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<section id="installation">
<h1>Installation<a class="headerlink" href="#installation" title="Permalink to this heading">#</a></h1>
<section id="installing-an-official-release">
<h2>Installing an official release<a class="headerlink" href="#installing-an-official-release" title="Permalink to this heading">#</a></h2>
<p>Matplotlib releases are available as wheel packages for macOS, Windows and
Linux on <a class="reference external" href="https://pypi.org/project/matplotlib/">PyPI</a>. Install it using
<code class="docutils literal notranslate"><span class="pre">pip</span></code>:</p>
<div class="highlight-sh notranslate"><div class="highlight"><pre><span></span>python -m pip install -U pip
python -m pip install -U matplotlib
</pre></div>
</div>
<p>If this command results in Matplotlib being compiled from source and
there's trouble with the compilation, you can add <code class="docutils literal notranslate"><span class="pre">--prefer-binary</span></code> to
select the newest version of Matplotlib for which there is a
precompiled wheel for your OS and Python.</p>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>The following backends work out of the box: Agg, ps, pdf, svg</p>
<p>Python is typically shipped with tk bindings which are used by
TkAgg.</p>
<p>For support of other GUI frameworks, LaTeX rendering, saving
animations and a larger selection of file formats, you can
install <a class="reference internal" href="../../devel/dependencies.html#optional-dependencies"><span class="std std-ref">Optional dependencies</span></a>.</p>
</div>
</section>
<section id="third-party-distributions">
<h2>Third-party distributions<a class="headerlink" href="#third-party-distributions" title="Permalink to this heading">#</a></h2>
<p>Various third-parties provide Matplotlib for their environments.</p>
<section id="conda-packages">
<h3>Conda packages<a class="headerlink" href="#conda-packages" title="Permalink to this heading">#</a></h3>
<p>Matplotlib is available both via the <em>anaconda main channel</em></p>
<div class="highlight-sh notranslate"><div class="highlight"><pre><span></span>conda install matplotlib
</pre></div>
</div>
<p>as well as via the <em>conda-forge community channel</em></p>
<div class="highlight-sh notranslate"><div class="highlight"><pre><span></span>conda install -c conda-forge matplotlib
</pre></div>
</div>
</section>
<section id="python-distributions">
<h3>Python distributions<a class="headerlink" href="#python-distributions" title="Permalink to this heading">#</a></h3>
<p>Matplotlib is part of major Python distributions:</p>
<ul class="simple">
<li><p><a class="reference external" href="https://www.anaconda.com/">Anaconda</a></p></li>
<li><p><a class="reference external" href="https://www.activestate.com/products/python/downloads/">ActiveState ActivePython</a></p></li>
<li><p><a class="reference external" href="https://winpython.github.io/">WinPython</a></p></li>
</ul>
</section>
<section id="linux-package-manager">
<h3>Linux package manager<a class="headerlink" href="#linux-package-manager" title="Permalink to this heading">#</a></h3>
<p>If you are using the Python version that comes with your Linux distribution,
you can install Matplotlib via your package manager, e.g.:</p>
<ul class="simple">
<li><p>Debian / Ubuntu: <code class="docutils literal notranslate"><span class="pre">sudo</span> <span class="pre">apt-get</span> <span class="pre">install</span> <span class="pre">python3-matplotlib</span></code></p></li>
<li><p>Fedora: <code class="docutils literal notranslate"><span class="pre">sudo</span> <span class="pre">dnf</span> <span class="pre">install</span> <span class="pre">python3-matplotlib</span></code></p></li>
<li><p>Red Hat: <code class="docutils literal notranslate"><span class="pre">sudo</span> <span class="pre">yum</span> <span class="pre">install</span> <span class="pre">python3-matplotlib</span></code></p></li>
<li><p>Arch: <code class="docutils literal notranslate"><span class="pre">sudo</span> <span class="pre">pacman</span> <span class="pre">-S</span> <span class="pre">python-matplotlib</span></code></p></li>
</ul>
</section>
</section>
<section id="installing-a-nightly-build">
<span id="install-from-source"></span><h2>Installing a nightly build<a class="headerlink" href="#installing-a-nightly-build" title="Permalink to this heading">#</a></h2>
<p>Matplotlib makes nightly development build wheels available on the
<a class="reference external" href="https://anaconda.org/scipy-wheels-nightly">scipy-wheels-nightly Anaconda Cloud organization</a>.
