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<li><a class="reference internal" href="#">Installing</a><ul>
<li><a class="reference internal" href="#installing-pre-built-packages">Installing pre-built packages</a><ul>
<li><a class="reference internal" href="#most-platforms-scientific-python-distributions">Most platforms : scientific Python distributions</a></li>
<li><a class="reference internal" href="#linux-using-your-package-manager">Linux : using your package manager</a></li>
<li><a class="reference internal" href="#mac-osx-using-pip">Mac OSX : using pip</a></li>
<li><a class="reference internal" href="#windows">Windows</a></li>
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<li><a class="reference internal" href="#installing-from-source">Installing from source</a><ul>
<li><a class="reference internal" href="#build-requirements">Build requirements</a><ul>
<li><a class="reference internal" href="#required-dependencies">Required Dependencies</a></li>
<li><a class="reference internal" href="#optional-gui-framework">Optional GUI framework</a></li>
<li><a class="reference internal" href="#optional-external-programs">Optional external programs</a></li>
<li><a class="reference internal" href="#optional-dependencies">Optional dependencies</a></li>
<li><a class="reference internal" href="#required-libraries-that-ship-with-matplotlib">Required libraries that ship with matplotlib</a></li>
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<li><a class="reference internal" href="#building-on-linux">Building on Linux</a></li>
<li><a class="reference internal" href="#building-on-osx">Building on OSX</a></li>
<li><a class="reference internal" href="#building-on-windows">Building on Windows</a></li>
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<div class="section" id="installing">
<h1>Installing<a class="headerlink" href="#installing" title="Permalink to this headline">¶</a></h1>
<p>There are many different ways to install matplotlib, and the best way
depends on what operating system you are using, what you already have
installed, and how you want to use it. To avoid wading through all
the details (and potential complications) on this page, there are several
convenient options.</p>
<div class="section" id="installing-pre-built-packages">
<h2>Installing pre-built packages<a class="headerlink" href="#installing-pre-built-packages" title="Permalink to this headline">¶</a></h2>
<div class="section" id="most-platforms-scientific-python-distributions">
<h3>Most platforms : scientific Python distributions<a class="headerlink" href="#most-platforms-scientific-python-distributions" title="Permalink to this headline">¶</a></h3>
<p>The first option is to use one of the pre-packaged python
distributions that already provide matplotlib built-in. The
Continuum.io Python distribution (<a class="reference external" href="https://store.continuum.io/cshop/anaconda/">Anaconda</a> or <a class="reference external" href="http://conda.pydata.org/miniconda.html">miniconda</a>) and the Enthought
distribution <a class="reference external" href="https://www.enthought.com/products/canopy/">(Canopy)</a>
are both excellent choices that “just work” out of the box for
Windows, OSX and common Linux platforms. Both of these distributions
include matplotlib and <em>lots</em> of other useful tools. Another
excellent alternative for Windows users is <a class="reference external" href="https://code.google.com/p/pythonxy">Python (x, y)</a> .</p>
</div>
<div class="section" id="linux-using-your-package-manager">
<h3>Linux : using your package manager<a class="headerlink" href="#linux-using-your-package-manager" title="Permalink to this headline">¶</a></h3>
<p>If you are on Linux, you might prefer to use your package manager. matplotlib
is packaged for almost every major Linux distribution.</p>
<ul class="simple">
<li>Debian / Ubuntu : <code class="docutils literal"><span class="pre">sudo</span> <span class="pre">apt-get</span> <span class="pre">install</span> <span class="pre">python-matplotlib</span></code></li>
<li>Fedora / Redhat : <code class="docutils literal"><span class="pre">sudo</span> <span class="pre">yum</span> <span class="pre">install</span> <span class="pre">python-matplotlib</span></code></li>
</ul>
</div>
<div class="section" id="mac-osx-using-pip">
<h3>Mac OSX : using pip<a class="headerlink" href="#mac-osx-using-pip" title="Permalink to this headline">¶</a></h3>
<p>If you are on Mac OSX you can probably install matplotlib binaries using the
standard Python installation program <a class="reference external" href="https://pypi.python.org/pypi/pip">pip</a>.
