Welcome! typeshed is a community project that aims to work for a wide range of Python users and Python codebases. If you're trying a type checker on your Python code, your experience and what you can contribute are important to the project's success.
- Read the README.md file.
- Set up your environment to be able to run all tests. They should pass.
- Prepare your changes:
- Small fixes and additions can be submitted directly as pull requests, but contact us before starting significant work.
- Create your stubs conforming to the coding style.
- Make sure your tests pass cleanly on
mypy
,pytype
, andflake8
.
- Submit your changes by opening a pull request.
- You can expect a reply within a few days:
- Diffs are merged when considered ready by the core team.
- Feel free to ping the core team if your pull request goes without a reply for more than a few days.
For more details, read below.
If you've run into behavior in the type checker that suggests the type stubs for a given library are incorrect or incomplete, we want to hear from you!
Our main forum for discussion is the project's GitHub issue tracker. This is the right place to start a discussion of any of the above or most any other topic concerning the project.
For less formal discussion, try the typing chat room on gitter.im. Some Mypy core developers are almost always present; feel free to find us there and we're happy to chat. Substantive technical discussion will be directed to the issue tracker.
Everyone participating in the typeshed community, and in particular in our issue tracker, pull requests, and IRC channel, is expected to treat other people with respect and more generally to follow the guidelines articulated in the Python Community Code of Conduct.
Even more excellent than a good bug report is a fix for a bug, or the implementation of a much-needed stub. We'd love to have your contributions.
We use the usual GitHub pull-request flow, which may be familiar to you if you've contributed to other projects on GitHub. For the mechanics, see Mypy's git and GitHub workflow help page, or GitHub's own documentation.
Anyone interested in type stubs may review your code. One of the core developers will merge your pull request when they think it's ready. For every pull request, we aim to promptly either merge it or say why it's not yet ready; if you go a few days without a reply, please feel free to ping the thread by adding a new comment.
To get your pull request merged sooner, you should explain why you are making the change. For example, you can point to a code sample that is processed incorrectly by a type checker. It is also helpful to add links to online documentation or to the implementation of the code you are changing.
Also, do not squash your commits after you have submitted a pull request, as this erases context during review. We will squash commits when the pull request is merged.
At present the core developers are (alphabetically):
- David Fisher (@ddfisher)
- Łukasz Langa (@ambv)
- Jukka Lehtosalo (@JukkaL)
- Ivan Levkivskyi (@ilevkivskyi)
- Matthias Kramm (@matthiaskramm)
- Greg Price (@gnprice)
- Sebastian Rittau (@srittau)
- Guido van Rossum (@gvanrossum)
- Jelle Zijlstra (@JelleZijlstra)
NOTE: the process for preparing and submitting changes also applies to core developers. This ensures high quality contributions and keeps everybody on the same page. Avoid direct pushes to the repository.
If your change will be a significant amount of work to write, we highly recommend starting by opening an issue laying out what you want to do. That lets a conversation happen early in case other contributors disagree with what you'd like to do or have ideas that will help you do it.
Stubs should include the complete interface (classes, functions, constants, etc.) of the module they cover, but it is not always clear exactly what is part of the interface.
The following should always be included:
- All objects listed in the module's documentation.
- All objects included in
__all__
(if present).
Other objects may be included if they are being used in practice
or if they are not prefixed with an underscore. This means
that typeshed will generally accept contributions that add missing
objects, even if they are undocumented. Undocumented objects should
be marked with a comment of the form # undocumented
.
Example:
def list2cmdline(seq: Sequence[str]) -> str: ... # undocumented
We accept such undocumented objects because omitting objects can confuse users. Users who see an error like "module X has no attribute Y" will not know whether the error appeared because their code had a bug or because the stub is wrong. Although it may also be helpful for a type checker to point out usage of private objects, we usually prefer false negatives (no errors for wrong code) over false positives (type errors for correct code). In addition, even for private objects a type checker can be helpful in pointing out that an incorrect type was used.
