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<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></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>
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<div class="section" id="contributing">
<span id="id1"></span><h1>Contributing<a class="headerlink" href="#contributing" title="Permalink to this headline">¶</a></h1>
<p>This project is a community effort, and everyone is welcome to
contribute.</p>
<p>The project is hosted on <a class="reference external" href="https://github.com/matplotlib/matplotlib">https://github.com/matplotlib/matplotlib</a></p>
<div class="section" id="submitting-a-bug-report">
<h2>Submitting a bug report<a class="headerlink" href="#submitting-a-bug-report" title="Permalink to this headline">¶</a></h2>
<p>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.</p>
<p>If you are reporting a bug, please do your best to include the following:</p>
<blockquote>
<div><ol class="arabic">
<li><p class="first">A short, top-level summary of the bug. In most cases, this should be 1-2
sentences.</p>
</li>
<li><p class="first">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.</p>
</li>
<li><p class="first">The actual outcome of the code snippet</p>
</li>
<li><p class="first">The expected outcome of the code snippet</p>
</li>
<li><p class="first">The Matplotlib version, Python version and platform that you are using. You
can grab the version with the following commands:</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="kn">import</span> <span class="nn">matplotlib</span>
<span class="gp">>>> </span><span class="n">matplotlib</span><span class="o">.</span><span class="n">__version__</span>
<span class="go">'1.5.3'</span>
<span class="gp">>>> </span><span class="kn">import</span> <span class="nn">platform</span>
<span class="gp">>>> </span><span class="n">platform</span><span class="o">.</span><span class="n">python_version</span><span class="p">()</span>
<span class="go">'2.7.12'</span>
</pre></div>
</div>
</li>
</ol>
</div></blockquote>
<p>We have preloaded the issue creation page with a Markdown template that you can
use to organize this information.</p>
<p>Thank you for your help in keeping bug reports complete, targeted and descriptive.</p>
</div>
<div class="section" id="retrieving-and-installing-the-latest-version-of-the-code">
<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>
<p>When developing Matplotlib, sources must be downloaded, built, and installed into
a local environment on your machine.</p>
<p>Follow the instructions detailed <a class="reference internal" href="../users/installing.html#install-from-source"><span class="std std-ref">here</span></a> to set up your
environment to build Matplotlib from source.</p>
<div class="admonition warning">
<p class="first admonition-title">Warning</p>
<p class="last">When working on Matplotlib sources, having multiple versions installed by
different methods into the same environment may not always work as expected.</p>
</div>
<p>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="http://conda.pydata.org/docs/using/envs.html">conda environment</a>.</p>
<p>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 enviroment
using the same method used to install it.</p>
<p>If working on Matplotlib documentation only, the above steps are <em>not</em> absolutely
necessary.</p>
<p>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.</p>
<p>You can check out the latest sources with the command (see
<a class="reference internal" href="gitwash/set_up_fork.html#set-up-fork"><span class="std std-ref">Set up your fork</span></a> for more details):</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="n">git</span> <span class="n">clone</span> <span class="n">https</span><span class="p">:</span><span class="o">//</span><span class="n">github</span><span class="o">.</span><span class="n">com</span><span class="p">:</span><span class="n">matplotlib</span><span class="o">/</span><span class="n">matplotlib</span><span class="o">.</span><span class="n">git</span>
</pre></div>
</div>
<p>and navigate to the <code class="file docutils literal"><span class="pre">matplotlib</span></code> directory. If you have the proper privileges,
you can use <code class="docutils literal"><span class="pre">git@</span></code> instead of <code class="docutils literal"><span class="pre">https://</span></code>, which works through the ssh protocol
and might be easier to use if you are using 2-factor authentication.</p>
<p>To make sure the tests run locally you must build against the correct version
of freetype. To configure the build system to fetch and build it either export
the env <code class="docutils literal"><span class="pre">MPLLOCALFREETYPE</span></code> as:</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="n">export</span> <span class="n">MPLLOCALFREETYPE</span><span class="o">=</span><span class="mi">1</span>
