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<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN"

"http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd">

<head>

<title>Contributing — Matplotlib 3.3.0 documentation</title>

title="Search within Matplotlib 3.3.0 documentation"

href="../_static/opensearch.xml"/>

</head><body>

<div id="unreleased-message"> You are reading an old version of the documentation (v3.3.0). For the latest version see <a href="https://matplotlib.org/stable/devel/contributing.html">https://matplotlib.org/stable/devel/contributing.html</a></div>

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<div style="float: left; position: absolute; width: 496px; bottom: 0; padding-bottom: 24px">Version 3.3.0</div>

<div id="forkongithub"><a href="https://github.com/matplotlib/matplotlib">Fork me on GitHub</a></div>

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<ul>

<li><a href="../users/installing.html">Installation</a></li>

<li><a href="../contents.html">Documentation</a></li>

<li><a href="../gallery/index.html">Examples</a></li>

<li><a href="../tutorials/index.html">Tutorials</a></li>

<li><a href="index.html">Contributing</a></li>

</form>

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<h3>Navigation</h3>

<ul>

<a href="../genindex.html" title="General Index"

accesskey="I">index</a></li>

<a href="../py-modindex.html" title="Python Module Index"

>modules</a> |</li>

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accesskey="N">next</a> |</li>

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<li class="nav-item nav-item-1"><a href="index.html" accesskey="U">The Matplotlib Developers' Guide</a> »</li>

</ul>

</div>

<h3><a href="../contents.html">Table of Contents</a></h3>

<ul>

<li><a class="reference internal" href="#">Contributing</a><ul>

<li><a class="reference internal" href="#submitting-a-bug-report">Submitting a bug report</a></li>

<li><a class="reference internal" href="#retrieving-and-installing-the-latest-version-of-the-code">Retrieving and installing the latest version of the code</a><ul>

<li><a class="reference internal" href="#installing-matplotlib-in-developer-mode">Installing Matplotlib in developer mode</a></li>

</ul>

</li>

<li><a class="reference internal" href="#contributing-code">Contributing code</a><ul>

<li><a class="reference internal" href="#how-to-contribute">How to contribute</a></li>

<li><a class="reference internal" href="#contributing-pull-requests">Contributing pull requests</a></li>

<li><a class="reference internal" href="#issues-for-new-contributors">Issues for New Contributors</a></li>

</ul>

</li>

<li><a class="reference internal" href="#contributing-documentation">Contributing documentation</a></li>

<li><a class="reference internal" href="#other-ways-to-contribute">Other ways to contribute</a></li>

<li><a class="reference internal" href="#coding-guidelines">Coding guidelines</a><ul>

<li><a class="reference internal" href="#api-changes">API changes</a></li>

<li><a class="reference internal" href="#adding-new-api">Adding new API</a></li>

<li><a class="reference internal" href="#new-modules-and-files-installation">New modules and files: installation</a></li>

<li><a class="reference internal" href="#c-c-extensions">C/C++ extensions</a></li>

<li><a class="reference internal" href="#keyword-argument-processing">Keyword argument processing</a></li>

<li><a class="reference internal" href="#using-logging-for-debug-messages">Using logging for debug messages</a><ul>

<li><a class="reference internal" href="#which-logging-level-to-use">Which logging level to use?</a></li>

</ul>

</li>

<li><a class="reference internal" href="#writing-examples">Writing examples</a></li>

</ul>

</li>

</ul>

</li>

</ul>

<h3>Related Topics</h3>

<ul>

<li><a href="../contents.html">Documentation overview</a><ul>

<li><a href="index.html">The Matplotlib Developers' Guide</a><ul>

<li>Previous: <a href="index.html" title="previous chapter">The Matplotlib Developers' Guide</a></li>

<li>Next: <a href="testing.html" title="next chapter">Developer's tips for testing</a></li>

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<a href="../_sources/devel/contributing.rst.txt"

style="color: #c0c0c0" rel="nofollow">Show Page Source</a>

</div>

<h1>Contributing<a class="headerlink" href="#contributing" title="Permalink to this headline">¶</a></h1>

This project is a community effort, and everyone is welcome to

contribute. We follow the <a class="reference external" href="http://www.python.org/psf/codeofconduct/">Python Software Foundation Code of Conduct</a> in everything we do.