We accept partial stubs, especially for larger packages. These need to follow the following guidelines:
- Included functions and methods must list all arguments, but the arguments
can be left unannotated. Do not use
Any
to mark unannotated arguments or return values. - Partial classes must include a
__getattr__()
method marked with an# incomplete
comment (see example below). - Partial modules (i.e. modules that are missing some or all classes,
functions, or attributes) must include a top-level
__getattr__()
function marked with an# incomplete
comment (see example below). - Partial packages (i.e. packages that are missing one or more sub-modules)
must have a
__init__.pyi
stub that is marked as incomplete (see above). A better alternative is to create empty stubs for all sub-modules and mark them as incomplete individually.
Example of a partial module with a partial class Foo
and a partially
annotated function bar()
:
def __getattr__(name: str) -> Any: ... # incomplete
class Foo:
def __getattr__(self, name: str) -> Any: ... # incomplete
x: int
y: str
def bar(x: str, y, *, z=...): ...
Mypy includes a tool called stubgen
that auto-generates stubs for Python and C modules using static analysis,
Sphinx docs, and runtime introspection. It can be used to get a starting
point for your stubs. Note that this generator is currently unable to
determine most argument and return types and omits them or uses Any
in
their place. Fill out manually the types that you know.
The below is an excerpt from the types for the datetime
module.
MAXYEAR: int
MINYEAR: int
class date:
def __init__(self, year: int, month: int, day: int) -> None: ...
@classmethod
def fromtimestamp(cls, timestamp: float) -> date: ...
@classmethod
def today(cls) -> date: ...
@classmethod
def fromordinal(cls, ordinal: int) -> date: ...
@property
def year(self) -> int: ...
def replace(self, year: int = ..., month: int = ..., day: int = ...) -> date: ...
def ctime(self) -> str: ...
def weekday(self) -> int: ...
Stub files are like Python files and you should generally expect them to look the same. Your tools should be able to successfully treat them as regular Python files. However, there are a few important differences you should know about.
Style conventions for stub files are different from PEP 8. The general rule is that they should be as concise as possible. Specifically:
- lines can be up to 130 characters long;
- functions and methods that don't fit in one line should be split up with one argument per line;
- all function bodies should be empty;
- prefer
...
overpass
; - prefer
...
on the same line as the class/function signature; - avoid vertical whitespace between consecutive module-level functions, names, or methods and fields within a single class;
- use a single blank line between top-level class definitions, or none if the classes are very small;
- do not use docstrings;
- use variable annotations instead of type comments, even for stubs that target older versions of Python;
- for arguments with a type and a default, use spaces around the
=
. The code formatter black will format stubs according to this standard.
Stub files should only contain information necessary for the type checker, and leave out unnecessary detail:
- for arguments with a default, use
...
instead of the actual default; - for arguments that default to
None
, useOptional[]
explicitly (see below for details); - use
float
instead ofUnion[int, float]
.
Some further tips for good type hints:
- avoid invariant collection types (
List
,Dict
) in argument positions, in favor of covariant types likeMapping
orSequence
; - avoid Union return types: python/mypy#1693;
- in Python 2, whenever possible, use
unicode
if that's the only possible type, andText
if it can be eitherunicode
orbytes
; - use platform checks like
if sys.platform == 'win32'
to denote platform-dependent APIs.
Imports in stubs are considered private (not part of the exported API) unless:
- they use the form
from library import name as name
(sic, using explicitas
even if the name stays the same); or - they use the form
from library import *
which means all names from that library are exported.
When adding type hints, avoid using the Any
type when possible. Reserve
the use of Any
for when:
- the correct type cannot be expressed in the current type system; and
- to avoid Union returns (see above).
Note that Any
is not the correct type to use if you want to indicate
that some function can accept literally anything: in those cases use
object
instead.
