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<div class="section" id="module-apache_beam.ml.gcp.recommendations_ai">
<span id="apache-beam-ml-gcp-recommendations-ai-module"></span><h1>apache_beam.ml.gcp.recommendations_ai module<a class="headerlink" href="#module-apache_beam.ml.gcp.recommendations_ai" title="Permalink to this headline"></a></h1>
<p>A connector for sending API requests to the GCP Recommendations AI
API (<a class="reference external" href="https://cloud.google.com/recommendations">https://cloud.google.com/recommendations</a>).</p>
<dl class="class">
<dt id="apache_beam.ml.gcp.recommendations_ai.CreateCatalogItem">
<em class="property">class </em><code class="descclassname">apache_beam.ml.gcp.recommendations_ai.</code><code class="descname">CreateCatalogItem</code><span class="sig-paren">(</span><em>project: str = None</em>, <em>retry: google.api_core.retry.Retry = None</em>, <em>timeout: float = 120</em>, <em>metadata: Sequence[Tuple[str</em>, <em>str]] = ()</em>, <em>catalog_name: str = 'default_catalog'</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/apache_beam/ml/gcp/recommendations_ai.html#CreateCatalogItem"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#apache_beam.ml.gcp.recommendations_ai.CreateCatalogItem" 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 notranslate"><span class="pre">apache_beam.transforms.ptransform.PTransform</span></code></a></p>
<p>Creates catalogitem information.
The <code class="docutils literal notranslate"><span class="pre">PTranform</span></code> returns a PCollectionTuple with a PCollections of
successfully and failed created CatalogItems.</p>
<p>Example usage:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">pipeline</span> <span class="o">|</span> <span class="n">CreateCatalogItem</span><span class="p">(</span>
<span class="n">project</span><span class="o">=</span><span class="s1">&#39;example-gcp-project&#39;</span><span class="p">,</span>
<span class="n">catalog_name</span><span class="o">=</span><span class="s1">&#39;my-catalog&#39;</span><span class="p">)</span>
</pre></div>
</div>
<p>Initializes a <a class="reference internal" href="#apache_beam.ml.gcp.recommendations_ai.CreateCatalogItem" title="apache_beam.ml.gcp.recommendations_ai.CreateCatalogItem"><code class="xref py py-class docutils literal notranslate"><span class="pre">CreateCatalogItem</span></code></a> 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 last simple">
<li><strong>project</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.9)"><em>str</em></a>) – Optional. GCP project name in which the catalog
data will be imported.</li>
<li><strong>retry</strong> – Optional. Designation of what
errors, if any, should be retried.</li>
<li><strong>timeout</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.9)"><em>float</em></a>) – Optional. The amount of time, in seconds, to wait
for the request to complete.</li>
<li><strong>metadata</strong> – Optional. Strings which
should be sent along with the request as metadata.</li>
<li><strong>catalog_name</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.9)"><em>str</em></a>) – Optional. Name of the catalog.
Default: ‘default_catalog’</li>
</ul>
</td>
</tr>
</tbody>
</table>
<dl class="method">
<dt id="apache_beam.ml.gcp.recommendations_ai.CreateCatalogItem.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/ml/gcp/recommendations_ai.html#CreateCatalogItem.expand"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#apache_beam.ml.gcp.recommendations_ai.CreateCatalogItem.expand" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
</dd></dl>
<dl class="class">
<dt id="apache_beam.ml.gcp.recommendations_ai.ImportCatalogItems">
<em class="property">class </em><code class="descclassname">apache_beam.ml.gcp.recommendations_ai.</code><code class="descname">ImportCatalogItems</code><span class="sig-paren">(</span><em>max_batch_size: int = 5000</em>, <em>project: str = None</em>, <em>retry: google.api_core.retry.Retry = None</em>, <em>timeout: float = 120</em>, <em>metadata: Sequence[Tuple[str</em>, <em>str]] = ()</em>, <em>catalog_name: str = 'default_catalog'</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/apache_beam/ml/gcp/recommendations_ai.html#ImportCatalogItems"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#apache_beam.ml.gcp.recommendations_ai.ImportCatalogItems" 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 notranslate"><span class="pre">apache_beam.transforms.ptransform.PTransform</span></code></a></p>
<p>Imports catalogitems in bulk.
