Airflow Breeze CI Environment
Prerequisites
Using the Airflow Breeze Environment
Using Your Host IDE
Running static checks in Breeze
Running Tests in Breeze
Breeze Command-Line Interface Reference
- Airflow Breeze Syntax
- Convenience Scripts
Troubleshooting
- Fixing File/Directory Ownership

Airflow Breeze CI Environment

Airflow Breeze is an easy-to-use development environment using Docker Compose. The environment is available for local use and is also used in Airflow's CI tests.

We called it Airflow Breeze as It's a Breeze to develop Airflow.

The advantages and disadvantages of using the Breeze environment vs. other ways of testing Airflow are described in CONTRIBUTING.rst.

Here is a short 10-minute video about Airflow Breeze (note that it shows an old version of Breeze. Some of the points in the video are not valid anymore. The video will be updated shortly with more up-to-date version):

Airflow Breeze Simplified Development Workflow

Prerequisites

Docker Community Edition

Version: Install the latest stable Docker Community Edition and add it to the PATH.
Permissions: Configure to run the docker commands directly and not only via root user. Your user should be in the docker group. See Docker installation guide for details.
Disk space: On macOS, increase your available disk space before starting to work with the environment. At least 128 GB of free disk space is recommended. You can also get by with a smaller space but make sure to clean up the Docker disk space periodically. See also Docker for Mac - Space for details on increasing disk space available for Docker on Mac.
Docker problems: Sometimes it is not obvious that space is an issue when you run into a problem with Docker. If you see a weird behaviour, try breeze cleanup-image command. Also see pruning instructions from Docker.

Here is an example configuration with more than 200GB disk space for Docker:

Docker Compose

Version: Install the latest stable Docker Compose and add it to the PATH. See Docker Compose Installation Guide for details.
Permissions: Configure to run the docker-compose command.

Docker in WSL

WSL installation :

WSL Installation Guide for details.
Docker installation :

You should install docker in WSL. follow Docker Installtion Guide only docker-ce without docker-ce-cli containerd.io.
Docker setting :

You should expose Docker daemon,

and set env variable DOCKER_HOST.

echo "export DOCKER_HOST=tcp://localhost:2375" >> ~/.bashrc && source ~/.bashrc

WSL problems : There is a mounting problem in docker because docker could not recognize /mnt/c, /mnt/d driver path. run this command in Windows Version 18.03+ and reboot Windows

printf '[automount]\nroot = /\n options = "metadata"\n' >> /etc/wsl.conf

Docker Images Used by Breeze

For all development tasks, unit tests, integration tests, and static code checks, we use the CI image maintained on the DockerHub in the apache/airflow repository. This Docker image contains a lot of test-related packages (size of ~1GB). Its tag follows the pattern of <BRANCH>-python<PYTHON_MAJOR_MINOR_VERSION>-ci (for example, apache/airflow:master-python3.6-ci or apache/airflow:v1-10-test-python3.6-ci). The image is built using the Dockerfile.ci Dockerfile.

For testing production image, the Production image is used and maintained on the DockerHub in the `apache/airflow repository. This Docker image contains only size-optimised Airflow with selected extras and dependencies. Its tag follows the pattern of <BRANCH>-python<PYTHON_MAJOR_MINOR_VERSION> (for example, apache/airflow:master-python3.6 or apache/airflow:v1-10-test-python3.6).

More information about the images can be found in IMAGES.rst.

By default CI images are used unless --production-image flag is used.

Before you run tests, enter the environment or run local static checks, the necessary local images should be pulled and built from Docker Hub. This happens automatically for the test environment but you need to manually trigger it for static checks as described in Building the images and Pulling the latest images. The static checks will fail and inform what to do if the image is not yet built.

Building the image first time pulls a pre-built version of images from the Docker Hub, which may take some time. But for subsequent source code changes, no wait time is expected. However, changes to sensitive files like setup.py or Dockerfile.ci will trigger a rebuild that may take more time though it is highly optimized to only rebuild what is needed.

In most cases, rebuilding an image requires network connectivity (for example, to download new dependencies). If you work offline and do not want to rebuild the images when needed, you can set the FORCE_ANSWER_TO_QUESTIONS variable to no as described in the Default behaviour for user interaction section.

See the Troubleshooting section for steps you can make to clean the environment.

Getopt and gstat

For Linux, run apt install util-linux coreutils or an equivalent if your system is not Debian-based.
For macOS, install GNU getopt and gstat utilities to get Airflow Breeze running.

