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  <h1>River function</h1>

<div class="doc doc-object doc-module">


<a id="streampipes.function_zoo.river_function"></a>
  <div class="doc doc-contents first">

  
  <div class="doc doc-children">


<div class="doc doc-object doc-class">


<h2 id="streampipes.function_zoo.river_function.OnlineML" class="doc doc-heading">
<code class="highlight language-python"><span class="n">OnlineML</span><span class="p">(</span><span class="n">client</span><span class="p">,</span> <span class="n">stream_ids</span><span class="p">,</span> <span class="n">model</span><span class="p">,</span> <span class="n">prediction_type</span><span class="o">=</span><span class="n">RuntimeType</span><span class="o">.</span><span class="n">STRING</span><span class="o">.</span><span class="n">value</span><span class="p">,</span> <span class="n">supervised</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">target_label</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">on_start</span><span class="o">=</span><span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">context</span><span class="p">:</span> <span class="kc">None</span><span class="p">,</span> <span class="n">on_event</span><span class="o">=</span><span class="k">lambda</span> <span class="bp">self</span><span class="p">,</span> <span class="n">event</span><span class="p">,</span> <span class="n">streamId</span><span class="p">:</span> <span class="kc">None</span><span class="p">,</span> <span class="n">on_stop</span><span class="o">=</span><span class="k">lambda</span> <span class="bp">self</span><span class="p">:</span> <span class="kc">None</span><span class="p">)</span></code>

<a href="#streampipes.function_zoo.river_function.OnlineML" class="headerlink" title="Permanent link">&para;</a></h2>


  <div class="doc doc-contents ">

  
      <p>Wrapper class to enable an easy usage for Online Machine Learning models of the River library.</p>
<p>It creates a StreamPipesFunction to train a model with the incoming events of a data stream and
creates an output data stream to publishes the prediction to StreamPipes.</p>