The project is hosted on <a class="reference external" href="https://github.com/matplotlib/matplotlib">https://github.com/matplotlib/matplotlib</a>

<h2>Submitting a bug report<a class="headerlink" href="#submitting-a-bug-report" title="Permalink to this headline">¶</a></h2>

If you find a bug in the code or documentation, do not hesitate to submit a

ticket to the

<a class="reference external" href="https://github.com/matplotlib/matplotlib/issues">Bug Tracker</a>. You are also

welcome to post feature requests or pull requests.

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

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

sentences.

</li>

<li>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.

</li>

<li>The actual outcome of the code snippet.

</li>

<li>The expected outcome of the code snippet.

</li>

<li>The Matplotlib version, Python version and platform that you are using. You

can grab the version with the following commands:

<div class="highlight-default notranslate"><div class="highlight"><pre>>>> import matplotlib

>>> matplotlib.__version__

'1.5.3'

>>> import platform

>>> platform.python_version()

'2.7.12'

</pre></div>

</div>

</li>

</ol>

We have preloaded the issue creation page with a Markdown template that you can

use to organize this information.

Thank you for your help in keeping bug reports complete, targeted and descriptive.

</div>

<h2>Retrieving and installing the latest version of the code<a class="headerlink" href="#retrieving-and-installing-the-latest-version-of-the-code" title="Permalink to this headline">¶</a></h2>

When developing Matplotlib, sources must be downloaded, built, and installed

into a local environment on your machine.

We use <a class="reference external" href="https://git-scm.com/">Git</a> for version control and

<a class="reference external" href="https://github.com/">GitHub</a> for hosting our main repository.

You can check out the latest sources with the command (see

<a class="reference internal" href="gitwash/set_up_fork.html#set-up-fork">Set up your fork</a> for more details):

<div class="highlight-default notranslate"><div class="highlight"><pre>git clone https://github.com/matplotlib/matplotlib.git

</pre></div>

</div>

and navigate to the <code class="file docutils literal notranslate">matplotlib</code> directory. If you have the proper privileges,

you can use <code class="docutils literal notranslate">git@</code> instead of <code class="docutils literal notranslate">https://</code>, which works through the ssh protocol

and might be easier to use if you are using 2-factor authentication.

<h3>Installing Matplotlib in developer mode<a class="headerlink" href="#installing-matplotlib-in-developer-mode" title="Permalink to this headline">¶</a></h3>

It is strongly recommended to set up a clean <a class="reference external" href="https://docs.python.org/3/library/venv.html">virtual environment</a>. Do not

use on a preexisting environment!

A new environment can be set up with

<div class="highlight-default notranslate"><div class="highlight"><pre>python3 -mvenv /path/to/devel/env

</pre></div>

</div>

and activated with one of the following:

<div class="highlight-default notranslate"><div class="highlight"><pre>source /path/to/devel/env/bin/activate # Linux/macOS

/path/to/devel/env/Scripts/activate.bat # Windows cmd.exe

/path/to/devel/env/Scripts/Activate.ps1 # Windows PowerShell

</pre></div>

</div>

Whenever you plan to work on Matplotlib, remember to activate the development

environment in your shell!

To install Matplotlib (and compile the C-extensions) run the following

command from the top-level directory

<div class="highlight-default notranslate"><div class="highlight"><pre>python -mpip install -ve .

</pre></div>

</div>

This installs Matplotlib in 'editable/develop mode', i.e., builds

everything and places the correct link entries in the install

directory so that python will be able to import Matplotlib from the

source directory. Thus, any changes to the <code class="docutils literal notranslate">*.py</code> files will be

reflected the next time you import the library. If you change the

C-extension source (which might happen if you change branches) you

will need to run

<div class="highlight-default notranslate"><div class="highlight"><pre>python setup.py build_ext --inplace

</pre></div>

</div>

or re-run <code class="docutils literal notranslate">python -mpip install -ve .</code>.