Run brew install gnu-getopt coreutils and then follow instructions to link the gnu-getopt version to become the first on the PATH. Make sure to re-login after you make the suggested changes.

Examples:

If you use bash, run this command and re-login:

echo 'export PATH="/usr/local/opt/gnu-getopt/bin:$PATH"' >> ~/.bash_profile
. ~/.bash_profile

If you use zsh, run this command and re-login:

echo 'export PATH="/usr/local/opt/gnu-getopt/bin:$PATH"' >> ~/.zprofile
. ~/.zprofile

Memory

Minimum 4GB RAM is required to run the full Breeze environment.

On macOS, 2GB of RAM are available for your Docker containers by default, but more memory is recommended (4GB should be comfortable). For details see Docker for Mac - Advanced tab.

Airflow Directory Structure inside Docker

When you are in the CI container, the following directories are used:

/opt/airflow - Contains sources of Airflow mounted from the host (AIRFLOW_SOURCES).
/root/airflow - Contains all the "dynamic" Airflow files (AIRFLOW_HOME), such as:
    airflow.db - sqlite database in case sqlite is used;
    dags - folder with non-test dags (test dags are in /opt/airflow/tests/dags);
    logs - logs from Airflow executions;
    unittest.cfg - unit test configuration generated when entering the environment;
    webserver_config.py - webserver configuration generated when running Airflow in the container.

Note that when running in your local environment, the /root/airflow/logs folder is actually mounted from your logs directory in the Airflow sources, so all logs created in the container are automatically visible in the host as well. Every time you enter the container, the logs directory is cleaned so that logs do not accumulate.

When you are in the production container, the following directories are used:

/opt/airflow - Contains sources of Airflow mounted from the host (AIRFLOW_SOURCES).
/root/airflow - Contains all the "dynamic" Airflow files (AIRFLOW_HOME), such as:
    airflow.db - sqlite database in case sqlite is used;
    dags - folder with non-test dags (test dags are in /opt/airflow/tests/dags);
    logs - logs from Airflow executions;
    unittest.cfg - unit test configuration generated when entering the environment;
    webserver_config.py - webserver configuration generated when running Airflow in the container.

Note that when running in your local environment, the /root/airflow/logs folder is actually mounted from your logs directory in the Airflow sources, so all logs created in the container are automatically visible in the host as well. Every time you enter the container, the logs directory is cleaned so that logs do not accumulate.

Using the Airflow Breeze Environment

Airflow Breeze is a bash script serving as a "swiss-army-knife" of Airflow testing. Under the hood it uses other scripts that you can also run manually if you have problem with running the Breeze environment.

Breeze script allows performing the following tasks:

Manage environments - CI (default) or Production - if --production-image flag is specified:

Build docker images with breeze build-image command

Enter interactive shell when no command are specified (default behaviour)

Join running interactive shell with breeze exec command

Start Kind Kubernetes cluster for Kubernetes tests if --start-kind-cluster flag is specified

Stop running interactive environment with breeze stop command

Restart running interactive environment with breeze restart command

Optionally reset database if specified as extra --db-reset flag

Optionally start integrations (separate images) if specified as extra --integration flags (only CI)

Interact with CI environment:

Run test target specified with breeze test-target command

Execute arbitrary command in the test environment with breeze execute-command command

Execute arbitrary docker-compose command with breeze docker-compose command

Run static checks:

Run static checks - either for currently staged change or for all files with breeze static-check or breeze static-check-all-files command

Build documentation:

Build documentation with breeze build-docs command

Set up local development environment:

Setup local virtualenv with breeze setup-virtualenv command

Setup autocomplete for itself with breeze setup-autocomplete command

Note that the below environment interaction is by default with the CI image. If you want to use production image for those commands you need to add --production-image flag.

Entering Breeze CI environment

You enter the Breeze test environment by running the ./breeze script. You can run it with the help command to see the list of available options. See Breeze Command-Line Interface Reference for details.

./breeze

The First time you run Breeze, it pulls and builds a local version of Docker images. It pulls the latest Airflow CI images from Airflow DockerHub and uses them to build your local Docker images. Note that the first run (per python) might take up to 10 minutes on a fast connection to start. Subsequent runs should be much faster.

Once you enter the environment, you are dropped into bash shell of the Airflow container and you can run tests immediately.