</pre></div>
</div>
<p>or copy <code class="file docutils literal"><span class="pre">setup.cfg.template</span></code> to <code class="file docutils literal"><span class="pre">setup.cfg</span></code> and edit it to contain</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="p">[</span><span class="n">test</span><span class="p">]</span>
<span class="n">local_freetype</span> <span class="o">=</span> <span class="kc">True</span>
</pre></div>
</div>
<p>To install Matplotlib (and compile the c-extensions) run the following
command from the top-level directory</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="n">python</span> <span class="o">-</span><span class="n">mpip</span> <span class="n">install</span> <span class="o">-</span><span class="n">ve</span> <span class="o">.</span>
</pre></div>
</div>
<p>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"><span class="pre">*.py</span></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</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="n">python</span> <span class="n">setup</span><span class="o">.</span><span class="n">py</span> <span class="n">build</span>
</pre></div>
</div>
<p>or re-run <code class="docutils literal"><span class="pre">python</span> <span class="pre">-mpip</span> <span class="pre">install</span> <span class="pre">-ve</span> <span class="pre">.</span></code>.</p>
<p>Alternatively, if you do</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="n">python</span> <span class="o">-</span><span class="n">mpip</span> <span class="n">install</span> <span class="o">-</span><span class="n">v</span> <span class="o">.</span>
</pre></div>
</div>
<p>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"><span class="pre">setup.cfg.template</span></code> to
<code class="file docutils literal"><span class="pre">setup.cfg</span></code> and edit it to contain</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="p">[</span><span class="n">test</span><span class="p">]</span>
<span class="n">local_freetype</span> <span class="o">=</span> <span class="kc">True</span>
<span class="n">tests</span> <span class="o">=</span> <span class="kc">True</span>
</pre></div>
</div>
<p>In either case you can then run the tests to check your work
environment is set up properly:</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="n">python</span> <span class="n">tests</span><span class="o">.</span><span class="n">py</span>
</pre></div>
</div>
<div class="admonition note">
<p class="first admonition-title">Note</p>
<p class="last"><strong>Additional dependencies for testing</strong>: <a class="reference external" href="http://doc.pytest.org/en/latest/">pytest</a> (version 3.0 or later),
<a class="reference external" href="https://docs.python.org/dev/library/unittest.mock.html">mock</a> (if python < 3.3), <a class="reference external" href="https://www.ghostscript.com/">Ghostscript</a>, <a class="reference external" href="https://inkscape.org>">Inkscape</a></p>
</div>
<div class="admonition seealso">
<p class="first admonition-title">See also</p>
<ul class="last simple">
<li><a class="reference internal" href="testing.html#testing"><span class="std std-ref">Developer’s tips for testing</span></a></li>
</ul>
</div>
</div>
<div class="section" id="contributing-code">
<h2>Contributing code<a class="headerlink" href="#contributing-code" title="Permalink to this headline">¶</a></h2>
<div class="section" id="how-to-contribute">
<h3>How to contribute<a class="headerlink" href="#how-to-contribute" title="Permalink to this headline">¶</a></h3>
<p>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):</p>
<blockquote>
<div><ol class="arabic">
<li><p class="first"><a class="reference external" href="https://github.com/join">Create an account</a> on
GitHub if you do not already have one.</p>
</li>
<li><p class="first">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.</p>
</li>
<li><p class="first">Clone this copy to your local disk:</p>
<div class="highlight-default"><div class="highlight"><pre><span></span>$ git clone https://github.com:YourLogin/matplotlib.git
</pre></div>
</div>
</li>
<li><p class="first">Create a branch to hold your changes:</p>
<div class="highlight-default"><div class="highlight"><pre><span></span>$ git checkout -b my-feature origin/master
</pre></div>
</div>
<p>and start making changes. Never work in the <code class="docutils literal"><span class="pre">master</span></code> branch!</p>
</li>
<li><p class="first">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"><span class="pre">lib/matplotlib/collections.py</span></code>,
do:</p>
<div class="highlight-default"><div class="highlight"><pre><span></span>$ git add lib/matplotlib/collections.py
$ git commit
</pre></div>
</div>
<p>to record your changes in Git, then push them to GitHub with:</p>
