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Running Airflow locally

This quick start guide will help you bootstrap a Airflow standalone instance on your local machine.

Note

Only pip installation is currently officially supported.

While they are some successes with using other tools like poetry or pip-tools, they do not share the same workflow as pip - especially when it comes to constraint vs. requirements management. Installing via Poetry or pip-tools is not currently supported.

If you wish to install airflow using those tools you should use the constraint files and convert them to appropriate format and workflow that your tool requires.

The installation of Airflow is painless if you are following the instructions below. Airflow uses constraint files to enable reproducible installation, so using pip and constraint files is recommended.

# airflow needs a home, ~/airflow is the default,
# but you can lay foundation somewhere else if you prefer
# (optional)
export AIRFLOW_HOME=~/airflow

AIRFLOW_VERSION=2.1.2
PYTHON_VERSION="$(python --version | cut -d " " -f 2 | cut -d "." -f 1-2)"
# For example: 3.6
CONSTRAINT_URL="https://raw.githubusercontent.com/apache/airflow/constraints-${AIRFLOW_VERSION}/constraints-${PYTHON_VERSION}.txt"
# For example: https://raw.githubusercontent.com/apache/airflow/constraints-2.1.2/constraints-3.6.txt
pip install "apache-airflow==${AIRFLOW_VERSION}" --constraint "${CONSTRAINT_URL}"

# initialize the database
airflow db init

airflow users create \
    --username admin \
    --firstname Peter \
    --lastname Parker \
    --role Admin \
    --email spiderman@superhero.org

# start the web server, default port is 8080
airflow webserver --port 8080

# start the scheduler
# open a new terminal or else run webserver with ``-D`` option to run it as a daemon
airflow scheduler

# visit localhost:8080 in the browser and use the admin account you just
# created to login. Enable the example_bash_operator dag in the home page

Upon running these commands, Airflow will create the $AIRFLOW_HOME folder and create the “airflow.cfg” file with defaults that will get you going fast. You can inspect the file either in $AIRFLOW_HOME/airflow.cfg, or through the UI in the Admin->Configuration menu. The PID file for the webserver will be stored in $AIRFLOW_HOME/airflow-webserver.pid or in /run/airflow/webserver.pid if started by systemd.

Out of the box, Airflow uses a SQLite database, which you should outgrow fairly quickly since no parallelization is possible using this database backend. It works in conjunction with the SequentialExecutor which will only run task instances sequentially. While this is very limiting, it allows you to get up and running quickly and take a tour of the UI and the command line utilities.

Here are a few commands that will trigger a few task instances. You should be able to see the status of the jobs change in the example_bash_operator DAG as you run the commands below.

# run your first task instance
airflow tasks run example_bash_operator runme_0 2015-01-01
# run a backfill over 2 days
airflow dags backfill example_bash_operator \
    --start-date 2015-01-01 \
    --end-date 2015-01-02

What’s Next?

From this point, you can head to the Tutorial section for further examples or the How-to Guides section if you’re ready to get your hands dirty.

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