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Airflow Breeze - Development and Test Environment for Apache Airflow

Airflow Breeze is an easy-to-use development and test 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 contribute to Airflow.

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

All the output from the last ./breeze command is automatically logged to the logs/breeze.out file.

Watch the video below about Airflow Breeze. It explains the motivation for Breeze and screencasts all its uses.

  • 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:

Disk space MacOS
  • Version: Install the latest stable Docker Compose and add it to the PATH. See Docker Compose Installation Guide for details.
  • Permissions: Configure permission to run the docker-compose command.
Airflow Breeze - Docker WSL2 integration
  • WSL 2 Filesystem Performance :

    Accessing the host Windows filesystem incurs a performance penalty, it is therefore recommended to do development on the Linux filesystem. E.g. Run cd ~ and create a development folder in your Linux distro home and git pull the Airflow repo there.

  • WSL 2 Docker mount errors:

    Another reason to use Linux filesystem, is that sometimes - depending on the length of your path, you might get strange errors when you try start Breeze, such us caused: mount through procfd: not a directory: unknown:. Therefore checking out Airflow in Windows-mounted Filesystem is strongly discouraged.

  • WSL 2 Memory Usage :

    WSL 2 can consume a lot of memory under the process name "Vmmem". To reclaim the memory after development you can:

    • On the Linux distro clear cached memory: sudo sysctl -w vm.drop_caches=3
    • If no longer using Docker you can quit Docker Desktop (right click system try icon and select "Quit Docker Desktop")
    • If no longer using WSL you can shut it down on the Windows Host with the following command: wsl --shutdown
  • Developing in WSL 2:

    You can use all the standard Linux command line utilities to develop on WSL 2. Further VS Code supports developing in Windows but remotely executing in WSL. If VS Code is installed on the Windows host system then in the WSL Linux Distro you can run code . in the root directory of you Airflow repo to launch VS Code.

  • 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="$(brew --prefix)/opt/gnu-getopt/bin:$PATH"' >> ~/.bash_profile
. ~/.bash_profile

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

echo 'export PATH="$(brew --prefix)/opt/gnu-getopt/bin:$PATH"' >> ~/.zprofile
. ~/.zprofile

Let's confirm that getopt and gstat utilities are successfully installed

$ getopt --version
getopt from util-linux *
$ gstat --version
stat (GNU coreutils) *
Copyright (C) 2020 Free Software Foundation, Inc.
License GPLv3+: GNU GPL version 3 or later <https://gnu.org/licenses/gpl.html>.
This is free software: you are free to change and redistribute it.
There is NO WARRANTY, to the extent permitted by law.

Written by Michael Meskes.

Minimum 4GB RAM for Docker Engine 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.

On Windows WSL 2 expect the Linux Distro and Docker containers to use 7 - 8 GB of RAM.

Minimum 40GB free disk space is required for your Docker Containers.

On Mac OS This might deteriorate over time so you might need to increase it or run docker system --prune periodically. For details see Docker for Mac - Advanced tab.

On WSL2 you might want to increase your Virtual Hard Disk by following: Expanding the size of your WSL 2 Virtual Hard Disk

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:

  1. Stop Breeze with ./breeze stop. (If Breeze is already running)

  2. Run the docker system prune command.

  3. 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.

Installation is as easy as checking out Airflow repository and running Breeze command. 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 the GitHub Container Registry 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.

To use the full potential of breeze you should set up autocomplete and you can add the checked-out Airflow repository to your PATH to run Breeze without the ./ and from any directory.

The breeze command comes with a built-in bash/zsh autocomplete setup command. After installing, when you start typing the command, you can use <TAB> to show all the available switches and get auto-completion on typical values of parameters that you can use.

You should set up the autocomplete option automatically by running:

./breeze setup-autocomplete

You get the auto-completion working when you re-enter the shell.

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.

You can also add your local tmux configuration in files/airflow-breeze-config/.tmux.conf and these configurations will be available for your tmux environment.

there is a symlink between files/airflow-breeze-config/.tmux.conf and ~/.tmux.conf in the container, so you can change it at any place, and run

tmux source ~/.tmux.conf

inside container, to enable modified tmux configurations.

Breeze helps with running tests in the same environment/way as CI tests are run. You can run various types of tests while you enter Breeze CI interactive environment - this is described in detail in TESTING.rst

You can use additional breeze flags to choose your environment. You can specify a Python version to use, and backend (the meta-data database). Thanks to that, with Breeze, you can recreate the same environments as we have in matrix builds in the 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 version and SQLite database.

