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<h1>🏡 Home</h1>
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<p><img alt="StreamPipes Logo with Python" src="img/streampipes-python.png#only-light" />
<img alt="StreamPipes Logo with Python" src="img/streampipes-python-dark.png#only-dark" /></p>
<h4 align="center"><a href="https://github.com/apache/streampipes">StreamPipes</a> is a self-service (Industrial) IoT toolbox to enable non-technical users to connect, analyze and explore IoT data streams.</h4>
<p><br></p>
<div class="admonition danger">
<p class="admonition-title">Dependency issue with StreamPipes Python 0.92.0</p>
<p>In StreamPipes Python <code>0.92.0</code> there is a problem with the required dependencies.<br>
Pydantic has recently released the new version <code>2.0</code> with many exciting improvements, but also some breaking changes.
Unfortunately, we didn't limit our requirements strictly enough, so yydantic <code>2.0</code> is installed together with streampipes, which is not (yet) compatible.<br>
To fix this bug, simply run the following command after installing streampipes, or adjust your dependencies accordingly:</p>
<div class="language-python highlight"><pre><span></span><code><span class="n">pip</span> <span class="n">install</span> <span class="s2">&quot;pydantic&lt;2.0&quot;</span> <span class="s2">&quot;pydantic_core&lt;2.0&quot;</span>
</code></pre></div>
</div>
<p><br></p>
<h3 align="center">Apache StreamPipes for Python 🐍</h3>
<p align="center"> Apache StreamPipes meets Python! We are working highly motivated on a Python library to interact with StreamPipes.
In this way, we would like to unite the power of StreamPipes to easily connect to and read from different data sources, especially in the IoT domain,
and the amazing universe of data analytics libraries in Python. </p>
<hr />
<p><br></p>
<div class="admonition warning">
<p class="admonition-title">StreamPipes Python is in beta</p>
<p>The current version of this Python library is still a beta version.<br>
This means that it is still heavily under development, which may result in frequent and extensive API changes, unstable behavior, etc.</p>
</div>
<hr />
<h2 id="quickstart">⚡️ Quickstart<a class="headerlink" href="#quickstart" title="Permanent link">&para;</a></h2>
<p>As a quick example, we demonstrate how to set up and configure a StreamPipes client.
In addition, we will get the available data lake measures out of StreamPipes.</p>
<p><div class="language-python highlight"><pre><span></span><code><span class="kn">from</span> <span class="nn">streampipes.client</span> <span class="kn">import</span> <span class="n">StreamPipesClient</span>
<span class="kn">from</span> <span class="nn">streampipes.client.config</span> <span class="kn">import</span> <span class="n">StreamPipesClientConfig</span>
<span class="kn">from</span> <span class="nn">streampipes.client.credential_provider</span> <span class="kn">import</span> <span class="n">StreamPipesApiKeyCredentials</span>
<span class="n">config</span> <span class="o">=</span> <span class="n">StreamPipesClientConfig</span><span class="p">(</span>
<span class="n">credential_provider</span> <span class="o">=</span> <span class="n">StreamPipesApiKeyCredentials</span><span class="p">(</span>
<span class="n">username</span> <span class="o">=</span> <span class="s2">&quot;test@streampipes.apache.org&quot;</span><span class="p">,</span>
<span class="n">api_key</span> <span class="o">=</span> <span class="s2">&quot;DEMO-KEY&quot;</span><span class="p">,</span>
<span class="p">),</span>
<span class="n">host_address</span> <span class="o">=</span> <span class="s2">&quot;localhost&quot;</span><span class="p">,</span>
<span class="n">https_disabled</span> <span class="o">=</span> <span class="kc">True</span><span class="p">,</span>
<span class="n">port</span> <span class="o">=</span> <span class="mi">80</span>
<span class="p">)</span>
<span class="n">client</span> <span class="o">=</span> <span class="n">StreamPipesClient</span><span class="p">(</span><span class="n">client_config</span><span class="o">=</span><span class="n">config</span><span class="p">)</span>
<span class="c1"># get all available datat lake measures</span>
<span class="n">measures</span> <span class="o">=</span> <span class="n">client</span><span class="o">.</span><span class="n">dataLakeMeasureApi</span><span class="o">.</span><span class="n">all</span><span class="p">()</span>
<span class="c1"># get amount of retrieved measures</span>
<span class="nb">len</span><span class="p">(</span><span class="n">measures</span><span class="p">)</span>
</code></pre></div>
Output:
<div class="language-text highlight"><pre><span></span><code>1
</code></pre></div>
<br></p>
<div class="language-text highlight"><pre><span></span><code># inspect the data lake measures as pandas dataframe
measures.to_pandas()
</code></pre></div>
<p>Output:
<div class="language-text highlight"><pre><span></span><code>measure_name timestamp_field ... pipeline_is_running num_event_properties
0 test s0::timestamp ... False 2
[1 rows x 6 columns]
</code></pre></div>
<br>
Alternatively, you can provide your credentials via environment variables.
Simply define your credential provider as follows:</p>
<p><div class="language-python highlight"><pre><span></span><code><span class="kn">from</span> <span class="nn">streampipes.client.credential_provider</span> <span class="kn">import</span> <span class="n">StreamPipesApiKeyCredentials</span>
<span class="n">StreamPipesApiKeyCredentials</span><span class="p">()</span>
</code></pre></div>
This requires to set the following environment variables: <code>SP_API_KEY</code> and <code>SP_USERNAME</code>
<br></p>
<p><code>username</code> is always the username that is used to log in into StreamPipes. <br></p>
<details class="tip">
<summary>How to get your StreamPipes API key</summary>
<p>The <code>api_key</code> can be generated within the UI as demonstrated below:
<br></p>
<p><img alt="Howto API Key" src="img/how-to-get-api-key.gif" /></p>
</details>
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