The <cite>PTransform</cite> returns a PCollectionTuple with PCollections of
successfully and failed imported CatalogItems.</p>
<p>Example usage:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">pipeline</span>
<span class="o">|</span> <span class="n">ImportCatalogItems</span><span class="p">(</span>
<span class="n">project</span><span class="o">=</span><span class="s1">&#39;example-gcp-project&#39;</span><span class="p">,</span>
<span class="n">catalog_name</span><span class="o">=</span><span class="s1">&#39;my-catalog&#39;</span><span class="p">)</span>
</pre></div>
</div>
<p>Initializes a <a class="reference internal" href="#apache_beam.ml.gcp.recommendations_ai.ImportCatalogItems" title="apache_beam.ml.gcp.recommendations_ai.ImportCatalogItems"><code class="xref py py-class docutils literal notranslate"><span class="pre">ImportCatalogItems</span></code></a> 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 last simple">
<li><strong>batch_size</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.9)"><em>int</em></a>) – Required. Maximum number of catalogitems per
request.</li>
<li><strong>project</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.9)"><em>str</em></a>) – Optional. GCP project name in which the catalog
data will be imported.</li>
<li><strong>retry</strong> – Optional. Designation of what
errors, if any, should be retried.</li>
<li><strong>timeout</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.9)"><em>float</em></a>) – Optional. The amount of time, in seconds, to wait
for the request to complete.</li>
<li><strong>metadata</strong> – Optional. Strings which
should be sent along with the request as metadata.</li>
<li><strong>catalog_name</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.9)"><em>str</em></a>) – Optional. Name of the catalog.
Default: ‘default_catalog’</li>
</ul>
</td>
</tr>
</tbody>
</table>
<dl class="method">
<dt id="apache_beam.ml.gcp.recommendations_ai.ImportCatalogItems.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/ml/gcp/recommendations_ai.html#ImportCatalogItems.expand"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#apache_beam.ml.gcp.recommendations_ai.ImportCatalogItems.expand" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
</dd></dl>
<dl class="class">
<dt id="apache_beam.ml.gcp.recommendations_ai.WriteUserEvent">
<em class="property">class </em><code class="descclassname">apache_beam.ml.gcp.recommendations_ai.</code><code class="descname">WriteUserEvent</code><span class="sig-paren">(</span><em>project: str = None</em>, <em>retry: google.api_core.retry.Retry = None</em>, <em>timeout: float = 120</em>, <em>metadata: Sequence[Tuple[str</em>, <em>str]] = ()</em>, <em>catalog_name: str = 'default_catalog'</em>, <em>event_store: str = 'default_event_store'</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/apache_beam/ml/gcp/recommendations_ai.html#WriteUserEvent"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#apache_beam.ml.gcp.recommendations_ai.WriteUserEvent" 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 notranslate"><span class="pre">apache_beam.transforms.ptransform.PTransform</span></code></a></p>
<p>Write user event information.
