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  <section id="linux-installation">
<h1>Linux Installation<a class="headerlink" href="#linux-installation" title="Link to this heading">¶</a></h1>
<p>If using your system’s built-in Python SpacePy we recommend installing
dependencies <a class="reference internal" href="#linux-dep-apt"><span class="std std-ref">via the package manager</span></a>. Our
recommended (but not required) standalone Python distribution is
<a class="reference external" href="https://docs.anaconda.com/anaconda/">Anaconda</a> running 64-bit
Python 3. Anaconda includes much of the scientific Python stack.</p>
<p>SpacePy ships 64-bit binaries for most modern Linux
distributions. They are built with the <a class="reference external" href="https://github.com/pypa/manylinux/">manylinux2014_x86_64</a> Docker images and should work
on any x86_64 Linux using glibc2.17 or later, e.g. Ubuntu 16.04 and
CentOS 7.</p>
<p>Building from source on Linux requires both a C and a Fortran
compiler; a recent GCC is recommended (the C compiler is likely
included with your distribution). On Debian and Ubuntu:</p>
<div class="highlight-default notranslate"><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">install</span> <span class="n">gfortran</span>
</pre></div>
</div>
<p>Once this is set up, <code class="docutils literal notranslate"><span class="pre">pip</span> <span class="pre">install</span> <span class="pre">spacepy</span></code> should Just Work. If
you’re installing as a single user (not in a virtual environment) then
add the <code class="docutils literal notranslate"><span class="pre">--user</span></code> flag.</p>
<p>You will also need the <a class="reference internal" href="#linux-cdf"><span class="std std-ref">NASA CDF library</span></a> to use
<a class="reference internal" href="autosummary/spacepy.pycdf.html#module-spacepy.pycdf" title="spacepy.pycdf"><code class="xref py py-mod docutils literal notranslate"><span class="pre">pycdf</span></code></a>.</p>
<p>If you prefer to install the dependencies some way other than pip, see
<a class="reference internal" href="#linux-dep-conda"><span class="std std-ref">Dependencies via conda</span></a> and <a class="reference internal" href="#linux-dep-apt"><span class="std std-ref">Dependencies via system packages</span></a>.</p>
<nav class="contents local" id="contents">
<ul class="simple">
<li><p><a class="reference internal" href="#dependencies-via-conda" id="id1">Dependencies via conda</a></p></li>
<li><p><a class="reference internal" href="#dependencies-via-system-packages" id="id2">Dependencies via system packages</a></p></li>
<li><p><a class="reference internal" href="#cdf" id="id3">CDF</a></p></li>
<li><p><a class="reference internal" href="#raspberry-pi" id="id4">Raspberry Pi</a></p></li>
</ul>
</nav>
<section id="dependencies-via-conda">
<span id="linux-dep-conda"></span><h2><a class="toc-backref" href="#id1" role="doc-backlink">Dependencies via conda</a><a class="headerlink" href="#dependencies-via-conda" title="Link to this heading">¶</a></h2>
<p>Installation via <code class="docutils literal notranslate"><span class="pre">pip</span></code> will automatically install most Python
dependencies (but not the <a class="reference internal" href="#linux-cdf"><span class="std std-ref">NASA CDF library</span></a>). They
can also be installed from conda:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">conda</span> <span class="n">install</span> <span class="n">numpy</span> <span class="n">python</span><span class="o">-</span><span class="n">dateutil</span> <span class="n">scipy</span> <span class="n">matplotlib</span> <span class="n">h5py</span>
</pre></div>
</div>
</section>
<section id="dependencies-via-system-packages">
<span id="linux-dep-apt"></span><h2><a class="toc-backref" href="#id2" role="doc-backlink">Dependencies via system packages</a><a class="headerlink" href="#dependencies-via-system-packages" title="Link to this heading">¶</a></h2>
<p>SpacePy usually works with the system Python on Linux. To install dependencies via the package manager on Debian or Ubuntu:</p>
<div class="highlight-default notranslate"><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">install</span> <span class="n">python3</span><span class="o">-</span><span class="n">dev</span> <span class="n">python3</span><span class="o">-</span><span class="n">h5py</span> <span class="n">python3</span><span class="o">-</span><span class="n">matplotlib</span> <span class="n">python3</span><span class="o">-</span><span class="n">numpy</span> <span class="n">python3</span><span class="o">-</span><span class="n">dateutil</span> <span class="n">python3</span><span class="o">-</span><span class="n">scipy</span>
</pre></div>
</div>
<p>For other distributions, check <a class="reference internal" href="dependencies.html"><span class="doc">SpacePy Dependencies</span></a> and install by hand