<div class="highlight-default"><div class="highlight"><pre><span></span>$ git push -u origin my-feature
</pre></div>
</div>
</li>
</ol>
</div></blockquote>
<p>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.</p>
<div class="admonition seealso">
<p class="first admonition-title">See also</p>
<ul class="last simple">
<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"><span class="std std-ref">Development workflow</span></a>.</li>
<li><a class="reference internal" href="gitwash/index.html#using-git"><span class="std std-ref">Working with Matplotlib source code</span></a></li>
</ul>
</div>
</div>
<div class="section" id="contributing-pull-requests">
<h3>Contributing pull requests<a class="headerlink" href="#contributing-pull-requests" title="Permalink to this headline">¶</a></h3>
<p>It is recommended to check that your contribution complies with the following
rules before submitting a pull request:</p>
<blockquote>
<div><ul>
<li><p class="first">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 a link is created to the original issue.</p>
</li>
<li><p class="first">All public methods should have informative docstrings with sample
usage when appropriate. Use the
<a class="reference external" href="https://github.com/numpy/numpy/blob/master/doc/HOWTO_DOCUMENT.rst.txt">numpy docstring standard</a></p>
</li>
<li><p class="first">Formatting should follow <a class="reference external" href="https://www.python.org/dev/peps/pep-0008/">PEP8 recommendation</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.</p>
</li>
<li><p class="first">Each high-level plotting function should have a simple example in
the <code class="docutils literal"><span class="pre">Example</span></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"><span class="pre">examples</span></code> tree.</p>
</li>
<li><p class="first">Changes (both new features and bugfixes) should be tested. See
<a class="reference internal" href="testing.html#testing"><span class="std std-ref">Developer’s tips for testing</span></a> for more details.</p>
</li>
<li><p class="first">Import the following modules using the standard scipy conventions:</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">import</span> <span class="nn">numpy.ma</span> <span class="k">as</span> <span class="nn">ma</span>
<span class="kn">import</span> <span class="nn">matplotlib</span> <span class="k">as</span> <span class="nn">mpl</span>
<span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
<span class="kn">import</span> <span class="nn">matplotlib.cbook</span> <span class="k">as</span> <span class="nn">cbook</span>
<span class="kn">import</span> <span class="nn">matplotlib.patches</span> <span class="k">as</span> <span class="nn">mpatches</span>
</pre></div>
</div>
</li>
<li><p class="first">If your change is a major new feature, add an entry to the <code class="docutils literal"><span class="pre">What's</span> <span class="pre">new</span></code>
section by adding a new file in <code class="docutils literal"><span class="pre">doc/users/whats_new</span></code> (see
<code class="file docutils literal"><span class="pre">doc/users/whats_new/README</span></code> for more information).</p>
</li>
<li><p class="first">If you change the API in a backward-incompatible way, please
document it in <code class="xref py py-obj docutils literal"><span class="pre">doc/api/api_changes</span></code>, by adding a new file describing your
changes (see <code class="file docutils literal"><span class="pre">doc/api/api_changes/README</span></code> for more information)</p>
</li>
<li><p class="first">See below for additional points about
<a class="reference internal" href="#keyword-argument-processing"><span class="std std-ref">Keyword argument processing</span></a>, if code in your pull request
does that.</p>
</li>
</ul>
</div></blockquote>
<p>In addition, you can check for common programming errors with the following
tools:</p>
<blockquote>
<div><ul>
<li><p class="first">Code with a good unittest coverage (at least 70%, better 100%), check
with:</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="n">python</span> <span class="o">-</span><span class="n">mpip</span> <span class="n">install</span> <span class="n">coverage</span>
<span class="n">python</span> <span class="n">tests</span><span class="o">.</span><span class="n">py</span> <span class="o">--</span><span class="k">with</span><span class="o">-</span><span class="n">coverage</span>
</pre></div>
</div>
</li>
<li><p class="first">No pyflakes warnings, check with:</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="n">python</span> <span class="o">-</span><span class="n">mpip</span> <span class="n">install</span> <span class="n">pyflakes</span>
<span class="n">pyflakes</span> <span class="n">path</span><span class="o">/</span><span class="n">to</span><span class="o">/</span><span class="n">module</span><span class="o">.</span><span class="n">py</span>
</pre></div>