The <cite>PTransform</cite> returns a PCollectionTuple with PCollections of
successfully and failed written UserEvents.</p>
<p>Example usage:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">pipeline</span>
<span class="o">|</span> <span class="n">WriteUserEvent</span><span class="p">(</span>
<span class="n">project</span><span class="o">=</span><span class="s1">&#39;example-gcp-project&#39;</span><span class="p">,</span>
<span class="n">catalog_name</span><span class="o">=</span><span class="s1">&#39;my-catalog&#39;</span><span class="p">,</span>
<span class="n">event_store</span><span class="o">=</span><span class="s1">&#39;my_event_store&#39;</span><span class="p">)</span>
</pre></div>
</div>
<p>Initializes a <a class="reference internal" href="#apache_beam.ml.gcp.recommendations_ai.WriteUserEvent" title="apache_beam.ml.gcp.recommendations_ai.WriteUserEvent"><code class="xref py py-class docutils literal notranslate"><span class="pre">WriteUserEvent</span></code></a> 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 last simple">
<li><strong>project</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.9)"><em>str</em></a>) – Optional. GCP project name in which the catalog
data will be imported.</li>
<li><strong>retry</strong> – Optional. Designation of what
errors, if any, should be retried.</li>
<li><strong>timeout</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.9)"><em>float</em></a>) – Optional. The amount of time, in seconds, to wait
for the request to complete.</li>
<li><strong>metadata</strong> – Optional. Strings which
should be sent along with the request as metadata.</li>
<li><strong>catalog_name</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.9)"><em>str</em></a>) – Optional. Name of the catalog.
Default: ‘default_catalog’</li>
<li><strong>event_store</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.9)"><em>str</em></a>) – Optional. Name of the event store.
Default: ‘default_event_store’</li>
</ul>
</td>
</tr>
</tbody>
</table>
<dl class="method">
<dt id="apache_beam.ml.gcp.recommendations_ai.WriteUserEvent.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/ml/gcp/recommendations_ai.html#WriteUserEvent.expand"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#apache_beam.ml.gcp.recommendations_ai.WriteUserEvent.expand" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
</dd></dl>
<dl class="class">
<dt id="apache_beam.ml.gcp.recommendations_ai.ImportUserEvents">
<em class="property">class </em><code class="descclassname">apache_beam.ml.gcp.recommendations_ai.</code><code class="descname">ImportUserEvents</code><span class="sig-paren">(</span><em>max_batch_size: int = 5000</em>, <em>project: str = None</em>, <em>retry: google.api_core.retry.Retry = None</em>, <em>timeout: float = 120</em>, <em>metadata: Sequence[Tuple[str</em>, <em>str]] = ()</em>, <em>catalog_name: str = 'default_catalog'</em>, <em>event_store: str = 'default_event_store'</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/apache_beam/ml/gcp/recommendations_ai.html#ImportUserEvents"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#apache_beam.ml.gcp.recommendations_ai.ImportUserEvents" 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 notranslate"><span class="pre">apache_beam.transforms.ptransform.PTransform</span></code></a></p>
<p>Imports userevents in bulk.
The <cite>PTransform</cite> returns a PCollectionTuple with PCollections of
successfully and failed imported UserEvents.</p>
<p>Example usage:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">pipeline</span>
<span class="o">|</span> <span class="n">ImportUserEvents</span><span class="p">(</span>
<span class="n">project</span><span class="o">=</span><span class="s1">&#39;example-gcp-project&#39;</span><span class="p">,</span>
<span class="n">catalog_name</span><span class="o">=</span><span class="s1">&#39;my-catalog&#39;</span><span class="p">,</span>
<span class="n">event_store</span><span class="o">=</span><span class="s1">&#39;my_event_store&#39;</span><span class="p">)</span>
</pre></div>
</div>
<p>Initializes a <a class="reference internal" href="#apache_beam.ml.gcp.recommendations_ai.WriteUserEvent" title="apache_beam.ml.gcp.recommendations_ai.WriteUserEvent"><code class="xref py py-class docutils literal notranslate"><span class="pre">WriteUserEvent</span></code></a> 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 last simple">
<li><strong>batch_size</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.9)"><em>int</em></a>) – Required. Maximum number of catalogitems
per request.</li>
<li><strong>project</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.9)"><em>str</em></a>) – Optional. GCP project name in which the catalog
data will be imported.</li>
<li><strong>retry</strong> – Optional. Designation of what
errors, if any, should be retried.</li>
<li><strong>timeout</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.9)"><em>float</em></a>) – Optional. The amount of time, in seconds, to wait
for the request to complete.</li>
<li><strong>metadata</strong> – Optional. Strings which
should be sent along with the request as metadata.</li>
<li><strong>catalog_name</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.9)"><em>str</em></a>) – Optional. Name of the catalog.