See <a class="reference internal" href="../faq/installing_faq.html#install-osx-binaries"><span>Installing OSX binary wheels</span></a>.</p>
</div>
<div class="section" id="windows">
<h3>Windows<a class="headerlink" href="#windows" title="Permalink to this headline">¶</a></h3>
<p>If you don’t already have Python installed, we recommend using
one of the <a class="reference external" href="http://www.scipy.org/install.html">scipy-stack compatible Python distributions</a> such as WinPython, Python(x,y),
Enthought Canopy, or Continuum Anaconda, which have matplotlib and
many of its dependencies, plus other useful packages, preinstalled.</p>
<p>For <a class="reference external" href="http://www.python.org/download/">standard Python</a> installations
you will also need to install compatible versions of
<a class="reference external" href="https://pypi.python.org/pypi/setuptools/">setuptools</a>,
<a class="reference external" href="https://pypi.python.org/pypi/numpy/">numpy</a>,
<a class="reference external" href="https://pypi.python.org/pypi/python-dateutil/">python-dateutil</a>,
<a class="reference external" href="https://pypi.python.org/pypi/pytz">pytz</a>,
<a class="reference external" href="https://pypi.python.org/pypi/pyparsing/">pyparsing</a>, and
<a class="reference external" href="https://pypi.python.org/pypi/Cycler">cycler</a>
in addition to
<a class="reference external" href="http://pypi.python.org/pypi/matplotlib/">matplotlib</a>.</p>
<p>For Python 3.5 the <a class="reference external" href="http://www.microsoft.com/en-us/download/details.aspx?id=48145">Visual C++ Redistributable for Visual Studio 2015</a>
needs to be installed.
In case Python 2.7 to 3.4 are not installed for all users (not the default),
the Microsoft Visual C++ 2008 (
<a class="reference external" href="http://www.microsoft.com/download/en/details.aspx?id=15336">64 bit</a>
or
<a class="reference external" href="http://www.microsoft.com/download/en/details.aspx?id=29">32 bit</a>
for Python 2.7 to 3.2) or Microsoft Visual C++ 2010 (
<a class="reference external" href="http://www.microsoft.com/en-us/download/details.aspx?id=14632">64 bit</a>
or
<a class="reference external" href="http://www.microsoft.com/en-us/download/details.aspx?id=5555">32 bit</a>
for Python 3.3 and 3.4) redistributable packages need to be installed.</p>
<p>Matplotlib depends on <a class="reference external" href="https://pypi.python.org/pypi/Pillow">Pillow</a>
for reading and saving JPEG, BMP, and TIFF image files.
Matplotlib requires <a class="reference external" href="http://miktex.org/">MiKTeX</a> and
<a class="reference external" href="http://www.ghostscript.com/download/">GhostScript</a> for rendering text
with LaTeX.
<a class="reference external" href="https://www.ffmpeg.org/">FFmpeg</a>, <a class="reference external" href="https://libav.org/">avconv</a>,
<a class="reference external" href="http://www.mplayerhq.hu">mencoder</a>, or
<a class="reference external" href="http://www.imagemagick.org/">ImageMagick</a> are required for the
animation module.</p>
<p>The following backends should work out of the box: agg, tkagg, ps,
pdf and svg.
For other backends you may need to install
<a class="reference external" href="https://pypi.python.org/pypi/pycairo">pycairo</a>,
<a class="reference external" href="https://pypi.python.org/pypi/PyQt4">PyQt4</a>,
<a class="reference external" href="https://pypi.python.org/pypi/PyQt5">PyQt5</a>,
<a class="reference external" href="https://pypi.python.org/pypi/PySide">PySide</a>,
<a class="reference external" href="https://pypi.python.org/pypi/wxPython">wxPython</a>,
<a class="reference external" href="https://pypi.python.org/pypi/PyGTK">PyGTK</a>,
<a class="reference external" href="https://pypi.python.org/pypi/tornado">Tornado</a>,
or GhostScript.</p>
<p>TkAgg is probably the best backend for interactive use from the
standard Python shell or IPython. It is enabled as the default backend
for the official binaries. GTK3 is not supported on Windows.</p>
<p>The Windows installers (<code class="file docutils literal"><span class="pre">*.exe</span></code>) and wheels (<code class="file docutils literal"><span class="pre">*.whl</span></code>) on
the <a class="reference external" href="http://pypi.python.org/pypi/matplotlib/">PyPI download page</a> do
not contain test data or example code. If you want to try the many
demos that come in the matplotlib source distribution, download the
<code class="file docutils literal"><span class="pre">*.tar.gz</span></code> file and look in the <code class="file docutils literal"><span class="pre">examples</span></code> subdirectory.