</div>
</li>
</ul>
</div></blockquote>
<div class="admonition note">
<p class="first admonition-title">Note</p>
<p class="last">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.</p>
</div>
<div class="admonition seealso">
<p class="first admonition-title">See also</p>
<ul class="last simple">
<li><a class="reference internal" href="#coding-guidelines"><span class="std std-ref">Coding guidelines</span></a></li>
<li><a class="reference internal" href="testing.html#testing"><span class="std std-ref">Developer’s tips for testing</span></a></li>
<li><a class="reference internal" href="documenting_mpl.html#documenting-matplotlib"><span class="std std-ref">Developer’s tips for documenting matplotlib</span></a></li>
</ul>
</div>
</div>
<div class="section" id="issues-for-new-contributors">
<span id="new-contributors"></span><h3>Issues for New Contributors<a class="headerlink" href="#issues-for-new-contributors" title="Permalink to this headline">¶</a></h3>
<p>New contributors should look for the following tags when looking for issues.
We strongly recommend that new contributors tackle
<a class="reference external" href="https://github.com/matplotlib/matplotlib/labels/new-contributor-friendly">new-contributor-friendly</a>
issues (easy, well documented issues, that do not require an understanding of
the different submodules of Matplotlib) and
<a class="reference external" href="https://github.com/matplotlib/matplotlib/labels/Difficulty%3A%20Easy">Easy-fix</a>
issues. 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!</p>
</div>
</div>
<div class="section" id="other-ways-to-contribute">
<span id="id2"></span><h2>Other ways to contribute<a class="headerlink" href="#other-ways-to-contribute" title="Permalink to this headline">¶</a></h2>
<p>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.</p>
<p>It also helps us if you spread the word: reference the project from your blog
and articles or link to it from your website!</p>
</div>
<div class="section" id="coding-guidelines">
<span id="id3"></span><h2>Coding guidelines<a class="headerlink" href="#coding-guidelines" title="Permalink to this headline">¶</a></h2>
<div class="section" id="new-modules-and-files-installation">
<h3>New modules and files: installation<a class="headerlink" href="#new-modules-and-files-installation" title="Permalink to this headline">¶</a></h3>
<ul class="simple">
<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"><span class="pre">MANIFEST.in</span></code>, and/or in <code class="xref py py-obj docutils literal"><span class="pre">package_data</span></code> in <code class="xref py py-obj docutils literal"><span class="pre">setup.py</span></code>.</li>
</ul>
</div>
<div class="section" id="c-c-extensions">
<h3>C/C++ extensions<a class="headerlink" href="#c-c-extensions" title="Permalink to this headline">¶</a></h3>
<ul class="simple">
<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"><span class="pre">FOO_wrap.cpp</span></code> or
<code class="xref py py-obj docutils literal"><span class="pre">FOO_wrapper.cpp</span></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>
<div class="section" id="keyword-argument-processing">
<span id="id4"></span><h3>Keyword argument processing<a class="headerlink" href="#keyword-argument-processing" title="Permalink to this headline">¶</a></h3>
<p>Matplotlib makes extensive use of <code class="docutils literal"><span class="pre">**kwargs</span></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"><span class="pre">matplotlib.pyplot.text()</span></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"><span class="pre">matplotlib.axes.Axes.text()</span></code></a>:</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="c1"># in pylab.py</span>
<span class="k">def</span> <span class="nf">text</span><span class="p">(</span><span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="n">ret</span> <span class="o">=</span> <span class="n">gca</span><span class="p">()</span><span class="o">.</span><span class="n">text</span><span class="p">(</span><span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
<span class="n">draw_if_interactive</span><span class="p">()</span>
<span class="k">return</span> <span class="n">ret</span>
</pre></div>
</div>
<p><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"><span class="pre">text()</span></code></a> in simplified form looks like this,
i.e., it just passes all <code class="docutils literal"><span class="pre">args</span></code> and <code class="docutils literal"><span class="pre">kwargs</span></code> on to
<code class="xref py py-meth docutils literal"><span class="pre">matplotlib.text.Text.__init__()</span></code>:</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="c1"># in axes/_axes.py</span>
