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PEP 692: Using TypedDict for more precise `**kwargs` typing (#2620) Co-authored-by: CAM Gerlach <CAM.Gerlach@Gerlach.CAM>
2022-06-28 18:20:28 -04:00
PEP: 692
Title: Using TypedDict for more precise \*\*kwargs typing
Author: Franek Magiera <framagie@gmail.com>
Sponsor: Jelle Zijlstra <jelle.zijlstra@gmail.com>
Discussions-To: https://mail.python.org/archives/list/typing-sig@python.org/thread/U42MJE6QZYWPVIFHJIGIT7OE52ZGIQV3/
Status: Draft
Type: Standards Track
Content-Type: text/x-rst
Created: 29-May-2022
Python-Version: 3.12
Post-History: `29-May-2022 <https://mail.python.org/archives/list/typing-sig@python.org/thread/U42MJE6QZYWPVIFHJIGIT7OE52ZGIQV3/>`__,
Abstract
========
Currently ``**kwargs`` can be type hinted as long as all of the keyword
arguments specified by them are of the same type. However, that behaviour can
be very limiting. Therefore, in this PEP we propose a new way to enable more
precise ``**kwargs`` typing. The new approach revolves around using
``TypedDict`` to type ``**kwargs`` that comprise keyword arguments of different
types. It also involves introducing a grammar change and a new dunder
``__unpack__``.
Motivation
==========
Currently annotating ``**kwargs`` with a type ``T`` means that the ``kwargs``
type is in fact ``dict[str, T]``. For example::
def foo(**kwargs: str) -> None: ...
means that all keyword arguments in ``foo`` are strings (i.e., ``kwargs`` is
of type ``dict[str, str]``). This behaviour limits the ability to type
annotate ``**kwargs`` only to the cases where all of them are of the same type.
However, it is often the case that keyword arguments conveyed by ``**kwargs``
have different types that are dependent on the keyword's name. In those cases
type annotating ``**kwargs`` is not possible. This is especially a problem for
already existing codebases where the need of refactoring the code in order to
introduce proper type annotations may be considered not worth the effort. This
in turn prevents the project from getting all of the benefits that type hinting
can provide. As a consequence, there has been a `lot of discussion <mypyIssue4441_>`__
around supporting more precise ``**kwargs`` typing and it became a
feature that would be valuable for a large part of the Python community.
Rationale
=========
:pep:`589` introduced the ``TypedDict`` type constructor that supports dictionary
types consisting of string keys and values of potentially different types. A
function's keyword arguments represented by a formal parameter that begins with
double asterisk, such as ``**kwargs``, are received as a dictionary.
Additionally, such functions are often called using unpacked dictionaries to
provide keyword arguments. This makes ``TypedDict`` a perfect candidate to be
used for more precise ``**kwargs`` typing. In addition, with ``TypedDict``
keyword names can be taken into account during static type analysis. However,
specifying ``**kwargs`` type with a ``TypedDict`` means, as mentioned earlier,
that each keyword argument specified by ``**kwargs`` is a ``TypedDict`` itself.
For instance::
class Movie(TypedDict):
name: str
year: int
def foo(**kwargs: Movie) -> None: ...
means that each keyword argument in ``foo`` is itself a ``Movie`` dictionary
that has a ``name`` key with a string type value and a ``year`` key with an
integer type value. Therefore, in order to support specifying ``kwargs`` type
as a ``TypedDict`` without breaking current behaviour, a new syntax has to be
introduced.
Specification
=============
To support the aforementioned use case we propose to use the double asterisk
syntax inside of the type annotation. The required grammar change is discussed
in more detail in section `Grammar Changes`_. Continuing the previous example::
def foo(**kwargs: **Movie) -> None: ...
would mean that the ``**kwargs`` comprise two keyword arguments specified by
``Movie`` (i.e. a ``name`` keyword of type ``str`` and a ``year`` keyword of
type ``int``). This indicates that the function should be called as follows::
kwargs: Movie = {name: "Life of Brian", year: 1979}
foo(**kwargs) # OK!
foo(name="The Meaning of Life", year=1983) # OK!