  <table>
    <thead>
      <tr>
        <th><b>PARAMETER</b></th>
        <th><b>DESCRIPTION</b></th>
      </tr>
    </thead>
    <tbody>
        <tr>
          <td><code>client</code></td>
          <td class="doc-param-details">
            <p>The client for the StreamPipes API.</p>
            <p>
                <span class="doc-param-annotation">
                  <b>TYPE:</b>
                    <code><a class="autorefs autorefs-internal" title="streampipes.client.client.StreamPipesClient" href="../../client/client/#streampipes.client.client.StreamPipesClient">StreamPipesClient</a></code>
                </span>
            </p>
          </td>
        </tr>
        <tr>
          <td><code>stream_ids</code></td>
          <td class="doc-param-details">
            <p>The ids of the data stream to train the model.</p>
            <p>
                <span class="doc-param-annotation">
                  <b>TYPE:</b>
                    <code><span title="typing.List">List</span>[str]</code>
                </span>
            </p>
          </td>
        </tr>
        <tr>
          <td><code>model</code></td>
          <td class="doc-param-details">
            <p>The model to train. It meant to be a River model/pipeline,
but can be every model with a 'learn_one' and 'predict_one' methode.</p>
            <p>
                <span class="doc-param-annotation">
                  <b>TYPE:</b>
                    <code><span title="typing.Any">Any</span></code>
                </span>
            </p>
          </td>
        </tr>
        <tr>
          <td><code>prediction_type</code></td>
          <td class="doc-param-details">
            <p>The data type of the prediction.
Is only needed when you continue to work with the prediction in StreamPipes.</p>
            <p>
                <span class="doc-param-annotation">
                  <b>TYPE:</b>
                    <code>str</code>
                </span>
                <span class="doc-param-default">
                  <b>DEFAULT:</b> 
                    <code>RuntimeType.STRING.value</code>
                </span>
            </p>
          </td>
        </tr>
        <tr>
          <td><code>supervised</code></td>
          <td class="doc-param-details">
            <p>Define if the model is supervised or unsupervised.</p>
            <p>
                <span class="doc-param-annotation">
                  <b>TYPE:</b>
                    <code>bool</code>
                </span>
                <span class="doc-param-default">
                  <b>DEFAULT:</b> 
                    <code>False</code>
                </span>
            </p>
          </td>
        </tr>
        <tr>
          <td><code>target_label</code></td>
          <td class="doc-param-details">
            <p>Define the name of the target attribute if the model is supervised.</p>
            <p>
                <span class="doc-param-annotation">
                  <b>TYPE:</b>
                    <code><span title="typing.Optional">Optional</span>[str]</code>
                </span>
                <span class="doc-param-default">
                  <b>DEFAULT:</b> 
                    <code>None</code>
                </span>
            </p>
          </td>
        </tr>
        <tr>
          <td><code>on_start</code></td>
          <td class="doc-param-details">
            <p>A function to be called when this StreamPipesFunction gets started.</p>
            <p>
                <span class="doc-param-annotation">
                  <b>TYPE:</b>
                    <code><span title="typing.Callable">Callable</span>[[<span title="typing.Any">Any</span>, <a class="autorefs autorefs-internal" title="streampipes.functions.utils.function_context.FunctionContext" href="../../functions/utils/function_context/#streampipes.functions.utils.function_context.FunctionContext">FunctionContext</a>], None]</code>
                </span>
                <span class="doc-param-default">
                  <b>DEFAULT:</b> 
                    <code>lambda self, context: None</code>
                </span>
            </p>
          </td>
        </tr>
        <tr>
          <td><code>on_event</code></td>
          <td class="doc-param-details">
            <p>A function to be called when this StreamPipesFunction receives an event.</p>
            <p>
                <span class="doc-param-annotation">
                  <b>TYPE:</b>
                    <code><span title="typing.Callable">Callable</span>[[<span title="typing.Any">Any</span>, <span title="typing.Dict">Dict</span>[str, <span title="typing.Any">Any</span>], str], None]</code>
                </span>
                <span class="doc-param-default">
                  <b>DEFAULT:</b> 
                    <code>lambda self, event, streamId: None</code>
                </span>
            </p>
          </td>
        </tr>
        <tr>
          <td><code>on_stop</code></td>
          <td class="doc-param-details">
            <p>A function to be called when this StreamPipesFunction gets stopped.</p>
            <p>
                <span class="doc-param-annotation">
                  <b>TYPE:</b>
                    <code><span title="typing.Callable">Callable</span>[[<span title="typing.Any">Any</span>], None]</code>
                </span>
                <span class="doc-param-default">
                  <b>DEFAULT:</b> 
                    <code>lambda self: None</code>
                </span>
            </p>
          </td>
        </tr>
    </tbody>
  </table>


  <div class="doc doc-children">


<div class="doc doc-object doc-function">


<h3 id="streampipes.function_zoo.river_function.OnlineML.set_learning" class="doc doc-heading">
<code class="highlight language-python"><span class="n">set_learning</span><span class="p">(</span><span class="n">learning</span><span class="p">)</span></code>

<a href="#streampipes.function_zoo.river_function.OnlineML.set_learning" class="headerlink" title="Permanent link">&para;</a></h3>


  <div class="doc doc-contents ">
  
      <p>Start or stop the training of the model.</p>

  <table>
    <thead>
      <tr>
        <th><b>PARAMETER</b></th>
        <th><b>DESCRIPTION</b></th>
      </tr>
    </thead>
    <tbody>
        <tr>
          <td><code>learning</code></td>
          <td class="doc-param-details">
            <p>Defines if the training should be continued</p>
            <p>
                <span class="doc-param-annotation">
                  <b>TYPE:</b>
                    <code>bool</code>
                </span>
            </p>
          </td>
        </tr>
    </tbody>
  </table>

  </div>

</div>

<div class="doc doc-object doc-function">


<h3 id="streampipes.function_zoo.river_function.OnlineML.start" class="doc doc-heading">
<code class="highlight language-python"><span class="n">start</span><span class="p">()</span></code>

<a href="#streampipes.function_zoo.river_function.OnlineML.start" class="headerlink" title="Permanent link">&para;</a></h3>