You can set up autocomplete for commands and add the checked-out Airflow repository to your PATH to run Breeze without the ./ and from any directory.

When you enter the Breeze environment, automatically an environment file is sourced from files/airflow-breeze-config/variables.env. The files folder from your local sources is automatically mounted to the container under /files path and you can put there any files you want to make available for the Breeze container.

Launching multiple terminals

Often if you want to run full airflow in the Breeze environment you need to launch multiple terminals and run airflow webserver, airflow scheduler, airflow worker in separate terminals.

This can be achieved either via tmux or via exec-ing into the running container from the host. Tmux is installed inside the container and you can launch it with tmux command. Tmux provides you with the capability of creating multiple virtual terminals and multiplex between them. More about tmux can be found at tmux github wiki page . Tmux has several useful shortcuts that allow you to split the terminals, open new tabs etc - it's pretty useful to learn it.

Another - slightly easier - way is to exec into Breeze terminal from the host's terminal. Often you can have multiple terminals in the host (Linux/MacOS/WSL2 on Windows) and you can simply use those terminals to enter the running container. It's as easy as launching breeze exec while you already started the Breeze environment. You will be dropped into bash and environment variables will be read in the same way as when you enter the environment. You can do it multiple times and open as many terminals as you need.

Stopping Interactive environment

After starting up, the environment runs in the background and takes precious memory. You can always stop it via:

./breeze stop

Restarting Breeze environment

You can also restart the environment and enter it via:

./breeze restart

Choosing a Breeze Environment

You can use additional breeze flags to customize your environment. For example, you can specify a Python version to use, backend and a container environment for testing. With Breeze, you can recreate the same environments as we have in matrix builds in Travis CI.

For example, you can choose to run Python 3.6 tests with MySQL as backend and in the Docker environment as follows:

./breeze --python 3.6 --backend mysql

The choices you make are persisted in the ./.build/ cache directory so that next time when you use the breeze script, it could use the values that were used previously. This way you do not have to specify them when you run the script. You can delete the .build/ directory in case you want to restore the default settings.

The defaults when you run the Breeze environment are Python 3.6, Sqlite, and Docker.

Launching Breeze Integrations

When Breeze starts, it can start additional integrations. Those are additional docker containers that are started in the same docker-compose command. Those are required by some of the tests as described in TESTING.rst.

By default Breeze starts only airflow container without any integration enabled. If you selected postgres or mysql backend, the container for the selected backend is also started (but only the one that is selected). You can start the additional integrations by passing --integration flag with appropriate integration name when starting Breeze. You can specify several --integration flags to start more than one integration at a time. Finally you can specify --integration all to start all integrations.

Once integration is started, it will continue to run until the environment is stopped with breeze stop command. or restarted via breeze restart command

Note that running integrations uses significant resources - CPU and memory.

Cleaning the Environment

You may need to clean up your Docker environment occasionally. The images are quite big (1.5GB for both images needed for static code analysis and CI tests) and, if you often rebuild/update them, you may end up with some unused image data.

To clean up the Docker environment:

Stop Breeze with ./breeze stop.
Run the docker system prune command.
Run docker images --all and docker ps --all to verify that your Docker is clean.

Both commands should return an empty list of images and containers respectively.

If you run into disk space errors, consider pruning your Docker images with the docker system prune --all command. You may need to restart the Docker Engine before running this command.

In case of disk space errors on macOS, increase the disk space available for Docker. See Prerequisites for details.

Running Arbitrary Commands in the Breeze Environment

To run other commands/executables inside the Breeze Docker-based environment, use the ./breeze execute-command command. To add arguments, specify them together with the command surrounded with either " or ', or pass them after -- as extra arguments.

./breeze execute-command "ls -la"

./breeze execute-command ls -- --la

Running Docker Compose Commands

To run Docker Compose commands (such as help, pull, etc), use the docker-compose command. To add extra arguments, specify them after -- as extra arguments.

./breeze docker-compose pull -- --ignore-pull-failures

Mounting Local Sources to Breeze

Important sources of Airflow are mounted inside the airflow container that you enter. This means that you can continue editing your changes on the host in your favourite IDE and have them visible in the Docker immediately and ready to test without rebuilding images. You can disable mounting by specifying --skip-mounting-local-sources flag when running Breeze. In this case you will have sources embedded in the container and changes to these sources will not be persistent.