Inside the function itself, the type checkers should treat
the ``kwargs`` parameter as a ``TypedDict``::
def foo(**kwargs: **Movie) -> None:
assert_type(kwargs, Movie) # OK!
Using the new annotation will not have any runtime effect - it should only be
taken into account by type checkers. Any mention of errors in the following
sections relates to type checker errors.
Function calls with standard dictionaries
-----------------------------------------
Calling a function that has ``**kwargs`` typed using the ``**kwargs: **Movie``
syntax with a dictionary of type ``dict[str, object]`` must generate a type
checker error. On the other hand, the behaviour for functions using standard,
untyped dictionaries can depend on the type checker. For example::
def foo(**kwargs: **Movie) -> None: ...
movie: dict[str, object] = {"name": "Life of Brian", "year": 1979}
foo(**movie) # WRONG! Movie is of type dict[str, object]
typed_movie: Movie = {"name": "The Meaning of Life", "year": 1983}
foo(**typed_movie) # OK!
another_movie = {"name": "Life of Brian", "year": 1979}
foo(**another_movie) # Depends on the type checker.
Keyword collisions
------------------
A ``TypedDict`` that is used to type ``**kwargs`` could potentially contain
keys that are already defined in the function's signature. If the duplicate
name is a standard argument, an error should be reported by type checkers.
If the duplicate name is a positional only argument, no errors should be
generated. For example::
def foo(name, **kwargs: **Movie) -> None: ... # WRONG! "name" will
# always bind to the
# first parameter.
def foo(name, /, **kwargs: **Movie) -> None: ... # OK! "name" is a
# positional argument,
# so **kwargs can contain
# a "name" keyword.
Required and non-required keys
------------------------------
By default all keys in a ``TypedDict`` are required. This behaviour can be
overridden by setting the dictionary's ``total`` parameter as ``False``.
Moreover, :pep:`655` introduced new type qualifiers - ``typing.Required`` and
``typing.NotRequired`` - that enable specifying whether a particular key is
required or not::
class Movie(TypedDict):
title: str
year: NotRequired[int]
When using a ``TypedDict`` to type ``**kwargs`` all of the required and
non-required keys should correspond to required and non-required function
keyword parameters. Therefore, if a required key is not supported by the
caller, then an error must be reported by type checkers.
Assignment
----------
Assignments of a function typed with the ``**kwargs: **Movie`` construct and
another callable type should pass type checking only if they are compatible.
This can happen for the scenarios described below.
Source and destination contain ``**kwargs``
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
Both destination and source functions have a ``**kwargs: **TypedDict``
parameter and the destination function's ``TypedDict`` is assignable to the
source function's ``TypedDict`` and the rest of the parameters are
compatible::
class Animal(TypedDict):
name: str
class Dog(Animal):
breed: str
def accept_animal(**kwargs: **Animal): ...
def accept_dog(**kwargs: **Dog): ...
accept_dog = accept_animal # OK! Expression of type Dog can be
# assigned to a variable of type Animal.
accept_animal = accept_dog # WRONG! Expression of type Animal
# cannot be assigned to a variable of type Dog.
.. _pep-692-assignment-dest-no-kwargs:
Source contains ``**kwargs`` and destination doesn't
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
The destination callable doesn't contain ``**kwargs``, the source callable
contains ``**kwargs: **TypedDict`` and the destination function's keyword
arguments are assignable to the corresponding keys in source function's
``TypedDict``. Moreover, not required keys should correspond to optional
function arguments, whereas required keys should correspond to required
function arguments. Again, the rest of the parameters have to be compatible.
Continuing the previous example::
class Example(TypedDict):
animal: Animal
string: str
number: NotRequired[int]
def src(**kwargs: **Example): ...
def dest(*, animal: Dog, string: str, number: int = ...): ...
dest = src # OK!
