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   <div class="section" id="module-apache_beam.io.avroio">
 <span id="apache-beam-io-avroio-module"></span><h1>apache_beam.io.avroio module<a class="headerlink" href="#module-apache_beam.io.avroio" title="Permalink to this headline">¶</a></h1>
 <p><code class="docutils literal"><span class="pre">PTransforms</span></code> for reading from and writing to Avro files.</p>
 <p>Provides two read <code class="docutils literal"><span class="pre">PTransform``s,</span> <span class="pre">``ReadFromAvro</span></code> and <code class="docutils literal"><span class="pre">ReadAllFromAvro</span></code>,
 that produces a <code class="docutils literal"><span class="pre">PCollection</span></code> of records.
 Each record of this <code class="docutils literal"><span class="pre">PCollection</span></code> will contain a single record read from
 an Avro file. Records that are of simple types will be mapped into
 corresponding Python types. Records that are of Avro type ‘RECORD’ will be
 mapped to Python dictionaries that comply with the schema contained in the
 Avro file that contains those records. In this case, keys of each dictionary
 will contain the corresponding field names and will be of type <code class="docutils literal"><span class="pre">string</span></code>
 while the values of the dictionary will be of the type defined in the
 corresponding Avro schema.</p>
 <p>For example, if schema of the Avro file is the following.
 {“namespace”: “example.avro”,”type”: “record”,”name”: “User”,”fields”:
 [{“name”: “name”, “type”: “string”},
 {“name”: “favorite_number”,  “type”: [“int”, “null”]},
 {“name”: “favorite_color”, “type”: [“string”, “null”]}]}</p>
 <p>Then records generated by read transforms will be dictionaries of the
 following form.
 {u’name’: u’Alyssa’, u’favorite_number’: 256, u’favorite_color’: None}).</p>
 <p>Additionally, this module provides a write <code class="docutils literal"><span class="pre">PTransform</span></code> <code class="docutils literal"><span class="pre">WriteToAvro</span></code>
 that can be used to write a given <code class="docutils literal"><span class="pre">PCollection</span></code> of Python objects to an
 Avro file.</p>
 <dl class="class">
 <dt id="apache_beam.io.avroio.ReadFromAvro">
 <em class="property">class </em><code class="descclassname">apache_beam.io.avroio.</code><code class="descname">ReadFromAvro</code><span class="sig-paren">(</span><em>file_pattern=None</em>, <em>min_bundle_size=0</em>, <em>validate=True</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/apache_beam/io/avroio.html#ReadFromAvro"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#apache_beam.io.avroio.ReadFromAvro" title="Permalink to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="apache_beam.transforms.ptransform.html#apache_beam.transforms.ptransform.PTransform" title="apache_beam.transforms.ptransform.PTransform"><code class="xref py py-class docutils literal"><span class="pre">apache_beam.transforms.ptransform.PTransform</span></code></a></p>
 <p>A <a class="reference internal" href="apache_beam.transforms.ptransform.html#apache_beam.transforms.ptransform.PTransform" title="apache_beam.transforms.ptransform.PTransform"><code class="xref py py-class docutils literal"><span class="pre">PTransform</span></code></a> for reading avro