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

  1. If you are on macOS, check if you have enough disk space for Docker.
  2. Restart Breeze with ./breeze restart.
  3. Delete the .build directory and run ./breeze build-image.
  4. Clean up Docker images via breeze cleanup-image command.
  5. Restart your Docker Engine and try again.
  6. Restart your machine and try again.
  7. 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.

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:

Managing CI environment:

  • Build CI docker image with breeze build-image command
  • Enter interactive shell in CI container when shell (or no command) is specified
  • Join running interactive shell with breeze exec command
  • Stop running interactive environment with breeze stop command
  • Restart running interactive environment with breeze restart command
  • Run test specified with breeze tests command
  • Generate constraints with breeze generate-constraints
  • Execute arbitrary command in the test environment with breeze shell command
  • Execute arbitrary docker-compose command with breeze docker-compose command
  • Push docker images with breeze push-image command (require committers rights to push images)

You can optionally reset the Airflow metadata database if specified as extra --db-reset flag and for CI image you can also start integrations (separate Docker images) if specified as extra --integration flags. You can also chose which backend database should be used with --backend flag and python version with --python flag.

You can also have breeze launch Airflow automatically breeze start-airflow, this will drop you in a tmux session with three panes:

  • one to monitor the scheduler,
  • one for the webserver,
  • one with a shell for additional commands.

Managing Prod environment (with --production-image flag):

  • Build CI docker image with breeze build-image command
  • Enter interactive shell in PROD container when shell (or no command) is specified
  • Join running interactive shell with breeze exec command
  • Stop running interactive environment with breeze stop command
  • Restart running interactive environment with breeze restart command
  • Execute arbitrary command in the test environment with breeze shell command
  • Execute arbitrary docker-compose command with breeze docker-compose command
  • Push docker images with breeze push-image command (require committers rights to push images)

You can optionally reset database if specified as extra --db-reset flag. You can also chose which backend database should be used with --backend flag and python version with --python flag.

Manage and Interact with Kubernetes tests environment:

  • Manage KinD Kubernetes cluster and deploy Airflow to KinD cluster breeze kind-cluster commands
  • Run Kubernetes tests specified with breeze kind-cluster tests command
  • Enter the interactive kubernetes test environment with breeze kind-cluster shell command

Run static checks:

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

Breeze keeps data for all it's integration in named docker volumes. Each backend and integration keeps data in their own volume. Those volumes are persisted until ./breeze stop command or ./breeze restart command is run. You can also preserve the volumes by adding flag --preserve-volumes when you run either of those commands. Then, next time when you start Breeze, it will have the data pre-populated. You can always delete the volumes by running ./breeze stop without the --preserve-volumes flag.

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 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.

To shrink the Docker image, not all tools are pre-installed in the Docker image. But we have made sure that there is an easy process to install additional tools.

Additional tools are installed in /files/bin. This path is added to $PATH, so your shell will automatically autocomplete files that are in that directory. You can also keep the binaries for your tools in this directory if you need to.

Installation scripts

For the development convenience, we have also provided installation scripts for commonly used tools. They are installed to /files/opt/, so they are preserved after restarting the Breeze environment. Each script is also available in $PATH, so just type install_<TAB> to get a list of tools.

Currently available scripts:

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#airflow-integration-tests.

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.

With Breeze you can build images that are used by Airflow CI and production ones.

For all development tasks, unit tests, integration tests, and static code checks, we use the CI image maintained in GitHub Container Registry.

The CI image is built automatically as needed, however it can be rebuilt manually with build-image command. The production image should be built manually - but also a variant of this image is built automatically when kubernetes tests are executed see Running Kubernetes tests

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.

Breeze has built in mechanism to check if your local image has not diverged too much from the latest image build on CI. This might happen when for example latest patches have been released as new Python images or when significant changes are made in the Dockerfile. In such cases, Breeze will download the latest images before rebuilding because this is usually faster than rebuilding the image.

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 Setting default behaviour for user interaction section.

Breeze can also be used to prepare airflow packages - both "apache-airflow" main package and provider packages.

You can read more about testing provider packages in TESTING.rst

There are several commands that you can run in Breeze to manage and build packages:

  • preparing Provider Readme files
  • preparing Airflow packages
  • preparing Provider packages

Preparing provider readme files is part of the release procedure by the release managers and it is described in detail in dev .