To run the test suite, copy the <code class="file docutils literal"><span class="pre">libmatplotlibtests</span></code> and
<code class="file docutils literal"><span class="pre">libmpl_toolkitstests</span></code> directories from the source
distribution to <code class="file docutils literal"><span class="pre">sys.prefixLibsite-packagesmatplotlib</span></code> and
<code class="file docutils literal"><span class="pre">sys.prefixLibsite-packagesmpl_toolkits</span></code> respectively, and
install <a class="reference external" href="https://pypi.python.org/pypi/nose">nose</a>, <a class="reference external" href="https://pypi.python.org/pypi/mock">mock</a>, Pillow, MiKTeX, GhostScript,
ffmpeg, avconv, mencoder, ImageMagick, and <a class="reference external" href="http://inkscape.org/">Inkscape</a>.</p>
</div>
</div>
<div class="section" id="installing-from-source">
<span id="install-from-source"></span><h2>Installing from source<a class="headerlink" href="#installing-from-source" title="Permalink to this headline">¶</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. Grab
the latest <em>tar.gz</em> release file from <a class="reference external" href="https://pypi.python.org/pypi/matplotlib/">the PyPI files page</a>, or if you want to
develop matplotlib or just need the latest bugfixed version, grab the
latest git version <a class="reference internal" href="../faq/installing_faq.html#install-from-git"><span>Source install from git</span></a>.</p>
<p>The standard environment variables <code class="xref py py-obj docutils literal"><span class="pre">CC</span></code>, <code class="xref py py-obj docutils literal"><span class="pre">CXX</span></code>, <code class="xref py py-obj docutils literal"><span class="pre">PKG_CONFIG</span></code> are respected.
This means you can set them if your toolchain is prefixed. This may be used for
cross compiling.</p>
<blockquote>
<div>export CC=x86_64-pc-linux-gnu-gcc
export CXX=x86_64-pc-linux-gnu-g++
export PKG_CONFIG=x86_64-pc-linux-gnu-pkg-config</div></blockquote>
<p>Once you have satisfied the requirements detailed below (mainly
python, numpy, libpng and freetype), you can build matplotlib:</p>
<div class="highlight-python"><div class="highlight"><pre>cd matplotlib
python setup.py build
python setup.py install
</pre></div>
</div>
<p>We provide a <a class="reference external" href="https://github.com/matplotlib/matplotlib/raw/master/setup.cfg.template">setup.cfg</a>
file that goes with <code class="file docutils literal"><span class="pre">setup.py</span></code> 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 have installed prerequisites to nonstandard places and need to
inform matplotlib where they are, edit <code class="docutils literal"><span class="pre">setupext.py</span></code> and add the base
dirs to the <code class="docutils literal"><span class="pre">basedir</span></code> dictionary entry for your <code class="docutils literal"><span class="pre">sys.platform</span></code>.
