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<ul>
<li><a class="reference internal" href="#">Installing</a><ul>
<li><a class="reference internal" href="#installing-an-official-release">Installing an official release</a><ul>
<li><a class="reference internal" href="#windows">Windows</a></li>
<li><a class="reference internal" href="#macos">macOS</a></li>
<li><a class="reference internal" href="#linux">Linux</a></li>
<li><a class="reference internal" href="#test-data">Test Data</a></li>
</ul>
</li>
<li><a class="reference internal" href="#third-party-distributions-of-matplotlib">Third-party distributions of Matplotlib</a><ul>
<li><a class="reference internal" href="#scientific-python-distributions">Scientific Python Distributions</a></li>
<li><a class="reference internal" href="#linux-using-your-package-manager">Linux : using your package manager</a></li>
</ul>
</li>
<li><a class="reference internal" href="#installing-from-source">Installing from source</a><ul>
<li><a class="reference internal" href="#dependencies">Dependencies</a></li>
<li><a class="reference internal" href="#building-on-linux">Building on Linux</a></li>
<li><a class="reference internal" href="#building-on-macos">Building on macOS</a></li>
<li><a class="reference internal" href="#building-on-windows">Building on Windows</a><ul>
<li><a class="reference internal" href="#wheel-builds-using-conda-packages">Wheel builds using conda packages</a></li>
<li><a class="reference internal" href="#conda-packages">Conda packages</a></li>
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<div class="section" id="installing">
<h1><a class="toc-backref" href="#id2">Installing</a><a class="headerlink" href="#installing" title="Permalink to this headline">¶</a></h1>
<div class="admonition note">
<p class="first admonition-title">Note</p>
<p class="last">If you wish to contribute to the project, it’s recommended you
<a class="reference internal" href="#install-from-source"><span class="std std-ref">install the latest development version</span></a>.</p>
</div>
<div class="contents topic" id="contents">
<p class="topic-title first">Contents</p>
<ul class="simple">
<li><a class="reference internal" href="#installing" id="id2">Installing</a><ul>
<li><a class="reference internal" href="#installing-an-official-release" id="id3">Installing an official release</a><ul>
<li><a class="reference internal" href="#windows" id="id4">Windows</a></li>
<li><a class="reference internal" href="#macos" id="id5">macOS</a></li>
<li><a class="reference internal" href="#linux" id="id6">Linux</a></li>
<li><a class="reference internal" href="#test-data" id="id7">Test Data</a></li>
</ul>
</li>
<li><a class="reference internal" href="#third-party-distributions-of-matplotlib" id="id8">Third-party distributions of Matplotlib</a><ul>
<li><a class="reference internal" href="#scientific-python-distributions" id="id9">Scientific Python Distributions</a></li>
<li><a class="reference internal" href="#linux-using-your-package-manager" id="id10">Linux : using your package manager</a></li>
</ul>
</li>
<li><a class="reference internal" href="#installing-from-source" id="id11">Installing from source</a><ul>
<li><a class="reference internal" href="#dependencies" id="id12">Dependencies</a></li>
<li><a class="reference internal" href="#building-on-linux" id="id13">Building on Linux</a></li>
<li><a class="reference internal" href="#building-on-macos" id="id14">Building on macOS</a></li>
<li><a class="reference internal" href="#building-on-windows" id="id15">Building on Windows</a><ul>
<li><a class="reference internal" href="#wheel-builds-using-conda-packages" id="id16">Wheel builds using conda packages</a></li>
<li><a class="reference internal" href="#conda-packages" id="id17">Conda packages</a></li>
</ul>
</li>
</ul>
</li>
</ul>
</li>
</ul>
</div>
<div class="section" id="installing-an-official-release">
<h2><a class="toc-backref" href="#id3">Installing an official release</a><a class="headerlink" href="#installing-an-official-release" title="Permalink to this headline">¶</a></h2>
<p>Matplotlib and most of its dependencies are all available as wheel
packages for macOS, Windows and Linux distributions:</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">U</span> <span class="n">pip</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">U</span> <span class="n">matplotlib</span>
</pre></div>
</div>
<div class="admonition note">
<p class="first admonition-title">Note</p>
<p>The following backends work out of the box: Agg, ps, pdf, svg and TkAgg.</p>
<p class="last">For support of other GUI frameworks, LaTeX rendering, saving
animations and a larger selection of file formats, you may need to