These wheels can be installed with <code class="docutils literal notranslate"><span class="pre">pip</span></code> by specifying scipy-wheels-nightly
as the package index to query:</p>
<div class="highlight-sh notranslate"><div class="highlight"><pre><span></span>python -m pip install <span class="se">\</span>
--upgrade <span class="se">\</span>
--pre <span class="se">\</span>
--index-url https://pypi.anaconda.org/scipy-wheels-nightly/simple <span class="se">\</span>
--extra-index-url https://pypi.org/simple <span class="se">\</span>
matplotlib
</pre></div>
</div>
</section>
<section id="installing-from-source">
<h2>Installing from source<a class="headerlink" href="#installing-from-source" title="Permalink to this heading">#</a></h2>
<p>If you are interested in contributing to Matplotlib development,
running the latest source code, or just like to build everything
yourself, it is not difficult to build Matplotlib from source.</p>
<p>First you need to install the <a class="reference internal" href="../../devel/dependencies.html#dependencies"><span class="std std-ref">Dependencies</span></a>.</p>
<p>A C compiler is required. Typically, on Linux, you will need <code class="docutils literal notranslate"><span class="pre">gcc</span></code>, which
should be installed using your distribution's package manager; on macOS, you
will need <a class="reference external" href="https://guide.macports.org/chunked/installing.html#installing.xcode">xcode</a>; on Windows, you will need <a class="reference external" href="https://visualstudio.microsoft.com/downloads/">Visual Studio</a> 2015 or later.</p>
<p>For those using Visual Studio, make sure "Desktop development with C++" is
selected, and that the latest MSVC, "C++ CMake tools for Windows," and a
Windows SDK compatible with your version of Windows are selected and installed.
They should be selected by default under the "Optional" subheading, but are
required to build matplotlib from source.</p>
<p>The easiest way to get the latest development version to start contributing
is to go to the git <a class="reference external" href="https://github.com/matplotlib/matplotlib">repository</a>
and run:</p>
<div class="highlight-default notranslate"><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="o">/</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>or:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">git</span> <span class="n">clone</span> <span class="n">git</span><span class="nd">@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>If you're developing, it's better to do it in editable mode. The reason why
is that pytest's test discovery only works for Matplotlib
if installation is done this way. Also, editable mode allows your code changes
to be instantly propagated to your library code without reinstalling (though
you will have to restart your python process / kernel):</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">cd</span> <span class="n">matplotlib</span>
<span class="n">python</span> <span class="o">-</span><span class="n">m</span> <span class="n">pip</span> <span class="n">install</span> <span class="o">-</span><span class="n">e</span> <span class="o">.</span>
</pre></div>
</div>
<p>If you're not developing, it can be installed from the source directory with
a simple (just replace the last step):</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">python</span> <span class="o">-</span><span class="n">m</span> <span class="n">pip</span> <span class="n">install</span> <span class="o">.</span>
</pre></div>
</div>
<p>To run the tests you will need to install some additional dependencies:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">python</span> <span class="o">-</span><span class="n">m</span> <span class="n">pip</span> <span class="n">install</span> <span class="o">-</span><span class="n">r</span> <span class="n">requirements</span><span class="o">/</span><span class="n">dev</span><span class="o">/</span><span class="n">dev</span><span class="o">-</span><span class="n">requirements</span><span class="o">.</span><span class="n">txt</span>