e.g., if the header to some required library is in
<code class="docutils literal"><span class="pre">/some/path/include/someheader.h</span></code>, put <code class="docutils literal"><span class="pre">/some/path</span></code> in the
<code class="docutils literal"><span class="pre">basedir</span></code> list for your platform.</p>
<div class="section" id="build-requirements">
<span id="install-requirements"></span><h3>Build requirements<a class="headerlink" href="#build-requirements" title="Permalink to this headline">¶</a></h3>
<p>These are external packages which you will need to install before
installing matplotlib. If you are building on OSX, see
<a class="reference internal" href="#build-osx"><span>Building on OSX</span></a>. If you are building on Windows, see
<a class="reference internal" href="#build-windows"><span>Building on Windows</span></a>. If you are installing dependencies with a
package manager on Linux, you may need to install the development
packages (look for a “-dev” postfix) in addition to the libraries
themselves.</p>
<div class="section" id="required-dependencies">
<h4>Required Dependencies<a class="headerlink" href="#required-dependencies" title="Permalink to this headline">¶</a></h4>
<dl class="docutils">
<dt><a class="reference internal" href="../glossary/index.html#term-python"><span class="xref std std-term">python</span></a> 2.7, 3.4, or 3.5</dt>
<dd><a class="reference external" href="http://www.python.org/download/">Download python</a>.</dd>
<dt><a class="reference internal" href="../glossary/index.html#term-numpy"><span class="xref std std-term">numpy</span></a> 1.6 (or later)</dt>
<dd>array support for python (<a class="reference external" href="http://numpy.org">download numpy</a>)</dd>
<dt><a class="reference internal" href="../glossary/index.html#term-dateutil"><span class="xref std std-term">dateutil</span></a> 1.1 or later</dt>
<dd>Provides extensions to python datetime handling. If using pip,
easy_install or installing from source, the installer will attempt
to download and install <code class="xref py py-obj docutils literal"><span class="pre">python_dateutil</span></code> from PyPI.</dd>
<dt><code class="xref py py-obj docutils literal"><span class="pre">pyparsing</span></code></dt>
<dd>Required for matplotlib’s mathtext math rendering support. If
using pip, easy_install or installing from source, the installer
will attempt to download and install <code class="xref py py-obj docutils literal"><span class="pre">pyparsing</span></code> from PyPI.</dd>
<dt>libpng 1.2 (or later)</dt>
<dd>library for loading and saving <a class="reference internal" href="../glossary/index.html#term-png"><span class="xref std std-term">PNG</span></a> files (<a class="reference external" href="http://www.libpng.org/pub/png/libpng.html">download</a>). libpng requires
zlib.</dd>
<dt><code class="xref py py-obj docutils literal"><span class="pre">pytz</span></code></dt>
<dd>Used to manipulate time-zone aware datetimes.</dd>
<dt><a class="reference internal" href="../glossary/index.html#term-freetype"><span class="xref std std-term">freetype</span></a> 2.3 or later</dt>
<dd>library for reading true type font files.</dd>
<dt><code class="docutils literal"><span class="pre">cycler</span></code> 0.9 or later</dt>
<dd>Composable cycle class used for constructing style-cycles</dd>
</dl>
</div>
<div class="section" id="optional-gui-framework">
<h4>Optional GUI framework<a class="headerlink" href="#optional-gui-framework" title="Permalink to this headline">¶</a></h4>
<p>These are optional packages which you may want to install to use
matplotlib with a user interface toolkit. See
<a class="reference internal" href="../faq/usage_faq.html#what-is-a-backend"><span>What is a backend?</span></a> for more details on the optional matplotlib
backends and the capabilities they provide.</p>
<dl class="docutils">
<dt><a class="reference internal" href="../glossary/index.html#term-tk"><span class="xref std std-term">tk</span></a> 8.3 or later</dt>
<dd>The TCL/Tk widgets library used by the TkAgg backend</dd>
<dt><a class="reference internal" href="../glossary/index.html#term-pyqt"><span class="xref std std-term">pyqt</span></a> 4.0 or later</dt>
<dd>The Qt4 widgets library python wrappers for the Qt4Agg backend</dd>
<dt><a class="reference internal" href="../glossary/index.html#term-pygtk"><span class="xref std std-term">pygtk</span></a> 2.4 or later</dt>
<dd>The python wrappers for the GTK widgets library for use with the
GTK or GTKAgg backend</dd>
<dt><a class="reference internal" href="../glossary/index.html#term-wxpython"><span class="xref std std-term">wxpython</span></a> 2.8 or later</dt>
<dd>The python wrappers for the wx widgets library for use with the
WX or WXAgg backend</dd>
</dl>
</div>
<div class="section" id="optional-external-programs">
