Contributing to Tensorflow-stubs

The preferred workflow for contributing to Tensorflow-stubs is to fork the main repository on GitHub, clone, and develop on a branch. Steps:

Fork the project repository by clicking on the 'Fork' button near the top right of the page. This creates a copy of the code under your GitHub user account.
Clone your fork of the Tensorflow-stubs repository from your GitHub account to your local disk:
```
$ git clone git@github.com:Your-Username/tensorflow-stubs.git
$ cd tensorflow-stubs
```
Create a feature or bugfix or types branch to hold your development changes:
```
$ git checkout -b my-feature
```
Always use a branch. It's good practice to never work on the master branch! You don't need to worry about the history, changes can be rebased or squashed as needed.
Develop the feature on your feature branch. Add changed files using git add and then git commit files:
```
$ git add modified_files
$ git commit
```
to record your changes in Git, then push the changes to your GitHub account with:
```
$ git push -u origin my-feature
```
Go to the GitHub web page of your fork of the Tensorflow-stubs repo. Click the 'Pull request' button to send your changes to the project's maintainers for review. This will send an email to the maintainers.

(If you are unfamiliar with Git, please look up the Git documentation on the web, or ask a friend or another contributor for help.)

Pull Request Checklist

Please follow the following rules before you submit a pull request:

If your pull request addresses an issue, please use the pull request title to describe the issue and mention the issue number in the pull request description. This will make sure a link back to the original issue is created.
All public functions and methods should ideally have informative docstrings.
Please prefix the title of your pull request with [MRG] (Ready for Merge), if the contribution is complete and ready for a detailed review. Incomplete contributions should be prefixed [WIP] (to indicate a work in progress) and changed to [MRG] when it matures. WIPs may be useful to: indicate you are working on something to avoid duplicated work, request broad review of functionality or API, or seek collaborators. WIPs often benefit from the inclusion of a task list in the pull request description.

You can also check for common programming errors with the following tools:

$ pip install pylint
$ pylint path/to/code

Pylint errors are indicative of critical issues.

We use Github issues to track all bugs and feature requests; feel free to open an issue if you have found a bug or wish to see a feature implemented.

It is recommended to check that your issue complies with the following rules before submitting:

Verify that your issue is not being currently addressed by other issues or pull requests.
Please ensure all code snippets and error messages are formatted in appropriate code blocks. See Creating and highlighting code blocks.
If the bug is system specific please include your operating system type and version number, as well as your Python versions. This information can be found by running the following code snippet:

import platform; print(platform.platform())
import sys; print("Python", sys.version)