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<section id="python">
<span id="id1"></span><h1>Python<a class="headerlink" href="#python" title="Permalink to this heading"></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="admonition-title">注釈</p>
<p>PDAL's Python story always revolves around <a class="reference external" href="https://numpy.org">Numpy</a> support. PDAL's
data is provided to both the filters ands the extension as
Numpy arrays.</p>
</div>
<section id="versions">
<h2>Versions<a class="headerlink" href="#versions" title="Permalink to this heading"></a></h2>
<p>PDAL supports both Python 3.5+. <a class="reference internal" href="project/integration.html#integration"><span class="std std-ref">Continuous Integration</span></a> tests Python
Linux, OSX, and Windows.</p>
</section>
<section id="embed">
<h2>Embed<a class="headerlink" href="#embed" title="Permalink to this heading"></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>
<figure class="align-default" id="id2">
<img alt="_images/python-pdal-pipeline.png" src="_images/python-pdal-pipeline.png" />
<figcaption>
<p><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><a class="headerlink" href="#id2" title="この画像へのパーマリンク"></a></p>
</figcaption>
</figure>
</section>
<section id="extend">
<h2>Extend<a class="headerlink" href="#extend" title="Permalink to this heading"></a></h2>
<p id="index-2">PDAL provides a Python <a class="reference external" href="https://pypi.org/project/pdal/">extension</a>
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="https://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 PDAL
<a class="reference internal" href="pipeline.html#pipeline"><span class="std std-ref">pipeline</span></a>
using Python's <code class="docutils literal notranslate"><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="https://numpy.org">Numpy</a> arrays:</p>
<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">json</span> <span class="o">=</span> <span class="s2">"""</span>
<span class="s2">[</span>
<span class="s2"> "1.2-with-color.las",</span>
<span class="s2"> {</span>
<span class="s2"> "type": "filters.sort",</span>
<span class="s2"> "dimension": "X"</span>
<span class="s2"> }</span>
<span class="s2">]</span>
<span class="s2">"""</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">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>
<section id="installation">
<h3>Installation<a class="headerlink" href="#installation" title="Permalink to this heading"></a></h3>
<p id="index-3">The PDAL Python extension requires a working
<a class="reference internal" href="download.html#download"><span class="std std-ref">PDAL installation</span></a>. Unless you choose the Conda installation
method, make sure that you a current, working version of PDAL before
installing the extension.</p>
<div class="admonition note">
<p class="admonition-title">注釈</p>
<p>Previous to PDAL 2.1, Python support was spread across the embedded
stages (<a class="reference internal" href="stages/readers.numpy.html#readers-numpy"><span class="std std-ref">readers.numpy</span></a> and <a class="reference internal" href="stages/filters.python.html#filters-python"><span class="std std-ref">filters.python</span></a>) which were installed
by PDAL itself and the PDAL extension that was installed from PyPI.
As of PDAL 2.1 and PDAL/python 2.3, both the embedded stages and the
extension are installed from PyPI.</p>
</div>
<section id="installation-using-pip">
<h4>Installation Using pip<a class="headerlink" href="#installation-using-pip" title="Permalink to this heading"></a></h4>
<p id="index-4">As administrator, you can install PDAL using pip:</p>
<div class="highlight-default notranslate"><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="admonition-title">注釈</p>
<p>To install pip please read
<a class="reference external" href="https://pip.pypa.io/en/stable/installation/">here</a></p>
</div>
</section>
<section id="installation-from-source">
<h4>Installation from Source<a class="headerlink" href="#installation-from-source" title="Permalink to this heading"></a></h4>
<p id="index-5">PDAL Python support is hosted in a separate repository than PDAL itself at
<a class="reference external" href="https://github.com/PDAL/python">GitHub</a>. If you have a working PDAL
installation and a working Python installation, you can install the extension
using the following procedure on Unix. The procedure on Windows is similar</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>$ git clone https://github.com/PDAL/python pdalextension
$ cd pdalextension
$ pip install .
</pre></div>
</div>
</section>
<section id="install-using-conda">
<h4>Install using Conda<a class="headerlink" href="#install-using-conda" title="Permalink to this heading"></a></h4>
<p id="index-6">The PDAL Python support can also be installed using the <a class="reference external" href="https://conda.io/projects/conda/en/latest/">Conda</a>
package manager. An advantage of using Conda to install the extension is
that Conda will install PDAL. We recommend installing PDAL and the PDAL
Python extension in an environment other than the base environment. To
install in an existing environment, use the following</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">conda</span> <span class="n">install</span> <span class="o">-</span><span class="n">n</span> <span class="o"><</span><span class="n">environment</span> <span class="n">name</span><span class="o">></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">python</span><span class="o">-</span><span class="n">pdal</span>
</pre></div>
</div>
<p>Use the following command to install PDAL and the PDAL Python extension
into a new environment and activate that environment</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">conda</span> <span class="n">create</span> <span class="o">-</span><span class="n">n</span> <span class="o"><</span><span class="n">environment</span> <span class="n">name</span><span class="o">></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">python</span><span class="o">-</span><span class="n">pdal</span>
<span class="n">conda</span> <span class="n">activate</span> <span class="o"><</span><span class="n">environment</span> <span class="n">name</span><span class="o">></span>
</pre></div>
</div>
<div class="admonition note">
<p class="admonition-title">注釈</p>
<p>The official <code class="docutils literal notranslate"><span class="pre">pdal</span></code> and <code class="docutils literal notranslate"><span class="pre">python-pdal</span></code> packages reside in the
conda-forge channel, which can be added via <code class="docutils literal notranslate"><span class="pre">conda</span> <span class="pre">config</span></code> or manually
specified with the <code class="docutils literal notranslate"><span class="pre">-c</span></code> option, as shown in the examples above.</p>
</div>
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