install <a class="reference internal" href="#install-requirements"><span class="std std-ref">additional dependencies</span></a>.</p>
</div>
<p>Although not required, we suggest also installing <code class="docutils literal"><span class="pre">IPython</span></code> for
interactive use. To easily install a complete Scientific Python
stack, see <a class="reference internal" href="#install-scipy-dists"><span class="std std-ref">Scientific Python Distributions</span></a> below.</p>
<div class="section" id="windows">
<span id="installing-windows"></span><h3><a class="toc-backref" href="#id4">Windows</a><a class="headerlink" href="#windows" title="Permalink to this headline">¶</a></h3>
<p>In case Python 2.7 or 3.4 are not installed for all users,
the Microsoft Visual C++ 2008
(<a class="reference external" href="https://www.microsoft.com/en-us/download/details.aspx?id=15336">64 bit</a>
or
<a class="reference external" href="https://www.microsoft.com/en-us/download/details.aspx?id=29">32 bit</a>
for Python 2.7) or Microsoft Visual C++ 2010
(<a class="reference external" href="https://www.microsoft.com/en-us/download/details.aspx?id=14632">64 bit</a>
or
<a class="reference external" href="https://www.microsoft.com/en-us/download/details.aspx?id=5555">32 bit</a>
for Python 3.4) redistributable packages need to be installed.</p>
</div>
<div class="section" id="macos">
<h3><a class="toc-backref" href="#id5">macOS</a><a class="headerlink" href="#macos" title="Permalink to this headline">¶</a></h3>
<p>If you are using Python 2.7 on a Mac you may need to do:</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="n">xcode</span><span class="o">-</span><span class="n">select</span> <span class="o">--</span><span class="n">install</span>
</pre></div>
</div>
<p>so that <em>subprocess32</em>, a dependency, may be compiled.</p>
<p>To use the native OSX backend you will need <a class="reference internal" href="../faq/osx_framework.html#osxframework-faq"><span class="std std-ref">a framework build</span></a> build of Python.</p>
</div>
<div class="section" id="linux">
<h3><a class="toc-backref" href="#id6">Linux</a><a class="headerlink" href="#linux" title="Permalink to this headline">¶</a></h3>
<p>On extremely old versions of Linux and Python 2.7 you may need to
install the master version of <em>subprocess32</em> (<a class="reference external" href="https://github.com/google/python-subprocess32/issues/12#issuecomment-304724113">see comments</a>).</p>
</div>
<div class="section" id="test-data">
<h3><a class="toc-backref" href="#id7">Test Data</a><a class="headerlink" href="#test-data" title="Permalink to this headline">¶</a></h3>
<p>The wheels (<code class="file docutils literal"><span class="pre">*.whl</span></code>) on the <a class="reference external" href="https://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:</p>
<blockquote>
<div><ul class="simple">
<li>extract the <code class="file docutils literal"><span class="pre">lib\matplotlib\tests</span></code> or
<code class="file docutils literal"><span class="pre">lib\mpl_toolkits\tests</span></code> directories from the source distribution;</li>
<li>install test dependencies: <a class="reference external" href="https://pypi.python.org/pypi/pytest">pytest</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="https://inkscape.org/">Inkscape</a>;</li>
<li>run <code class="docutils literal"><span class="pre">py.test</span> <span class="pre">path\to\tests\directory</span></code>.</li>
</ul>
</div></blockquote>
</div>
</div>
<div class="section" id="third-party-distributions-of-matplotlib">
<h2><a class="toc-backref" href="#id8">Third-party distributions of Matplotlib</a><a class="headerlink" href="#third-party-distributions-of-matplotlib" title="Permalink to this headline">¶</a></h2>
<div class="section" id="scientific-python-distributions">
<span id="install-scipy-dists"></span><h3><a class="toc-backref" href="#id9">Scientific Python Distributions</a><a class="headerlink" href="#scientific-python-distributions" title="Permalink to this headline">¶</a></h3>
<p>Both <a class="reference external" href="https://www.continuum.io/downloads/">Anaconda</a> and <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, macOS and common
Linux platforms. <a class="reference external" href="https://winpython.github.io/">WinPython</a> is an
option for windows users. All of these distributions include
Matplotlib and <em>lots</em> of other useful tools.</p>
</div>
<div class="section" id="linux-using-your-package-manager">
<h3><a class="toc-backref" href="#id10">Linux : using your package manager</a><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">python3-matplotlib</span></code></li>