</pre></div>
</div>
<p>Then, if you want to update your Matplotlib at any time, just do:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">git</span> <span class="n">pull</span>
</pre></div>
</div>
<p>When you run <code class="docutils literal notranslate"><span class="pre">git</span> <span class="pre">pull</span></code>, if the output shows that only Python files have
been updated, you are all set. If C files have changed, you need to run <code class="docutils literal notranslate"><span class="pre">pip</span>
<span class="pre">install</span> <span class="pre">-e</span> <span class="pre">.</span></code> again to compile them.</p>
<p>There is more information on <a class="reference internal" href="../../devel/gitwash/index.html#using-git"><span class="std std-ref">using git</span></a> in the developer
docs.</p>
<div class="admonition warning">
<p class="admonition-title">Warning</p>
<p>The following instructions in this section are for very custom
installations of Matplotlib. Proceed with caution because these instructions
may result in your build producing unexpected behavior and/or causing
local testing to fail.</p>
</div>
<p>If you would like to build from a tarball, grab the latest <em>tar.gz</em> release
file from <a class="reference external" href="https://pypi.org/project/matplotlib/">the PyPI files page</a>.</p>
<p>We provide a <a class="reference external" href="https://raw.githubusercontent.com/matplotlib/matplotlib/main/mplsetup.cfg.template">mplsetup.cfg</a> file which you can use to customize the build
process. For example, which default backend to use, whether some of the
optional libraries that Matplotlib ships with are installed, and so on. This
file will be particularly useful to those packaging Matplotlib.</p>
<p>If you are building your own Matplotlib wheels (or sdists) on Windows, note
that any DLLs that you copy into the source tree will be packaged too.</p>
</section>
<section id="installing-for-development">
<h2>Installing for development<a class="headerlink" href="#installing-for-development" title="Permalink to this heading">#</a></h2>
<p>See <a class="reference internal" href="../../devel/development_setup.html#installing-for-devs"><span class="std std-ref">Setting up Matplotlib for development</span></a>.</p>
</section>
<section id="frequently-asked-questions">
<span id="installing-faq"></span><h2>Frequently asked questions<a class="headerlink" href="#frequently-asked-questions" title="Permalink to this heading">#</a></h2>
<nav class="contents local" id="contents">
<ul class="simple">
<li><p><a class="reference internal" href="#report-a-compilation-problem" id="id3">Report a compilation problem</a></p></li>
<li><p><a class="reference internal" href="#matplotlib-compiled-fine-but-nothing-shows-up-when-i-use-it" id="id4">Matplotlib compiled fine, but nothing shows up when I use it</a></p></li>
<li><p><a class="reference internal" href="#how-to-completely-remove-matplotlib" id="id5">How to completely remove Matplotlib</a></p></li>
<li><p><a class="reference internal" href="#osx-notes" id="id6">OSX Notes</a></p>
<ul>
<li><p><a class="reference internal" href="#which-python-for-osx" id="id7">Which python for OSX?</a></p></li>
<li><p><a class="reference internal" href="#installing-osx-binary-wheels" id="id8">Installing OSX binary wheels</a></p></li>
<li><p><a class="reference internal" href="#checking-your-installation" id="id9">Checking your installation</a></p></li>
</ul>
</li>
</ul>
</nav>
<section id="report-a-compilation-problem">
<h3>Report a compilation problem<a class="headerlink" href="#report-a-compilation-problem" title="Permalink to this heading">#</a></h3>
<p>See <a class="reference internal" href="../faq/troubleshooting_faq.html#reporting-problems"><span class="std std-ref">Getting help</span></a>.</p>
