title: Is there a simple way to skip an entire DAG run in Airflow but still allow future runs?
body: <p>I currently have a DAG that runs every day at noon. I would now like it to run every Friday and the 10th of each month in order to save myself some costs, but still have it scheduled to run daily so that I can easily go back and run the dag on any day. (Reasoning behind this is sometimes I need the data produced by this dag on a specific day rather than on the 10th and every Friday, but I won't know ahead of time when this is needed).</p>
  
  <p>One thought that I had was to use a BranchPythonOperator that checked if the criteria was met and if so would trigger all the tasks that are needed to start, otherwise it triggers a dummy task and everything else is skipped.  The main issue with this is this DAG is enormous and contains many tasks spread across different files, so I'm struggling to make sure everything depends on this BranchPythonOperator task. (One question about this, if I just make the BranchPythonOperator standalone, not depending on or having anything depend on it, will returning the names of the tasks still work?)</p>
  
  <p>I figured there must be an easier way to just skip the entire DAG run if a criteria is not met without preventing me from running on that date in the future.</p>
  
  <p>Edited with example:</p>
  
  <pre><code>partition_sensor_1 --&gt;
  partition_sensor_2 --&gt;
  .                         first_dag_task
  .
  .
  partition_sensor_15 --&gt;
  
  </code></pre>
  
  <p>So in this example, I would like to make sure all these partition sensors and the rest of the DAG is skipped. Would I have to list each partition sensor as being dependent on the Branch python operator?  The way these partition sensors are set up they are often created in different files, so it is not easy to set them dependent on the Branching operator.  Hope that makes sense</p>