Image build arguments reference

The following build arguments (--build-arg in docker build command) can be used for production images. Those arguments are used when you want to customize the image. You can see some examples of it in Building from PyPI packages.

Basic arguments

Those are the most common arguments that you use when you want to build a custom image.

Build argument

Default value

Description

PYTHON_BASE_IMAGE

python:3.6-slim-buster

Base python image.

AIRFLOW_VERSION

2.1.4

version of Airflow.

AIRFLOW_EXTRAS

(see Dockerfile)

Default extras with which airflow is installed.

ADDITIONAL_AIRFLOW_EXTRAS

Optional additional extras with which airflow is installed.

AIRFLOW_HOME

/opt/airflow

Airflow’s HOME (that’s where logs and SQLite databases are stored).

AIRFLOW_USER_HOME_DIR

/home/airflow

Home directory of the Airflow user.

AIRFLOW_PIP_VERSION

21.2.4 | PIP version used.

PIP_PROGRESS_BAR

on

Progress bar for PIP installation

AIRFLOW_UID

50000

Airflow user UID.

AIRFLOW_GID

50000

Airflow group GID. Note that writable files/dirs, created on behalf of airflow user are set to the root group (0) to allow arbitrary UID to run the image.

AIRFLOW_CONSTRAINTS_REFERENCE

Reference (branch or tag) from GitHub where constraints file is taken from It can be constraints-main or constraints-2-0 for 2.0.* installation. In case of building specific version you want to point it to specific tag, for example constraints-2.1.4. Auto-detected if empty.

Image optimization options

The main advantage of Customization method of building Airflow image, is that it allows to build highly optimized image because the final image (RUNTIME) might not contain all the dependencies that are needed to build and install all other dependencies (DEV). Those arguments allow to control what is installed in the DEV image and what is installed in RUNTIME one, thus allowing to produce much more optimized images. See Building optimized images. for examples of using those arguments.

Build argument

Default value

Description

UPGRADE_TO_NEWER_DEPENDENCIES

false

If set to true, the dependencies are upgraded to newer versions matching setup.py before installation.

ADDITIONAL_PYTHON_DEPS

Optional python packages to extend the image with some extra dependencies.

DEV_APT_COMMAND

(see Dockerfile)

Dev apt command executed before dev deps are installed in the Build image.

ADDITIONAL_DEV_APT_COMMAND

Additional Dev apt command executed before dev dep are installed in the Build image. Should start with &&.

DEV_APT_DEPS

(see Dockerfile)

Dev APT dependencies installed in the Build image.

ADDITIONAL_DEV_APT_DEPS

Additional apt dev dependencies installed in the Build image.

ADDITIONAL_DEV_APT_ENV

Additional env variables defined when installing dev deps.

RUNTIME_APT_COMMAND

(see Dockerfile)

Runtime apt command executed before deps are installed in the Main image.

ADDITIONAL_RUNTIME_APT_COMMAND

Additional Runtime apt command executed before runtime dep are installed in the Main image. Should start with &&.

RUNTIME_APT_DEPS

(see Dockerfile)

Runtime APT dependencies installed in the Main image.

ADDITIONAL_RUNTIME_APT_DEPS

Additional apt runtime dependencies installed in the Main image.

ADDITIONAL_RUNTIME_APT_ENV

Additional env variables defined when installing runtime deps.

INSTALL_MYSQL_CLIENT

true

Whether MySQL client should be installed The mysql extra is removed from extras if the client is not installed.

Installing Airflow using different methods

Those parameters are useful only if you want to install Airflow using different installation methods than the default (installing from PyPI packages).

This is usually only useful if you have your own fork of Airflow and want to build the images locally from those sources - either locally or directly from GitHub sources. This way you do not need to release your Airflow and Providers via PyPI - they can be installed directly from sources or from GitHub repository. Another option of installation is to build Airflow from previously prepared binary Python packages which might be useful if you need to build Airflow in environments that require high levels of security.

You can see some examples of those in:

Build argument

Default value

Description

AIRFLOW_INSTALLATION_METHOD

apache-airflow

Installation method of Apache Airflow. apache-airflow for installation from PyPI. It can be GitHub repository URL including branch or tag to install from that repository or "." to install from local sources. Installing from sources requires appropriate values of the AIRFLOW_SOURCES_FROM and AIRFLOW_SOURCES_TO variables (see below)

AIRFLOW_SOURCES_FROM

empty

Sources of Airflow. Set it to "." when you install Airflow from local sources

AIRFLOW_SOURCES_TO

/empty

Target for Airflow sources. Set to "/opt/airflow" when you install Airflow from local sources.

AIRFLOW_VERSION_SPECIFICATION

Optional - might be used for using limit for Airflow version installation - for example <2.0.2 for automated builds.

INSTALL_PROVIDERS_FROM_SOURCES

false

If set to true and image is built from sources, all provider packages are installed from sources rather than from packages. It has no effect when installing from PyPI or GitHub repo.

AIRFLOW_CONSTRAINTS_LOCATION

If not empty, it will override the source of the constraints with the specified URL or file. Note that the file has to be in docker context so it's best to place such file in one of the folders included in .dockerignore file.

INSTALL_FROM_DOCKER_CONTEXT_FILES

false

If set to true, Airflow, providers and all dependencies are installed from from locally built/downloaded .whl and .tar.gz files placed in the docker-context-files. In certain corporate environments, this is required to install airflow from such pre-vetted packages rather than from PyPI. For this to work, also set INSTALL_FROM_PYPI. Note that packages starting with apache?airflow glob are treated differently than other packages. All apache?airflow packages are installed with dependencies limited by airflow constraints. All other packages are installed without dependencies 'as-is'. If you wish to install airflow via 'pip download' with all dependencies downloaded, you have to rename the apache airflow and provider packages to not start with apache?airflow glob.

Pre-caching PIP dependencies

When image is build from PIP, by default pre-caching of PIP dependencies is used. This is in order to speed-up incremental builds during development. When pre-cached PIP dependencies are used and setup.py or setup.cfg changes, the PIP dependencies are already pre-installed, thus resulting in much faster image rebuild. This is purely an optimization of time needed to build the images and should be disabled if you want to install Airflow from docker context files.

Build argument

Default value

Description

AIRFLOW_BRANCH

main

the branch from which PIP dependencies are pre-installed initially.

AIRFLOW_REPO

apache/airflow

the repository from which PIP dependencies are pre-installed.

AIRFLOW_PRE_CACHED_PIP_PACKAGES

false

Allows to pre-cache airflow PIP packages from the GitHub of Apache Airflow This allows to optimize iterations for Image builds and speeds up CI builds.

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