</section>
<section id="matplotlib-compiled-fine-but-nothing-shows-up-when-i-use-it">
<h3>Matplotlib compiled fine, but nothing shows up when I use it<a class="headerlink" href="#matplotlib-compiled-fine-but-nothing-shows-up-when-i-use-it" title="Permalink to this heading">#</a></h3>
<p>The first thing to try is a <a class="reference internal" href="#clean-install"><span class="std std-ref">clean install</span></a> and see if
that helps. If not, the best way to test your install is by running a script,
rather than working interactively from a python shell or an integrated
development environment such as <strong class="program">IDLE</strong> which add additional
complexities. Open up a UNIX shell or a DOS command prompt and run, for
example:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">python</span> <span class="o">-</span><span class="n">c</span> <span class="s2">"from pylab import *; set_loglevel('debug'); plot(); show()"</span>
</pre></div>
</div>
<p>This will give you additional information about which backends Matplotlib is
loading, version information, and more. At this point you might want to make
sure you understand Matplotlib's <a class="reference internal" href="../../tutorials/introductory/customizing.html"><span class="doc">configuration</span></a>
process, governed by the <code class="file docutils literal notranslate"><span class="pre">matplotlibrc</span></code> configuration file which contains
instructions within and the concept of the Matplotlib backend.</p>
<p>If you are still having trouble, see <a class="reference internal" href="../faq/troubleshooting_faq.html#reporting-problems"><span class="std std-ref">Getting help</span></a>.</p>
</section>
<section id="how-to-completely-remove-matplotlib">
<span id="clean-install"></span><h3>How to completely remove Matplotlib<a class="headerlink" href="#how-to-completely-remove-matplotlib" title="Permalink to this heading">#</a></h3>
<p>Occasionally, problems with Matplotlib can be solved with a clean
installation of the package. In order to fully remove an installed Matplotlib:</p>
<ol class="arabic simple">
<li><p>Delete the caches from your <a class="reference internal" href="../faq/troubleshooting_faq.html#locating-matplotlib-config-dir"><span class="std std-ref">Matplotlib configuration directory</span></a>.</p></li>
<li><p>Delete any Matplotlib directories or eggs from your <a class="reference internal" href="../faq/troubleshooting_faq.html#locating-matplotlib-install"><span class="std std-ref">installation
directory</span></a>.</p></li>
</ol>
</section>
<section id="osx-notes">
<h3>OSX Notes<a class="headerlink" href="#osx-notes" title="Permalink to this heading">#</a></h3>
<section id="which-python-for-osx">
<span id="id1"></span><h4>Which python for OSX?<a class="headerlink" href="#which-python-for-osx" title="Permalink to this heading">#</a></h4>
<p>Apple ships OSX with its own Python, in <code class="docutils literal notranslate"><span class="pre">/usr/bin/python</span></code>, and its own copy
of Matplotlib. Unfortunately, the way Apple currently installs its own copies
of NumPy, Scipy and Matplotlib means that these packages are difficult to
upgrade (see <a class="reference external" href="https://github.com/MacPython/wiki/wiki/Which-Python#system-python-and-extra-python-packages">system python packages</a>). For that reason we strongly suggest
that you install a fresh version of Python and use that as the basis for
installing libraries such as NumPy and Matplotlib. One convenient way to
install Matplotlib with other useful Python software is to use the <a class="reference external" href="https://www.anaconda.com/">Anaconda</a>
Python scientific software collection, which includes Python itself and a
wide range of libraries; if you need a library that is not available from the
collection, you can install it yourself using standard methods such as <em>pip</em>.