 files.</p>
 <p>Initializes <a class="reference internal" href="#apache_beam.io.avroio.ReadFromAvro" title="apache_beam.io.avroio.ReadFromAvro"><code class="xref py py-class docutils literal"><span class="pre">ReadFromAvro</span></code></a>.</p>
 <p>Uses source <code class="xref py py-class docutils literal"><span class="pre">_AvroSource</span></code> to read a set of Avro
 files defined by a given file pattern.</p>
 <p>If <code class="docutils literal"><span class="pre">/mypath/myavrofiles*</span></code> is a file-pattern that points to a set of Avro
 files, a <a class="reference internal" href="apache_beam.pvalue.html#apache_beam.pvalue.PCollection" title="apache_beam.pvalue.PCollection"><code class="xref py py-class docutils literal"><span class="pre">PCollection</span></code></a> for the records in
 these Avro files can be created in the following manner.</p>
 <div class="highlight-default"><div class="highlight"><pre><span></span><span class="k">with</span> <span class="n">beam</span><span class="o">.</span><span class="n">Pipeline</span><span class="p">()</span> <span class="k">as</span> <span class="n">p</span><span class="p">:</span>
   <span class="n">records</span> <span class="o">=</span> <span class="n">p</span> <span class="o">|</span> <span class="s1">&#39;Read&#39;</span> <span class="o">&gt;&gt;</span> <span class="n">beam</span><span class="o">.</span><span class="n">io</span><span class="o">.</span><span class="n">ReadFromAvro</span><span class="p">(</span><span class="s1">&#39;/mypath/myavrofiles*&#39;</span><span class="p">)</span>
 </pre></div>
 </div>
 <p>Each record of this <a class="reference internal" href="apache_beam.pvalue.html#apache_beam.pvalue.PCollection" title="apache_beam.pvalue.PCollection"><code class="xref py py-class docutils literal"><span class="pre">PCollection</span></code></a> will contain
 a single record read from a source. Records that are of simple types will be
 mapped into corresponding Python types. Records that are of Avro type
 <code class="docutils literal"><span class="pre">RECORD</span></code> will be mapped to Python dictionaries that comply with the schema
 contained in the Avro file that contains those records. In this case, keys
 of each dictionary will contain the corresponding field names and will be of
 type <a class="reference external" href="https://docs.python.org/2/library/functions.html#str" title="(in Python v2.7)"><code class="xref py py-class docutils literal"><span class="pre">str</span></code></a> while the values of the dictionary will be of the type
 defined in the corresponding Avro schema.</p>
 <p>For example, if schema of the Avro file is the following.</p>
 <div class="highlight-default"><div class="highlight"><pre><span></span><span class="p">{</span>
   <span class="s2">&quot;namespace&quot;</span><span class="p">:</span> <span class="s2">&quot;example.avro&quot;</span><span class="p">,</span>
   <span class="s2">&quot;type&quot;</span><span class="p">:</span> <span class="s2">&quot;record&quot;</span><span class="p">,</span>
   <span class="s2">&quot;name&quot;</span><span class="p">:</span> <span class="s2">&quot;User&quot;</span><span class="p">,</span>
   <span class="s2">&quot;fields&quot;</span><span class="p">:</span> <span class="p">[</span>

