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<h1>Resource</h1>
<div class="doc doc-object doc-module">
<a id="streampipes.model.resource.resource"></a>
<div class="doc doc-contents first">
<p>General and abstract implementation for a resource.</p>
<p>A resource defines the data model that is used by a resource container (<code>model.container.resourceContainer</code>).</p>
<div class="doc doc-children">
<div class="doc doc-object doc-class">
<h2 id="streampipes.model.resource.resource.Resource" class="doc doc-heading">
<code>Resource</code>
<a href="#streampipes.model.resource.resource.Resource" class="headerlink" title="Permanent link">&para;</a></h2>
<div class="doc doc-contents ">
<p class="doc doc-class-bases">
Bases: <code><span title="abc.ABC">ABC</span></code>, <code><a class="autorefs autorefs-internal" title="streampipes.model.common.BasicModel" href="../../common/#streampipes.model.common.BasicModel">BasicModel</a></code></p>
<p>General and abstract implementation for a resource.</p>
<p>A resource defines the data model used by a resource container (<code>model.container.resourceContainer</code>).
It inherits from Pydantic's BaseModel to get all its superpowers,
which are used to parse, validate the API response and to easily switch between
the Python representation (both serialized and deserialized) and Java representation (serialized only).</p>
<div class="doc doc-children">
<div class="doc doc-object doc-function">
<h3 id="streampipes.model.resource.resource.Resource.convert_to_pandas_representation" class="doc doc-heading">
<code class="highlight language-python"><span class="n">convert_to_pandas_representation</span><span class="p">()</span></code>
<span class="doc doc-labels">
<small class="doc doc-label doc-label-abstractmethod"><code>abstractmethod</code></small>
</span>
<a href="#streampipes.model.resource.resource.Resource.convert_to_pandas_representation" class="headerlink" title="Permanent link">&para;</a></h3>
<div class="doc doc-contents ">
<p>Returns a dictionary representation to be used when creating a pandas Dataframe.</p>
<table>
<thead>
<tr>
<th><b>RETURNS</b></th>
<th><b>DESCRIPTION</b></th>
</tr>
</thead>
<tbody>
<tr>
<td>
<code>pandas_repr</code>
</td>
<td class="doc-returns-details">
<div class="doc-md-description">
<p>Pandas representation of the resource as a dictionary, which is then used by the respource container
to create a data frame from a collection of resources.</p>
</div>
<p>
<span class="doc-returns-annotation">
<b>TYPE:</b>
<code><span title="typing.Dict">Dict</span>[str, Any]</code>
</span>
</p>
</td>
</tr>
</tbody>
</table>
</div>
</div>
<div class="doc doc-object doc-function">
<h3 id="streampipes.model.resource.resource.Resource.to_dict" class="doc doc-heading">
<code class="highlight language-python"><span class="n">to_dict</span><span class="p">(</span><span class="n">use_source_names</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span></code>
<a href="#streampipes.model.resource.resource.Resource.to_dict" class="headerlink" title="Permanent link">&para;</a></h3>
<div class="doc doc-contents ">
<p>Returns the resource in dictionary representation.</p>
<table>
<thead>
<tr>
<th><b>PARAMETER</b></th>
<th><b> DESCRIPTION</b></th>
</tr>
</thead>
<tbody>
<tr>
<td><code>use_source_names</code></td>
<td class="doc-param-details">
<div class="doc-md-description">
<p>Indicates if the dictionary keys are in python representation or
equally named to the StreamPipes backend</p>
</div>
<p>
<span class="doc-param-default">
<b>DEFAULT:</b>
<code>True</code>
</span>
</p>
</td>
</tr>
</tbody>
</table>
<table>
<thead>
<tr>
<th><b>RETURNS</b></th>
<th><b>DESCRIPTION</b></th>
</tr>
</thead>
<tbody>
<tr>
<td>
<code>resource</code>
</td>
<td class="doc-returns-details">
<div class="doc-md-description">
<p>The resource as dictionary representation</p>
</div>
<p>
<span class="doc-returns-annotation">
<b>TYPE:</b>
<code><span title="typing.Dict">Dict</span>[str, Any]</code>
</span>
</p>
</td>
</tr>
</tbody>
</table>
</div>
</div>
</div>
</div>
</div>
</div>
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