<li>Fedora: <code class="docutils literal"><span class="pre">sudo</span> <span class="pre">dnf</span> <span class="pre">install</span> <span class="pre">python3-matplotlib</span></code></li>
<li>Red Hat: <code class="docutils literal"><span class="pre">sudo</span> <span class="pre">yum</span> <span class="pre">install</span> <span class="pre">python3-matplotlib</span></code></li>
<li>Arch: <code class="docutils literal"><span class="pre">sudo</span> <span class="pre">pacman</span> <span class="pre">-S</span> <span class="pre">python-matplotlib</span></code></li>
</ul>
</div>
</div>
<div class="section" id="installing-from-source">
<span id="install-from-source"></span><h2><a class="toc-backref" href="#id11">Installing from source</a><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 class="std std-ref">Install from source</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>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="n">export</span> <span class="n">CC</span><span class="o">=</span><span class="n">x86_64</span><span class="o">-</span><span class="n">pc</span><span class="o">-</span><span class="n">linux</span><span class="o">-</span><span class="n">gnu</span><span class="o">-</span><span class="n">gcc</span>
<span class="n">export</span> <span class="n">CXX</span><span class="o">=</span><span class="n">x86_64</span><span class="o">-</span><span class="n">pc</span><span class="o">-</span><span class="n">linux</span><span class="o">-</span><span class="n">gnu</span><span class="o">-</span><span class="n">g</span><span class="o">++</span>
<span class="n">export</span> <span class="n">PKG_CONFIG</span><span class="o">=</span><span class="n">x86_64</span><span class="o">-</span><span class="n">pc</span><span class="o">-</span><span class="n">linux</span><span class="o">-</span><span class="n">gnu</span><span class="o">-</span><span class="n">pkg</span><span class="o">-</span><span class="n">config</span>
</pre></div>
</div>
<p>Once you have satisfied the requirements detailed below (mainly
Python, NumPy, libpng and FreeType), you can build Matplotlib.</p>
<div class="highlight-default"><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">mpip</span> <span class="n">install</span> <span class="o">.</span>
</pre></div>
</div>
<p>We provide a <a class="reference external" href="https://raw.githubusercontent.com/matplotlib/matplotlib/master/setup.cfg.template">setup.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 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 of 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="dependencies">
<span id="install-requirements"></span><h3><a class="toc-backref" href="#id12">Dependencies</a><a class="headerlink" href="#dependencies" title="Permalink to this headline">¶</a></h3>
<p>Matplotlib requires a large number of dependencies:</p>
<blockquote>
<div><ul class="simple">
<li><a class="reference external" href="https://www.python.org/downloads/">Python</a> (>= 2.7 or >= 3.4)</li>
<li><a class="reference external" href="http://www.numpy.org">NumPy</a> (>= 1.7.1)</li>
<li><a class="reference external" href="https://setuptools.readthedocs.io/en/latest/">setuptools</a></li>
<li><a class="reference external" href="https://pypi.python.org/pypi/python-dateutil">dateutil</a> (>= 2.0)</li>
<li><a class="reference external" href="https://pyparsing.wikispaces.com/">pyparsing</a></li>
<li><a class="reference external" href="http://www.libpng.org">libpng</a> (>= 1.2)</li>
<li><a class="reference external" href="http://pytz.sourceforge.net/">pytz</a></li>
<li>FreeType (>= 2.3)</li>
<li><a class="reference external" href="http://matplotlib.org/cycler/">cycler</a> (>= 0.10.0)</li>
<li><a class="reference external" href="https://pypi.python.org/pypi/six">six</a></li>
<li><a class="reference external" href="https://pypi.python.org/pypi/backports.functools_lru_cache">backports.functools_lru_cache</a>
(for Python 2.7 only)</li>
<li><a class="reference external" href="https://pypi.python.org/pypi/subprocess32/">subprocess32</a> (for Python
2.7 only, on Linux and macOS only)</li>
</ul>
</div></blockquote>
<p>Optionally, you can also install a number of packages to enable better user
interface toolkits. See <a class="reference internal" href="../tutorials/introductory/usage.html#what-is-a-backend"><span class="std std-ref">What is a backend?</span></a> for more details on the
optional Matplotlib backends and the capabilities they provide.</p>
<blockquote>
<div><ul class="simple">
<li><a class="reference internal" href="../glossary/index.html#term-tk"><span class="xref std std-term">tk</span></a> (>= 8.3, != 8.6.0 or 8.6.1): for the TkAgg backend;</li>
<li><a class="reference external" href="https://pypi.python.org/pypi/PyQt4">PyQt4</a> (>= 4.4) or
