Installation

Getting Airflow

Airflow is published as apache-airflow package in PyPI. Installing it however might be sometimes tricky because Airflow is a bit of both a library and application. Libraries usually keep their dependencies open and applications usually pin them, but we should do neither and both at the same time. We decided to keep our dependencies as open as possible (in setup.py) so users can install different version of libraries if needed. This means that from time to time plain pip install apache-airflow will not work or will produce unusable Airflow installation.

In order to have repeatable installation, however, starting from Airflow 1.10.10 and updated in Airflow 1.10.12 we also keep a set of “known-to-be-working” constraint files in the constraints-master and constraints-1-10 orphan branches. Those “known-to-be-working” constraints are per major/minor python version. You can use them as constraint files when installing Airflow from PyPI. Note that you have to specify correct Airflow version and python versions in the URL.

Prerequisites

On Debian based Linux OS:

sudo apt-get update
sudo apt-get install build-essential
  1. Installing just Airflow

AIRFLOW_VERSION=1.10.15
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-${PYTHON_VERSION}.txt"
# For example: https://raw.githubusercontent.com/apache/airflow/constraints-1.10.15/constraints-3.6.txt
pip install "apache-airflow==${AIRFLOW_VERSION}" --constraint "${CONSTRAINT_URL}"

Note

On November 2020, new version of PIP (20.3) has been released with a new, 2020 resolver. This resolver does not yet work with Apache Airflow and might leads to errors in installation - depends on your choice of extras. In order to install Airflow you need to either downgrade pip to version 20.2.4 pip upgrade --pip==20.2.4 or, in case you use Pip 20.3, you need to add option --use-deprecated legacy-resolver to your pip install command.

  1. Installing with extras (for example postgres, google)

AIRFLOW_VERSION=1.10.15
PYTHON_VERSION="$(python --version | cut -d " " -f 2 | cut -d "." -f 1-2)"
CONSTRAINT_URL="https://raw.githubusercontent.com/apache/airflow/constraints-${AIRFLOW_VERSION}/constraints-${PYTHON_VERSION}.txt"
pip install "apache-airflow[postgres,google]==${AIRFLOW_VERSION}" --constraint "${CONSTRAINT_URL}"

Note

On November 2020, new version of PIP (20.3) has been released with a new, 2020 resolver. This resolver does not yet work with Apache Airflow and might leads to errors in installation - depends on your choice of extras. In order to install Airflow you need to either downgrade pip to version 20.2.4 pip upgrade --pip==20.2.4 or, in case you use Pip 20.3, you need to add option --use-deprecated legacy-resolver to your pip install command.

You need certain system level requirements in order to install Airflow. Those are requirements that are known to be needed for Linux system (Tested on Ubuntu Buster LTS) :

sudo apt-get install -y --no-install-recommends \
        freetds-bin \
        krb5-user \
        ldap-utils \
        libffi6 \
        libsasl2-2 \
        libsasl2-modules \
        libssl1.1 \
        locales  \
        lsb-release \
        sasl2-bin \
        sqlite3 \
        unixodbc

You also need database client packages (Postgres or MySQL) if you want to use those databases.

If the airflow command is not getting recognized (can happen on Windows when using WSL), then ensure that ~/.local/bin is in your PATH environment variable, and add it in if necessary:

PATH=$PATH:~/.local/bin

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:

Fundamentals:

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

devel

pip install 'apache-airflow[devel]'

Minimum dev tools requirements

devel_all

pip install 'apache-airflow[devel_all]'

All dev tools requirements

devel_azure

pip install 'apache-airflow[devel_azure]'

Azure development requirements

devel_ci

pip install 'apache-airflow[devel_ci]'

Development requirements used in CI

devel_hadoop

pip install 'apache-airflow[devel_hadoop]'

Airflow + dependencies on the Hadoop stack

doc

pip install 'apache-airflow[doc]'

Packages needed to build docs

password

pip install 'apache-airflow[password]'

Password authentication for users

Apache Software:

subpackage

install command

enables

atlas

pip install 'apache-airflow[apache.atlas]'

Apache Atlas to use Data Lineage feature

cassandra

pip install 'apache-airflow[apache.cassandra]'

Cassandra related operators & hooks

druid

pip install 'apache-airflow[apache.druid]'

Druid related operators & hooks

hdfs

pip install 'apache-airflow[apache.hdfs]'

HDFS hooks and operators

hive

pip install 'apache-airflow[apache.hive]'

All Hive related operators

presto

pip install 'apache-airflow[apache.presto]'

All Presto related operators & hooks

webhdfs

pip install 'apache-airflow[webhdfs]'

HDFS hooks and operators

Services:

subpackage

install command

enables

aws

pip install 'apache-airflow[amazon]'