<span class="k">def</span> <span class="nf">text</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">x</span><span class="p">,</span> <span class="n">y</span><span class="p">,</span> <span class="n">s</span><span class="p">,</span> <span class="n">fontdict</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">withdash</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="n">t</span> <span class="o">=</span> <span class="n">Text</span><span class="p">(</span><span class="n">x</span><span class="o">=</span><span class="n">x</span><span class="p">,</span> <span class="n">y</span><span class="o">=</span><span class="n">y</span><span class="p">,</span> <span class="n">text</span><span class="o">=</span><span class="n">s</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
</pre></div>
</div>
<p>and <code class="xref py py-meth docutils literal"><span class="pre">__init__()</span></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"><span class="pre">matplotlib.artist.Artist.update()</span></code></a> method:</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="c1"># in text.py</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">x</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">y</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">text</span><span class="o">=</span><span class="s1">''</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="n">Artist</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">update</span><span class="p">(</span><span class="n">kwargs</span><span class="p">)</span>
</pre></div>
</div>
<p><code class="docutils literal"><span class="pre">update</span></code> does the work looking for methods named like
<code class="docutils literal"><span class="pre">set_property</span></code> if <code class="docutils literal"><span class="pre">property</span></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.</p>
<p>As a general rule, the use of <code class="docutils literal"><span class="pre">**kwargs</span></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"><span class="pre">**kwargs</span></code> idiom.</p>
<p>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"><span class="pre">pop</span></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"><span class="pre">plot()</span></code></a>, <code class="docutils literal"><span class="pre">scalex</span></code> and <code class="docutils literal"><span class="pre">scaley</span></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"><span class="pre">Line2D()</span></code></a> keyword arguments:</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="c1"># in axes/_axes.py</span>
<span class="k">def</span> <span class="nf">plot</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="n">scalex</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="s1">'scalex'</span><span class="p">,</span> <span class="kc">True</span><span class="p">)</span>
<span class="n">scaley</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="s1">'scaley'</span><span class="p">,</span> <span class="kc">True</span><span class="p">)</span>
<span class="k">if</span> <span class="ow">not</span> <span class="bp">self</span><span class="o">.</span><span class="n">_hold</span><span class="p">:</span> <span class="bp">self</span><span class="o">.</span><span class="n">cla</span><span class="p">()</span>
<span class="n">lines</span> <span class="o">=</span> <span class="p">[]</span>
<span class="k">for</span> <span class="n">line</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">_get_lines</span><span class="p">(</span><span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="bp">self</span><span class="o">.</span><span class="n">add_line</span><span class="p">(</span><span class="n">line</span><span class="p">)</span>
<span class="n">lines</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">line</span><span class="p">)</span>
</pre></div>
</div>
<p>Note: there is a use case when <code class="docutils literal"><span class="pre">kwargs</span></code> are meant to be used locally
in the function (not passed on), but you still need the <code class="docutils literal"><span class="pre">**kwargs</span></code>
idiom. That is when you want to use <code class="docutils literal"><span class="pre">*args</span></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"><span class="pre">*args</span></code> usage, so you will be
forced to use <code class="docutils literal"><span class="pre">**kwargs</span></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"><span class="pre">matplotlib.contour.ContourLabeler.clabel()</span></code></a>:</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="c1"># in contour.py</span>
<span class="k">def</span> <span class="nf">clabel</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="n">fontsize</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'fontsize'</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
