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<span class="target" id="advanced-installation"></span><section id="installing-the-development-version-of-scikit-learn">
<h1>Installing the development version of scikit-learn<a class="headerlink" href="#installing-the-development-version-of-scikit-learn" title="Link to this heading">#</a></h1>
<p>This section introduces how to install the <strong>main branch</strong> of scikit-learn.
This can be done by either installing a nightly build or building from source.</p>
<section id="installing-nightly-builds">
<span id="install-nightly-builds"></span><h2>Installing nightly builds<a class="headerlink" href="#installing-nightly-builds" title="Link to this heading">#</a></h2>
<p>The continuous integration servers of the scikit-learn project build, test
and upload wheel packages for the most recent Python version on a nightly
basis.</p>
<p>Installing a nightly build is the quickest way to:</p>
<ul class="simple">
<li><p>try a new feature that will be shipped in the next release (that is, a
feature from a pull-request that was recently merged to the main branch);</p></li>
<li><p>check whether a bug you encountered has been fixed since the last release.</p></li>
</ul>
<p>You can install the nightly build of scikit-learn using the <code class="docutils literal notranslate"><span class="pre">scientific-python-nightly-wheels</span></code>
index from the PyPI registry of <code class="docutils literal notranslate"><span class="pre">anaconda.org</span></code>:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><style type="text/css">
span.prompt1:before {
content: "$ ";
}
</style><span class="prompt1">pip<span class="w"> </span>install<span class="w"> </span>--pre<span class="w"> </span>--extra-index<span class="w"> </span>https://pypi.anaconda.org/scientific-python-nightly-wheels/simple<span class="w"> </span>scikit-learn</span>
</pre></div></div><p>Note that first uninstalling scikit-learn might be required to be able to
install nightly builds of scikit-learn.</p>
</section>
<section id="building-from-source">
<span id="install-bleeding-edge"></span><h2>Building from source<a class="headerlink" href="#building-from-source" title="Link to this heading">#</a></h2>
<p>Building from source is required to work on a contribution (bug fix, new
feature, code or documentation improvement).</p>
<ol class="arabic" id="git-repo">
<li><p>Use <a class="reference external" href="https://git-scm.com/">Git</a> to check out the latest source from the
<a class="reference external" href="https://github.com/scikit-learn/scikit-learn">scikit-learn repository</a> on
Github.:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span class="prompt1">git<span class="w"> </span>clone<span class="w"> </span>[email protected]:scikit-learn/scikit-learn.git<span class="w"> </span><span class="c1"># add --depth 1 if your connection is slow</span></span>
<span class="prompt1"><span class="nb">cd</span><span class="w"> </span>scikit-learn</span>
</pre></div></div><p>If you plan on submitting a pull-request, you should clone from your fork
instead.</p>
</li>
<li><p>Install a recent version of Python (3.10 or later) for
instance using <a class="reference external" href="https://conda-forge.org/download/">conda-forge</a>. Conda-forge provides a conda-based distribution of
Python and the most popular scientific libraries.</p>
<p>If you installed Python with conda, we recommend to create a dedicated
<a class="reference external" href="https://docs.conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html">conda environment</a> with all the build dependencies of scikit-learn
(namely <a class="reference external" href="https://numpy.org">NumPy</a>, <a class="reference external" href="https://www.scipy.org">SciPy</a>, <a class="reference external" href="https://cython.org">Cython</a>, <a class="reference external" href="https://mesonbuild.com/meson-python">meson-python</a> and <a class="reference external" href="https://ninja-build.org/">Ninja</a>):</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span class="prompt1">conda<span class="w"> </span>create<span class="w"> </span>-n<span class="w"> </span>sklearn-env<span class="w"> </span>-c<span class="w"> </span>conda-forge<span class="w"> </span>python<span class="w"> </span>numpy<span class="w"> </span>scipy<span class="w"> </span>cython<span class="w"> </span>meson-python<span class="w"> </span>ninja</span>
</pre></div></div><p>It is not always necessary but it is safer to open a new prompt before
activating the newly created conda environment.</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span class="prompt1">conda<span class="w"> </span>activate<span class="w"> </span>sklearn-env</span>
</pre></div></div></li>
<li><p><strong>Alternative to conda:</strong> You can use alternative installations of Python
provided they are recent enough (3.10 or higher).