After you run Breeze for the first time, you will have empty directory files in your source code, which will be mapped to /files in your Docker container. You can pass there any files you need to configure and run Docker. They will not be removed between Docker runs.

By default /files/dags folder is mounted from your local <AIRFLOW_SOURCES>/files/dags and this is the directory used by airflow scheduler and webserver to scan dags for. You can use it to test your dags from local sources in Airflow. If you wish to add local DAGs that can be run by Breeze.

Adding/Modifying Dependencies

If you need to change apt dependencies in the Dockerfile.ci, add Python packages in setup.py or add javascript dependencies in package.json, you can either add dependencies temporarily for a single Breeze session or permanently in setup.py, Dockerfile.ci, or package.json files.

Installing Dependencies for a Single Breeze Session

You can install dependencies inside the container using sudo apt install, pip install or yarn install (in airflow/www folder) respectively. This is useful if you want to test something quickly while you are in the container. However, these changes are not retained: they disappear once you exit the container (except for the node.js dependencies if your sources are mounted to the container). Therefore, if you want to retain a new dependency, follow the second option described below.

Adding Dependencies Permanently

You can add dependencies to the Dockerfile.ci, setup.py or package.json and rebuild the image. This should happen automatically if you modify any of these files. After you exit the container and re-run breeze, Breeze detects changes in dependencies, asks you to confirm rebuilding the image and proceeds with rebuilding if you confirm (or skip it if you do not confirm). After rebuilding is done, Breeze drops you to shell. You may also use the build-image command to only rebuild CI image and not to go into shell.

Changing apt Dependencies in the Dockerfile.ci

During development, changing dependencies in apt-get closer to the top of the Dockerfile.ci invalidates cache for most of the image. It takes long time for Breeze to rebuild the image. So, it is a recommended practice to add new dependencies initially closer to the end of the Dockerfile.ci. This way dependencies will be added incrementally.

Before merge, these dependencies should be moved to the appropriate apt-get install command, which is already in the Dockerfile.ci.

Port Forwarding

When you run Airflow Breeze, the following ports are automatically forwarded:

28080 -> forwarded to Airflow webserver -> airflow:8080
25433 -> forwarded to Postgres database -> postgres:5432
23306 -> forwarded to MySQL database -> mysql:3306

You can connect to these ports/databases using:

Webserver: http://127.0.0.1:28080
Postgres: jdbc:postgresql://127.0.0.1:25433/airflow?user=postgres&password=airflow
Mysql: jdbc:mysql://localhost:23306/airflow?user=root

Start the webserver manually with the airflow webserver command if you want to connect to the webserver. You can use tmux to multiply terminals. You may need to create a user prior to running the webserver in order to log in. This can be done with the following command:

airflow users create --role Admin --username admin --password admin --email admin@example.com --firstname foo --lastname bar

For databases, you need to run airflow db reset at least once (or run some tests) after you started Airflow Breeze to get the database/tables created. You can connect to databases with IDE or any other database client:

You can change the used host port numbers by setting appropriate environment variables:

WEBSERVER_HOST_PORT
POSTGRES_HOST_PORT
MYSQL_HOST_PORT

If you set these variables, next time when you enter the environment the new ports should be in effect.

Setting Up Autocompletion

The breeze command comes with a built-in bash/zsh autocomplete option for its options. When you start typing the command, you can use <TAB> to show all the available switches and get autocompletion on typical values of parameters that you can use.

You can set up the autocomplete option automatically by running:

./breeze setup-autocomplete

You get the autocompletion working when you re-enter the shell.

Zsh autocompletion is currently limited to only autocomplete options. Bash autocompletion also completes options values (for example, Python version or static check name).

Setting Defaults for User Interaction

Sometimes during the build, you are asked whether to perform an action, skip it, or quit. This happens when rebuilding or removing an image - actions that take a lot of time and could be potentially destructive.

For automation scripts, you can export one of the three variables to control the default interaction behaviour:

export FORCE_ANSWER_TO_QUESTIONS="yes"

If FORCE_ANSWER_TO_QUESTIONS is set to yes, the images are automatically rebuilt when needed. Images are deleted without asking.

export FORCE_ANSWER_TO_QUESTIONS="no"

If FORCE_ANSWER_TO_QUESTIONS is set to no, the old images are used even if rebuilding is needed. This is useful when you work offline. Deleting images is aborted.

export FORCE_ANSWER_TO_QUESTIONS="quit"

If FORCE_ANSWER_TO_QUESTIONS is set to quit, the whole script is aborted. Deleting images is aborted.