  <div class="doc doc-contents ">
  
      <p>Registers the function and starts the training.</p>

  </div>

</div>

<div class="doc doc-object doc-function">


<h3 id="streampipes.function_zoo.river_function.OnlineML.stop" class="doc doc-heading">
<code class="highlight language-python"><span class="n">stop</span><span class="p">()</span></code>

<a href="#streampipes.function_zoo.river_function.OnlineML.stop" class="headerlink" title="Permanent link">&para;</a></h3>


  <div class="doc doc-contents ">
  
      <p>Stops the function and ends the training for ever.</p>

  </div>

</div>


  </div>

  </div>

</div>

<div class="doc doc-object doc-class">


<h2 id="streampipes.function_zoo.river_function.RiverFunction" class="doc doc-heading">
<code class="highlight language-python"><span class="n">RiverFunction</span><span class="p">(</span><span class="n">function_definition</span><span class="p">,</span> <span class="n">stream_ids</span><span class="p">,</span> <span class="n">model</span><span class="p">,</span> <span class="n">supervised</span><span class="p">,</span> <span class="n">target_label</span><span class="p">,</span> <span class="n">on_start</span><span class="p">,</span> <span class="n">on_event</span><span class="p">,</span> <span class="n">on_stop</span><span class="p">)</span></code>

<a href="#streampipes.function_zoo.river_function.RiverFunction" class="headerlink" title="Permanent link">&para;</a></h2>


  <div class="doc doc-contents ">
      <p class="doc doc-class-bases">
        Bases: <code><a class="autorefs autorefs-internal" title="streampipes.functions.streampipes_function.StreamPipesFunction" href="../../functions/streampipes_function/#streampipes.functions.streampipes_function.StreamPipesFunction">StreamPipesFunction</a></code></p>

  
      <p>Implementation of a StreamPipesFunction to enable an easy usage
for Online Machine Learning models of the River library.</p>
<p>The function trains the model with the incoming events and publishes the prediction to an output data stream.</p>

  <table>
    <thead>
      <tr>
        <th><b>PARAMETER</b></th>
        <th><b>DESCRIPTION</b></th>
      </tr>
    </thead>
    <tbody>
        <tr>
          <td><code>function_definition</code></td>
          <td class="doc-param-details">
            <p>The function definition which contains the output stream.</p>
            <p>
                <span class="doc-param-annotation">
                  <b>TYPE:</b>
                    <code><a class="autorefs autorefs-internal" title="streampipes.model.resource.function_definition.FunctionDefinition" href="../../model/resource/function_definition/#streampipes.model.resource.function_definition.FunctionDefinition">FunctionDefinition</a></code>
                </span>
            </p>
          </td>
        </tr>
        <tr>
          <td><code>stream_ids</code></td>
          <td class="doc-param-details">
            <p>The ids of the data stream to train the model.</p>
            <p>
                <span class="doc-param-annotation">
                  <b>TYPE:</b>
                    <code><span title="typing.List">List</span>[str]</code>
                </span>
            </p>
          </td>
        </tr>
        <tr>
          <td><code>model</code></td>
          <td class="doc-param-details">
            <p>The model to train. It meant to be a River model/pipeline,
but can be every model with a 'learn_one' and 'predict_one' method.</p>
            <p>
                <span class="doc-param-annotation">
                  <b>TYPE:</b>
                    <code><span title="typing.Any">Any</span></code>
                </span>
            </p>
          </td>
        </tr>
        <tr>
          <td><code>supervised</code></td>
          <td class="doc-param-details">
            <p>Define if the model is supervised or unsupervised.</p>
            <p>
                <span class="doc-param-annotation">
                  <b>TYPE:</b>
                    <code>bool</code>
                </span>
            </p>
          </td>
        </tr>
        <tr>
          <td><code>target_label</code></td>
          <td class="doc-param-details">
            <p>Define the name of the target attribute if the model is supervised.</p>
            <p>
                <span class="doc-param-annotation">
                  <b>TYPE:</b>
                    <code><span title="typing.Optional">Optional</span>[str]</code>
                </span>
            </p>
          </td>
        </tr>
        <tr>
          <td><code>on_start</code></td>
          <td class="doc-param-details">
            <p>A function to be called when this StreamPipesFunction gets started.</p>
            <p>
                <span class="doc-param-annotation">
                  <b>TYPE:</b>
                    <code><span title="typing.Callable">Callable</span>[[<span title="typing.Any">Any</span>, <a class="autorefs autorefs-internal" title="streampipes.functions.utils.function_context.FunctionContext" href="../../functions/utils/function_context/#streampipes.functions.utils.function_context.FunctionContext">FunctionContext</a>], None]</code>
                </span>
            </p>
          </td>
        </tr>
        <tr>
          <td><code>on_event</code></td>
          <td class="doc-param-details">
            <p>A function to be called when this StreamPipesFunction receives an event.</p>
            <p>
                <span class="doc-param-annotation">
                  <b>TYPE:</b>
                    <code><span title="typing.Callable">Callable</span>[[<span title="typing.Any">Any</span>, <span title="typing.Dict">Dict</span>[str, <span title="typing.Any">Any</span>], str], None]</code>
                </span>
            </p>
          </td>
        </tr>
        <tr>
          <td><code>on_stop</code></td>
          <td class="doc-param-details">
            <p>A function to be called when this StreamPipesFunction gets stopped.</p>
            <p>
                <span class="doc-param-annotation">
                  <b>TYPE:</b>
                    <code><span title="typing.Callable">Callable</span>[[<span title="typing.Any">Any</span>], None]</code>
                </span>
            </p>
          </td>
        </tr>
    </tbody>
  </table>