The packages are prepared in dist folder. Note, that this command cleans up the dist folder before running, so you should run it before generating airflow package below as it will be removed.

The below example builds provider packages in the wheel format.

./breeze prepare-provider-packages

If you run this command without packages, you will prepare all packages, you can however specify providers that you would like to build. By default both types of packages are prepared ( wheel and sdist, but you can change it providing optional --package-format flag.

./breeze prepare-provider-packages google amazon

You can see all providers available by running this command:

./breeze prepare-provider-packages -- --help

You can also prepare airflow packages using breeze:

./breeze prepare-airflow-packages

This prepares airflow .whl package in the dist folder.

Again, you can specify optional --package-format flag to build selected formats of airflow packages, default is to build both type of packages sdist and wheel.

./breeze prepare-airflow-packages --package-format=wheel

The Production image is also maintained in GitHub Container Registry for Caching and in apache/airflow manually pushed for released versions. This Docker image (built using official Dockerfile) contains size-optimised Airflow installation with selected extras and dependencies.

However in many cases you want to add your own custom version of the image - with added apt dependencies, python dependencies, additional Airflow extras. Breeze's build-image command helps to build your own, customized variant of the image that contains everything you need.

You can switch to building the production image by adding --production-image flag to the build_image command. Note, that the images can also be built using docker build command by passing appropriate build-args as described in IMAGES.rst , but Breeze provides several flags that makes it easier to do it. You can see all the flags by running ./breeze build-image --help, but here typical examples are presented:

./breeze build-image --production-image --additional-extras "jira"

This installs additional jira extra while installing airflow in the image.

./breeze build-image --production-image --additional-python-deps "torchio==0.17.10"

This install additional pypi dependency - torchio in specified version.

./breeze build-image --production-image --additional-dev-apt-deps "libasound2-dev" \
   --additional-runtime-apt-deps "libasound2"

This installs additional apt dependencies - libasound2-dev in the build image and libasound in the final image. Those are development dependencies that might be needed to build and use python packages added via the --additional-python-deps flag. The dev dependencies are not installed in the final production image, they are only installed in the build "segment" of the production image that is used as an intermediate step to build the final image. Usually names of the dev dependencies end with -dev suffix and they need to also be paired with corresponding runtime dependency added for the runtime image (without -dev).

./breeze build-image --production-image --python 3.7 --additional-dev-deps "libasound2-dev" \
   --additional-runtime-apt-deps "libasound2"

Same as above but uses python 3.7.

You can run static checks via Breeze. You can also run them via pre-commit command but with auto-completion Breeze makes it easier to run selective static checks. If you press <TAB> after the static-check and if you have auto-complete setup you should see auto-completable list of all checks available.

./breeze static-check mypy

The above will run mypy check for currently staged files.

You can also add arbitrary pre-commit flag after --

./breeze static-check mypy -- --all-files

The above will run mypy check for all files.

If you ever need to get a list of the files that will be checked (for troubleshooting when playing with --from-ref and --to-ref), use these commands:

./breeze static-check identity --verbose # currently staged files
./breeze static-check identity --verbose -- --from-ref $(git merge-base main HEAD) --to-ref HEAD #  branch updates

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.

The documentation build consists of three steps:

  • verifying consistency of indexes
  • building documentation
  • spell checking

You can choose only one stage of the two by providing --spellcheck-only or --docs-only after extra -- flag.

./breeze build-docs -- --spellcheck-only

This process can take some time, so in order to make it shorter you can filter by package, using the flag --package-filter <PACKAGE-NAME>. The package name has to be one of the providers or apache-airflow. For instance, for using it with Amazon, the command would be:

./breeze build-docs -- --package-filter apache-airflow-providers-amazon

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.

Whenever setup.py gets modified, the CI main job will re-generate constraint files. Those constraint files are stored in separated orphan branches: constraints-main, constraints-2-0.

Those are constraint files as described in detail in the CONTRIBUTING.rst#pinned-constraint-files contributing documentation.

You can use ./breeze generate-constraints command to manually generate constraints for a single python version and single constraint mode like this:

./breeze generate-constraints --generate-constraints-mode pypi-providers

Constraints are generated separately for each python version and there are separate constraints modes:

  • 'constraints' - those are constraints generated by matching the current airflow version from sources
    and providers that are installed from PyPI. Those are constraints used by the users who want to install airflow with pip. Use pypi-providers mode for that.
  • "constraints-source-providers" - those are constraints generated by using providers installed from current sources. While adding new providers their dependencies might change, so this set of providers is the current set of the constraints for airflow and providers from the current main sources. Those providers are used by CI system to keep "stable" set of constraints. Use source-providers mode for that.
  • "constraints-no-providers" - those are constraints generated from only Apache Airflow, without any providers. If you want to manage airflow separately and then add providers individually, you can use those. Use no-providers mode for that.