It is worth pointing out that the destination function's arguments that are to
be compatible with the keys and values from the ``TypedDict`` must be keyword
only arguments::
def dest(animal: Dog, string: str, number: int = ...): ...
dest(animal_instance, "some string") # OK!
dest = src
dest(animal_instance, "some string") # WRONG! The same call fails at
# runtime now because 'src' expects
# keyword arguments.
The reverse situation where the destination callable contains
``**kwargs: **TypedDict`` and the source callable doesn't contain
``**kwargs`` should be disallowed. This is because, we cannot be sure that
additional keyword arguments are not being passed in when an instance of a
subclass had been assigned to a variable with a base class type and then
unpacked in the destination callable invocation::
def dest(**Animal): ...
def src(name: str): ...
dog: Dog = {"name": "Daisy", "breed": "Labrador"}
animal: Animal = dog
dest = src # WRONG!
dest(**animal) # Fails at runtime.
Similar situation can happen even without inheritance as compatibility
between ``TypedDict``\s is based on structural subtyping.
Source contains untyped ``**kwargs``
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
The destination callable contains ``**kwargs: **TypedDict`` and the source
callable contains untyped ``**kwargs``::
def src(**kwargs): ...
def dest(**kwargs: **Movie): ...
dest = src # OK!
Source contains traditionally typed ``**kwargs: T``
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
The destination callable contains ``**kwargs: **TypedDict``, the source
callable contains traditionally typed ``**kwargs: T`` and each of the
destination function ``TypedDict``'s fields is assignable to a variable of
type ``T``::
class Vehicle:
...
class Car(Vehicle):
...
class Motorcycle(Vehicle):
...
class Vehicles(TypedDict):
car: Car
moto: Motorcycle
def dest(**kwargs: **Vehicles): ...
def src(**kwargs: Vehicle): ...
dest = src # OK!
On the other hand, if the destination callable contains either untyped or
traditionally typed ``**kwargs: T`` and the source callable is typed using
``**kwargs: **TypedDict`` then an error should be generated, because
traditionally typed ``**kwargs`` aren't checked for keyword names.
To summarize, function parameters should behave contravariantly and function
return types should behave covariantly.
Passing kwargs inside a function to another function
----------------------------------------------------
:ref:`A previous point <pep-692-assignment-dest-no-kwargs>`
mentions the problem of possibly passing additional keyword arguments by
assigning a subclass instance to a variable that has a base class type. Let's
consider the following example::
class Animal(TypedDict):
name: str
class Dog(Animal):
breed: str
def takes_name(name: str): ...
dog: Dog = {"name": "Daisy", "breed": "Labrador"}
animal: Animal = dog
def foo(**kwargs: **Animal):
print(kwargs["name"].capitalize())
def bar(**kwargs: **Animal):
takes_name(**kwargs)
def baz(animal: Animal):
takes_name(**animal)
def spam(**kwargs: **Animal):
baz(kwargs)
foo(**animal) # OK! foo only expects and uses keywords of 'Animal'.
bar(**animal) # WRONG! This will fail at runtime because 'breed' keyword
# will be passed to 'takes_name' as well.
spam(**animal) # WRONG! Again, 'breed' keyword will be eventually passed
# to 'takes_name'.
In the example above, the call to ``foo`` will not cause any issues at
runtime. Even though ``foo`` expects ``kwargs`` of type ``Animal`` it doesn't
matter if it receives additional arguments because it only reads and uses what
it needs completely ignoring any additional values.
The calls to ``bar`` and ``spam`` will fail because an unexpected keyword
argument will be passed to the ``takes_name`` function.
Therefore, ``kwargs`` hinted with an unpacked ``TypedDict`` can only be passed
to another function if the function to which unpacked kwargs are being passed
to has ``**kwargs`` in its signature as well, because then additional keywords
would not cause errors at runtime during function invocation. Otherwise, the
type checker should generate an error.