<span class="n">inline</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'inline'</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">fmt</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'fmt'</span><span class="p">,</span> <span class="s1">'</span><span class="si">%1.3f</span><span class="s1">'</span><span class="p">)</span>
<span class="n">colors</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'colors'</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">args</span><span class="p">)</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
<span class="n">levels</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">levels</span>
<span class="n">indices</span> <span class="o">=</span> <span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">levels</span><span class="p">))</span>
<span class="k">elif</span> <span class="nb">len</span><span class="p">(</span><span class="n">args</span><span class="p">)</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
<span class="o">...</span><span class="n">etc</span><span class="o">...</span>
</pre></div>
</div>
</div>
<div class="section" id="developing-a-new-backend">
<span id="custom-backend"></span><h3>Developing a new backend<a class="headerlink" href="#developing-a-new-backend" title="Permalink to this headline">¶</a></h3>
<p>If you are working on a custom backend, the <em>backend</em> setting in
<code class="file docutils literal"><span class="pre">matplotlibrc</span></code> (<a class="reference internal" href="../tutorials/introductory/customizing.html#sphx-glr-tutorials-introductory-customizing-py"><span class="std std-ref">Customizing matplotlib</span></a>) supports an
external backend via the <code class="docutils literal"><span class="pre">module</span></code> directive. If
<code class="file docutils literal"><span class="pre">my_backend.py</span></code> is a Matplotlib backend in your
<span class="target" id="index-0"></span><a class="reference internal" href="../faq/environment_variables_faq.html#envvar-PYTHONPATH"><code class="xref std std-envvar docutils literal"><span class="pre">PYTHONPATH</span></code></a>, you can set it on one of several ways</p>
<ul>
<li><p class="first">in <code class="file docutils literal"><span class="pre">matplotlibrc</span></code>:</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="n">backend</span> <span class="p">:</span> <span class="n">module</span><span class="p">:</span><span class="o">//</span><span class="n">my_backend</span>
</pre></div>
</div>
</li>
<li><p class="first">with the <span class="target" id="index-1"></span><a class="reference internal" href="../faq/environment_variables_faq.html#envvar-MPLBACKEND"><code class="xref std std-envvar docutils literal"><span class="pre">MPLBACKEND</span></code></a> environment variable:</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="o">></span> <span class="n">export</span> <span class="n">MPLBACKEND</span><span class="o">=</span><span class="s2">"module://my_backend"</span>
<span class="o">></span> <span class="n">python</span> <span class="n">simple_plot</span><span class="o">.</span><span class="n">py</span>
</pre></div>
</div>
</li>
<li><p class="first">with the use directive in your script:</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="kn">import</span> <span class="nn">matplotlib</span>
<span class="n">matplotlib</span><span class="o">.</span><span class="n">use</span><span class="p">(</span><span class="s1">'module://my_backend'</span><span class="p">)</span>
</pre></div>
</div>
</li>
</ul>
</div>
<div class="section" id="writing-examples">
<span id="sample-data"></span><h3>Writing examples<a class="headerlink" href="#writing-examples" title="Permalink to this headline">¶</a></h3>
<p>We have hundreds of examples in subdirectories of
<code class="file docutils literal"><span class="pre">matplotlib/examples</span></code>, and these are automatically generated
when the website is built to show up in the <code class="xref py py-obj docutils literal"><span class="pre">examples</span></code> section of the website.</p>
<p>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"><span class="pre">lib/matplotlib/mpl-data/sample_data/</span></code> directory. Then in your
example code you can load it into a file handle with:</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="kn">import</span> <span class="nn">matplotlib.cbook</span> <span class="k">as</span> <span class="nn">cbook</span>
<span class="n">fh</span> <span class="o">=</span> <span class="n">cbook</span><span class="o">.</span><span class="n">get_sample_data</span><span class="p">(</span><span class="s1">'mydata.dat'</span><span class="p">)</span>
</pre></div>
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© Copyright 2002 - 2012 John Hunter, Darren Dale, Eric Firing, Michael Droettboom and the Matplotlib development team; 2012 - 2017 The Matplotlib development team.
Last updated on Oct 13, 2017.
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