In case someone modifies setup.py, the scheduled CI Tests automatically upgrades and pushes changes to the constraint files, however you can also perform test run of this locally using the procedure described in CONTRIBUTING.rst#manually-generating-constraint-files which utilises multiple processors on your local machine to generate such constraints faster.

This bumps the constraint files to latest versions and stores hash of setup.py. The generated constraint and setup.py hash files are stored in the files folder and while generating the constraints diff of changes vs the previous constraint files is printed.

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, language auto-completion, documentation support, etc.

To use your host IDE with Breeze:

  1. Create a local virtual environment:

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

    Ideally, you should have virtualenvs for all Python versions supported by Airflow (3.5, 3.6, 3.7)

  2. Use the right command to activate the virtualenv (workon if you use virtualenvwrapper or pyenv activate if you use pyenv.

  3. Initialize the created local virtualenv:

./breeze initialize-local-virtualenv --python 3.8
  1. 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.

Breeze helps with running Kubernetes tests in the same environment/way as CI tests are run. Breeze helps to setup KinD cluster for testing, setting up virtualenv and downloads the right tools automatically to run the tests.

This is described in detail in Testing Kubernetes.

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

./breeze stop

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.

To run other commands/executables inside the Breeze Docker-based environment, use the ./breeze shell command. You should add your command as -c "command" after -- as extra arguments.

./breeze shell -- -c "ls -la"

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

You can also restart the environment and enter it via:

./breeze restart

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.

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 by the root user, you can fix the ownership of those files by running this script:

./scripts/ci/tools/fix_ownership.sh

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.

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

  • 28080 -> forwarded to Airflow webserver -> airflow:8080
  • 25555 -> forwarded to Flower dashboard -> airflow:5555
  • 25433 -> forwarded to Postgres database -> postgres:5432
  • 23306 -> forwarded to MySQL database -> mysql:3306
  • 26379 -> forwarded to Redis broker -> redis:6379

You can connect to these ports/databases using:

  • Webserver: http://127.0.0.1:28080
  • Flower: http://127.0.0.1:25555
  • Postgres: jdbc:postgresql://127.0.0.1:25433/airflow?user=postgres&password=airflow
  • Mysql: jdbc:mysql://127.0.0.1:23306/airflow?user=root
  • Redis: redis://127.0.0.1:26379/0`

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 [email protected] --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:

Airflow Breeze - Database view

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

  • SSH_PORT
  • 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.

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.

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.

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.

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.

This is the current syntax for ./breeze:

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

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

 By default the script enters the  CI container 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-constraints                     Generates pinned constraint files
   push-image                               Pushes images to registry
   initialize-local-virtualenv              Initializes local virtualenv
   prepare-airflow-packages                 Prepares airflow packages
   setup-autocomplete                       Sets up autocomplete for breeze
   start-airflow                            Starts Scheduler and Webserver and enters the shell
   stop                                     Stops the docker-compose environment
   restart                                  Stops the docker-compose environment 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
   kind-cluster                       <ARG>      Manages KinD cluster on the host
   prepare-provider-documentation     <ARG>      Prepares provider packages documentation
   prepare-provider-packages          <ARG>      Prepares provider packages
   static-check                       <ARG>      Performs selected static check for changed files
   tests                              <ARG>      Runs selected tests 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

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


 Detailed usage for command: shell


 breeze shell [FLAGS] [-- <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.

       You can also pass <EXTRA_ARGS> after -- they will be passed as bash parameters, this is
       especially useful to pass bash options, for example -c to execute command:

       'breeze shell -- -c "ls -la"'
       'breeze -- -c "ls -la"'

       For GitHub repository, the --github-repository flag can be used to specify the repository
       to pull and push images. You can also use --github-image-id <COMMIT_SHA> in case
       you want to pull the image with specific COMMIT_SHA tag.

       'breeze shell \
             --github-image-id 9a621eaa394c0a0a336f8e1b31b35eff4e4ee86e' - pull/use image with SHA
       'breeze \
             --github-image-id 9a621eaa394c0a0a336f8e1b31b35eff4e4ee86e' - pull/use image with SHA

 Most flags are applicable to the shell command as it will run build when needed.