If more than one variable is set, yes takes precedence over no, which takes precedence over quit.

Building the Documentation

To build documentation in Breeze, use the build-docs command:

./breeze build-docs

Results of the build can be found in the docs/_build folder.

Often errors during documentation generation come from the docstrings of auto-api generated classes. During the docs building auto-api generated files are stored in the docs/_api folder. This helps you easily identify the location the problems with documentation originated from.

Using Your Host IDE

You can set up your host IDE (for example, IntelliJ's PyCharm/Idea) to work with Breeze and benefit from all the features provided by your IDE, such as local and remote debugging, autocompletion, documentation support, etc.

To use your host IDE with Breeze:

Create a local virtual environment as follows:

mkvirtualenv <ENV_NAME> --python=python<VERSION>

You can use any of the following wrappers to create and manage your virtual environemnts: pyenv, pyenv-virtualenv, or virtualenvwrapper.

Ideally, you should have virtualenvs for all Python versions supported by Airflow (3.5, 3.6, 3.7) and switch between them with the workon command.
Use the workon command to enter the Breeze environment.
Initialize the created local virtualenv:

./breeze initialize-local-virtualenv
Select the virtualenv you created as the project's default virtualenv in your IDE.

Note that you can also use the local virtualenv for Airflow development without Breeze. This is a lightweight solution that has its own limitations.

More details on using the local virtualenv are available in the LOCAL_VIRTUALENV.rst.

Running static checks in Breeze

The Breeze environment is also used to run some of the static checks as described in STATIC_CODE_CHECKS.rst.

Running Tests in Breeze

As soon as you enter the Breeze environment, you can run Airflow unit tests via the pytest command.

For supported CI test suites, types of unit tests, and other tests, see TESTING.rst.

Breeze Command-Line Interface Reference

Airflow Breeze Syntax

This is the current syntax for ./breeze:

####################################################################################################

Usage: breeze [FLAGS] [COMMAND] -- <EXTRA_ARGS>

By default the script enters IT environment and drops you to bash shell, but you can choose one
of the commands to run specific actions instead. Add --help after each command to see details:

Commands without arguments:

shell [Default] Enters interactive shell in the container
build-docs Builds documentation in the container
build-image Builds CI or Production docker image
cleanup-image Cleans up the container image created
exec Execs into running breeze container in new terminal
generate-requirements Generates pinned requirements for pip dependencies
initialize-local-virtualenv Initializes local virtualenv
setup-autocomplete Sets up autocomplete for breeze
stop Stops the docker-compose evironment
restart Stops the docker-compose evironment including DB cleanup
toggle-suppress-cheatsheet Toggles on/off cheatsheet
toggle-suppress-asciiart Toggles on/off asciiart

Commands with arguments:

docker-compose <ARG> Executes specified docker-compose command
execute-command <ARG> Executes specified command in the container
static-check <ARG> Performs selected static check for changed files
static-check-all-files <ARG> Performs selected static check for all files
test-target <ARG> Runs selected test target in the container

Help commands:

flags Shows all breeze's flags
help Shows this help message
help-all Shows detailed help for all commands and flags

####################################################################################################

Detailed usage

####################################################################################################

breeze [FLAGS] shell -- <EXTRA_ARGS>

This is default subcommand if no subcommand is used.

Enters interactive shell where you can run all tests, start airflow webserver, scheduler,
workers, interact with the database, run DAGs etc. It is the default command if no command
is selected. The shell is executed in the container and in case integrations are chosen,
the integrations will be started as separated docker containers - under the docker-compose
supervision. Local sources are by default mounted to within the container so you can edit
them locally and run tests immediately in the container. Several folders ('files', 'dist')
are also mounted so that you can exchange files between the host and container.