<a class="reference external" href="https://pypi.python.org/pypi/PySide">PySide</a>: for the Qt4Agg backend;</li>
<li><a class="reference external" href="https://pypi.python.org/pypi/PyQt5">PyQt5</a>: for the Qt5Agg backend;</li>
<li><a class="reference internal" href="../glossary/index.html#term-pygtk"><span class="xref std std-term">pygtk</span></a> (>= 2.4): for the GTK and the GTKAgg backend;</li>
<li><a class="reference internal" href="../glossary/index.html#term-wxpython"><span class="xref std std-term">wxpython</span></a> (>= 2.8 or later): for the WX or WXAgg backend;</li>
<li><a class="reference external" href="https://pypi.python.org/pypi/pycairo">pycairo</a>: for GTK3Cairo;</li>
<li><a class="reference external" href="https://pypi.python.org/pypi/tornado">Tornado</a>: for the WebAgg backend.</li>
</ul>
</div></blockquote>
<p>For better support of animation output format and image file formats, LaTeX,
etc., you can install the following:</p>
<blockquote>
<div><ul class="simple">
<li><a class="reference external" href="https://www.ffmpeg.org/">ffmpeg</a>/<a class="reference external" href="https://libav.org/avconv.html">avconv</a>: for saving movies;</li>
<li><a class="reference external" href="https://www.imagemagick.org/script/index.php">ImageMagick</a>: for saving
animated gifs;</li>
<li><a class="reference external" href="https://python-pillow.org/">Pillow</a> (>=2.0): for a larger selection of
image file formats: JPEG, BMP, and TIFF image files;</li>
<li><a class="reference external" href="https://miktex.org/">LaTeX</a> and <a class="reference external" href="https://ghostscript.com/download/">GhostScript</a> (for rendering text with LaTeX).</li>
</ul>
</div></blockquote>
<div class="admonition note">
<p class="first admonition-title">Note</p>
<p class="last">Matplotlib depends on a large number of non-Python libraries.
<a class="reference external" href="https://www.freedesktop.org/wiki/Software/pkg-config/">pkg-config</a>
can be used to find required non-Python libraries and thus make the install
go more smoothly if the libraries and headers are not in the expected
locations.</p>
</div>
<div class="admonition note">
<p class="first admonition-title">Note</p>
<p>The following libraries are shipped with Matplotlib:</p>
<blockquote class="last">
<div><ul class="simple">
<li><code class="xref py py-obj docutils literal"><span class="pre">Agg</span></code>: the Anti-Grain Geometry C++ rendering engine;</li>
<li><code class="xref py py-obj docutils literal"><span class="pre">qhull</span></code>: to compute Delaunay triangulation;</li>
<li><code class="xref py py-obj docutils literal"><span class="pre">ttconv</span></code>: a true type font utility.</li>
</ul>
</div></blockquote>
</div>
</div>
<div class="section" id="building-on-linux">
<span id="build-linux"></span><h3><a class="toc-backref" href="#id13">Building on Linux</a><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-default"><div class="highlight"><pre><span></span><span class="n">sudo</span> <span class="n">apt</span><span class="o">-</span><span class="n">get</span> <span class="n">build</span><span class="o">-</span><span class="n">dep</span> <span class="n">python</span><span class="o">-</span><span class="n">matplotlib</span>
</pre></div>
</div>
<p>If you are on Fedora, you can get all the dependencies required to build
Matplotlib with:</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="n">sudo</span> <span class="n">dnf</span> <span class="n">builddep</span> <span class="n">python</span><span class="o">-</span><span class="n">matplotlib</span>
</pre></div>
</div>
<p>If you are on 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-default"><div class="highlight"><pre><span></span><span class="n">su</span> <span class="o">-</span><span class="n">c</span> <span class="s2">"yum-builddep python-matplotlib"</span>
</pre></div>
</div>
<p>These commands do not build Matplotlib, but instead get and install the
build dependencies, which will make building from source easier.</p>
</div>
<div class="section" id="building-on-macos">
<span id="build-osx"></span><h3><a class="toc-backref" href="#id14">Building on macOS</a><a class="headerlink" href="#building-on-macos" title="Permalink to this headline">¶</a></h3>
<p>The build situation on macOS is complicated by the various places one
can get the libpng and FreeType requirements (MacPorts, Fink,
/usr/X11R6), the different architectures (e.g., x86, ppc, universal), and
the different macOS versions (e.g., 10.4 and 10.5). We recommend that you build
the way we do for the macOS release: get the source from the tarball or the
git repository and install the required dependencies through a third-party
package manager. Two widely used package managers are Homebrew, and MacPorts.