Here is an example of how to create a build environment for a Linux system’s
Python. Build dependencies are installed with <code class="docutils literal notranslate"><span class="pre">pip</span></code> in a dedicated <a class="reference external" href="https://docs.python.org/3/tutorial/venv.html">virtualenv</a>
to avoid disrupting other Python programs installed on the system:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span class="prompt1">python3<span class="w"> </span>-m<span class="w"> </span>venv<span class="w"> </span>sklearn-env</span>
<span class="prompt1"><span class="nb">source</span><span class="w"> </span>sklearn-env/bin/activate</span>
<span class="prompt1">pip<span class="w"> </span>install<span class="w"> </span>wheel<span class="w"> </span>numpy<span class="w"> </span>scipy<span class="w"> </span>cython<span class="w"> </span>meson-python<span class="w"> </span>ninja</span>
</pre></div></div></li>
<li><p>Install a compiler with <a class="reference external" href="https://en.wikipedia.org/wiki/OpenMP">OpenMP</a> support for your platform. See instructions
for <a class="reference internal" href="#compiler-windows"><span class="std std-ref">Windows</span></a>, <a class="reference internal" href="#compiler-macos"><span class="std std-ref">macOS</span></a>, <a class="reference internal" href="#compiler-linux"><span class="std std-ref">Linux</span></a>
and <a class="reference internal" href="#compiler-freebsd"><span class="std std-ref">FreeBSD</span></a>.</p>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>If OpenMP is not supported by the compiler, the build will be done with
OpenMP functionalities disabled. This is not recommended since it will force
some estimators to run in sequential mode instead of leveraging thread-based
parallelism. Setting the <code class="docutils literal notranslate"><span class="pre">SKLEARN_FAIL_NO_OPENMP</span></code> environment variable
(before cythonization) will force the build to fail if OpenMP is not
supported.</p>
</div>
</li>
<li><p>Build the project with pip:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span class="prompt1">pip<span class="w"> </span>install<span class="w"> </span>--editable<span class="w"> </span>.<span class="w"> </span><span class="se">\</span>
<span class="w"> </span>--verbose<span class="w"> </span>--no-build-isolation<span class="w"> </span><span class="se">\</span>
<span class="w"> </span>--config-settings<span class="w"> </span>editable-verbose<span class="o">=</span><span class="nb">true</span></span>
</pre></div></div></li>
<li><p>Check that the installed scikit-learn has a version number ending with
<code class="docutils literal notranslate"><span class="pre">.dev0</span></code>:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span class="prompt1">python<span class="w"> </span>-c<span class="w"> </span><span class="s2">"import sklearn; sklearn.show_versions()"</span></span>
</pre></div></div></li>
<li><p>Please refer to the <a class="reference internal" href="index.html#developers-guide"><span class="std std-ref">Developer’s Guide</span></a> and <a class="reference internal" href="tips.html#pytest-tips"><span class="std std-ref">Useful pytest aliases and flags</span></a> to run
the tests on the module of your choice.</p></li>
</ol>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p><code class="docutils literal notranslate"><span class="pre">--config-settings</span> <span class="pre">editable-verbose=true</span></code> is optional but recommended
to avoid surprises when you import <code class="docutils literal notranslate"><span class="pre">sklearn</span></code>. <code class="docutils literal notranslate"><span class="pre">meson-python</span></code> implements
editable installs by rebuilding <code class="docutils literal notranslate"><span class="pre">sklearn</span></code> when executing <code class="docutils literal notranslate"><span class="pre">import</span> <span class="pre">sklearn</span></code>.