You can then run the tests to check your work environment is set up properly:

<div class="highlight-default notranslate"><div class="highlight"><pre>python -mpytest

</pre></div>

</div>

Note

Additional dependencies for testing: <a class="reference external" href="http://doc.pytest.org/en/latest/">pytest</a> (version 3.6 or later),

<a class="reference external" href="https://www.ghostscript.com/">Ghostscript</a>, <a class="reference external" href="https://inkscape.org/">Inkscape</a>

</div>

See also

<li><a class="reference internal" href="testing.html#testing">Developer's tips for testing</a></li>

</ul>

</div>

<h2>Contributing code<a class="headerlink" href="#contributing-code" title="Permalink to this headline">¶</a></h2>

<h3>How to contribute<a class="headerlink" href="#how-to-contribute" title="Permalink to this headline">¶</a></h3>

The preferred way to contribute to Matplotlib is to fork the <a class="reference external" href="https://github.com/matplotlib/matplotlib/">main

repository</a> on GitHub,

then submit a "pull request" (PR).

The best practices for using GitHub to make PRs to Matplotlib are

documented in the <a class="reference internal" href="gitwash/development_workflow.html#development-workflow">Development workflow</a> section.

A brief overview is:

<li><a class="reference external" href="https://github.com/join">Create an account</a> on GitHub if you do not

already have one.

</li>

<li>Fork the <a class="reference external" href="https://github.com/matplotlib/matplotlib">project repository</a>:

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.

</li>

<li>Clone this copy to your local disk:

<div class="highlight-default notranslate"><div class="highlight"><pre>$ git clone https://github.com/YourLogin/matplotlib.git

</pre></div>

</div>

</li>

<li>Create a branch to hold your changes:

<div class="highlight-default notranslate"><div class="highlight"><pre>$ git checkout -b my-feature origin/master

</pre></div>

</div>

and start making changes. Never work in the <code class="docutils literal notranslate">master</code> branch!

</li>

<li>Work on this copy, on your computer, using Git to do the version control.

When you're done editing e.g., <code class="docutils literal notranslate">lib/matplotlib/collections.py</code>, do:

<div class="highlight-default notranslate"><div class="highlight"><pre>$ git add lib/matplotlib/collections.py

$ git commit

</pre></div>

</div>

to record your changes in Git, then push them to GitHub with:

<div class="highlight-default notranslate"><div class="highlight"><pre>$ git push -u origin my-feature

</pre></div>

</div>

</li>

</ol>

Finally, go to the web page of your fork of the Matplotlib repo, and click

'Pull request' to send your changes to the maintainers for review. You may

want to consider sending an email to the mailing list for more visibility.

See also

<li><a class="reference external" href="https://git-scm.com/documentation">Git documentation</a></li>

<li><a class="reference external" href="https://git-scm.com/book/en/v2/GitHub-Contributing-to-a-Project">Git-Contributing to a Project</a></li>

<li><a class="reference external" href="https://lab.github.com/githubtraining/introduction-to-github">Introduction to GitHub</a></li>

<li><a class="reference internal" href="gitwash/development_workflow.html#development-workflow">Development workflow</a></li>

<li><a class="reference internal" href="gitwash/index.html#using-git">Working with Matplotlib source code</a></li>

</ul>

</div>

<h3>Contributing pull requests<a class="headerlink" href="#contributing-pull-requests" title="Permalink to this headline">¶</a></h3>

It is recommended to check that your contribution complies with the following

rules before submitting a pull request:

<ul>

<li>If your pull request addresses an issue, please use the title to describe the

issue and mention the issue number in the pull request description to ensure

that a link is created to the original issue.

</li>

<li>All public methods should have informative docstrings with sample usage when

appropriate. Use the <a class="reference external" href="https://numpydoc.readthedocs.io/en/latest/format.html">numpy docstring standard</a>.

</li>

<li>Formatting should follow the recommendations of <a class="reference external" href="https://www.python.org/dev/peps/pep-0008/">PEP8</a>. You should consider

installing/enabling automatic PEP8 checking in your editor. Part of the test

suite is checking PEP8 compliance, things go smoother if the code is mostly

PEP8 compliant to begin with.

</li>

<li>Each high-level plotting function should have a simple example in the

<code class="docutils literal notranslate">Example</code> section of the docstring. This should be as simple as possible

to demonstrate the method. More complex examples should go in the

<code class="docutils literal notranslate">examples</code> tree.

</li>

<li>Changes (both new features and bugfixes) should be tested. See <a class="reference internal" href="testing.html#testing">Developer's tips for testing</a>

for more details.

