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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 2.2.4 documentation</title>

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<body>

<div id="unreleased-message"> You are reading an old version of the documentation (v2.2.4). For the latest version see <a href="https://matplotlib.org/stable/devel/contributing.html">https://matplotlib.org/stable/devel/contributing.html</a></div>

<div style="float: left; position: absolute; width: 496px; bottom: 0; padding-bottom: 24px">Version 2.2.4</div>

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

</div>

<h3>Navigation</h3>

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<h3>Quick search</h3>

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</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="#building-matplotlib-for-image-comparison-tests">Building Matplotlib for image comparison tests</a></li>

<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="#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="#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="#developing-a-new-backend">Developing a new backend</a></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>

</ul></li>

</ul>

</div>

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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.

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.

Follow the instructions detailed <a class="reference internal" href="../users/installing.html#install-from-source">here</a> to set up your

environment to build Matplotlib from source.

Warning

When working on Matplotlib sources, having multiple versions installed by

different methods into the same environment may not always work as expected.

</div>

To work on Matplotlib sources, it is strongly recommended to set up an alternative

development environment, using the something like <a class="reference external" href="http://docs.python-guide.org/en/latest/dev/virtualenvs/">virtual environments in python</a>, or a

<a class="reference external" href="https://docs.conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html">conda environment</a>.

If you choose to use an already existing environment, and not a clean virtual or

conda environment, uninstall the current version of Matplotlib in that environment

using the same method used to install it.

If working on Matplotlib documentation only, the above steps are not absolutely

necessary.

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>Building Matplotlib for image comparison tests<a class="headerlink" href="#building-matplotlib-for-image-comparison-tests" title="Permalink to this headline">¶</a></h3>

Matplotlib's test suite makes heavy use of image comparison tests,

meaning the result of a plot is compared against a known good result.

Unfortunately, different versions of FreeType produce differently

formed characters, causing these image comparisons to fail. To make

them reproducible, Matplotlib can be built with a special local copy

of FreeType. This is recommended for all Matplotlib developers.

Copy <code class="file docutils literal notranslate">setup.cfg.template</code> to <code class="file docutils literal notranslate">setup.cfg</code> and edit it to contain:

<div class="highlight-default notranslate"><div class="highlight"><pre>[test]

local_freetype = True

tests = True

</pre></div>

</div>

or set the <code class="docutils literal notranslate">MPLLOCALFREETYPE</code> environmental variable to any true

value.

</div>

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

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

</pre></div>

</div>

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

Alternatively, if you do

</pre></div>

</div>

all of the files will be copied to the installation directory however,

you will have to rerun this command every time the source is changed.

Additionally you will need to copy <code class="file docutils literal notranslate">setup.cfg.template</code> to

<code class="file docutils literal notranslate">setup.cfg</code> and edit it to contain

<div class="highlight-default notranslate"><div class="highlight"><pre>[test]

local_freetype = True

tests = True

</pre></div>

</div>

In either case 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 tests.py

</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://docs.python.org/dev/library/unittest.mock.html">mock</a> (if Python 2), <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 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>

</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="xref py py-obj docutils literal notranslate">doc/api/api_changes</code>, by adding a new file describing your changes (see

<code class="file docutils literal notranslate">doc/api/api_changes/README.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 tests.py --with-coverage

</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>Other ways to contribute<a class="headerlink" href="#other-ways-to-contribute" 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. Full documentation can be found under

the doc/ directory.

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

and articles or link to it from your website!

</div>

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

<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 <code class="xref py py-obj docutils literal notranslate">package_data</code> in <code class="xref py py-obj 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="xref py py-obj docutils literal notranslate">FOO_wrap.cpp</code> or

<code class="xref py py-obj 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. You can <code class="docutils literal notranslate">pop</code> the ones to be

used locally and pass on the rest. 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, **kwargs):

scalex = kwargs.pop('scalex', True)

scaley = kwargs.pop('scaley', True)

if not self._hold: self.cla()

lines = []

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

self.add_line(line)

lines.append(line)

</pre></div>

</div>

Note: there is a use case when <code class="docutils literal notranslate">kwargs</code> are meant to be used locally

in the function (not passed on), but you still need the <code class="docutils literal notranslate">**kwargs</code>

idiom. That is when you want to use <code class="docutils literal notranslate">*args</code> to allow variable

numbers of non-keyword args. In this case, python will not allow you

to use named keyword args after the <code class="docutils literal notranslate">*args</code> usage, so you will be

forced to use <code class="docutils literal notranslate">**kwargs</code>. An example is

<a class="reference internal" href="../api/contour_api.html#matplotlib.contour.ContourLabeler.clabel" title="matplotlib.contour.ContourLabeler.clabel"><code class="xref py py-meth docutils literal notranslate">matplotlib.contour.ContourLabeler.clabel()</code></a>:

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

def clabel(self, *args, **kwargs):

fontsize = kwargs.get('fontsize', None)

inline = kwargs.get('inline', 1)

self.fmt = kwargs.get('fmt', '%1.3f')

colors = kwargs.get('colors', None)

if len(args) == 0:

levels = self.levels

indices = range(len(self.levels))

elif len(args) == 1:

...etc...