The following example illustrates how to install libpng and FreeType using
<code class="docutils literal"><span class="pre">brew</span></code>:</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="n">brew</span> <span class="n">install</span> <span class="n">libpng</span> <span class="n">freetype</span> <span class="n">pkg</span><span class="o">-</span><span class="n">config</span>
</pre></div>
</div>
<p>If you are using MacPorts, execute the following instead:</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="n">port</span> <span class="n">install</span> <span class="n">libpng</span> <span class="n">freetype</span> <span class="n">pkgconfig</span>
</pre></div>
</div>
<p>After installing the above requirements, install Matplotlib from source by
executing:</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>
</pre></div>
</div>
<p>Note that your environment is somewhat important. Some conda users have
found that, to run the tests, their PYTHONPATH must include
/path/to/anaconda/…/site-packages and their DYLD_FALLBACK_LIBRARY_PATH
must include /path/to/anaconda/lib.</p>
</div>
<div class="section" id="building-on-windows">
<span id="build-windows"></span><h3><a class="toc-backref" href="#id15">Building on Windows</a><a class="headerlink" href="#building-on-windows" title="Permalink to this headline">¶</a></h3>
<p>The Python shipped from <a class="reference external" href="https://www.python.org">https://www.python.org</a> is compiled with Visual Studio
2008 for versions before 3.3, Visual Studio 2010 for 3.3 and 3.4, and
Visual Studio 2015 for 3.5 and 3.6. Python extensions are recommended to be compiled
with the same compiler.</p>
<p>Since there is no canonical Windows package manager, the methods for building
FreeType, zlib, and libpng from source code are documented as a build script
at <a class="reference external" href="https://github.com/jbmohler/matplotlib-winbuild">matplotlib-winbuild</a>.</p>
<p>There are a few possibilities to build Matplotlib on Windows:</p>
<ul class="simple">
<li>Wheels via <a class="reference external" href="https://github.com/jbmohler/matplotlib-winbuild">matplotlib-winbuild</a></li>
<li>Wheels by using conda packages</li>
<li>Conda packages</li>
</ul>
<div class="section" id="wheel-builds-using-conda-packages">
<h4><a class="toc-backref" href="#id16">Wheel builds using conda packages</a><a class="headerlink" href="#wheel-builds-using-conda-packages" title="Permalink to this headline">¶</a></h4>
<p>This is a wheel build, but we use conda packages to get all the requirements. The binary
requirements (png, FreeType,…) are statically linked and therefore not needed during the wheel
install.</p>
<p>The commands below assume that you can compile a native Python lib for the Python version of your
choice. See <a class="reference external" href="https://blog.ionelmc.ro/2014/12/21/compiling-python-extensions-on-windows/">this howto</a>
for how to install and setup such environments. If in doubt: use Python >= 3.5 as it mostly works
without fiddling with environment variables:</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="c1"># create a new environment with the required packages</span>
<span class="n">conda</span> <span class="n">create</span> <span class="o">-</span><span class="n">n</span> <span class="s2">"matplotlib_build"</span> <span class="n">python</span><span class="o">=</span><span class="mf">3.5</span> <span class="n">numpy</span> <span class="n">python</span><span class="o">-</span><span class="n">dateutil</span> <span class="n">pyparsing</span> <span class="n">pytz</span> <span class="n">tornado</span> <span class="s2">"cycler>=0.10"</span> <span class="n">tk</span> <span class="n">libpng</span> <span class="n">zlib</span> <span class="n">freetype</span>
<span class="n">activate</span> <span class="n">matplotlib_build</span>
<span class="c1"># if you want a qt backend, you also have to install pyqt (be aware that pyqt doesn't mix well if</span>
<span class="c1"># you have created the environment with conda-forge already activated...)</span>