</li>

<li>Import the following modules using the standard scipy conventions:

<div class="highlight-default notranslate"><div class="highlight"><pre>import numpy as np

import numpy.ma as ma

import matplotlib as mpl

import matplotlib.pyplot as plt

import matplotlib.cbook as cbook

import matplotlib.patches as mpatches

</pre></div>

</div>

In general, Matplotlib modules should not import <a class="reference internal" href="../api/matplotlib_configuration_api.html#matplotlib.rcParams" title="matplotlib.rcParams"><code class="xref py py-obj docutils literal notranslate">rcParams</code></a> using <code class="docutils literal notranslate">from

matplotlib import rcParams</code>, but rather access it as <code class="docutils literal notranslate">mpl.rcParams</code>. This

is because some modules are imported very early, before the <a class="reference internal" href="../api/matplotlib_configuration_api.html#matplotlib.rcParams" title="matplotlib.rcParams"><code class="xref py py-obj docutils literal notranslate">rcParams</code></a>

singleton is constructed.

</li>

<li>If your change is a major new feature, add an entry to the <code class="docutils literal notranslate">What's new</code>

section by adding a new file in <code class="docutils literal notranslate">doc/users/next_whats_new</code> (see

<code class="file docutils literal notranslate">doc/users/next_whats_new/README.rst</code> for more information).

</li>

<li>If you change the API in a backward-incompatible way, please document it in

<code class="file docutils literal notranslate">doc/api/api_changes</code>, by adding to the relevant file

(see <code class="file docutils literal notranslate">doc/api/api_changes.rst</code> for more information)

</li>

<li>See below for additional points about <a class="reference internal" href="#keyword-argument-processing">Keyword argument processing</a>, if

applicable for your pull request.

</li>

</ul>

In addition, you can check for common programming errors with the following

tools:

<ul>

<li>Code with a good unittest coverage (at least 70%, better 100%), check with:

python -mpytest --cov=matplotlib --showlocals -v

</pre></div>

</div>

</li>

<li>No pyflakes warnings, check with:

pyflakes path/to/module.py

</pre></div>

</div>

</li>

</ul>

Note

The current state of the Matplotlib code base is not compliant with all

of those guidelines, but we expect that enforcing those constraints on all

new contributions will move the overall code base quality in the right

direction.

</div>

See also

<li><a class="reference internal" href="#coding-guidelines">Coding guidelines</a></li>

<li><a class="reference internal" href="testing.html#testing">Developer's tips for testing</a></li>

<li><a class="reference internal" href="documenting_mpl.html#documenting-matplotlib">Writing documentation</a></li>

</ul>

</div>

<h3>Issues for New Contributors<a class="headerlink" href="#issues-for-new-contributors" title="Permalink to this headline">¶</a></h3>

New contributors should look for the following tags when looking for issues.

We strongly recommend that new contributors tackle issues labeled

<a class="reference external" href="https://github.com/matplotlib/matplotlib/labels/good%20first%20issue">good first issue</a>

as they are easy, well documented issues, that do not require an understanding of

the different submodules of Matplotlib.

This helps the contributor become familiar with the contribution

workflow, and for the core devs to become acquainted with the contributor;

besides which, we frequently underestimate how easy an issue is to solve!

</div>

<h2>Contributing documentation<a class="headerlink" href="#contributing-documentation" title="Permalink to this headline">¶</a></h2>

Code is not the only way to contribute to Matplotlib. For instance,

documentation is also a very important part of the project and often doesn't

get as much attention as it deserves. If you find a typo in the documentation,

or have made improvements, do not hesitate to send an email to the mailing

list or submit a GitHub pull request. To make a pull request, refer to the

guidelines outlined in <a class="reference internal" href="#how-to-contribute">How to contribute</a>.

Full documentation can be found under the <code class="file docutils literal notranslate">doc/</code>, <code class="file docutils literal notranslate">tutorials/</code>,

and <code class="file docutils literal notranslate">examples/</code> directories.

See also

<li><a class="reference internal" href="documenting_mpl.html#documenting-matplotlib">Writing documentation</a></li>

</ul>

</div>

<h2>Other ways to contribute<a class="headerlink" href="#other-ways-to-contribute" title="Permalink to this headline">¶</a></h2>

It also helps us if you spread the word: reference the project from your blog

and articles or link to it from your website! If Matplotlib contributes to a

project that leads to a scientific publication, please follow the

<a class="reference internal" href="../citing.html">Citing Matplotlib</a> guidelines.