With the recommended setting you will see a message when this happens,
rather than potentially waiting without feedback and wondering
what is taking so long. Bonus: this means you only have to run the <code class="docutils literal notranslate"><span class="pre">pip</span>
<span class="pre">install</span></code> command once, <code class="docutils literal notranslate"><span class="pre">sklearn</span></code> will automatically be rebuilt when
importing <code class="docutils literal notranslate"><span class="pre">sklearn</span></code>.</p>
<p>Note that <code class="docutils literal notranslate"><span class="pre">--config-settings</span></code> is only supported in <code class="docutils literal notranslate"><span class="pre">pip</span></code> version 23.1 or
later. To upgrade <code class="docutils literal notranslate"><span class="pre">pip</span></code> to a compatible version, run <code class="docutils literal notranslate"><span class="pre">pip</span> <span class="pre">install</span> <span class="pre">-U</span> <span class="pre">pip</span></code>.</p>
</div>
<section id="building-a-specific-version-from-a-tag">
<h3>Building a specific version from a tag<a class="headerlink" href="#building-a-specific-version-from-a-tag" title="Link to this heading">#</a></h3>
<p>If you want to build a stable version, you can <code class="docutils literal notranslate"><span class="pre">git</span> <span class="pre">checkout</span> <span class="pre"><VERSION></span></code>
to get the code for that particular version, or download an zip archive of
the version from github.</p>
</section>
</section>
<section id="platform-specific-instructions">
<span id="id1"></span><h2>Platform-specific instructions<a class="headerlink" href="#platform-specific-instructions" title="Link to this heading">#</a></h2>
<p>Here are instructions to install a working C/C++ compiler with OpenMP support
to build scikit-learn Cython extensions for each supported platform.</p>
<section id="windows">
<span id="compiler-windows"></span><h3>Windows<a class="headerlink" href="#windows" title="Link to this heading">#</a></h3>
<p>First, download the <a class="reference external" href="https://aka.ms/vs/17/release/vs_buildtools.exe">Build Tools for Visual Studio installer</a>.</p>
<p>Run the downloaded <code class="docutils literal notranslate"><span class="pre">vs_buildtools.exe</span></code> file, during the installation you will
need to make sure you select “Desktop development with C++”, similarly to this
screenshot:</p>
<img alt="../_images/visual-studio-build-tools-selection.png" src="../_images/visual-studio-build-tools-selection.png" />
<p>Build scikit-learn by running the following command in your <code class="docutils literal notranslate"><span class="pre">sklearn-env</span></code> conda environment
or virtualenv:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span class="prompt1">pip<span class="w"> </span>install<span class="w"> </span>--editable<span class="w"> </span>.<span class="w"> </span>--verbose<span class="w"> </span>--no-build-isolation<span class="w"> </span>--config-settings<span class="w"> </span>editable-verbose<span class="o">=</span><span class="nb">true</span></span>
</pre></div></div></section>
<section id="macos">
<span id="compiler-macos"></span><h3>macOS<a class="headerlink" href="#macos" title="Link to this heading">#</a></h3>
<p>The default C compiler on macOS, Apple clang (confusingly aliased as
<code class="docutils literal notranslate"><span class="pre">/usr/bin/gcc</span></code>), does not directly support OpenMP. We present two alternatives
to enable OpenMP support:</p>
<ul class="simple">
<li><p>either install <code class="docutils literal notranslate"><span class="pre">conda-forge::compilers</span></code> with conda;</p></li>
<li><p>or install <code class="docutils literal notranslate"><span class="pre">libomp</span></code> with Homebrew to extend the default Apple clang compiler.</p></li>
</ul>
<p>For Apple Silicon M1 hardware, only the conda-forge method below is known to
work at the time of writing (January 2021). You can install the <code class="docutils literal notranslate"><span class="pre">macos/arm64</span></code>
distribution of conda using the <a class="reference external" href="https://conda-forge.org/download/">conda-forge installer</a></p>
<section id="macos-compilers-from-conda-forge">
<h4>macOS compilers from conda-forge<a class="headerlink" href="#macos-compilers-from-conda-forge" title="Link to this heading">#</a></h4>
<p>If you use the conda package manager (version >= 4.7), you can install the
<code class="docutils literal notranslate"><span class="pre">compilers</span></code> meta-package from the conda-forge channel, which provides
OpenMP-enabled C/C++ compilers based on the llvm toolchain.</p>