or via your package manager.</p>
<p>To get the dependencies for building documentation:</p>
<div class="highlight-default notranslate"><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">install</span> <span class="n">python3</span><span class="o">-</span><span class="n">sphinx</span> <span class="n">python3</span><span class="o">-</span><span class="n">numpydoc</span>
</pre></div>
</div>
</section>
<section id="cdf">
<span id="linux-cdf"></span><h2><a class="toc-backref" href="#id3" role="doc-backlink">CDF</a><a class="headerlink" href="#cdf" title="Link to this heading">¶</a></h2>
<p>The NASA CDF library is included if installing from a binary wheel. If
you build SpacePy from source or wish to use a different version of the
CDF library, you will need to install it.</p>
<p>It is recommended to install the ncurses library; on Ubuntu and Debian:</p>
<div class="highlight-default notranslate"><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">install</span> <span class="n">ncurses</span><span class="o">-</span><span class="n">dev</span>
</pre></div>
</div>
<p>Download the latest <a class="reference external" href="http://cdf.gsfc.nasa.gov/">CDF library</a>. Choose
the file ending in <code class="docutils literal notranslate"><span class="pre">-dist-all.tar.gz</span></code> from the <code class="docutils literal notranslate"><span class="pre">linux</span></code>
directory. Untar and cd into the resulting directory. Then build:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">make</span> <span class="n">OS</span><span class="o">=</span><span class="n">linux</span> <span class="n">ENV</span><span class="o">=</span><span class="n">gnu</span> <span class="n">CURSES</span><span class="o">=</span><span class="n">yes</span> <span class="n">FORTRAN</span><span class="o">=</span><span class="n">no</span> <span class="n">UCOPTIONS</span><span class="o">=-</span><span class="n">O2</span> <span class="n">SHARED</span><span class="o">=</span><span class="n">yes</span> <span class="nb">all</span>
</pre></div>
</div>
<p>Use <code class="docutils literal notranslate"><span class="pre">CURSES=no</span></code> if the curses library is not installed. (The
distribution-specific directions above will install curses.)</p>
<p>Install:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">sudo</span> <span class="n">make</span> <span class="n">install</span>
</pre></div>
</div>
<p>This will install the library into the default location <code class="docutils literal notranslate"><span class="pre">/usr/local/cdf</span></code>, where
SpacePy can find it. If you choose to install elsewhere, see the CDF documentation,
particularly the notes on the <code class="docutils literal notranslate"><span class="pre">CDF_BASE</span></code> and <code class="docutils literal notranslate"><span class="pre">CDF_LIB</span></code> environment variables.
SpacePy uses these variables to find the library.</p>
</section>
<section id="raspberry-pi">
<h2><a class="toc-backref" href="#id4" role="doc-backlink">Raspberry Pi</a><a class="headerlink" href="#raspberry-pi" title="Link to this heading">¶</a></h2>
<p>SpacePy works on Raspberry Pi, using Raspberry Pi OS in 32-bit or
64-bit flavors. A few tips:</p>
<blockquote>
<div><ul>
<li><p>Binary wheels are provided for 64-bit only.</p></li>
<li><p>It is highly recommended to install all dependencies (numpy,
etc.) via the system package manager <code class="docutils literal notranslate"><span class="pre">apt-get</span></code> rather than
pip, as prebuilt wheels are not generally available and compiling
dependencies on the Pi can take a very long time:</p>
<div class="highlight-default notranslate"><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">install</span> <span class="n">gfortran</span> <span class="n">python3</span><span class="o">-</span><span class="n">numpy</span> <span class="n">python3</span><span class="o">-</span><span class="n">dateutil</span> <span class="n">python3</span><span class="o">-</span><span class="n">scipy</span> <span class="n">python3</span><span class="o">-</span><span class="n">h5py</span> <span class="n">python3</span><span class="o">-</span><span class="n">matplotlib</span>
</pre></div>
</div>
</li>
</ul>
</div></blockquote>
</section>
</section>


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  <div>
    <h3><a href="index.html">Table of Contents</a></h3>
    <ul>
<li><a class="reference internal" href="#">Linux Installation</a><ul>
<li><a class="reference internal" href="#dependencies-via-conda">Dependencies via conda</a></li>
<li><a class="reference internal" href="#dependencies-via-system-packages">Dependencies via system packages</a></li>
<li><a class="reference internal" href="#cdf">CDF</a></li>
<li><a class="reference internal" href="#raspberry-pi">Raspberry Pi</a></li>
</ul>
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