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  <div class="section" id="python">
<span id="id1"></span><h1>Python<a class="headerlink" href="#python" title="Permalink to this headline"></a></h1>
<p id="index-0">PDAL provides Python support in two significant ways. First it <a class="reference external" href="https://docs.python.org/3/extending/embedding.html">embeds</a> Python
to allow you to write Python programs that interact with data using
<a class="reference internal" href="stages/filters.python.html#filters-python"><span class="std std-ref">filters.python</span></a> filter. Second, it <a class="reference external" href="https://docs.python.org/3/extending/extending.html">extends</a> Python by providing an
extension that Python programmers can use to leverage PDAL capabilities in
their own applications.</p>
<div class="admonition note">
<p class="first admonition-title">Note</p>
<p class="last">PDAL’s Python story always revolves around <a class="reference external" href="http://www.numpy.org/">Numpy</a> support. PDAL’s
data is provided to both the filters ands the extension as
Numpy arrays.</p>
</div>
<div class="section" id="versions">
<h2>Versions<a class="headerlink" href="#versions" title="Permalink to this headline"></a></h2>
<p>PDAL supports both Python 2.7 and Python 3.4+. <a class="reference internal" href="development/integration.html#integration"><span class="std std-ref">Continuous Integration</span></a> tests Python
2.7 on both Linux and Windows. Python 3 is used by a number of developers
for adhoc development and testing.</p>
</div>
<div class="section" id="embed">
<h2>Embed<a class="headerlink" href="#embed" title="Permalink to this headline"></a></h2>
<p id="index-1">PDAL allows users to embed Python functions inline with other <a class="reference internal" href="pipeline.html#pipeline"><span class="std std-ref">Pipeline</span></a>
processing operations. The purpose of this capability is to allow users to
write small programs that implement interesting actions without requiring a
full C++ development activity of building a PDAL stage to implement it. A
Python filter is an opportunity to interactively and iteratively prototype a
data operation without strong considerations of performance or generality.  If
something works well enough, maybe one takes on the effort to formalize it, but
that isn’t necessary. PDAL’s embed of Python allows you to be as grimy as you
need to get the job done.</p>
<div class="figure" id="id2">
<img alt="_images/python-pdal-pipeline.png" src="_images/python-pdal-pipeline.png" />
<p class="caption"><span class="caption-text">Embedding a Python function to take Z values read from a
<a class="reference internal" href="stages/readers.las.html#readers-las"><span class="std std-ref">readers.las</span></a> and then output them to a <a class="reference internal" href="stages/writers.bpf.html#writers-bpf"><span class="std std-ref">writers.bpf</span></a>.</span></p>
</div>
</div>
<div class="section" id="extend">
<h2>Extend<a class="headerlink" href="#extend" title="Permalink to this headline"></a></h2>
<p id="index-2">PDAL provides a Python extension that gives users access to executing
<a class="reference internal" href="pipeline.html#pipeline"><span class="std std-ref">Pipeline</span></a> instantiations and capturing the results as <a class="reference external" href="http://www.numpy.org/">Numpy</a> arrays.
This mode of operation is useful if you are looking to have PDAL simply act as
your data format and processing handler.</p>
<p>Python extension users are expected to construct their own JSON <a class="reference internal" href="pipeline.html#pipeline"><span class="std std-ref">Pipeline</span></a>
using Python’s <code class="docutils literal"><span class="pre">json</span></code> library, or whatever other libraries they wish to
manipulate JSON. They then feed it into the extension and get back the
results as <a class="reference external" href="http://www.numpy.org/">Numpy</a> arrays:</p>
<div class="highlight-python"><div class="highlight"><pre><span></span><span class="n">json</span> <span class="o">=</span> <span class="s2">&quot;&quot;&quot;</span>
<span class="s2">{</span>
<span class="s2">  &quot;pipeline&quot;: [</span>
<span class="s2">    &quot;1.2-with-color.las&quot;,</span>
<span class="s2">    {</span>
<span class="s2">        &quot;type&quot;: &quot;filters.sort&quot;,</span>
<span class="s2">        &quot;dimension&quot;: &quot;X&quot;</span>
<span class="s2">    }</span>
<span class="s2">  ]</span>
<span class="s2">}&quot;&quot;&quot;</span>

<span class="kn">import</span> <span class="nn">pdal</span>
<span class="n">pipeline</span> <span class="o">=</span> <span class="n">pdal</span><span class="o">.</span><span class="n">Pipeline</span><span class="p">(</span><span class="n">json</span><span class="p">)</span>
<span class="n">pipeline</span><span class="o">.</span><span class="n">validate</span><span class="p">()</span> <span class="c1"># check if our JSON and options were good</span>
<span class="n">pipeline</span><span class="o">.</span><span class="n">loglevel</span> <span class="o">=</span> <span class="mi">8</span> <span class="c1">#really noisy</span>
<span class="n">count</span> <span class="o">=</span> <span class="n">pipeline</span><span class="o">.</span><span class="n">execute</span><span class="p">()</span>
<span class="n">arrays</span> <span class="o">=</span> <span class="n">pipeline</span><span class="o">.</span><span class="n">arrays</span>
<span class="n">metadata</span> <span class="o">=</span> <span class="n">pipeline</span><span class="o">.</span><span class="n">metadata</span>
<span class="n">log</span> <span class="o">=</span> <span class="n">pipeline</span><span class="o">.</span><span class="n">log</span>
</pre></div>
</div>
<div class="section" id="installation">
<h3>Installation<a class="headerlink" href="#installation" title="Permalink to this headline"></a></h3>
<p>PDAL Python bindings require a working PDAL install (<a class="reference internal" href="development/compilation/index.html#building"><span class="std std-ref">PDAL</span></a>)
and then installation of the Python extension. The extension lives on <a class="reference external" href="https://pypi.python.org/pypi/PDAL">PyPI</a>
at <a class="reference external" href="https://pypi.python.org/pypi/PDAL">https://pypi.python.org/pypi/PDAL</a> and you should use that version as your
canonical Python extension install.</p>
<div class="section" id="install-from-local">
<h4>Install from local<a class="headerlink" href="#install-from-local" title="Permalink to this headline"></a></h4>
<p>In the source code of PDAL there is a <code class="docutils literal"><span class="pre">python</span></code> folder, you have to enter
there and run</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="n">python</span> <span class="n">setup</span><span class="o">.</span><span class="n">py</span> <span class="n">build</span>
<span class="c1"># this should be run as administrator/super user</span>
<span class="n">python</span> <span class="n">setup</span><span class="o">.</span><span class="n">py</span> <span class="n">install</span>
</pre></div>
</div>
</div>
<div class="section" id="install-from-repository">
<h4>Install from repository<a class="headerlink" href="#install-from-repository" title="Permalink to this headline"></a></h4>
<p id="index-3">The second method to install the PDAL Python extension is to use <a class="reference external" href="https://pip.pypa.io/en/stable/">pip</a>
or <a class="reference external" href="https://pypi.python.org/pypi/setuptools">easy_install</a>, you have to run the command as administrator.</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="n">pip</span> <span class="n">install</span> <span class="n">PDAL</span>
</pre></div>
</div>
<div class="admonition note">
<p class="first admonition-title">Note</p>
<p class="last">To install pip please read
<a class="reference external" href="https://pip.pypa.io/en/stable/installing/">here</a></p>
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