<p>First install the macOS command line tools:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span class="prompt1">xcode-select<span class="w"> </span>--install</span>
</pre></div></div><p>It is recommended to use a dedicated <a class="reference external" href="https://docs.conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html">conda environment</a> to build
scikit-learn from source:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span class="prompt1">conda<span class="w"> </span>create<span class="w"> </span>-n<span class="w"> </span>sklearn-dev<span class="w"> </span>-c<span class="w"> </span>conda-forge<span class="w"> </span>python<span class="w"> </span>numpy<span class="w"> </span>scipy<span class="w"> </span>cython<span class="w"> </span><span class="se">\</span>
<span class="w"> </span>joblib<span class="w"> </span>threadpoolctl<span class="w"> </span>pytest<span class="w"> </span>compilers<span class="w"> </span>llvm-openmp<span class="w"> </span>meson-python<span class="w"> </span>ninja</span>
</pre></div></div><p>It is not always necessary but it is safer to open a new prompt before
activating the newly created conda environment.</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span class="prompt1">conda<span class="w"> </span>activate<span class="w"> </span>sklearn-dev</span>
<span class="prompt1">make<span class="w"> </span>clean</span>
<span class="prompt1">pip<span class="w"> </span>install<span class="w"> </span>--editable<span class="w"> </span>.<span class="w"> </span><span class="se">\</span>
<span class="w"> </span>--verbose<span class="w"> </span>--no-build-isolation<span class="w"> </span><span class="se">\</span>
<span class="w"> </span>--config-settings<span class="w"> </span>editable-verbose<span class="o">=</span><span class="nb">true</span></span>
</pre></div></div><div class="admonition note">
<p class="admonition-title">Note</p>
<p>If you get any conflicting dependency error message, try commenting out
any custom conda configuration in the <code class="docutils literal notranslate"><span class="pre">$HOME/.condarc</span></code> file. In
particular the <code class="docutils literal notranslate"><span class="pre">channel_priority:</span> <span class="pre">strict</span></code> directive is known to cause
problems for this setup.</p>
</div>
<p>You can check that the custom compilers are properly installed from conda
forge using the following command:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span class="prompt1">conda<span class="w"> </span>list</span>
</pre></div></div><p>which should include <code class="docutils literal notranslate"><span class="pre">compilers</span></code> and <code class="docutils literal notranslate"><span class="pre">llvm-openmp</span></code>.</p>
<p>The compilers meta-package will automatically set custom environment
variables:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span class="prompt1"><span class="nb">echo</span><span class="w"> </span><span class="nv">$CC</span></span>
<span class="prompt1"><span class="nb">echo</span><span class="w"> </span><span class="nv">$CXX</span></span>
<span class="prompt1"><span class="nb">echo</span><span class="w"> </span><span class="nv">$CFLAGS</span></span>
<span class="prompt1"><span class="nb">echo</span><span class="w"> </span><span class="nv">$CXXFLAGS</span></span>
<span class="prompt1"><span class="nb">echo</span><span class="w"> </span><span class="nv">$LDFLAGS</span></span>
</pre></div></div><p>They point to files and folders from your <code class="docutils literal notranslate"><span class="pre">sklearn-dev</span></code> conda environment
(in particular in the bin/, include/ and lib/ subfolders). For instance
<code class="docutils literal notranslate"><span class="pre">-L/path/to/conda/envs/sklearn-dev/lib</span></code> should appear in <code class="docutils literal notranslate"><span class="pre">LDFLAGS</span></code>.</p>
<p>In the log, you should see the compiled extension being built with the clang
and clang++ compilers installed by conda with the <code class="docutils literal notranslate"><span class="pre">-fopenmp</span></code> command line
flag.</p>
</section>
<section id="macos-compilers-from-homebrew">
<h4>macOS compilers from Homebrew<a class="headerlink" href="#macos-compilers-from-homebrew" title="Link to this heading">#</a></h4>
<p>Another solution is to enable OpenMP support for the clang compiler shipped
by default on macOS.</p>
<p>First install the macOS command line tools:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span class="prompt1">xcode-select<span class="w"> </span>--install</span>
</pre></div></div><p>Install the <a class="reference external" href="https://brew.sh">Homebrew</a> package manager for macOS.</p>
<p>Install the LLVM OpenMP library:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span class="prompt1">brew<span class="w"> </span>install<span class="w"> </span>libomp</span>