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


 Detailed usage for command: build-docs


 breeze 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.

       The possible extra args are: --docs-only, --spellcheck-only, --package-filter, --help


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


 Detailed usage for command: build-image


 breeze build-image [FLAGS]

       Builds docker image (CI or production) without entering the container. You can pass
       additional options to this command, such as:

       Choosing python version:
         '--python'

       Choosing cache option:
          '--build-cache-local' or '-build-cache-pulled', or '--build-cache-none'

       Choosing whether to force pull images or force build the image:
           '--force-build-image', '--force-pull-image'

       Checking if the base python image has been updated:
           '--check-if-base-python-image-updated'

       You can also pass '--production-image' flag to build production image rather than CI image.

       For GitHub repository, the '--github-repository' can be used to choose repository
       to pull/push images.

 Flags:

 -p, --python PYTHON_MAJOR_MINOR_VERSION
         Python version used for the image. This is always major/minor version.

         One of:

                3.7 3.8 3.9

 -a, --install-airflow-version INSTALL_AIRFLOW_VERSION
         Uses different version of Airflow when building PROD image.

                2.0.2 2.0.1 2.0.0 wheel sdist

 -t, --install-airflow-reference INSTALL_AIRFLOW_REFERENCE
         Installs Airflow directly from reference in GitHub when building PROD image.
         This can be a GitHub branch like main or v2-2-test, or a tag like 2.2.0rc1.

 --installation-method INSTALLATION_METHOD
         Method of installing Airflow in PROD image - either from the sources ('.')
         or from package 'apache-airflow' to install from PyPI.
         Default in Breeze is to install from sources. One of:

                . apache-airflow

 --upgrade-to-newer-dependencies
         Upgrades PIP packages to latest versions available without looking at the constraints.

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

 -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 GitHub Container Registry 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.

 --check-if-base-python-image-updated
         Checks if Python base image from DockerHub has been updated vs the current python base
         image we store in GitHub Container Registry. Python images are updated regularly with
         security fixes, this switch will check if a new one has been released and will pull and
         prepare a new base python based on the latest one.

 --cleanup-docker-context-files
         Removes whl and tar.gz files created in docker-context-files before running the command.
         In case there are some files there it unnecessarily increases the context size and
         makes the COPY . always invalidated - if you happen to have those files when you build your
         image.

 Customization options:

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

         CI image:
                devel_ci

         Production image:
                amazon,async,celery,cncf.kubernetes,dask,docker,elasticsearch,ftp,google,google_auth,
                grpc,hashicorp,http,ldap,microsoft.azure,mysql,odbc,pandas,postgres,redis,sendgrid,
                sftp,slack,ssh,statsd,virtualenv

 --image-tag TAG
         Additional tag in the image.

 --skip-installing-airflow-providers-from-sources
         By default 'pip install' in Airflow 2.0 installs only the provider packages that
         are needed by the extras. When you build image during the development (which is
         default in Breeze) all providers are installed by default from sources.
         You can disable it by adding this flag but then you have to install providers from
         wheel packages via --use-packages-from-dist flag.

 --disable-pypi-when-building
         Disable installing Airflow from pypi when building. If you use this flag and want
         to install Airflow, you have to install it from packages placed in
         'docker-context-files' and use --install-from-docker-context-files flag.

 --additional-extras ADDITIONAL_EXTRAS
         Additional extras to pass to build images The default is no additional extras.

 --additional-python-deps ADDITIONAL_PYTHON_DEPS
         Additional python dependencies to use when building the images.

 --dev-apt-command DEV_APT_COMMAND
         The basic command executed before dev apt deps are installed.

 --additional-dev-apt-command ADDITIONAL_DEV_APT_COMMAND
         Additional command executed before dev apt deps are installed.

 --additional-dev-apt-deps ADDITIONAL_DEV_APT_DEPS
         Additional apt dev dependencies to use when building the images.

 --dev-apt-deps DEV_APT_DEPS
         The basic apt dev dependencies to use when building the images.

 --additional-dev-apt-deps ADDITIONAL_DEV_DEPS
         Additional apt dev dependencies to use when building the images.

 --additional-dev-apt-envs ADDITIONAL_DEV_APT_ENVS
         Additional environment variables set when adding dev dependencies.

 --runtime-apt-command RUNTIME_APT_COMMAND
         The basic command executed before runtime apt deps are installed.

