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FrancescAlted committed Dec 23, 2022
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<section id="faq">
<h1>FAQ<a class="headerlink" href="#faq" title="Permalink to this heading"></a></h1>
<section id="general-questions">
Expand Down Expand Up @@ -280,7 +366,7 @@ <h3>Can PyTables be used in concurrent access scenarios?<a class="headerlink" hr
<li><p>Using <code class="xref py py-class docutils literal notranslate"><span class="pre">multiprocessing.Pipe</span></code> from the Python standard library.</p></li>
<li><p>Using a memory mapped file that is shared between two processes. The NumPy
array associated with the file is passed as the <em>out</em> argument to the
<code class="xref py py-meth docutils literal notranslate"><span class="pre">tables.Array.read()</span></code> method.</p></li>
<a class="reference internal" href="usersguide/libref/homogenous_storage.html#tables.Array.read" title="tables.Array.read"><code class="xref py py-meth docutils literal notranslate"><span class="pre">tables.Array.read()</span></code></a> method.</p></li>
<li><p>Using a Unix domain socket. Note that this example uses the ‘abstract
namespace’ and will only work under Linux.</p></li>
<li><p>Using an IPv4 socket.</p></li>
Expand All @@ -293,23 +379,23 @@ <h3>What kind of containers does PyTables implement?<a class="headerlink" href="
<p>PyTables does support a series of data containers that address specific needs
of the user. Below is a brief description of them:</p>
<dl class="simple">
<dt>:<code class="xref py py-class docutils literal notranslate"><span class="pre">Table</span></code>:</dt><dd><p>Lets you deal with heterogeneous datasets. Allows compression. Enlargeable.
<dt>:<a class="reference internal" href="usersguide/libref/structured_storage.html#tables.Table" title="tables.Table"><code class="xref py py-class docutils literal notranslate"><span class="pre">Table</span></code></a>:</dt><dd><p>Lets you deal with heterogeneous datasets. Allows compression. Enlargeable.
Supports nested types. Good performance for read/writing data.</p>
</dd>
<dt>:<code class="xref py py-class docutils literal notranslate"><span class="pre">Array</span></code>:</dt><dd><p>Provides quick and dirty array handling. Not compression allowed.
<dt>:<a class="reference internal" href="usersguide/libref/homogenous_storage.html#tables.Array" title="tables.Array"><code class="xref py py-class docutils literal notranslate"><span class="pre">Array</span></code></a>:</dt><dd><p>Provides quick and dirty array handling. Not compression allowed.
Not enlargeable. Can be used only with relatively small datasets (i.e.
those that fit in memory). It provides the fastest I/O speed.</p>
</dd>
<dt>:<code class="xref py py-class docutils literal notranslate"><span class="pre">CArray</span></code>:</dt><dd><p>Provides compressed array support. Not enlargeable. Good speed when
<dt>:<a class="reference internal" href="usersguide/libref/homogenous_storage.html#tables.CArray" title="tables.CArray"><code class="xref py py-class docutils literal notranslate"><span class="pre">CArray</span></code></a>:</dt><dd><p>Provides compressed array support. Not enlargeable. Good speed when
reading/writing.</p>
</dd>
<dt>:<code class="xref py py-class docutils literal notranslate"><span class="pre">EArray</span></code>:</dt><dd><p>Most general array support. Compressible and enlargeable. It is pretty
<dt>:<a class="reference internal" href="usersguide/libref/homogenous_storage.html#tables.EArray" title="tables.EArray"><code class="xref py py-class docutils literal notranslate"><span class="pre">EArray</span></code></a>:</dt><dd><p>Most general array support. Compressible and enlargeable. It is pretty
fast at extending, and very good at reading.</p>
</dd>
<dt>:<code class="xref py py-class docutils literal notranslate"><span class="pre">VLArray</span></code>:</dt><dd><p>Supports collections of homogeneous data with a variable number of entries.