</div>

<h2>Coding guidelines<a class="headerlink" href="#coding-guidelines" title="Permalink to this headline">¶</a></h2>

<h3>API changes<a class="headerlink" href="#api-changes" title="Permalink to this headline">¶</a></h3>

Changes to the public API must follow a standard deprecation procedure to

prevent unexpected breaking of code that uses Matplotlib.

<li>Deprecations must be announced via an entry in

the most recent <code class="file docutils literal notranslate">doc/api/api_changes_X.Y</code></li>

<li>Deprecations are targeted at the next point-release (i.e. 3.x.0).</li>

<li>The deprecated API should, to the maximum extent possible, remain fully

functional during the deprecation period. In cases where this is not

possible, the deprecation must never make a given piece of code do something

different than it was before; at least an exception should be raised.</li>

<li>If possible, usage of an deprecated API should emit a

<a class="reference internal" href="../api/cbook_api.html#matplotlib.cbook.deprecation.MatplotlibDeprecationWarning" title="matplotlib.cbook.deprecation.MatplotlibDeprecationWarning"><code class="xref py py-obj docutils literal notranslate">MatplotlibDeprecationWarning</code></a>. There are a number of helper tools for this:<ul>

<li>Use <code class="docutils literal notranslate">cbook.warn_deprecated()</code> for general deprecation warnings.</li>

<li>Use the decorator <code class="docutils literal notranslate">@cbook.deprecated</code> to deprecate classes, functions,

methods, or properties.</li>

<li>To warn on changes of the function signature, use the decorators

<code class="docutils literal notranslate">@cbook._delete_parameter</code>, <code class="docutils literal notranslate">@cbook._rename_parameter</code>, and

<code class="docutils literal notranslate">@cbook._make_keyword_only</code>.</li>

</ul>

</li>

<li>Deprecated API may be removed two point-releases after they were deprecated.</li>

</ul>

</div>

<h3>Adding new API<a class="headerlink" href="#adding-new-api" title="Permalink to this headline">¶</a></h3>

Every new function, parameter and attribute that is not explicitly marked as

private (i.e., starts with an underscore) becomes part of Matplotlib's public

API. As discussed above, changing the existing API is cumbersome. Therefore,

take particular care when adding new API:

<li>Mark helper functions and internal attributes as private by prefixing them

with an underscore.</li>

<li>Carefully think about good names for your functions and variables.</li>

<li>Try to adopt patterns and naming conventions from existing parts of the

Matplotlib API.</li>

<li>Consider making as many arguments keyword-only as possible. See also

<a class="reference external" href="https://emptysqua.re/blog/api-evolution-the-right-way/#adding-parameters">API Evolution the Right Way -- Add Parameters Compatibly</a>.</li>

</ul>

</div>

<h3>New modules and files: installation<a class="headerlink" href="#new-modules-and-files-installation" title="Permalink to this headline">¶</a></h3>

<li>If you have added new files or directories, or reorganized existing

ones, make sure the new files are included in the match patterns in

<code class="file docutils literal notranslate">MANIFEST.in</code>, and/or in package_data in <code class="file docutils literal notranslate">setup.py</code>.</li>

</ul>

</div>

<h3>C/C++ extensions<a class="headerlink" href="#c-c-extensions" title="Permalink to this headline">¶</a></h3>

<li>Extensions may be written in C or C++.</li>

<li>Code style should conform to PEP7 (understanding that PEP7 doesn't

address C++, but most of its admonitions still apply).</li>

<li>Python/C interface code should be kept separate from the core C/C++

code. The interface code should be named <code class="file docutils literal notranslate">FOO_wrap.cpp</code> or

<code class="file docutils literal notranslate">FOO_wrapper.cpp</code>.</li>

<li>Header file documentation (aka docstrings) should be in Numpydoc

format. We don't plan on using automated tools for these

docstrings, and the Numpydoc format is well understood in the

scientific Python community.</li>

</ul>

</div>

<h3>Keyword argument processing<a class="headerlink" href="#keyword-argument-processing" title="Permalink to this headline">¶</a></h3>