See the Anaconda web page for installation support.</p>
<p>Other options for a fresh Python install are the standard installer from
<a class="reference external" href="https://www.python.org/downloads/mac-osx/">python.org</a>, or installing
Python using a general OSX package management system such as <a class="reference external" href="https://brew.sh/">homebrew</a> or <a class="reference external" href="https://www.macports.org">macports</a>. Power users on
OSX will likely want one of homebrew or macports on their system to install
open source software packages, but it is perfectly possible to use these
systems with another source for your Python binary, such as Anaconda
or Python.org Python.</p>
</section>
<section id="installing-osx-binary-wheels">
<span id="install-osx-binaries"></span><h4>Installing OSX binary wheels<a class="headerlink" href="#installing-osx-binary-wheels" title="Permalink to this heading">#</a></h4>
<p>If you are using Python from <a class="reference external" href="https://www.python.org">https://www.python.org</a>, Homebrew, or Macports,
then you can use the standard pip installer to install Matplotlib binaries in
the form of wheels.</p>
<p>pip is installed by default with python.org and Homebrew Python, but needs to
be manually installed on Macports with</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">sudo</span> <span class="n">port</span> <span class="n">install</span> <span class="n">py38</span><span class="o">-</span><span class="n">pip</span>
</pre></div>
</div>
<p>Once pip is installed, you can install Matplotlib and all its dependencies with
from the Terminal.app command line:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">python3</span> <span class="o">-</span><span class="n">m</span> <span class="n">pip</span> <span class="n">install</span> <span class="n">matplotlib</span>
</pre></div>
</div>
<p>You might also want to install IPython or the Jupyter notebook (<code class="docutils literal notranslate"><span class="pre">python3</span> <span class="pre">-m</span> <span class="pre">pip</span>
<span class="pre">install</span> <span class="pre">ipython</span> <span class="pre">notebook</span></code>).</p>
</section>
<section id="checking-your-installation">
<h4>Checking your installation<a class="headerlink" href="#checking-your-installation" title="Permalink to this heading">#</a></h4>
<p>The new version of Matplotlib should now be on your Python "path". Check this
at the Terminal.app command line:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">python3</span> <span class="o">-</span><span class="n">c</span> <span class="s1">'import matplotlib; print(matplotlib.__version__, matplotlib.__file__)'</span>
</pre></div>
</div>
<p>You should see something like</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="mf">3.6.0</span> <span class="o">/</span><span class="n">Library</span><span class="o">/</span><span class="n">Frameworks</span><span class="o">/</span><span class="n">Python</span><span class="o">.</span><span class="n">framework</span><span class="o">/</span><span class="n">Versions</span><span class="o">/</span><span class="mf">3.9</span><span class="o">/</span><span class="n">lib</span><span class="o">/</span><span class="n">python3</span><span class="mf">.9</span><span class="o">/</span><span class="n">site</span><span class="o">-</span><span class="n">packages</span><span class="o">/</span><span class="n">matplotlib</span><span class="o">/</span><span class="fm">__init__</span><span class="o">.</span><span class="n">py</span>
</pre></div>
</div>
<p>where <code class="docutils literal notranslate"><span class="pre">3.6.0</span></code> is the Matplotlib version you just installed, and the path
following depends on whether you are using Python.org Python, Homebrew or
Macports. If you see another version, or you get an error like</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">Traceback</span> <span class="p">(</span><span class="n">most</span> <span class="n">recent</span> <span class="n">call</span> <span class="n">last</span><span class="p">):</span>
<span class="n">File</span> <span class="s2">"<string>"</span><span class="p">,</span> <span class="n">line</span> <span class="mi">1</span><span class="p">,</span> <span class="ow">in</span> <span class="o"><</span><span class="n">module</span><span class="o">></span>
<span class="ne">ImportError</span><span class="p">:</span> <span class="n">No</span> <span class="n">module</span> <span class="n">named</span> <span class="n">matplotlib</span>
</pre></div>
</div>
<p>then check that the Python binary is the one you expected by running</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">which</span> <span class="n">python3</span>
</pre></div>
</div>
<p>If you get a result like <code class="docutils literal notranslate"><span class="pre">/usr/bin/python...</span></code>, then you are getting the
Python installed with OSX, which is probably not what you want. Try closing
and restarting Terminal.app before running the check again. If that doesn't fix
the problem, depending on which Python you wanted to use, consider reinstalling
Python.org Python, or check your homebrew or macports setup. Remember that
the disk image installer only works for Python.org Python, and will not get
picked up by other Pythons. If all these fail, please <a class="reference internal" href="../faq/troubleshooting_faq.html#reporting-problems"><span class="std std-ref">let us know</span></a>.</p>
</section>
</section>
</section>
</section>
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