In cases similar to the ``bar`` function above the problem could be worked
around by explicitly dereferencing desired fields and using them as parameters
to perform the function call::
def bar(**kwargs: **Animal):
name = kwargs["name"]
takes_name(name)
Intended Usage
--------------
This proposal will bring a large benefit to the codebases that already use
``**kwargs`` because of the flexibility that they provided in the initial
phases of the development, but now are mature enough to use a stricter
contract via type hints.
Adding type hints directly in the source code as opposed to the ``*.pyi``
stubs benefits anyone who reads the code as it is easier to understand. Given
that currently precise ``**kwargs`` type hinting is impossible in that case the
choices are to either not type hint ``**kwargs`` at all, which isn't ideal, or
to refactor the function to use explicit keyword arguments, which often exceeds
the scope of time and effort allocated to adding type hinting and, as any code
change, introduces risk for both project maintainers and users. In that case
hinting ``**kwargs`` using a ``TypedDict`` as described in this PEP will not
require refactoring and function body and function invocations could be
appropriately type checked.
Another useful pattern that justifies using and typing ``**kwargs`` as proposed
is when the function's API should allow for optional keyword arguments that
don't have default values.
However, it has to be pointed out that in some cases there are better tools
for the job than using ``TypedDict`` to type ``**kwargs`` as proposed in this
PEP. For example, when writing new code if all the keyword arguments are
required or have default values then writing everything explicitly is better
than using ``**kwargs`` and a ``TypedDict``::
def foo(name: str, year: int): ... # Preferred way.
def foo(**kwargs: **Movie): ...
Similarly, when type hinting third party libraries via stubs it is again better
to state the function signature explicitly - this is the only way to type such
a function if it has default parameters. Another issue that may arise in this
case when trying to type hint the function with a ``TypedDict`` is that some
standard function arguments may be treated as keyword only::
def foo(name, year): ... # Function in a third party library.
def foo(**Movie): ... # Function signature in a stub file.
foo("Life of Brian", 1979) # This would be now failing type
# checking but is fine.
foo(name="Life of Brian", year=1979) # This would be the only way to call
# the function now that passes type
# checking.
Therefore, in this case it is again preferred to type hint such function
explicitly as::
def foo(name: str, year: int): ...
Grammar Changes
===============
This PEP requires a grammar change so that the double asterisk syntax is
allowed for ``**kwargs`` annotations. The proposed change is to extend the
``kwds`` rule in `the grammar <https://docs.python.org/3/reference/grammar.html>`__
as follows:
Before:
.. code-block:: peg
kwds: '**' param_no_default
After:
.. code-block:: peg
kwds:
| '**' param_no_default_double_star_annotation
| '**' param_no_default
param_no_default_double_star_annotation:
| param_double_star_annotation & ')'
param_double_star_annotation: NAME double_star_annotation
double_star_annotation: ':' double_star_expression
double_star_expression: '**' expression
A new AST node needs to be created so that type checkers can differentiate the
semantics of the new syntax from the existing one, which indicates that all
``**kwargs`` should be of the same type. Then, whenever the new syntax is
used, type checkers will be able to take into account that ``**kwargs`` should
be unpacked. The proposition is to add a new ``DoubleStarred`` AST node. Then,
an AST node for the function defined as::
def foo(**kwargs: **Movie): ...
should look as below::
FunctionDef(
name='foo',
args=arguments(
posonlyargs=[],
args=[],
kwonlyargs=[],
kw_defaults=[],
kwarg=arg(
arg='kwargs',
annotation=DoubleStarred(
value=Name(id='Movie', ctx=Load()),
ctx=Load())),
defaults=[]),
body=[
Expr(
value=Constant(value=Ellipsis))],
decorator_list=[])
The runtime annotations should be consistent with the AST. Continuing the
previous example::
>>> def foo(**kwargs: **Movie): ...
...