<h4>Optional external programs<a class="headerlink" href="#optional-external-programs" title="Permalink to this headline">¶</a></h4>
<dl class="docutils">
<dt>ffmpeg/avconv or mencoder</dt>
<dd>Required for the animation module to be save out put to movie
formats.</dd>
<dt>ImageMagick</dt>
<dd>Required for the animation module to be able to save to animated gif.</dd>
</dl>
</div>
<div class="section" id="optional-dependencies">
<h4>Optional dependencies<a class="headerlink" href="#optional-dependencies" title="Permalink to this headline">¶</a></h4>
<dl class="docutils">
<dt><a class="reference external" href="http://python-pillow.github.io/">Pillow</a></dt>
<dd>If Pillow is installed, matplotlib can read and write a larger
selection of image file formats.</dd>
<dt>pkg-config</dt>
<dd>A tool used to find required non-python libraries. This is not strictly
required, but can make installation go more smoothly if the libraries and
headers are not in the expected locations.</dd>
</dl>
</div>
<div class="section" id="required-libraries-that-ship-with-matplotlib">
<h4>Required libraries that ship with matplotlib<a class="headerlink" href="#required-libraries-that-ship-with-matplotlib" title="Permalink to this headline">¶</a></h4>
<dl class="docutils">
<dt><a class="reference internal" href="../glossary/index.html#term-agg"><span class="xref std std-term">agg</span></a> 2.4</dt>
<dd>The antigrain C++ rendering engine. matplotlib links against the
agg template source statically, so it will not affect anything on
your system outside of matplotlib.</dd>
<dt><code class="xref py py-obj docutils literal"><span class="pre">qhull</span></code> 2012.1</dt>
<dd>A library for computing Delaunay triangulations.</dd>
<dt><code class="xref py py-obj docutils literal"><span class="pre">ttconv</span></code></dt>
<dd>truetype font utility</dd>
<dt>six 1.9.0</dt>
<dd>Python 2/3 compatibility library. Do not use this in third-party
code.</dd>
</dl>
</div>
</div>
<div class="section" id="building-on-linux">
<span id="build-linux"></span><h3>Building on Linux<a class="headerlink" href="#building-on-linux" title="Permalink to this headline">¶</a></h3>
<p>It is easiest to use your system package manager to install the dependencies.</p>
<p>If you are on Debian/Ubuntu, you can get all the dependencies
required to build matplotlib with:</p>
<div class="highlight-python"><div class="highlight"><pre>sudo apt-get build-dep python-matplotlib
</pre></div>
</div>
<p>If you are on Fedora/RedHat, you can get all the dependencies required
to build matplotlib by first installing <code class="docutils literal"><span class="pre">yum-builddep</span></code> and then
running:</p>
<div class="highlight-python"><div class="highlight"><pre>su -c "yum-builddep python-matplotlib"
</pre></div>
</div>
<p>This does not build matplotlib, but it does get the install the
build dependencies, which will make building from source easier.</p>
</div>
<div class="section" id="building-on-osx">
<span id="build-osx"></span><h3>Building on OSX<a class="headerlink" href="#building-on-osx" title="Permalink to this headline">¶</a></h3>
<p>The build situation on OSX is complicated by the various places one
can get the libpng and freetype requirements (darwinports, fink,
/usr/X11R6) and the different architectures (e.g., x86, ppc, universal) and
the different OSX version (e.g., 10.4 and 10.5). We recommend that you build
the way we do for the OSX release: get the source from the tarball or the
git repository and follow the instruction in <code class="file docutils literal"><span class="pre">README.osx</span></code>.</p>
</div>
<div class="section" id="building-on-windows">
<span id="build-windows"></span><h3>Building on Windows<a class="headerlink" href="#building-on-windows" title="Permalink to this headline">¶</a></h3>
<p>The Python shipped from <a class="reference external" href="http://www.python.org">http://www.python.org</a> is compiled with Visual Studio
2008 for versions before 3.3 and Visual Studio 2010 for 3.3 and later. Python
extensions are recommended to be compiled with the same compiler. The .NET
Framework 4.0 is required for MSBuild (you’ll likely have the requisite
Framework with Visual Studio). In addition to Visual Studio <a class="reference external" href="http://www.cmake.org">CMake</a> is required for building libpng.</p>
<p>Since there is no canonical Windows package manager the build methods for
freetype, zlib, libpng, tcl, & tk source code are documented as a build script
at <a class="reference external" href="https://github.com/jbmohler/matplotlib-winbuild">matplotlib-winbuild</a>.</p>
</div>
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© Copyright 2002 - 2012 John Hunter, Darren Dale, Eric Firing, Michael Droettboom and the matplotlib development team; 2012 - 2014 The matplotlib development team.
Last updated on Oct 29, 2015.
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