</pre></div></div><p>Set the following environment variables:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span class="prompt1"><span class="nb">export</span><span class="w"> </span><span class="nv">CC</span><span class="o">=</span>/usr/bin/clang</span>
<span class="prompt1"><span class="nb">export</span><span class="w"> </span><span class="nv">CXX</span><span class="o">=</span>/usr/bin/clang++</span>
<span class="prompt1"><span class="nb">export</span><span class="w"> </span><span class="nv">CPPFLAGS</span><span class="o">=</span><span class="s2">"</span><span class="nv">$CPPFLAGS</span><span class="s2"> -Xpreprocessor -fopenmp"</span></span>
<span class="prompt1"><span class="nb">export</span><span class="w"> </span><span class="nv">CFLAGS</span><span class="o">=</span><span class="s2">"</span><span class="nv">$CFLAGS</span><span class="s2"> -I/usr/local/opt/libomp/include"</span></span>
<span class="prompt1"><span class="nb">export</span><span class="w"> </span><span class="nv">CXXFLAGS</span><span class="o">=</span><span class="s2">"</span><span class="nv">$CXXFLAGS</span><span class="s2"> -I/usr/local/opt/libomp/include"</span></span>
<span class="prompt1"><span class="nb">export</span><span class="w"> </span><span class="nv">LDFLAGS</span><span class="o">=</span><span class="s2">"</span><span class="nv">$LDFLAGS</span><span class="s2"> -Wl,-rpath,/usr/local/opt/libomp/lib -L/usr/local/opt/libomp/lib -lomp"</span></span>
</pre></div></div><p>Finally, build scikit-learn in verbose mode (to check for the presence of the
<code class="docutils literal notranslate"><span class="pre">-fopenmp</span></code> flag in the compiler commands):</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span class="prompt1">make<span class="w"> </span>clean</span>
<span class="prompt1">pip<span class="w"> </span>install<span class="w"> </span>--editable<span class="w"> </span>.<span class="w"> </span><span class="se">\</span>
<span class="w"> </span>--verbose<span class="w"> </span>--no-build-isolation<span class="w"> </span><span class="se">\</span>
<span class="w"> </span>--config-settings<span class="w"> </span>editable-verbose<span class="o">=</span><span class="nb">true</span></span>
</pre></div></div></section>
</section>
<section id="linux">
<span id="compiler-linux"></span><h3>Linux<a class="headerlink" href="#linux" title="Link to this heading">#</a></h3>
<section id="linux-compilers-from-the-system">
<h4>Linux compilers from the system<a class="headerlink" href="#linux-compilers-from-the-system" title="Link to this heading">#</a></h4>
<p>Installing scikit-learn from source without using conda requires you to have
installed the scikit-learn Python development headers and a working C/C++
compiler with OpenMP support (typically the GCC toolchain).</p>
<p>Install build dependencies for Debian-based operating systems, e.g.
Ubuntu:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span class="prompt1">sudo<span class="w"> </span>apt-get<span class="w"> </span>install<span class="w"> </span>build-essential<span class="w"> </span>python3-dev<span class="w"> </span>python3-pip</span>
</pre></div></div><p>then proceed as usual:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span class="prompt1">pip3<span class="w"> </span>install<span class="w"> </span>cython</span>
<span class="prompt1">pip3<span class="w"> </span>install<span class="w"> </span>--editable<span class="w"> </span>.<span class="w"> </span><span class="se">\</span>
<span class="w"> </span>--verbose<span class="w"> </span>--no-build-isolation<span class="w"> </span><span class="se">\</span>
<span class="w"> </span>--config-settings<span class="w"> </span>editable-verbose<span class="o">=</span><span class="nb">true</span></span>
</pre></div></div><p>Cython and the pre-compiled wheels for the runtime dependencies (numpy, scipy
and joblib) should automatically be installed in
<code class="docutils literal notranslate"><span class="pre">$HOME/.local/lib/pythonX.Y/site-packages</span></code>. Alternatively you can run the
above commands from a <a class="reference external" href="https://docs.python.org/3/tutorial/venv.html">virtualenv</a> or a <a class="reference external" href="https://docs.conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html">conda environment</a> to get full
isolation from the Python packages installed via the system packager. When
using an isolated environment, <code class="docutils literal notranslate"><span class="pre">pip3</span></code> should be replaced by <code class="docutils literal notranslate"><span class="pre">pip</span></code> in the
above commands.</p>
<p>When precompiled wheels of the runtime dependencies are not available for your
