Getting Airflow

The easiest way to install the latest stable version of Airflow is with pip:

pip install apache-airflow

You can also install Airflow with support for extra features like s3 or postgres:

pip install "apache-airflow[s3, postgres]"


GPL dependency

One of the dependencies of Apache Airflow by default pulls in a GPL library (‘unidecode’). In case this is a concern you can force a non GPL library by issuing export SLUGIFY_USES_TEXT_UNIDECODE=yes and then proceed with the normal installation. Please note that this needs to be specified at every upgrade. Also note that if unidecode is already present on the system the dependency will still be used.

Extra Packages

The apache-airflow PyPI basic package only installs what’s needed to get started. Subpackages can be installed depending on what will be useful in your environment. For instance, if you don’t need connectivity with Postgres, you won’t have to go through the trouble of installing the postgres-devel yum package, or whatever equivalent applies on the distribution you are using.

Behind the scenes, Airflow does conditional imports of operators that require these extra dependencies.

Here’s the list of the subpackages and what they enable:

subpackage install command enables
all pip install apache-airflow[all] All Airflow features known to man
all_dbs pip install apache-airflow[all_dbs] All databases integrations
async pip install apache-airflow[async] Async worker classes for gunicorn
devel pip install apache-airflow[devel] Minimum dev tools requirements
devel_hadoop pip install apache-airflow[devel_hadoop] Airflow + dependencies on the Hadoop stack
celery pip install apache-airflow[celery] CeleryExecutor
crypto pip install apache-airflow[crypto] Encrypt connection passwords in metadata db
druid pip install apache-airflow[druid] related operators & hooks
gcp_api pip install apache-airflow[gcp_api] Google Cloud Platform hooks and operators (using google-api-python-client)
jdbc pip install apache-airflow[jdbc] JDBC hooks and operators
hdfs pip install apache-airflow[hdfs] HDFS hooks and operators
hive pip install apache-airflow[hive] All Hive related operators
kerberos pip install apache-airflow[kerberos] kerberos integration for kerberized hadoop
ldap pip install apache-airflow[ldap] ldap authentication for users
mssql pip install apache-airflow[mssql] Microsoft SQL operators and hook, support as an Airflow backend
mysql pip install apache-airflow[mysql] MySQL operators and hook, support as an Airflow backend. The version of MySQL server has to be 5.6.4+. The exact version upper bound depends on version of mysqlclient package. For example, mysqlclient 1.3.12 can only be used with MySQL server 5.6.4 through 5.7.
password pip install apache-airflow[password] Password Authentication for users
postgres pip install apache-airflow[postgres] Postgres operators and hook, support as an Airflow backend
qds pip install apache-airflow[qds] Enable QDS (qubole data services) support
rabbitmq pip install apache-airflow[rabbitmq] Rabbitmq support as a Celery backend
s3 pip install apache-airflow[s3] S3KeySensor, S3PrefixSensor
samba pip install apache-airflow[samba] Hive2SambaOperator
slack pip install apache-airflow[slack] SlackAPIPostOperator
vertica pip install apache-airflow[vertica] Vertica hook support as an Airflow backend
cloudant pip install apache-airflow[cloudant] Cloudant hook
redis pip install apache-airflow[redis] Redis hooks and sensors

Initiating Airflow Database

Airflow requires a database to be initiated before you can run tasks. If you’re just experimenting and learning Airflow, you can stick with the default SQLite option. If you don’t want to use SQLite, then take a look at Initializing a Database Backend to setup a different database.

After configuration, you’ll need to initialize the database before you can run tasks:

airflow initdb