</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 v3.7)"><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 v3.7)"><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 v3.7)"><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 v3.7)"><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">logger.WARNING</code> in their code as follows:

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

fmt = '%(name)s:%(lineno)5d - %(levelname)s - %(message)s'

logging.basicConfig(level=logging.DEBUG, format=fmt)

import matplotlib.pyplot as plt

</pre></div>

</div>

Then they will receive messages like:

<div class="highlight-default notranslate"><div class="highlight"><pre>matplotlib.backends: 89 - INFO - backend MacOSX version unknown

matplotlib.yourmodulename: 347 - INFO - Here is some information

matplotlib.yourmodulename: 348 - DEBUG - Here is some more detailed 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.

<a class="reference external" href="https://docs.python.org/3/library/logging.html#logging.critical" title="(in Python v3.7)"><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 v3.7)"><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. <a class="reference external" href="https://docs.python.org/3/library/logging.html#logging.warning" title="(in Python v3.7)"><code class="xref py py-obj docutils literal notranslate">logging.warning</code></a> overlaps with the

<code class="docutils literal notranslate">warnings</code> library. 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 v3.7)"><code class="xref py py-obj docutils literal notranslate">logging.warning</code></a> and <a class="reference external" href="https://docs.python.org/3/library/warnings.html#warnings.warn" title="(in Python v3.7)"><code class="xref py py-obj docutils literal notranslate">warnings.warn</code></a> is that

<a class="reference external" href="https://docs.python.org/3/library/warnings.html#warnings.warn" title="(in Python v3.7)"><code class="xref py py-obj docutils literal notranslate">warnings.warn</code></a> be used for things the user must change to stop

the warning, whereas <a class="reference external" href="https://docs.python.org/3/library/logging.html#logging.warning" title="(in Python v3.7)"><code class="xref py py-obj docutils literal notranslate">logging.warning</code></a> can be more persistent.

By default, <a class="reference external" href="https://docs.python.org/3/library/logging.html#module-logging" title="(in Python v3.7)"><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 v3.7)"><code class="xref py py-obj docutils literal notranslate">sys.stderr</code></a>.

Calls to <a class="reference external" href="https://docs.python.org/3/library/logging.html#logging.info" title="(in Python v3.7)"><code class="xref py py-obj docutils literal notranslate">logging.info</code></a> are not displayed by default. They are for

information that the user may want to know if the program behaves oddly.

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 set

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

says why.

<a class="reference external" href="https://docs.python.org/3/library/logging.html#logging.debug" title="(in Python v3.7)"><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.

</div>

<h3>Developing a new backend<a class="headerlink" href="#developing-a-new-backend" title="Permalink to this headline">¶</a></h3>

If you are working on a custom backend, the backend setting in

<code class="file docutils literal notranslate">matplotlibrc</code> (<a class="reference internal" href="../tutorials/introductory/customizing.html">Customizing Matplotlib with style sheets and rcParams</a>) supports an

external backend via the <code class="docutils literal notranslate">module</code> directive. If

<code class="file docutils literal notranslate">my_backend.py</code> is a Matplotlib backend in your

<a class="reference internal" href="../faq/environment_variables_faq.html#envvar-PYTHONPATH"><code class="xref std std-envvar docutils literal notranslate">PYTHONPATH</code></a>, you can set it on one of several ways

<ul>

<li>in <code class="file docutils literal notranslate">matplotlibrc</code>:

<div class="highlight-default notranslate"><div class="highlight"><pre>backend : module://my_backend

</pre></div>

</div>

</li>

<li>with the <a class="reference internal" href="../faq/environment_variables_faq.html#envvar-MPLBACKEND"><code class="xref std std-envvar docutils literal notranslate">MPLBACKEND</code></a> environment variable:

<div class="highlight-default notranslate"><div class="highlight"><pre>> export MPLBACKEND="module://my_backend"

> python simple_plot.py

</pre></div>

</div>

</li>

<li>with the use directive in your script:

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

matplotlib.use('module://my_backend')

</pre></div>

</div>

</li>

</ul>

</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="xref py py-obj 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 Feb 28, 2019.

Created using

<ahref="http://sphinx-doc.org/">Sphinx</a> 1.8.4.

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