Matplotlib makes extensive use of <code class="docutils literal notranslate">**kwargs</code> for pass-through

customizations from one function to another. A typical example is in

<a class="reference internal" href="../api/_as_gen/matplotlib.pyplot.text.html#matplotlib.pyplot.text" title="matplotlib.pyplot.text"><code class="xref py py-func docutils literal notranslate">matplotlib.pyplot.text()</code></a>. The definition of the pylab text

function is a simple pass-through to

<a class="reference internal" href="../api/_as_gen/matplotlib.axes.Axes.text.html#matplotlib.axes.Axes.text" title="matplotlib.axes.Axes.text"><code class="xref py py-meth docutils literal notranslate">matplotlib.axes.Axes.text()</code></a>:

<div class="highlight-default notranslate"><div class="highlight"><pre># in pylab.py

def text(*args, **kwargs):

ret = gca().text(*args, **kwargs)

draw_if_interactive()

return ret

</pre></div>

</div>

<a class="reference internal" href="../api/_as_gen/matplotlib.axes.Axes.text.html#matplotlib.axes.Axes.text" title="matplotlib.axes.Axes.text"><code class="xref py py-meth docutils literal notranslate">text()</code></a> in simplified form looks like this,

i.e., it just passes all <code class="docutils literal notranslate">args</code> and <code class="docutils literal notranslate">kwargs</code> on to

<code class="xref py py-meth docutils literal notranslate">matplotlib.text.Text.__init__()</code>:

<div class="highlight-default notranslate"><div class="highlight"><pre># in axes/_axes.py

def text(self, x, y, s, fontdict=None, withdash=False, **kwargs):

t = Text(x=x, y=y, text=s, **kwargs)

</pre></div>

</div>

and <code class="xref py py-meth docutils literal notranslate">__init__()</code> (again with liberties for

illustration) just passes them on to the

<a class="reference internal" href="../api/_as_gen/matplotlib.artist.Artist.update.html#matplotlib.artist.Artist.update" title="matplotlib.artist.Artist.update"><code class="xref py py-meth docutils literal notranslate">matplotlib.artist.Artist.update()</code></a> method:

<div class="highlight-default notranslate"><div class="highlight"><pre># in text.py

def __init__(self, x=0, y=0, text='', **kwargs):

Artist.__init__(self)

self.update(kwargs)

</pre></div>

</div>

<code class="docutils literal notranslate">update</code> does the work looking for methods named like

<code class="docutils literal notranslate">set_property</code> if <code class="docutils literal notranslate">property</code> is a keyword argument. i.e., no one

looks at the keywords, they just get passed through the API to the

artist constructor which looks for suitably named methods and calls

them with the value.

As a general rule, the use of <code class="docutils literal notranslate">**kwargs</code> should be reserved for

pass-through keyword arguments, as in the example above. If all the

keyword args are to be used in the function, and not passed

on, use the key/value keyword args in the function definition rather

than the <code class="docutils literal notranslate">**kwargs</code> idiom.

In some cases, you may want to consume some keys in the local

function, and let others pass through. Instead of popping arguments to

use off <code class="docutils literal notranslate">**kwargs</code>, specify them as keyword-only arguments to the local

function. This makes it obvious at a glance which arguments will be

consumed in the function. For example, in

<a class="reference internal" href="../api/_as_gen/matplotlib.axes.Axes.plot.html#matplotlib.axes.Axes.plot" title="matplotlib.axes.Axes.plot"><code class="xref py py-meth docutils literal notranslate">plot()</code></a>, <code class="docutils literal notranslate">scalex</code> and <code class="docutils literal notranslate">scaley</code> are

local arguments and the rest are passed on as

<a class="reference internal" href="../api/_as_gen/matplotlib.lines.Line2D.html#matplotlib.lines.Line2D" title="matplotlib.lines.Line2D"><code class="xref py py-meth docutils literal notranslate">Line2D()</code></a> keyword arguments:

<div class="highlight-default notranslate"><div class="highlight"><pre># in axes/_axes.py

def plot(self, *args, scalex=True, scaley=True, **kwargs):

lines = []

for line in self._get_lines(*args, **kwargs):

self.add_line(line)

lines.append(line)

</pre></div>

</div>

<h3>Using logging for debug messages<a class="headerlink" href="#using-logging-for-debug-messages" title="Permalink to this headline">¶</a></h3>

Matplotlib uses the standard python <a class="reference external" href="https://docs.python.org/3/library/logging.html#module-logging" title="(in Python v3.8)"><code class="xref py py-obj docutils literal notranslate">logging</code></a> library to write verbose

warnings, information, and

debug messages. Please use it! In all those places you write <a class="reference external" href="https://docs.python.org/3/library/functions.html#print" title="(in Python v3.8)"><code class="xref py py-func docutils literal notranslate">print()</code></a>

statements to do your debugging, try using <code class="xref py py-func docutils literal notranslate">log.debug()</code> instead!