Default: ‘default_catalog’</li>
<li><strong>event_store</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.9)"><em>str</em></a>) – Optional. Name of the event store.
Default: ‘default_event_store’</li>
</ul>
</td>
</tr>
</tbody>
</table>
<dl class="method">
<dt id="apache_beam.ml.gcp.recommendations_ai.ImportUserEvents.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/ml/gcp/recommendations_ai.html#ImportUserEvents.expand"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#apache_beam.ml.gcp.recommendations_ai.ImportUserEvents.expand" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
</dd></dl>
<dl class="class">
<dt id="apache_beam.ml.gcp.recommendations_ai.PredictUserEvent">
<em class="property">class </em><code class="descclassname">apache_beam.ml.gcp.recommendations_ai.</code><code class="descname">PredictUserEvent</code><span class="sig-paren">(</span><em>project: str = None</em>, <em>retry: google.api_core.retry.Retry = None</em>, <em>timeout: float = 120</em>, <em>metadata: Sequence[Tuple[str</em>, <em>str]] = ()</em>, <em>catalog_name: str = 'default_catalog'</em>, <em>event_store: str = 'default_event_store'</em>, <em>placement_id: str = None</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/apache_beam/ml/gcp/recommendations_ai.html#PredictUserEvent"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#apache_beam.ml.gcp.recommendations_ai.PredictUserEvent" 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 notranslate"><span class="pre">apache_beam.transforms.ptransform.PTransform</span></code></a></p>
<p>Make a recommendation prediction.
The <cite>PTransform</cite> returns a PCollection</p>
<p>Example usage:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">pipeline</span>
<span class="o">|</span> <span class="n">PredictUserEvent</span><span class="p">(</span>
<span class="n">project</span><span class="o">=</span><span class="s1">&#39;example-gcp-project&#39;</span><span class="p">,</span>
<span class="n">catalog_name</span><span class="o">=</span><span class="s1">&#39;my-catalog&#39;</span><span class="p">,</span>
<span class="n">event_store</span><span class="o">=</span><span class="s1">&#39;my_event_store&#39;</span><span class="p">,</span>
<span class="n">placement_id</span><span class="o">=</span><span class="s1">&#39;recently_viewed_default&#39;</span><span class="p">)</span>
</pre></div>
</div>
<p>Initializes a <a class="reference internal" href="#apache_beam.ml.gcp.recommendations_ai.PredictUserEvent" title="apache_beam.ml.gcp.recommendations_ai.PredictUserEvent"><code class="xref py py-class docutils literal notranslate"><span class="pre">PredictUserEvent</span></code></a> 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 last simple">
<li><strong>project</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.9)"><em>str</em></a>) – Optional. GCP project name in which the catalog
data will be imported.</li>
<li><strong>retry</strong> – Optional. Designation of what
errors, if any, should be retried.</li>
<li><strong>timeout</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.9)"><em>float</em></a>) – Optional. The amount of time, in seconds, to wait
for the request to complete.</li>
<li><strong>metadata</strong> – Optional. Strings which
should be sent along with the request as metadata.</li>
<li><strong>catalog_name</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.9)"><em>str</em></a>) – Optional. Name of the catalog.
Default: ‘default_catalog’</li>
<li><strong>event_store</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.9)"><em>str</em></a>) – Optional. Name of the event store.
Default: ‘default_event_store’</li>
<li><strong>placement_id</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.9)"><em>str</em></a>) – Required. ID of the recommendation engine
placement. This id is used to identify the set of models that
will be used to make the prediction.</li>
</ul>
</td>
</tr>
</tbody>
</table>
<dl class="method">
<dt id="apache_beam.ml.gcp.recommendations_ai.PredictUserEvent.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/ml/gcp/recommendations_ai.html#PredictUserEvent.expand"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#apache_beam.ml.gcp.recommendations_ai.PredictUserEvent.expand" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
</dd></dl>
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