The 'files/airflow-breeze-config/variables.env' file can contain additional variables
and setup. This file is automatically sourced when you enter the container. Database
and webserver ports are forwarded to appropriate database/webserver so that you can
connect to it from your host environment.
****************************************************************************************************
breeze [FLAGS] build-docs -- <EXTRA_ARGS>

Builds airflow documentation. The documentation is build inside docker container - to
maintain the same build environment for everyone. Appropriate sources are mapped from
the host to the container so that latest sources are used. The folders where documentation
is generated ('docs/build') are also mounted to the container - this way results of
the documentation build is available in the host.
****************************************************************************************************
breeze [FLAGS] build-image -- <EXTRA_ARGS>

Builds docker image (CI or production) without entering the container. You can pass
additional options to this command, such as '--force-build-image',
'--force-pull-image' '--python' '--use-local-cache'' in order to modify build behaviour.
You can also pass '--production-image' flag to build production image rather than CI image.
****************************************************************************************************
breeze [FLAGS] cleanup-image -- <EXTRA_ARGS>

Removes the breeze-related images created in your local docker image cache. This will
not reclaim space in docker cache. You need to 'docker system prune' (optionally
with --all) to reclaim that space.
****************************************************************************************************
breeze [FLAGS] exec -- <EXTRA_ARGS>

Execs into interactive shell to an already running container. The container mus be started
already by breeze shell command. If you are not familiar with tmux, this is the best
way to run multiple processes in the same container at the same time for example scheduler,
webserver, workers, database console and interactive terminal.
****************************************************************************************************
breeze [FLAGS] generate-requirements -- <EXTRA_ARGS>

Generates pinned requirements from setup.py. Those requirements are generated in requirements
directory - separately for different python version. Those requirements are used to run
CI builds as well as run repeatable production image builds. You can use those requirements
to predictably install released airflow versions. You should run it always after you update
setup.py.
****************************************************************************************************
breeze [FLAGS] initialize-local-virtualenv -- <EXTRA_ARGS>

Initializes locally created virtualenv installing all dependencies of Airflow
taking into account the frozen requirements from requirements folder.
This local virtualenv can be used to aid autocompletion and IDE support as
well as run unit tests directly from the IDE. You need to have virtualenv
activated before running this command.
****************************************************************************************************
breeze [FLAGS] setup-autocomplete -- <EXTRA_ARGS>

Sets up autocomplete for breeze commands. Once you do it you need to re-enter the bash
shell and when typing breeze command <TAB> will provide autocomplete for
parameters and values.
****************************************************************************************************
breeze [FLAGS] stop -- <EXTRA_ARGS>

Brings down running docker compose environment. When you start the environment, the docker
containers will continue running so that startup time is shorter. But they take quite a lot of
memory and CPU. This command stops all running containers from the environment.
****************************************************************************************************
breeze [FLAGS] restart -- <EXTRA_ARGS>

Restarts running docker compose environment. When you restart the environment, the docker
containers will be restarted. That includes cleaning up the databases. This is
especially useful if you switch between different versions of airflow.
****************************************************************************************************
breeze [FLAGS] toggle-suppress-cheatsheet -- <EXTRA_ARGS>

Toggles on/off cheatsheet displayed before starting bash shell.
****************************************************************************************************
breeze [FLAGS] toggle-suppress-asciiart -- <EXTRA_ARGS>

Toggles on/off asciiart displayed before starting bash shell.
****************************************************************************************************
breeze [FLAGS] docker-compose -- <EXTRA_ARGS>

Run docker-compose command instead of entering the environment. Use 'help' as command
to see available commands. The <EXTRA_ARGS> passed after -- are treated
as additional options passed to docker-compose. For example

'breeze docker-compose pull -- --ignore-pull-failures'
****************************************************************************************************
breeze [FLAGS] execute-command -- <EXTRA_ARGS>

Run chosen command instead of entering the environment. The command is run using
'bash -c "<command with args>" if you need to pass arguments to your command, you need
to pass them together with command surrounded with " or '. Alternatively you can
pass arguments as <EXTRA_ARGS> passed after --. For example:

'breeze execute-command "ls -la"' or
'breeze execute-command ls -- --la'
****************************************************************************************************
breeze [FLAGS] static-check -- <EXTRA_ARGS>

Run selected static checks for currently changed files. You should specify static check that
you would like to run or 'all' to run all checks. One of:

all all-but-pylint bat-tests check-apache-license check-executables-have-shebangs
check-hooks-apply check-merge-conflict check-xml debug-statements doctoc
detect-private-key end-of-file-fixer flake8 forbid-tabs insert-license
lint-dockerfile mixed-line-ending mypy pylint pylint-test setup-order shellcheck

You can pass extra arguments including options to to the pre-commit framework as
<EXTRA_ARGS> passed after --. For example:

'breeze static-check mypy' or
'breeze static-check mypy -- --files tests/core.py'

You can see all the options by adding --help EXTRA_ARG:

