python airflow tutorial
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apache airflow is an open-source platform to programmatically author, schedule, and monitor workflows. it allows you to define workflows as directed acyclic graphs (dags) and execute them on a schedule or trigger them in response to events.
in this tutorial, we'll cover the basics of apache airflow and walk through the process of creating a simple dag with a code example.
before you begin, make sure you have python installed on your machine. you can install apache airflow using pip. open a terminal and run:
airflow requires a database to store metadata. initialize the database by running the following commands:
this command creates the necessary tables in the database for airflow to store metadata.
start the airflow web server by running the following command:
visit http://localhost:8080 in your web browser to access the airflow web ui.
open a new terminal and start the airflow scheduler:
the scheduler will start processing the dags based on the defined schedule intervals.
back in the airflow web ui, you should see your simple_dag. click on it, and you'll see the "trigger dag" button. click on it to manually trigger the dag.
you can also use the following command to trigger the dag from the terminal:
check the airflow web ui to view the status of
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