 --additional-runtime-apt-command ADDITIONAL_RUNTIME_APT_COMMAND
         Additional command executed before runtime apt deps are installed.

 --runtime-apt-deps ADDITIONAL_RUNTIME_APT_DEPS
         The basic apt runtime dependencies to use when building the images.

 --additional-runtime-apt-deps ADDITIONAL_RUNTIME_DEPS
         Additional apt runtime dependencies to use when building the images.

 --additional-runtime-apt-envs ADDITIONAL_RUNTIME_APT_DEPS
         Additional environment variables set when adding runtime dependencies.

 Build options:

 --disable-mysql-client-installation
         Disables installation of the mysql client which might be problematic if you are building
         image in controlled environment. Only valid for production image.

 --disable-mssql-client-installation
         Disables installation of the mssql client which might be problematic if you are building
         image in controlled environment. Only valid for production image.

 --constraints-location
         Url to the constraints file. In case of the production image it can also be a path to the
         constraint file placed in 'docker-context-files' folder, in which case it has to be
         in the form of '/docker-context-files/<NAME_OF_THE_FILE>'

 --disable-pip-cache
         Disables GitHub PIP cache during the build. Useful if GitHub is not reachable during build.

 --install-from-docker-context-files
         This flag is used during image building. If it is used additionally to installing
         Airflow from PyPI, the packages are installed from the .whl and .tar.gz packages placed
         in the 'docker-context-files' folder. The same flag can be used during entering the image in
         the CI image - in this case also the .whl and .tar.gz files will be installed automatically

 -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.

 -r, --skip-rebuild-check
         Skips checking image for rebuilds. It will use whatever image is available locally/pulled.

 -L, --build-cache-local
         Uses local cache to build images. No pulled images will be used, but results of local
         builds in the Docker cache are used instead. This will take longer than when the pulled
         cache is used for the first time, but subsequent '--build-cache-local' builds will be
         faster as they will use mostly the locally build cache.

         This is default strategy used by the Production image builds.

 -U, --build-cache-pulled
         Uses images pulled from GitHub Container Registry to build images.
         Those builds are usually faster than when ''--build-cache-local'' with the exception if
         the registry images are not yet updated. The images are updated after successful merges
         to main.

         This is default strategy used by the CI image builds.

 -X, --build-cache-disabled
         Disables cache during docker builds. This is useful if you want to make sure you want to
         rebuild everything from scratch.

         This strategy is used by default for both Production and CI images for the scheduled
         (nightly) builds in CI.

 -g, --github-repository GITHUB_REPOSITORY
         GitHub repository used to pull, push images.
         Default: apache/airflow.

 -v, --verbose
         Show verbose information about executed docker, kind, kubectl, helm commands. Useful for
         debugging - when you run breeze with --verbose flags you will be able to see the commands
         executed under the hood and copy&paste them to your terminal to debug them more easily.

         Note that you can further increase verbosity and see all the commands executed by breeze
         by running 'export VERBOSE_COMMANDS="true"' before running breeze.

 --dry-run-docker
         Only show docker commands to execute instead of actually executing them. The docker
         commands are printed in yellow color.


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


 Detailed usage for command: cleanup-image


 breeze cleanup-image [FLAGS]

       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.

 Flags:

 -p, --python PYTHON_MAJOR_MINOR_VERSION
         Python version used for the image. This is always major/minor version.

         One of:

                3.7 3.8 3.9

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

 -v, --verbose
         Show verbose information about executed docker, kind, kubectl, helm commands. Useful for
         debugging - when you run breeze with --verbose flags you will be able to see the commands
         executed under the hood and copy&paste them to your terminal to debug them more easily.

         Note that you can further increase verbosity and see all the commands executed by breeze
         by running 'export VERBOSE_COMMANDS="true"' before running breeze.

 --dry-run-docker
         Only show docker commands to execute instead of actually executing them. The docker
         commands are printed in yellow color.


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


 Detailed usage for command: exec


 breeze 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.


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


 Detailed usage for command: generate-constraints


 breeze generate-constraints [FLAGS]

       Generates pinned constraint files with all extras from setup.py. Those files are generated in
       files folder - separate files for different python version. Those constraint files when
       pushed to orphan constraints-main, constraints-2-0 branches are used
       to generate repeatable CI test runs as well as run repeatable production image builds and
       upgrades when you want to include installing or updating some of the released providers
       released at the time particular airflow version was released. You can use those
       constraints to predictably install released Airflow versions. This is mainly used to test
       the constraint generation or manually fix them - constraints are pushed to the orphan
       branches by a successful scheduled CRON job in CI automatically, but sometimes manual fix
       might be needed.