To include <a class="reference external" href="https://docs.python.org/3/library/logging.html#module-logging" title="(in Python v3.8)"><code class="xref py py-obj docutils literal notranslate">logging</code></a> in your module, at the top of the module, you need to

<code class="docutils literal notranslate">import logging</code>. Then calls in your code like:

<div class="highlight-default notranslate"><div class="highlight"><pre>_log = logging.getLogger(__name__) # right after the imports

# code

# more code

_log.info('Here is some information')

_log.debug('Here is some more detailed information')

</pre></div>

</div>

will log to a logger named <code class="docutils literal notranslate">matplotlib.yourmodulename</code>.

If an end-user of Matplotlib sets up <a class="reference external" href="https://docs.python.org/3/library/logging.html#module-logging" title="(in Python v3.8)"><code class="xref py py-obj docutils literal notranslate">logging</code></a> to display at levels

more verbose than <code class="xref py py-obj docutils literal notranslate">logging.WARNING</code> in their code with the Matplotlib-provided

helper:

<div class="highlight-default notranslate"><div class="highlight"><pre>plt.set_loglevel("debug")

</pre></div>

</div>

or manually with

<div class="highlight-default notranslate"><div class="highlight"><pre>import logging

logging.basicConfig(level=logging.DEBUG)

import matplotlib.pyplot as plt

</pre></div>

</div>

Then they will receive messages like:

<div class="highlight-default notranslate"><div class="highlight"><pre>DEBUG:matplotlib.backends:backend MacOSX version unknown

DEBUG:matplotlib.yourmodulename:Here is some information

</pre></div>

</div>

<h4>Which logging level to use?<a class="headerlink" href="#which-logging-level-to-use" title="Permalink to this headline">¶</a></h4>

There are five levels at which you can emit messages.

<li><a class="reference external" href="https://docs.python.org/3/library/logging.html#logging.critical" title="(in Python v3.8)"><code class="xref py py-obj docutils literal notranslate">logging.critical</code></a> and <a class="reference external" href="https://docs.python.org/3/library/logging.html#logging.error" title="(in Python v3.8)"><code class="xref py py-obj docutils literal notranslate">logging.error</code></a> are really only there for errors that

will end the use of the library but not kill the interpreter.</li>

<li><a class="reference external" href="https://docs.python.org/3/library/logging.html#logging.warning" title="(in Python v3.8)"><code class="xref py py-obj docutils literal notranslate">logging.warning</code></a> and <code class="xref py py-obj docutils literal notranslate">cbook._warn_external</code> are used to warn the user,

see below.</li>

<li><a class="reference external" href="https://docs.python.org/3/library/logging.html#logging.info" title="(in Python v3.8)"><code class="xref py py-obj docutils literal notranslate">logging.info</code></a> is for information that the user may want to know if the

program behaves oddly. They are not displayed by default. For instance, if

an object isn't drawn because its position is <code class="docutils literal notranslate">NaN</code>, that can usually

be ignored, but a mystified user could call

<code class="docutils literal notranslate">logging.basicConfig(level=logging.INFO)</code> and get an error message that

says why.</li>

<li><a class="reference external" href="https://docs.python.org/3/library/logging.html#logging.debug" title="(in Python v3.8)"><code class="xref py py-obj docutils literal notranslate">logging.debug</code></a> is the least likely to be displayed, and hence can be the

most verbose. "Expected" code paths (e.g., reporting normal intermediate

steps of layouting or rendering) should only log at this level.</li>

</ul>

By default, <a class="reference external" href="https://docs.python.org/3/library/logging.html#module-logging" title="(in Python v3.8)"><code class="xref py py-obj docutils literal notranslate">logging</code></a> displays all log messages at levels higher than

<code class="xref py py-obj docutils literal notranslate">logging.WARNING</code> to <a class="reference external" href="https://docs.python.org/3/library/sys.html#sys.stderr" title="(in Python v3.8)"><code class="xref py py-obj docutils literal notranslate">sys.stderr</code></a>.