'breeze static-check mypy -- --help'
****************************************************************************************************
breeze [FLAGS] static-check-all-files -- <EXTRA_ARGS>

Run selected static checks for all applicable files. You should specify static check that
you would like to run or 'all' to run all checks. One of:

all all-but-pylint bat-tests check-apache-license check-executables-have-shebangs
check-hooks-apply check-merge-conflict check-xml debug-statements doctoc
detect-private-key end-of-file-fixer flake8 forbid-tabs insert-license
lint-dockerfile mixed-line-ending mypy pylint pylint-test setup-order shellcheck

You can pass extra arguments including options to the pre-commit framework as
<EXTRA_ARGS> passed after --. For example:

'breeze static-check-all-files mypy' or
'breeze static-check-all-files mypy -- --verbose'

You can see all the options by adding --help EXTRA_ARG:

'breeze static-check-all-files mypy -- --help'
****************************************************************************************************
breeze [FLAGS] test-target -- <EXTRA_ARGS>

Run the specified unit test target. There might be multiple
targets specified separated with comas. The <EXTRA_ARGS> passed after -- are treated
as additional options passed to pytest. For example:

'breeze test-target tests/test_core.py -- --logging-level=DEBUG'
****************************************************************************************************
breeze [FLAGS] flags -- <EXTRA_ARGS>

Explains in detail all the flags that can be used with breeze.
****************************************************************************************************
breeze [FLAGS] help -- <EXTRA_ARGS>

Shows this help message.
****************************************************************************************************
breeze [FLAGS] help-all -- <EXTRA_ARGS>

Shows detailed help for all commands and flags.
****************************************************************************************************
####################################################################################################

Flags

####################################################################################################

****************************************************************************************************

List of flags supported by breeze:

****************************************************************************************************
Choose Airflow variant
****************************************************************************************************

-p, --python <PYTHON_MAJOR_MINOR_VERSION>
Python version used for the image. This is always major/minor version.
One of:

3.6 3.7

-b, --backend <BACKEND>
Backend to use for tests - it determines which database is used.
One of:

sqlite mysql postgres

Default: sqlite

-d, --db-reset
Resets the database at entry to the envvironment. It will drop all the tables
and data and recreate the DB from scratch even if 'restart' command was not used.
Combined with 'restart' command it enters the environment in the state that is
ready to start airflow webserver/scheduler/worker. Without the switch, the database
does not have any tables and you need to run reset db manually.

-i, --integration <INTEGRATION>
Integration to start during tests - it determines which integrations are started
for integration tests. There can be more than one integration started, or all to
start all integrations. Selected integrations are not saved for future execution.
One of:

cassandra kerberos mongo openldap presto rabbitmq redis all

-I, --production-image
Use production image for entering the environment and builds (not for tests).

****************************************************************************************************
Manage Kind kubernetes cluster (optional)
****************************************************************************************************

Acion for the cluster : only one of the --kind-cluster-* flags can be used at a time:

-s, --kind-cluster-start
Starts kind Kubernetes cluster after entering the environment. The cluster is started using
Kubernetes Mode selected and Kubernetes version specified via --kubernetes-mode and
--kubernetes-version flags.

-x, --kind-cluster-stop
Stops kind Kubernetes cluster if one has already been created. By default, if you do not
stop environment, the Kubernetes cluster created for testing is continuously running and
when you start Kubernetes testing again it will be reused. You can force deletion and
recreation of such cluster with this flag.

-r, --kind-cluster-recreate

Recreates kind Kubernetes cluster if one has already been created. By default, if you do
not stop environment, the Kubernetes cluster created for testing is continuously running
and when you start Kubernetes testing again it will be reused. You can force deletion and
recreation of such cluster with this flag.

Kubernetes mode/version flags:

-K, --kubernetes-mode <KUBERNETES_MODE>
Kubernetes mode - only used in case one of --kind-cluster-* commands is used.
One of:

persistent_mode git_mode

Default: git_mode

-V, --kubernetes-version <KUBERNETES_VERSION>
Kubernetes version - only used in case one of --kind-cluster-* commands is used.
One of:

v1.15.3 v1.16.2

Default: v1.15.3

****************************************************************************************************
Manage mounting local files
****************************************************************************************************

-l, --skip-mounting-local-sources
Skips mounting local volume with sources - you get exactly what is in the
docker image rather than your current local sources of airflow.