For arguments with type and a default value of None
, PEP 484
prescribes that the type automatically becomes Optional
. However we
prefer explicit over implicit in this case, and require the explicit
Optional[]
around the type. The mypy tests enforce this (through
the use of --no-implicit-optional) and the error looks like
Incompatible types in assignment (expression has type None, variable has type "Blah")
.
Stub files support forward references natively. In other words, the order of class declarations and type aliases does not matter in a stub file. You can also use the name of the class within its own body. Focus on making your stubs clear to the reader. Avoid using string literals in type annotations.
Type variables and aliases you introduce purely for legibility reasons should be prefixed with an underscore to make it obvious to the reader they are not part of the stubbed API.
When adding type annotations for context manager classes, annotate
the return type of __exit__
as bool only if the context manager
sometimes suppresses annotations -- if it sometimes returns True
at runtime. If the context manager never suppresses exceptions,
have the return type be either None
or Optional[bool]
. If you
are not sure whether exceptions are suppressed or not or if the
context manager is meant to be subclassed, pick Optional[bool]
.
See python/mypy#7214 for more details.
NOTE: there are stubs in this repository that don't conform to the style described above. Fixing them is a great starting point for new contributors.
There are separate directories for stdlib
and third_party
stubs.
Within those, there are separate directories for different versions of
Python the stubs target.
The directory name indicates the major version of Python that a stub targets
and optionally the lowest minor version, with the exception of the 2and3
directory which applies to both Python 2 and 3.
For example, stubs in the 3
directory will be applied to all versions of
Python 3, though stubs in the 3.7
directory will only be applied to versions
3.7 and above. However, stubs in the 2
directory will not be applied to
Python 3.
It is preferred to use a single stub in the more generic directory that
conditionally targets specific versions when needed, as opposed
to maintaining multiple stub files within more specific directories. Similarly,
if the given library works on both Python 2 and Python 3, prefer to put your
stubs in the 2and3
directory, unless the types are so different that the stubs
become unreadable that way.
You can use checks like if sys.version_info >= (3, 8):
to denote new
functionality introduced in a given Python version or solve type
differences. When doing so, only use one-tuples or two-tuples. This is
because:
-
mypy doesn't support more fine-grained version checks; and more importantly
-
the micro versions of a Python release will change over time in your checking environment and the checker should return consistent results regardless of the micro version used.
Because of this, if a given functionality was introduced in, say, Python 3.7.4, your check:
- should be expressed as
if sys.version_info >= (3, 7):
- should NOT be expressed as
if sys.version_info >= (3, 7, 4):
- should NOT be expressed as
if sys.version_info >= (3, 8):
This makes the type checker assume the functionality was also available in 3.7.0 - 3.7.3, which while technically incorrect is relatively harmless. This is a strictly better compromise than using the latter two forms, which would generate false positive errors for correct use under Python 3.7.4.
Note: in its current implementation, typeshed cannot contain stubs for multiple versions of the same third-party library. Prefer to generate stubs for the latest version released on PyPI at the time of your stubbing.
Type stubs are meant to be external type annotations for a given library. While they are useful documentation in its own merit, they augment the project's concrete implementation, not the project's documentation. Whenever you find them disagreeing, model the type information after the actual implementation and file an issue on the project's tracker to fix their documentation.
We aim to reply to all new issues promptly. We'll assign one or more labels to indicate we've triaged an issue, but most typeshed issues are relatively simple (stubs for a given module or package are missing, incomplete or incorrect) and we won't add noise to the tracker by labeling all of them. Please see the list of all labels for a detailed description of the labels we use.
Sometimes a PR can't make progress until some external issue is
addressed. We indicate this by editing the subject to add a [WIP]
prefix. (This should be removed before committing the issue once
unblocked!)
Core developers should follow these rules when processing pull requests:
- Always wait for tests to pass before merging PRs.
- Use "Squash and merge" to merge PRs.
- Delete branches for merged PRs (by core devs pushing to the main repo).
- Make sure commit messages to master are meaningful. For example, remove irrelevant intermediate commit messages.
- If stubs for a new library are submitted, notify the library's maintainers.