The <a class="reference external" href="https://docs.python.org/3/howto/logging.html#logging-basic-tutorial">logging tutorial</a> suggests that the difference

between <a class="reference external" href="https://docs.python.org/3/library/logging.html#logging.warning" title="(in Python v3.8)"><code class="xref py py-obj docutils literal notranslate">logging.warning</code></a> and <code class="xref py py-obj docutils literal notranslate">cbook._warn_external</code> (which uses

<a class="reference external" href="https://docs.python.org/3/library/warnings.html#warnings.warn" title="(in Python v3.8)"><code class="xref py py-obj docutils literal notranslate">warnings.warn</code></a>) is that <code class="xref py py-obj docutils literal notranslate">cbook._warn_external</code> should be used for things the

user must change to stop the warning (typically in the source), whereas

<a class="reference external" href="https://docs.python.org/3/library/logging.html#logging.warning" title="(in Python v3.8)"><code class="xref py py-obj docutils literal notranslate">logging.warning</code></a> can be more persistent. Moreover, note that

<code class="xref py py-obj docutils literal notranslate">cbook._warn_external</code> will by default only emit a given warning once for

each line of user code, whereas <a class="reference external" href="https://docs.python.org/3/library/logging.html#logging.warning" title="(in Python v3.8)"><code class="xref py py-obj docutils literal notranslate">logging.warning</code></a> will display the message

every time it is called.

By default, <a class="reference external" href="https://docs.python.org/3/library/warnings.html#warnings.warn" title="(in Python v3.8)"><code class="xref py py-obj docutils literal notranslate">warnings.warn</code></a> displays the line of code that has the <code class="xref py py-obj docutils literal notranslate">warn</code> call.

This usually isn't more informative than the warning message itself. Therefore,

Matplotlib uses <code class="xref py py-obj docutils literal notranslate">cbook._warn_external</code> which uses <a class="reference external" href="https://docs.python.org/3/library/warnings.html#warnings.warn" title="(in Python v3.8)"><code class="xref py py-obj docutils literal notranslate">warnings.warn</code></a>, but goes

up the stack and displays the first line of code outside of Matplotlib.

For example, for the module:

<div class="highlight-default notranslate"><div class="highlight"><pre># in my_matplotlib_module.py

import warnings

def set_range(bottom, top):

if bottom == top:

warnings.warn('Attempting to set identical bottom==top')

</pre></div>

</div>

running the script:

<div class="highlight-default notranslate"><div class="highlight"><pre>from matplotlib import my_matplotlib_module

my_matplotlib_module.set_range(0, 0) #set range

</pre></div>

</div>

will display:

<div class="highlight-default notranslate"><div class="highlight"><pre>UserWarning: Attempting to set identical bottom==top

warnings.warn('Attempting to set identical bottom==top')

</pre></div>

</div>

Modifying the module to use <code class="xref py py-obj docutils literal notranslate">cbook._warn_external</code>:

def set_range(bottom, top):

if bottom == top:

cbook._warn_external('Attempting to set identical bottom==top')

</pre></div>

</div>

and running the same script will display:

</pre></div>

</div>

<h3>Writing examples<a class="headerlink" href="#writing-examples" title="Permalink to this headline">¶</a></h3>

We have hundreds of examples in subdirectories of

<code class="file docutils literal notranslate">matplotlib/examples</code>, and these are automatically generated

when the website is built to show up in the <code class="xref py py-obj docutils literal notranslate">examples</code> section of the website.

Any sample data that the example uses should be kept small and

distributed with Matplotlib in the

<code class="file docutils literal notranslate">lib/matplotlib/mpl-data/sample_data/</code> directory. Then in your

example code you can load it into a file handle with:

<div class="highlight-default notranslate"><div class="highlight"><pre>import matplotlib.cbook as cbook

fh = cbook.get_sample_data('mydata.dat')

</pre></div>

</div>

</div>

Last updated on Jul 17, 2020.

Created using

<a href="http://sphinx-doc.org/">Sphinx</a> 2.2.2.

Doc version v3.3.0-3-g8994f1b60.

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