<dt>:<a class="reference internal" href="usersguide/libref/homogenous_storage.html#tables.VLArray" title="tables.VLArray"><code class="xref py py-class docutils literal notranslate"><span class="pre">VLArray</span></code></a>:</dt><dd><p>Supports collections of homogeneous data with a variable number of entries.
Compressible and enlargeable. I/O is not very fast.</p>
</dd>
<dt>:<code class="xref py py-class docutils literal notranslate"><span class="pre">Group</span></code>:</dt><dd><p>The structural component.
<dt>:<a class="reference internal" href="usersguide/libref/hierarchy_classes.html#tables.Group" title="tables.Group"><code class="xref py py-class docutils literal notranslate"><span class="pre">Group</span></code></a>:</dt><dd><p>The structural component.
A hierarchically-addressable container for HDF5 nodes (each of these
containers, including Group, are nodes), similar to a directory in a
UNIX filesystem.</p>
Expand Down Expand Up @@ -502,7 +588,7 @@ <h3>I’m already using PyTables 2.x but I’m still getting numarray objects in
this attribute and obediently converts the internal object (truly a NumPy
object) into a <cite>numarray</cite> one. For PyTables 2.x files the <cite>FLAVOR</cite> attribute
will only be saved when explicitly set via the <cite>leaf.flavor</cite> property (or when
passing data to an <code class="xref py py-class docutils literal notranslate"><span class="pre">Array</span></code> or <code class="xref py py-class docutils literal notranslate"><span class="pre">Table</span></code> at creation time), so you
passing data to an <a class="reference internal" href="usersguide/libref/homogenous_storage.html#tables.Array" title="tables.Array"><code class="xref py py-class docutils literal notranslate"><span class="pre">Array</span></code></a> or <a class="reference internal" href="usersguide/libref/structured_storage.html#tables.Table" title="tables.Table"><code class="xref py py-class docutils literal notranslate"><span class="pre">Table</span></code></a> at creation time), so you
will be able to distinguish default flavors from user-set ones by checking the
existence of the <cite>FLAVOR</cite> attribute.</p>
<p>Meanwhile, if you don’t want to receive <cite>numarray</cite> objects when reading old
Expand Down Expand Up @@ -549,7 +635,6 @@ <h4>Error when importing tables<a class="headerlink" href="#error-when-importing
these libraries in your PATH, upgrade it to the latest version available (you
don’t need to re-install PyTables).</p>
<hr class="docutils" />
<aside class="footnote-list brackets">
<aside class="footnote brackets" id="id3" role="note">
<span class="label"><span class="fn-bracket">[</span>1<span class="fn-bracket">]</span></span>
<span class="backrefs">(<a role="doc-backlink" href="#id4">1</a>,<a role="doc-backlink" href="#id5">2</a>,<a role="doc-backlink" href="#id6">3</a>,<a role="doc-backlink" href="#id7">4</a>,<a role="doc-backlink" href="#id8">5</a>,<a role="doc-backlink" href="#id9">6</a>,<a role="doc-backlink" href="#id10">7</a>,<a role="doc-backlink" href="#id11">8</a>,<a role="doc-backlink" href="#id12">9</a>,<a role="doc-backlink" href="#id13">10</a>,<a role="doc-backlink" href="#id14">11</a>,<a role="doc-backlink" href="#id15">12</a>,<a role="doc-backlink" href="#id16">13</a>,<a role="doc-backlink" href="#id17">14</a>,<a role="doc-backlink" href="#id18">15</a>)</span>
Expand Down Expand Up @@ -651,41 +736,58 @@ <h4>Error when importing tables<a class="headerlink" href="#error-when-importing
<span class="label"><span class="fn-bracket">[</span><a role="doc-backlink" href="#id79">24</a><span class="fn-bracket">]</span></span>
<p><a class="reference external" href="https://mail.python.org/pipermail/python-dev/2004-September/048763.html">https://mail.python.org/pipermail/python-dev/2004-September/048763.html</a></p>
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