architecture (e.g. ARM), you can install the system versions:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span class="prompt1">sudo<span class="w"> </span>apt-get<span class="w"> </span>install<span class="w"> </span>cython3<span class="w"> </span>python3-numpy<span class="w"> </span>python3-scipy</span>
</pre></div></div><p>On Red Hat and clones (e.g. CentOS), install the dependencies using:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span class="prompt1">sudo<span class="w"> </span>yum<span class="w"> </span>-y<span class="w"> </span>install<span class="w"> </span>gcc<span class="w"> </span>gcc-c++<span class="w"> </span>python3-devel<span class="w"> </span>numpy<span class="w"> </span>scipy</span>
</pre></div></div></section>
<section id="linux-compilers-from-conda-forge">
<h4>Linux compilers from conda-forge<a class="headerlink" href="#linux-compilers-from-conda-forge" title="Link to this heading">#</a></h4>
<p>Alternatively, install a recent version of the GNU C Compiler toolchain (GCC)
in the user folder using conda:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span class="prompt1">conda<span class="w"> </span>create<span class="w"> </span>-n<span class="w"> </span>sklearn-dev<span class="w"> </span>-c<span class="w"> </span>conda-forge<span class="w"> </span>python<span class="w"> </span>numpy<span class="w"> </span>scipy<span class="w"> </span>cython<span class="w"> </span><span class="se">\</span>
<span class="w"> </span>joblib<span class="w"> </span>threadpoolctl<span class="w"> </span>pytest<span class="w"> </span>compilers<span class="w"> </span>meson-python<span class="w"> </span>ninja</span>
</pre></div></div><p>It is not always necessary but it is safer to open a new prompt before
activating the newly created conda environment.</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span class="prompt1">conda<span class="w"> </span>activate<span class="w"> </span>sklearn-dev</span>
<span class="prompt1">pip<span class="w"> </span>install<span class="w"> </span>--editable<span class="w"> </span>.<span class="w"> </span><span class="se">\</span>
<span class="w"> </span>--verbose<span class="w"> </span>--no-build-isolation<span class="w"> </span><span class="se">\</span>
<span class="w"> </span>--config-settings<span class="w"> </span>editable-verbose<span class="o">=</span><span class="nb">true</span></span>
</pre></div></div></section>
</section>
<section id="freebsd">
<span id="compiler-freebsd"></span><h3>FreeBSD<a class="headerlink" href="#freebsd" title="Link to this heading">#</a></h3>
<p>The clang compiler included in FreeBSD 12.0 and 11.2 base systems does not
include OpenMP support. You need to install the <code class="docutils literal notranslate"><span class="pre">openmp</span></code> library from packages
(or ports):</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span class="prompt1">sudo<span class="w"> </span>pkg<span class="w"> </span>install<span class="w"> </span>openmp</span>
</pre></div></div><p>This will install header files in <code class="docutils literal notranslate"><span class="pre">/usr/local/include</span></code> and libs in
<code class="docutils literal notranslate"><span class="pre">/usr/local/lib</span></code>. Since these directories are not searched by default, you
can set the environment variables to these locations:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span class="prompt1"><span class="nb">export</span><span class="w"> </span><span class="nv">CFLAGS</span><span class="o">=</span><span class="s2">"</span><span class="nv">$CFLAGS</span><span class="s2"> -I/usr/local/include"</span></span>
<span class="prompt1"><span class="nb">export</span><span class="w"> </span><span class="nv">CXXFLAGS</span><span class="o">=</span><span class="s2">"</span><span class="nv">$CXXFLAGS</span><span class="s2"> -I/usr/local/include"</span></span>
<span class="prompt1"><span class="nb">export</span><span class="w"> </span><span class="nv">LDFLAGS</span><span class="o">=</span><span class="s2">"</span><span class="nv">$LDFLAGS</span><span class="s2"> -Wl,-rpath,/usr/local/lib -L/usr/local/lib -lomp"</span></span>
</pre></div></div><p>Finally, build the package using the standard command:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span class="prompt1">pip<span class="w"> </span>install<span class="w"> </span>--editable<span class="w"> </span>.<span class="w"> </span><span class="se">\</span>
<span class="w"> </span>--verbose<span class="w"> </span>--no-build-isolation<span class="w"> </span><span class="se">\</span>
<span class="w"> </span>--config-settings<span class="w"> </span>editable-verbose<span class="o">=</span><span class="nb">true</span></span>
</pre></div></div><p>For the upcoming FreeBSD 12.1 and 11.3 versions, OpenMP will be included in
the base system and these steps will not be necessary.</p>
</section>
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