocol
which was parameterized on a list-type variadic, and a map-type variadic like
so:

.. code-block::

   R = typing.TypeVar(“R”)
   Tpositionals = ....
   Tkeywords = ...
   class BetterCallable(typing.Protocol[Tpositionals, Tkeywords, R]):
     def __call__(*args: Tpositionals, **kwargs: Tkeywords) -> R: ...

However there are some problems with trying to come up with a consistent
solution for those type variables for a given callable. This problem comes up
with even the simplest of callables:

.. code-block::

   def simple(x: int) -> None: ...
   simple <: BetterCallable[[int], [], None]
   simple <: BetterCallable[[], {“x”: int}, None]
   BetterCallable[[int], [], None] </: BetterCallable[[], {“x”: int}, None]

Any time where a type can implement a protocol in more than one way that aren't
mutually compatible, we can run into situations where we lose information. If we
were to make a decorator using this protocol, we would have to pick one calling
convention to prefer.

.. code-block::

   def decorator(
     f: BetterCallable[[Ts], [Tmap], int],
   ) -> BetterCallable[[Ts], [Tmap], str]:
       def decorated(*args: Ts, **kwargs: Tmap) -> str:
          x = f(*args, **kwargs)
          return int_to_str(x)
       return decorated

   @decorator
   def foo(x: int) -> int:
       return x

   reveal_type(foo) # Option A: BetterCallable[[int], {}, str]
                    # Option B: BetterCallable[[], {x: int}, str]
   foo(7)   # fails under option B
   foo(x=7) # fails under option A

The core problem here is that, by default, parameters in Python can either be
called positionally or as a keyword argument. This means we really have
three categories (positional-only, positional-or-keyword, keyword-only) we’re
trying to jam into two categories. This is the same problem that we briefly
mentioned when discussing ``.args`` and ``.kwargs``. Fundamentally, in order to
capture two categories when there are some things that can be in either
category, we need a higher level primitive (\ ``ParamSpec``\ ) to
capture all three, and then split them out afterward.

Defining ParametersOf
^^^^^^^^^^^^^^^^^^^^^^

Another proposal we considered was defining ``ParametersOf`` and ``ReturnType``
operators which would operate on a domain of a newly defined ``Function`` type.
``Function`` would be callable with, and only with ``ParametersOf[F]``.
``ParametersOf`` and ``ReturnType`` would only operate on type variables with
precisely this bound.  The combination of these three features could express
everything that we can express with ``ParamSpecs``.


.. code-block::

   F = TypeVar("F", bound=Function)

   def no_change(f: F) -> F:
       def inner(
         *args: ParametersOf[F].args,
         **kwargs: ParametersOf[F].kwargs
       ) -> ReturnType[F]:
          return f(*args, **kwargs)
       return inner

   def wrapping(f: F) -> Callable[ParametersOf[F], List[ReturnType[F]]]:
       def inner(
           *args: ParametersOf[F].args,
           **kwargs: ParametersOf[F].kwargs
        ) -> List[ReturnType[F]]:
          return [f(*args, **kwargs)]
       return inner

   def unwrapping(
       f: Callable[ParametersOf[F], List[R]]
   ) -> Callable[ParametersOf[F], R]:
       def inner(
          *args: ParametersOf[F].args,
          **kwargs: ParametersOf[F].kwargs
       ) -> R:
          return f(*args, **kwargs)[0]
       return inner

We decided to go with ``ParamSpec``\ s over this approach for several reasons:

* The footprint of this change would be larger, as we would need two new
  operators, and a new type, while ``ParamSpec`` just introduces a new variable.
* Python typing has so far has avoided supporting operators, whether
  user-defined or built-in, in favor of destructuring.  Accordingly,
  ``ParamSpec`` based signatures look much more like existing Python.
* The lack of user-defined operators makes common patterns hard to spell.
  ``unwrapping`` is odd to read because ``F`` is not actually referring to any
  callable. It’s just being used as a container for the parameters we wish to
  propagate.  It would read better if we could define an operator
  ``RemoveList[List[X]] = X`` and then ``unwrapping`` could take ``F`` and
  return ``Callable[ParametersOf[F], RemoveList[ReturnType[F]]]``.  Without
  that, we unfortunately get into a situation where we have to use a
  ``Function``-variable as an improvised ``ParamSpec``, in that we never
  actually bind the return type.

In summary, between these two equivalently powerful syntaxes, ``ParamSpec`` fits
much more naturally into the status quo.

.. _Concatenating Keyword Parameters:

Concatenating Keyword Parameters
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

In principle the idea of concatenation as a means to modify a finite number of
positional parameters could be expanded to include keyword parameters.

.. code-block::

   def add_n(f: Callable[P, R]) -> Callable[Concatenate[("n", int), P], R]:
       def inner(*args: P.args, n: int, **kwargs: P.kwargs) -> R:
           # use n
           return f(*args, **kwargs)
       return inner

However, the key distinction is that while prepending positional-only parameters
to a valid callable type always yields another valid callable type, the same
cannot be said for adding keyword-only parameters. As alluded to above_ , the
issue is name collisions.  The parameters ``Concatenate[("n", int), P]`` are
only valid when ``P`` itself does not already have a parameter named ``n``\ .

.. code-block::

   def innocent_wrapper(f: Callable[P, R]) -> Callable[P, R]:
     def inner(*args: P.args, **kwargs: P.kwargs) -> R:
       added = add_n(f)
       return added(*args, n=1, **kwargs)
     return inner

   @innocent_wrapper
   def problem(n: int) -> None:
     pass

Calling ``problem(2)`` works fine, but calling ``problem(n=2)`` leads to a
``TypeError: problem() got multiple values for argument 'n'`` from the call to
``added`` inside of ``innocent_wrapper``\ .

This kind of situation could be avoided, and this kind of decorator could be
typed if we could reify the constraint that a set of parameters **not** contain
a certain name, with something like:

.. code-block::

   P_without_n = ParamSpec("P_without_n", banned_names=["n"])

   def add_n(
     f: Callable[P_without_n, R]
   ) -> Callable[Concatenate[("n", int), P_without_n], R]: ...

The call to ``add_n`` inside of ``innocent_wrapper`` could then be rejected
since the callable was not guaranteed not to already have a parameter named
``n``\ .


However, enforcing these constraints would require enough additional
implementation work that we judged this extension to be out of scope of this
PEP.  Fortunately the design of ``ParamSpec``\ s are such that we can return to
this idea later if there is sufficient demand.


Naming this a ``ParameterSpecification``
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
We decided that ParameterSpecification was a little too long-winded for use
here, and that this style of abbreviated name made it look more like TypeVar.

Naming this an ``ArgSpec``
^^^^^^^^^^^^^^^^^^^^^^^^^^

We think that calling this a ParamSpec is more correct than
referring to it as an ArgSpec, since callables have parameters,
which are distinct from the arguments which are passed to them in a given call
site.  A given binding for a ParamSpec is a set of function
parameters, not a call-site’s arguments.

Acknowledgements
----------------

Thanks to all of the members of the Pyre team for their comments on early drafts
of this PEP, and for their help with the reference implementation.

Thanks are also due to the whole Python typing community for their early
feedback on this idea at a Python typing meetup, leading directly to the much
more compact ``.args``\ /\ ``.kwargs`` syntax.

Copyright
---------

This document is placed in the public domain or under the CC0-1.0-Universal
license, whichever is more permissive.