Amazon Web Services

azure

pip install 'apache-airflow[microsoft.azure]'

Microsoft Azure

azure_blob_storage

pip install 'apache-airflow[azure_blob_storage]'

Microsoft Azure (blob storage)

azure_cosmos

pip install 'apache-airflow[azure_cosmos]'

Microsoft Azure (cosmos)

azure_container_instances

pip install 'apache-airflow[azure_container_instances]'

Microsoft Azure (container instances)

azure_data_lake

pip install 'apache-airflow[azure_data_lake]'

Microsoft Azure (data lake)

azure_secrets

pip install 'apache-airflow[azure_secrets]'

Microsoft Azure (secrets)

azure

pip install 'apache-airflow[microsoft.azure]'

Microsoft Azure

cloudant

pip install 'apache-airflow[cloudant]'

Cloudant hook

databricks

pip install 'apache-airflow[databricks]'

Databricks hooks and operators

datadog

pip install 'apache-airflow[datadog]'

Datadog hooks and sensors

gcp

pip install 'apache-airflow[gcp]'

Google Cloud

github_enterprise

pip install 'apache-airflow[github_enterprise]'

GitHub Enterprise auth backend

google

pip install 'apache-airflow[google]'

Google Cloud (same as gcp)

google_auth

pip install 'apache-airflow[google_auth]'

Google auth backend

hashicorp

pip install 'apache-airflow[hashicorp]'

Hashicorp Services (Vault)

jira

pip install 'apache-airflow[jira]'

Jira hooks and operators

qds

pip install 'apache-airflow[qds]'

Enable QDS (Qubole Data Service) support

salesforce

pip install 'apache-airflow[salesforce]'

Salesforce hook

sendgrid

pip install 'apache-airflow[sendgrid]'

Send email using sendgrid

segment

pip install 'apache-airflow[segment]'

Segment hooks and sensors

sentry

pip install 'apache-airflow[sentry]'

slack

pip install 'apache-airflow[slack]'

airflow.providers.slack.operators.slack.SlackAPIOperator

snowflake

pip install 'apache-airflow[snowflake]'

Snowflake hooks and operators

vertica

pip install 'apache-airflow[vertica]'

Vertica hook support as an Airflow backend

Software:

subpackage

install command

enables

async

pip install 'apache-airflow[async]'

Async worker classes for Gunicorn

celery

pip install 'apache-airflow[celery]'

CeleryExecutor

dask

pip install 'apache-airflow[dask]'

DaskExecutor

docker

pip install 'apache-airflow[docker]'

Docker hooks and operators

elasticsearch

pip install 'apache-airflow[elasticsearch]'

Elasticsearch hooks and Log Handler

kubernetes

pip install 'apache-airflow[cncf.kubernetes]'

Kubernetes Executor and operator

mongo

pip install 'apache-airflow[mongo]'

Mongo hooks and operators

mssql (deprecated)

pip install 'apache-airflow[microsoft.mssql]'

Microsoft SQL Server operators and hook, support as an Airflow backend. Uses pymssql. Will be replaced by subpackage odbc.

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.

oracle

pip install 'apache-airflow[oracle]'

Oracle hooks and operators

pinot

pip install 'apache-airflow[pinot]'

Pinot DB hook

postgres

pip install 'apache-airflow[postgres]'

PostgreSQL operators and hook, support as an Airflow backend

rabbitmq

pip install 'apache-airflow[rabbitmq]'

RabbitMQ support as a Celery backend

redis

pip install 'apache-airflow[redis]'

Redis hooks and sensors

samba

pip install 'apache-airflow[samba]'

airflow.providers.apache.hive.transfers.hive_to_samba.HiveToSambaOperator

statsd

pip install 'apache-airflow[statsd]'

Needed by StatsD metrics

virtualenv

pip install 'apache-airflow[virtualenv]'

Other:

subpackage

install command

enables

cgroups

pip install 'apache-airflow[cgroups]'

Needed To use CgroupTaskRunner

crypto

pip install 'apache-airflow[crypto]'

Cryptography libraries

grpc

pip install 'apache-airflow[grpc]'

Grpc hooks and operators

jdbc

pip install 'apache-airflow[jdbc]'

JDBC hooks and operators

kerberos

pip install 'apache-airflow[kerberos]'

Kerberos integration for Kerberized Hadoop

ldap

pip install 'apache-airflow[ldap]'

LDAP authentication for users

papermill

pip install 'apache-airflow[papermill]'

Papermill hooks and operators

ssh

pip install 'apache-airflow[ssh]'

SSH hooks and Operator

winrm

pip install 'apache-airflow[microsoft.winrm]'

WinRM hooks and operators

Initializing Airflow Database

Airflow requires a database to be initialized 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 db init

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