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<h1 class="title toc-ignore">Workflow</h1>
<h4 class="author">Paul Rougieux</h4>
<h4 class="date">03 October, 2024</h4>
</div>
<div id="apache-airflow" class="section level1">
<h1>Apache Airflow</h1>
<ul>
<li>Production deployment <a
href="https://airflow.apache.org/docs/apache-airflow/stable/administration-and-deployment/production-deployment.html"
class="uri">https://airflow.apache.org/docs/apache-airflow/stable/administration-and-deployment/production-deployment.html</a></li>
</ul>
</div>
<div id="tasks" class="section level1">
<h1>Tasks</h1>
<ul>
<li><p><a
href="https://airflow.apache.org/docs/apache-airflow/stable/core-concepts/tasks.html"
class="uri">https://airflow.apache.org/docs/apache-airflow/stable/core-concepts/tasks.html</a></p>
<blockquote>
<p>“Ideally, a task should flow from none, to scheduled, to queued, to
running, and finally to success.”</p>
</blockquote>
<ul>
<li>See more possible states such as upstream_failed or up_for_retry on
the tasks help page.</li>
</ul>
<blockquote>
<p>There are two ways of declaring dependencies - using the >> and
<< (bitshift) operators:</p>
</blockquote>
<pre><code> first_task >> second_task >> [third_task, fourth_task]</code></pre>
<blockquote>
<p>OR THE more explicit set_upstream and set_downstream methods:</p>
</blockquote>
<pre><code> first_task.set_downstream(second_task)
third_task.set_upstream(second_task)</code></pre>
<blockquote>
<p>These both do exactly the same thing, but in general we recommend you
use the bitshift operators, as they are easier to read in most
cases.</p>
</blockquote>
<blockquote>
<p>By default, a Task will run when all of its upstream (parent) tasks
have succeeded, but there are many ways of modifying this behaviour to
add branching, to only wait for some upstream tasks, or to change
behaviour based on where the current run is in history. For more, see
Control Flow.</p>
</blockquote></li>
</ul>
<div id="dags" class="section level2">
<h2>DAGs</h2>
<ul>
<li><p><a
href="https://airflow.apache.org/docs/apache-airflow/stable/core-concepts/dags.html#concepts-control-flow"
class="uri">https://airflow.apache.org/docs/apache-airflow/stable/core-concepts/dags.html#concepts-control-flow</a></p>
<blockquote>
<p>“DAGs are nothing without Tasks to run, and those will usually come
in the form of either Operators, Sensors or TaskFlow.”</p>
</blockquote></li>
</ul>
</div>
<div id="xcoms" class="section level2">
<h2>XComs</h2>
<p>Tasks can communication to each other with <a
href="https://airflow.apache.org/docs/apache-airflow/stable/core-concepts/xcoms.html">XComs</a></p>
<pre><code>> "An XCom is identified by a key (essentially its name), as well as the
> task_id and dag_id it came from. They can have any (serializable) value,
> but they are only designed for small amounts of data; do not use them to
> pass around large values, like dataframes."</code></pre>
</div>
</div>
<div id="uses-in-the-wild" class="section level1">
<h1>Uses in the wild</h1>
<p><a href="https://github.com/apache/airflow/blob/main/INTHEWILD.md"
class="uri">https://github.com/apache/airflow/blob/main/INTHEWILD.md</a></p>
<ul>
<li><p>A user from <a href="https://climate.com/"
class="uri">https://climate.com/</a> is using Apache Airflow in digital
farming.</p></li>
<li><p>Instacart, a digital shoping cart seems to be using at as
well.</p></li>
</ul>
</div>
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