 Flags:

 --generate-constraints-mode GENERATE_CONSTRAINTS_MODE
         Mode of generating constraints - determines whether providers are installed when generating
         constraints and which version of them (either the ones from sources are used or the ones
         from pypi.

         One of:

                source-providers pypi-providers no-providers

 -p, --python PYTHON_MAJOR_MINOR_VERSION
         Python version used for the image. This is always major/minor version.

         One of:

                3.7 3.8 3.9

 -v, --verbose
         Show verbose information about executed docker, kind, kubectl, helm commands. Useful for
         debugging - when you run breeze with --verbose flags you will be able to see the commands
         executed under the hood and copy&paste them to your terminal to debug them more easily.

         Note that you can further increase verbosity and see all the commands executed by breeze
         by running 'export VERBOSE_COMMANDS="true"' before running breeze.

 --dry-run-docker
         Only show docker commands to execute instead of actually executing them. The docker
         commands are printed in yellow color.


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


 Detailed usage for command: push-image


 breeze push_image [FLAGS]

       Pushes images to GitHub registry.

       You can add --github-repository to push to a different repository/organisation.
       You can add --github-image-id <COMMIT_SHA> in case you want to push image with specific
       SHA tag.
       You can also add --production-image flag to switch to production image (default is CI one)

       Examples:

       'breeze push-image' or
       'breeze push-image --production-image' - to push production image or
       'breeze push-image \
             --github-repository user/airflow' - to push to your user's fork
       'breeze push-image \
             --github-image-id 9a621eaa394c0a0a336f8e1b31b35eff4e4ee86e' - to push with COMMIT_SHA

 Flags:

 -g, --github-repository GITHUB_REPOSITORY
         GitHub repository used to pull, push images.
         Default: apache/airflow.




 -s, --github-image-id COMMIT_SHA
         <COMMIT_SHA> of the image. Images in GitHub registry are stored with those
         to be able to easily find the image for particular CI runs. Once you know the
         <COMMIT_SHA>, you can specify it in github-image-id flag and Breeze will
         automatically pull and use that image so that you can easily reproduce a problem
         that occurred in CI.

         Default: latest.

 -v, --verbose
         Show verbose information about executed docker, kind, kubectl, helm commands. Useful for
         debugging - when you run breeze with --verbose flags you will be able to see the commands
         executed under the hood and copy&paste them to your terminal to debug them more easily.

         Note that you can further increase verbosity and see all the commands executed by breeze
         by running 'export VERBOSE_COMMANDS="true"' before running breeze.

 --dry-run-docker
         Only show docker commands to execute instead of actually executing them. The docker
         commands are printed in yellow color.


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


 Detailed usage for command: initialize-local-virtualenv


 breeze initialize-local-virtualenv [FLAGS]

       Initializes locally created virtualenv installing all dependencies of Airflow
       taking into account the constraints for the version specified.
       This local virtualenv can be used to aid auto-completion and IDE support as
       well as run unit tests directly from the IDE. You need to have virtualenv
       activated before running this command.

 Flags:

 -p, --python PYTHON_MAJOR_MINOR_VERSION
         Python version used for the image. This is always major/minor version.

         One of:

                3.7 3.8 3.9


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


 Detailed usage for command: prepare-airflow-packages


 breeze prepare-airflow-packages [FLAGS]

       Prepares airflow packages (sdist and wheel) in dist folder. Note that
       prepare-provider-packages command cleans up the dist folder, so if you want also
       to generate provider packages, make sure you run prepare-provider-packages first,
       and prepare-airflow-packages second. You can specify optional
       --version-suffix-for-pypi flag to generate rc candidates for PyPI packages.
       The packages are prepared in dist folder

       Examples:

       'breeze prepare-airflow-packages --package-format wheel' or
       'breeze prepare-airflow-packages --version-suffix-for-pypi rc1'

 Flags:

 --package-format PACKAGE_FORMAT

         Chooses format of packages to prepare.

         One of:

                both,sdist,wheel

         Default: both

 -S, --version-suffix-for-pypi SUFFIX
         Adds optional suffix to the version in the generated provider package. It can be used
         to generate rc1/rc2 ... versions of the packages to be uploaded to PyPI.