     <span class="p">{</span><span class="s2">&quot;name&quot;</span><span class="p">:</span> <span class="s2">&quot;name&quot;</span><span class="p">,</span>
      <span class="s2">&quot;type&quot;</span><span class="p">:</span> <span class="s2">&quot;string&quot;</span><span class="p">},</span>

     <span class="p">{</span><span class="s2">&quot;name&quot;</span><span class="p">:</span> <span class="s2">&quot;favorite_number&quot;</span><span class="p">,</span>
      <span class="s2">&quot;type&quot;</span><span class="p">:</span> <span class="p">[</span><span class="s2">&quot;int&quot;</span><span class="p">,</span> <span class="s2">&quot;null&quot;</span><span class="p">]},</span>

     <span class="p">{</span><span class="s2">&quot;name&quot;</span><span class="p">:</span> <span class="s2">&quot;favorite_color&quot;</span><span class="p">,</span>
      <span class="s2">&quot;type&quot;</span><span class="p">:</span> <span class="p">[</span><span class="s2">&quot;string&quot;</span><span class="p">,</span> <span class="s2">&quot;null&quot;</span><span class="p">]}</span>

   <span class="p">]</span>
 <span class="p">}</span>
 </pre></div>
 </div>
 <p>Then records generated by <code class="xref py py-class docutils literal"><span class="pre">_AvroSource</span></code> will be
 dictionaries of the following form.</p>
 <div class="highlight-default"><div class="highlight"><pre><span></span><span class="p">{</span><span class="sa">u</span><span class="s1">&#39;name&#39;</span><span class="p">:</span> <span class="sa">u</span><span class="s1">&#39;Alyssa&#39;</span><span class="p">,</span> <span class="sa">u</span><span class="s1">&#39;favorite_number&#39;</span><span class="p">:</span> <span class="mi">256</span><span class="p">,</span> <span class="sa">u</span><span class="s1">&#39;favorite_color&#39;</span><span class="p">:</span> <span class="kc">None</span><span class="p">})</span><span class="o">.</span>
 </pre></div>
 </div>
 <table class="docutils field-list" frame="void" rules="none">
 <col class="field-name" />
 <col class="field-body" />
 <tbody valign="top">
 <tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
 <li><strong>file_pattern</strong> (<a class="reference external" href="https://docs.python.org/2/library/functions.html#str" title="(in Python v2.7)"><em>str</em></a>) – the file glob to read</li>
 <li><strong>min_bundle_size</strong> (<a class="reference external" href="https://docs.python.org/2/library/functions.html#int" title="(in Python v2.7)"><em>int</em></a>) – the minimum size in bytes, to be considered when
 splitting the input into bundles.</li>
 <li><strong>validate</strong> (<a class="reference external" href="https://docs.python.org/2/library/functions.html#bool" title="(in Python v2.7)"><em>bool</em></a>) – flag to verify that the files exist during the pipeline
 creation time.</li>
 </ul>
 </td>
 </tr>
 </tbody>
 </table>
 <dl class="method">
 <dt id="apache_beam.io.avroio.ReadFromAvro.expand">
 <code class="descname">expand</code><span class="sig-paren">(</span><em>pvalue</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/apache_beam/io/avroio.html#ReadFromAvro.expand"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#apache_beam.io.avroio.ReadFromAvro.expand" title="Permalink to this definition">¶</a></dt>
 <dd></dd></dl>

 <dl class="method">
 <dt id="apache_beam.io.avroio.ReadFromAvro.display_data">
 <code class="descname">display_data</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/apache_beam/io/avroio.html#ReadFromAvro.display_data"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#apache_beam.io.avroio.ReadFromAvro.display_data" title="Permalink to this definition">¶</a></dt>
 <dd></dd></dl>

 </dd></dl>

 <dl class="class">
 <dt id="apache_beam.io.avroio.ReadAllFromAvro">
 <em class="property">class </em><code class="descclassname">apache_beam.io.avroio.</code><code class="descname">ReadAllFromAvro</code><span class="sig-paren">(</span><em>min_bundle_size=0</em>, <em>desired_bundle_size=67108864</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/apache_beam/io/avroio.html#ReadAllFromAvro"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#apache_beam.io.avroio.ReadAllFromAvro" title="Permalink to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="apache_beam.transforms.ptransform.html#apache_beam.transforms.ptransform.PTransform" title="apache_beam.transforms.ptransform.PTransform"><code class="xref py py-class docutils literal"><span class="pre">apache_beam.transforms.ptransform.PTransform</span></code></a></p>
 <p>A <code class="docutils literal"><span class="pre">PTransform</span></code> for reading <code class="docutils literal"><span class="pre">PCollection</span></code> of Avro files.</p>
 <p>Uses source ‘_AvroSource’ to read a <code class="docutils literal"><span class="pre">PCollection</span></code> of Avro files or
 file patterns and produce a <code class="docutils literal"><span class="pre">PCollection</span></code> of Avro records.</p>
 <p>Initializes <code class="docutils literal"><span class="pre">ReadAllFromAvro</span></code>.</p>
 <table class="docutils field-list" frame="void" rules="none">
 <col class="field-name" />
 <col class="field-body" />
 <tbody valign="top">
 <tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first last simple">
 <li><strong>min_bundle_size</strong> – the minimum size in bytes, to be considered when
 splitting the input into bundles.</li>
 <li><strong>desired_bundle_size</strong> – the desired size in bytes, to be considered when
 splitting the input into bundles.</li>
 </ul>
 </td>
 </tr>
 </tbody>
 </table>
 <dl class="attribute">
 <dt id="apache_beam.io.avroio.ReadAllFromAvro.DEFAULT_DESIRED_BUNDLE_SIZE">
 <code class="descname">DEFAULT_DESIRED_BUNDLE_SIZE</code><em class="property"> = 67108864</em><a class="headerlink" href="#apache_beam.io.avroio.ReadAllFromAvro.DEFAULT_DESIRED_BUNDLE_SIZE" title="Permalink to this definition">¶</a></dt>
 <dd></dd></dl>

