CONTRIBUTING.md

Contributing to typeshed

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.

The contribution process at a glance

1. Read the README.md file.
2. Set up your environment to be able to run all tests. They should pass.
3. Prepare your changes:
   • Contact us before starting significant work.
   • IMPORTANT: For new libraries, get permission from the library owner first.
   • Create your stubs conforming to the coding style.
   • Make sure your tests pass cleanly on mypy, pytype, and flake8.
4. Submit your changes:
   • Open a pull request
   • For new libraries, include a reference to where you got permission
5. 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.

Discussion

If you've run into behavior in the type checker that suggests the type stubs for a given library are incorrect or incomplete, or a library you depend on is missing type annotations, 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.

Code of Conduct

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.

Submitting Changes

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.

Preparing Changes

Before you begin

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.

Adding a new library

If you want to submit type stubs for a new library, you need to contact the maintainers of the original library first to let them know and get their permission. Do it by opening an issue on their project's bug tracker. This gives them the opportunity to consider adopting type hints directly in their codebase (which you should prefer to external type stubs). When the project owners agree for you to submit stubs here, open a pull request referencing the message where you received permission.

Make sure your changes pass the tests (the README has more information).

What to include

Stubs should include all public objects (classes, functions, constants, etc.) in the module they cover. Omitting objects can confuse users, because 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. If you are submitting stubs to typeshed and you are unable to provide fully typed stubs for some of the objects in the library, you can use stubgen (see below) to generate untyped stubs. Although we prefer having exact types for all stubs, such stubs are better than nothing.

What counts as a "public object" is not always clear. Use your judgment, but objects that are listed in the module's documentation, that are included in __all__ (if present), and whose names do not start with an underscore are more likely to merit inclusion in a stub. If in doubt, err on the side of including more objects.

NEW: Sometimes it makes sense to include non-public objects in a stub. Mark these with a comment of the form # undocumented. See the motivation. Example:

def list2cmdline(seq: Sequence[str]) -> str: ...  # undocumented

Using stubgen

Mypy includes a tool called stubgen that you can use as 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 the types that you know.

Stub file coding style

Syntax example

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: ...

Conventions

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;
• all function bodies should be empty;
• prefer ... over pass;
• 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 =.

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, use Optional[] explicitly (see below for details);
• use float instead of Union[int, float].

Some further tips for good type hints:

• avoid invariant collection types (List, Dict) in argument positions, in favor of covariant types like Mapping or Sequence;
• avoid Union return types: python/mypy#1693;
• in Python 2, whenever possible, use unicode if that's the only possible type, and Text if it can be either unicode or bytes;
• 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 explicit as even if the name stays the same); or
• they use the form from library import * which means all names from that library are exported.

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.

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.

Stub versioning

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 3.6 directory will only be applied to versions 3.6 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, 4): 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 3.4.4, your check:

• should be expressed as if sys.version_info >= (3, 4):
• should NOT be expressed as if sys.version_info >= (3, 4, 4):
• should NOT be expressed as if sys.version_info >= (3, 5):

This makes the type checker assume the functionality was also available in 3.4.0 - 3.4.3, 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 3.4.4.

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.

What to do when a project's documentation and implementation disagree

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.

Issue-tracker conventions

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. Here's what our labels mean. (We also apply these to pull requests.)

• bug: It's a bug in a stub.
• bytes-unicode: It's related to bytes vs. unicode, usually Python 2.
• feature: It's a new typeshed feature.
• priority-high: This issue is more important than most.
• priority-low: This issue is less important than most.
• priority-normal: This issue has average priority.
• question: Not really an issue, but a question on how to do something.
• size-large: An issue of high complexity or affecting many files.
• size-medium: An issue of average complexity.
• size-small: An issue that will take only little effort to fix.

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 developer guidelines

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.