****************************************************************************************************
Install Airflow if different than current
****************************************************************************************************

-a, --install-airflow-version <INSTALL_AIRFLOW_VERSION>
If specified, installs airflow directly from PIP released version. One of:

1.10.9 1.10.8 1.10.7 1.10.6 1.10.5 1.10.4 1.10.3 1.10.2 master v1-10-test

-t, --install-airflow-reference <INSTALL_AIRFLOW_REFERENCE>
Only for production image - if specified, installs airflow directly from reference in GitHub

****************************************************************************************************
Database versions
****************************************************************************************************

--postgres-version <POSTGRES_VERSION>
Postgres version used. One of:

9.6 10

--mysql-version <MYSQL_VERSION>
Mysql version used. One of:

5.7 8

****************************************************************************************************
Assume answers to questions
****************************************************************************************************

-y, --assume-yes
Assume 'yes' answer to all questions.

-n, --assume-no
Assume 'no' answer to all questions.

-q, --assume-quit
Assume 'quit' answer to all questions.

****************************************************************************************************
Credentials
****************************************************************************************************

-f, --forward-credentials
Forwards host credentials to docker container. Use with care as it will make
your credentials available to everything you install in Docker.

****************************************************************************************************
Increase verbosity of the script
****************************************************************************************************

-v, --verbose
Show verbose information about executed commands (enabled by default for running test).
Note that you can further increase verbosity and see all the commands executed by breeze
by running 'export VERBOSE_COMMANDS="true"' before running breeze.

****************************************************************************************************
Flags for building the docker images
****************************************************************************************************

-F, --force-build-images
Forces building of the local docker images. The images are rebuilt
automatically for the first time or when changes are detected in
package-related files, but you can force it using this flag.

-P, --force-pull-images
Forces pulling of images from DockerHub before building to populate cache. The
images are pulled by default only for the first time you run the
environment, later the locally build images are used as cache.

-E, --extras
Extras to pass to build images The default are different for CI and production images:

CI image:
devel_ci

Production image:
async,aws,azure,celery,dask,elasticsearch,gcp,kubernetes,mysql,postgres,redis,slack,
ssh,statsd,virtualenv

-C, --force-clean-images
Force build images with cache disabled. This will remove the pulled or build images
and start building images from scratch. This might take a long time.

-L, --use-local-cache
Uses local cache to build images. No pulled images will be used, but results of local
builds in the Docker cache are used instead.

****************************************************************************************************
Flags for pushing the docker images
****************************************************************************************************

-u, --push-images
After building - uploads the images to DockerHub
It is useful in case you use your own DockerHub user to store images and you want
to build them locally. Note that you need to use 'docker login' before you upload images.

****************************************************************************************************
User and repo used to login to github registry
****************************************************************************************************

-D, --dockerhub-user
DockerHub user used to pull, push and build images. Default: apache.

-H, --dockerhub-repo
DockerHub repository used to pull, push, build images. Default: airflow.

****************************************************************************************************

.. END BREEZE HELP MARKER

Convenience Scripts

Once you run ./breeze you can also execute various actions via generated convenience scripts:

Enter the environment          : ./.build/cmd_run
Run command in the environment : ./.build/cmd_run "[command with args]" [bash options]
Run tests in the environment   : ./.build/test_run [test-target] [pytest options]
Run Docker compose command     : ./.build/dc [help/pull/...] [docker-compose options]

Troubleshooting

If you are having problems with the Breeze environment, try the steps below. After each step you can check whether your problem is fixed.

If you are on macOS, check if you have enough disk space for Docker.
Restart Breeze with ./breeze restart.
Delete the .build directory and run ./breeze build-image --force-pull-images.
Clean up Docker images via breeze cleanup-image command.
Restart your Docker Engine and try again.
Restart your machine and try again.
Re-install Docker CE and try again.

In case the problems are not solved, you can set the VERBOSE_COMMANDS variable to "true":

export VERBOSE_COMMANDS="true"

Then run the failed command, copy-and-paste the output from your terminal to the Airflow Slack #airflow-breeze channel and describe your problem.

Fixing File/Directory Ownership

On Linux, there is a problem with propagating ownership of created files (a known Docker problem). The files and directories created in the container are not owned by the host user (but by the root user in our case). This may prevent you from switching branches, for example, if files owned by the root user are created within your sources. In case you are on a Linux host and have some files in your sources created y the root user, you can fix the ownership of those files by running this script:

./scripts/ci/ci_fix_ownership.sh

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