>>> foo.__annotations__
{'kwargs': **Movie}
The double asterisk syntax should call the ``__unpack__`` special method on
the object it was used on. This means that ``def foo(**kwargs: **T): ...`` is
equivalent to ``def foo(**kwargs: T.__unpack__()): ...``. In addition,
``**Movie`` in the example above is the ``repr`` of the object that
``__unpack__()`` returns.
Backwards Compatibility
-----------------------
Using the double asterisk syntax for annotating ``**kwargs`` would be available
only in new versions of Python. :pep:`646` dealt with the similar problem and
its authors introduced a new type operator ``Unpack``. For the purposes of this
PEP, the proposition is to reuse ``Unpack`` for more precise ``**kwargs``
typing. For example::
def foo(**kwargs: Unpack[Movie]) -> None: ...
There are several reasons for reusing :pep:`646`'s ``Unpack``. Firstly, the
name is quite suitable and intuitive for the ``**kwargs`` typing use case as
the keywords arguments are "unpacked" from the ``TypedDict``. Secondly, there
would be no need to introduce any new special forms. Lastly, the use of
``Unpack`` for the purposes described in this PEP does not interfere with the
use cases described in :pep:`646`.
Alternatives
------------
Instead of making the grammar change, ``Unpack`` could be the only way to
annotate ``**kwargs`` of different types. However, introducing the double
asterisk syntax has two advantages. Namely, it is more concise and more
intuitive than using ``Unpack``.
How to Teach This
=================
This PEP could be linked in the ``typing`` module's documentation. Moreover, a
new section on using ``Unpack`` as well as the new double asterisk syntax could
be added to the aforementioned docs. Similar sections could be also added to
the `mypy documentation <https://mypy.readthedocs.io/>`_ and the
`typing RTD documentation <https://typing.readthedocs.io/>`_.
Reference Implementation
========================
There is a proof-of-concept implementation of typing ``**kwargs`` using
``TypedDict`` as a `pull request to mypy <mypyPull10576_>`__
and `to mypy_extensions <mypyExtensionsPull22_>`__.
The implementation uses ``Expand`` instead of ``Unpack``.
The `Pyright type checker <https://github.com/microsoft/pyright>`_
`provides provisional support <pyrightProvisionalImplementation_>`__
for `this feature <pyrightIssue3002_>`__.
A proof-of-concept implementation of the CPython `grammar changes`_ described in
this PEP is `available on GitHub <cpythonGrammarChangePoc_>`__.
Rejected Ideas
==============
``TypedDict`` unions
--------------------
It is possible to create unions of typed dictionaries. However, supporting
typing ``**kwargs`` with a union of typed dicts would greatly increase the
complexity of the implementation of this PEP and there seems to be no
compelling use case to justify the support for this. Therefore, using unions of
typed dictionaries to type ``**kwargs`` as described in the context of this PEP
can result in an error::
class Book(TypedDict):
genre: str
pages: int
TypedDictUnion = Movie | Book
def foo(**kwargs: **TypedDictUnion) -> None: ... # WRONG! Unsupported use
# of a union of
# TypedDicts to type
# **kwargs
Instead, a function that expects a union of ``TypedDict``\s can be
overloaded::
@overload
def foo(**kwargs: **Movie): ...
@overload
def foo(**kwargs: **Book): ...
References
==========
.. _mypyIssue4441: https://github.com/python/mypy/issues/4441
.. _mypyPull10576: https://github.com/python/mypy/pull/10576
.. _mypyExtensionsPull22: https://github.com/python/mypy_extensions/pull/22/files
.. _pyrightIssue3002: https://github.com/microsoft/pyright/issues/3002
.. _pyrightProvisionalImplementation: https://github.com/microsoft/pyright/commit/5bee749eb171979e3f526cd8e5bf66b00593378a
.. _cpythonGrammarChangePoc: https://github.com/python/cpython/compare/main...franekmagiera:annotate-kwargs
Copyright
=========
This document is placed in the public domain or under the
CC0-1.0-Universal license, whichever is more permissive.