If you are reporting a bug, please do your best to include the following:

1. A short, top-level summary of the bug. In most cases, this should be 1-2

#. A short, top-level summary of the bug. In most cases, this should be 1-2

sentences.

2. A short, self-contained code snippet to reproduce the bug, ideally allowing

#. A short, self-contained code snippet to reproduce the bug, ideally allowing

a simple copy and paste to reproduce. Please do your best to reduce the code

snippet to the minimum required.

3. The actual outcome of the code snippet.

#. The actual outcome of the code snippet.

4. The expected outcome of the code snippet.

#. The expected outcome of the code snippet.

5. The Matplotlib version, Python version and platform that you are using. You

#. The Matplotlib version, Python version and platform that you are using. You

can grab the version with the following commands::

A brief overview of the workflow is as follows.

1. `Create an account<https://github.com/join>`_ on GitHub if you do not

#. `Create an account<https://github.com/join>`_ on GitHub if you do not

already have one.

2. Fork the `project repository<https://github.com/matplotlib/matplotlib>`_:

click on the'Fork' button near the top of the page. This creates a copy of

the code under your account on the GitHub server.

#. Fork the `project repository<https://github.com/matplotlib/matplotlib>`_ by

clicking on the:octicon:`repo-forked` **Fork** button near the top of the page.

This creates a copy ofthe code under your account on the GitHub server.

..tab-set::

#. Set up a development environment:

..tab-item::Local development

..tab-set::

3. Check out the Matplotlib repository and activate your development

environment:

..tab-item::Using GitHub Codespaces

* Open codespaces on your fork by clicking on the green "Code" button

Check out the Matplotlib repository and activate your development environment:

#. Open codespaces on your fork by clicking on the green "Code" button

on the GitHub web interface and selecting the "Codespaces" tab.

* Next, click on "Open codespaces on <your branch name>". You will be

#. Next, click on "Open codespaces on <your branch name>". You will be

able to change branches later, so you can select the default

``main`` branch.

* After the codespace is created, you will be taken to a new browser

#. After the codespace is created, you will be taken to a new browser

tab where you can use the terminal to activate a pre-defined conda

environment called ``mpl-dev``::

4. Install the local version of Matplotlib with::

#. Install the local version of Matplotlib with::

5. Create a branch to hold your changes::

#. Create a branch to hold your changes::

6. Work on this task using Git to do the version control. Codespaces persist for

#. Work on this task using Git to do the version control. Codespaces persist for

some time (check the `documentation for details

<https://docs.github.com/codespaces/getting-started/the-codespace-lifecycle>`_)

and can be managed on https://github.com/codespaces. When you're done editing

<https://github.com/devcontainers/features/tree/main/src/desktop-lite>`_.

You can use it by connecting to this desktop via your web browser. To do this:

1. Press ``F1`` or ``Ctrl/Cmd+Shift+P`` and select

#. Press ``F1`` or ``Ctrl/Cmd+Shift+P`` and select

``Ports: Focus on Ports View`` in the VSCode session to bring it into

focus. Open the ports view in your tool, select the ``noVNC`` port, and

click the Globe icon.

2. In the browser that appears, click the Connect button and enter the desktop

#. In the browser that appears, click the Connect button and enter the desktop

password (``vscode`` by default).

Check the `GitHub instructions

Introducing

1. Announce the deprecation in a new file

#. Announce the deprecation in a new file

:file:`doc/api/next_api_changes/deprecations/99999-ABC.rst` where ``99999``

is the pull request number and ``ABC`` are the contributor's initials.

2. If possible, issue a `~matplotlib.MatplotlibDeprecationWarning` when the

#. If possible, issue a `~matplotlib.MatplotlibDeprecationWarning` when the

deprecated API is used. There are a number of helper tools for this:

- Use ``_api.warn_deprecated()`` for general deprecation warnings

You can use standard rst cross references in *alternative*.

3. Make appropriate changes to the type hints in the associated ``.pyi`` file.

#. Make appropriate changes to the type hints in the associated ``.pyi`` file.

The general guideline is to match runtime reported behavior.

- Items marked with ``@_api.deprecated`` or ``@_api.deprecate_privatize_attribute``

Expiring

1. Announce the API changes in a new file

#. Announce the API changes in a new file

:file:`doc/api/next_api_changes/[kind]/99999-ABC.rst` where ``99999``

is the pull request number and ``ABC`` are the contributor's initials, and

``[kind]`` is one of the folders:file:`behavior`,:file:`development`,

:file:`removals`. See:file:`doc/api/next_api_changes/README.rst` for more

information. For the content, you can usually copy the deprecation notice

and adapt it slightly.

2. Change the code functionality and remove any related deprecation warnings.

3. Make appropriate changes to the type hints in the associated ``.pyi`` file.

#. Change the code functionality and remove any related deprecation warnings.

#. Make appropriate changes to the type hints in the associated ``.pyi`` file.

- Items marked with ``@_api.deprecated`` or ``@_api.deprecate_privatize_attribute``

are to be removed on expiry.