  <div class="doc doc-children">


<div class="doc doc-object doc-function">


<h3 id="streampipes.function_zoo.river_function.RiverFunction.onEvent" class="doc doc-heading">
<code class="highlight language-python"><span class="n">onEvent</span><span class="p">(</span><span class="n">event</span><span class="p">,</span> <span class="n">streamId</span><span class="p">)</span></code>

<a href="#streampipes.function_zoo.river_function.RiverFunction.onEvent" class="headerlink" title="Permanent link">&para;</a></h3>


  <div class="doc doc-contents ">
  
      <p>Trains the model with the incoming events and sends the prediction back to StreamPipes.</p>

  </div>

</div>

<div class="doc doc-object doc-function">


<h3 id="streampipes.function_zoo.river_function.RiverFunction.onServiceStarted" class="doc doc-heading">
<code class="highlight language-python"><span class="n">onServiceStarted</span><span class="p">(</span><span class="n">context</span><span class="p">)</span></code>

<a href="#streampipes.function_zoo.river_function.RiverFunction.onServiceStarted" class="headerlink" title="Permanent link">&para;</a></h3>


  <div class="doc doc-contents ">
  
      <p>Executes the <code>on_start</code> function.</p>

  </div>

</div>

<div class="doc doc-object doc-function">


<h3 id="streampipes.function_zoo.river_function.RiverFunction.onServiceStopped" class="doc doc-heading">
<code class="highlight language-python"><span class="n">onServiceStopped</span><span class="p">()</span></code>

<a href="#streampipes.function_zoo.river_function.RiverFunction.onServiceStopped" class="headerlink" title="Permanent link">&para;</a></h3>


  <div class="doc doc-contents ">
  
      <p>Executes the <code>on_stop</code> function.</p>

  </div>

</div>

<div class="doc doc-object doc-function">


<h3 id="streampipes.function_zoo.river_function.RiverFunction.requiredStreamIds" class="doc doc-heading">
<code class="highlight language-python"><span class="n">requiredStreamIds</span><span class="p">()</span></code>

<a href="#streampipes.function_zoo.river_function.RiverFunction.requiredStreamIds" class="headerlink" title="Permanent link">&para;</a></h3>


  <div class="doc doc-contents ">
  
      <p>Returns the the stream ids.</p>

  </div>

</div>


  </div>

  </div>

</div>


  </div>

  </div>

</div>


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