 <dl class="method">
 <dt id="apache_beam.io.avroio.ReadAllFromAvro.expand">
 <code class="descname">expand</code><span class="sig-paren">(</span><em>pvalue</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/apache_beam/io/avroio.html#ReadAllFromAvro.expand"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#apache_beam.io.avroio.ReadAllFromAvro.expand" title="Permalink to this definition">¶</a></dt>
 <dd></dd></dl>

 </dd></dl>

 <dl class="class">
 <dt id="apache_beam.io.avroio.WriteToAvro">
 <em class="property">class </em><code class="descclassname">apache_beam.io.avroio.</code><code class="descname">WriteToAvro</code><span class="sig-paren">(</span><em>file_path_prefix</em>, <em>schema</em>, <em>codec='deflate'</em>, <em>file_name_suffix=''</em>, <em>num_shards=0</em>, <em>shard_name_template=None</em>, <em>mime_type='application/x-avro'</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/apache_beam/io/avroio.html#WriteToAvro"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#apache_beam.io.avroio.WriteToAvro" title="Permalink to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="apache_beam.transforms.ptransform.html#apache_beam.transforms.ptransform.PTransform" title="apache_beam.transforms.ptransform.PTransform"><code class="xref py py-class docutils literal"><span class="pre">apache_beam.transforms.ptransform.PTransform</span></code></a></p>
 <p>A <code class="docutils literal"><span class="pre">PTransform</span></code> for writing avro files.</p>
 <p>Initialize a WriteToAvro transform.</p>
 <table class="docutils field-list" frame="void" rules="none">
 <col class="field-name" />
 <col class="field-body" />
 <tbody valign="top">
 <tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
 <li><strong>file_path_prefix</strong> – The file path to write to. The files written will begin
 with this prefix, followed by a shard identifier (see num_shards), and
 end in a common extension, if given by file_name_suffix. In most cases,
 only this argument is specified and num_shards, shard_name_template, and
 file_name_suffix use default values.</li>
 <li><strong>schema</strong> – The schema to use, as returned by avro.schema.parse</li>
 <li><strong>codec</strong> – The codec to use for block-level compression. Any string supported
 by the Avro specification is accepted (for example ‘null’).</li>
 <li><strong>file_name_suffix</strong> – Suffix for the files written.</li>
 <li><strong>num_shards</strong> – The number of files (shards) used for output. If not set, the
 service will decide on the optimal number of shards.
 Constraining the number of shards is likely to reduce
 the performance of a pipeline.  Setting this value is not recommended
 unless you require a specific number of output files.</li>
 <li><strong>shard_name_template</strong> – A template string containing placeholders for
 the shard number and shard count. When constructing a filename for a
 particular shard number, the upper-case letters ‘S’ and ‘N’ are
 replaced with the 0-padded shard number and shard count respectively.
 This argument can be ‘’ in which case it behaves as if num_shards was
 set to 1 and only one file will be generated. The default pattern used
 is ‘-SSSSS-of-NNNNN’ if None is passed as the shard_name_template.</li>
 <li><strong>mime_type</strong> – The MIME type to use for the produced files, if the filesystem
 supports specifying MIME types.</li>
 </ul>
 </td>
 </tr>
 <tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">A WriteToAvro transform usable for writing.</p>
 </td>
 </tr>
 </tbody>
 </table>
 <dl class="method">
 <dt id="apache_beam.io.avroio.WriteToAvro.expand">
 <code class="descname">expand</code><span class="sig-paren">(</span><em>pcoll</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/apache_beam/io/avroio.html#WriteToAvro.expand"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#apache_beam.io.avroio.WriteToAvro.expand" title="Permalink to this definition">¶</a></dt>
 <dd></dd></dl>

 <dl class="method">
 <dt id="apache_beam.io.avroio.WriteToAvro.display_data">
 <code class="descname">display_data</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/apache_beam/io/avroio.html#WriteToAvro.display_data"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#apache_beam.io.avroio.WriteToAvro.display_data" title="Permalink to this definition">¶</a></dt>
 <dd></dd></dl>

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