<span class="n">conda</span> <span class="n">install</span> <span class="n">pyqt</span>
<span class="c1"># this package is only available in the conda-forge channel</span>
<span class="n">conda</span> <span class="n">install</span> <span class="o">-</span><span class="n">c</span> <span class="n">conda</span><span class="o">-</span><span class="n">forge</span> <span class="n">msinttypes</span>
<span class="c1"># for Python 2.7</span>
<span class="n">conda</span> <span class="n">install</span> <span class="o">-</span><span class="n">c</span> <span class="n">conda</span><span class="o">-</span><span class="n">forge</span> <span class="n">backports</span><span class="o">.</span><span class="n">functools_lru_cache</span>
<span class="c1"># copy the libs which have "wrong" names</span>
<span class="nb">set</span> <span class="n">LIBRARY_LIB</span><span class="o">=%</span><span class="n">CONDA_DEFAULT_ENV</span><span class="o">%</span>\<span class="n">Library</span>\<span class="n">lib</span>
<span class="n">mkdir</span> <span class="n">lib</span> <span class="o">||</span> <span class="n">cmd</span> <span class="o">/</span><span class="n">c</span> <span class="s2">"exit /b 0"</span>
<span class="n">copy</span> <span class="o">%</span><span class="n">LIBRARY_LIB</span><span class="o">%</span>\<span class="n">zlibstatic</span><span class="o">.</span><span class="n">lib</span> <span class="n">lib</span>\<span class="n">z</span><span class="o">.</span><span class="n">lib</span>
<span class="n">copy</span> <span class="o">%</span><span class="n">LIBRARY_LIB</span><span class="o">%</span>\<span class="n">libpng_static</span><span class="o">.</span><span class="n">lib</span> <span class="n">lib</span>\<span class="n">png</span><span class="o">.</span><span class="n">lib</span>
<span class="c1"># Make the header files and the rest of the static libs available during the build</span>
<span class="c1"># CONDA_DEFAULT_ENV is a env variable which is set to the currently active environment path</span>
<span class="nb">set</span> <span class="n">MPLBASEDIRLIST</span><span class="o">=%</span><span class="n">CONDA_DEFAULT_ENV</span><span class="o">%</span>\<span class="n">Library</span>\<span class="p">;</span><span class="o">.</span>
<span class="c1"># build the wheel</span>
<span class="n">python</span> <span class="n">setup</span><span class="o">.</span><span class="n">py</span> <span class="n">bdist_wheel</span>
</pre></div>
</div>
<p>The <code class="xref py py-obj docutils literal"><span class="pre">build_alllocal.cmd</span></code> script in the root folder automates these steps if
you have already created and activated the conda environment.</p>
</div>
<div class="section" id="conda-packages">
<h4><a class="toc-backref" href="#id17">Conda packages</a><a class="headerlink" href="#conda-packages" title="Permalink to this headline">¶</a></h4>
<p>This needs a <a class="reference external" href="https://blog.ionelmc.ro/2014/12/21/compiling-python-extensions-on-windows/">working installed C compiler</a>
for the version of Python you are compiling the package for but you don’t need
to setup the environment variables:</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="c1"># only the first time...</span>
<span class="n">conda</span> <span class="n">install</span> <span class="n">conda</span><span class="o">-</span><span class="n">build</span>
<span class="c1"># the Python version you want a package for...</span>
<span class="nb">set</span> <span class="n">CONDA_PY</span><span class="o">=</span><span class="mf">3.5</span>
<span class="c1"># builds the package, using a clean build environment</span>
<span class="n">conda</span> <span class="n">build</span> <span class="n">ci</span>\<span class="n">conda_recipe</span>
<span class="c1"># install the new package</span>
<span class="n">conda</span> <span class="n">install</span> <span class="o">--</span><span class="n">use</span><span class="o">-</span><span class="n">local</span> <span class="n">matplotlib</span>
</pre></div>
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