 -N, --version-suffix-for-svn SUFFIX
         Adds optional suffix to the generated names of package. It can be used to generate
         rc1/rc2 ... versions of the packages to be uploaded to SVN.

 -v, --verbose
         Show verbose information about executed docker, kind, kubectl, helm commands. Useful for
         debugging - when you run breeze with --verbose flags you will be able to see the commands
         executed under the hood and copy&paste them to your terminal to debug them more easily.

         Note that you can further increase verbosity and see all the commands executed by breeze
         by running 'export VERBOSE_COMMANDS="true"' before running breeze.

 --dry-run-docker
         Only show docker commands to execute instead of actually executing them. The docker
         commands are printed in yellow color.


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


 Detailed usage for command: setup-autocomplete


 breeze setup-autocomplete

       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.


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


 Detailed usage for command: start-airflow


 breeze start-airflow

       Like the Shell command this will enter the interactive shell, but it will also start
       automatically the Scheduler and the Webserver. It will leave you in a tmux session where you
       can also observe what is happening in your Airflow.

       This is a convenient way to setup a development environment. Your dags will be loaded from the
       folder 'files/dags' on your host machine (it could take some times).

       If you want to load default connections and example dags you can use the dedicated flags.

 Flags:

 --use-airflow-version AIRFLOW_SPECIFICATION
         In CI image, installs Airflow at runtime from PIP released version or using
         the installation method specified (sdist, wheel, none). When 'none' is used,
         airflow is just removed. In this case airflow package should be added to dist folder
         and --use-packages-from-dist flag should be used.

                2.0.2 2.0.1 2.0.0 wheel sdist none

 --use-packages-from-dist
         In CI image, if specified it will look for packages placed in dist folder and
         it will install the packages after entering the image.
         This is useful for testing provider packages.

 --load-example-dags
         Include Airflow example dags.

 --load-default-connections
         Include Airflow Default Connections.


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


 Detailed usage for command: stop


 breeze stop

       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.

 Flags:

 --preserve-volumes
         Use this flag if you would like to preserve data volumes from the databases used
         by the integrations. By default, those volumes are deleted, so when you run 'stop'
         or 'restart' commands you start from scratch, but by using this flag you can
         preserve them. If you want to delete those volumes after stopping Breeze, just
         run the 'breeze stop' again without this flag.


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


 Detailed usage for command: restart


 breeze restart [FLAGS]

       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.

 Flags:

 --preserve-volumes
         Use this flag if you would like to preserve data volumes from the databases used
         by the integrations. By default, those volumes are deleted, so when you run 'stop'
         or 'restart' commands you start from scratch, but by using this flag you can
         preserve them. If you want to delete those volumes after stopping Breeze, just
         run the 'breeze stop' again without this flag.


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


 Detailed usage for command: toggle-suppress-cheatsheet


 breeze toggle-suppress-cheatsheet

       Toggles on/off cheatsheet displayed before starting bash shell.


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


 Detailed usage for command: toggle-suppress-asciiart


 breeze toggle-suppress-asciiart

       Toggles on/off asciiart displayed before starting bash shell.


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


 Detailed usage for command: docker-compose


 breeze docker-compose [FLAGS] COMMAND [-- <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'

 Flags:

 -p, --python PYTHON_MAJOR_MINOR_VERSION
         Python version used for the image. This is always major/minor version.

         One of:

                3.7 3.8 3.9

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

                sqlite mysql postgres mssql

         Default: sqlite

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

                10 11 12 13

 --mysql-version MYSQL_VERSION
         MySql version used. One of:

                5.7 8

 --mssql-version MSSQL_VERSION
         MSSql version used. One of:

                2017-latest 2019-latest

 -v, --verbose
         Show verbose information about executed docker, kind, kubectl, helm commands. Useful for
         debugging - when you run breeze with --verbose flags you will be able to see the commands
         executed under the hood and copy&paste them to your terminal to debug them more easily.

         Note that you can further increase verbosity and see all the commands executed by breeze
         by running 'export VERBOSE_COMMANDS="true"' before running breeze.

 --dry-run-docker
         Only show docker commands to execute instead of actually executing them. The docker
         commands are printed in yellow color.


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


 Detailed usage for command: kind-cluster


 breeze kind-cluster [FLAGS] OPERATION

       Manages host-side Kind Kubernetes cluster that is used to run Kubernetes integration tests.
       It allows to start/stop/restart/status the Kind Kubernetes cluster and deploy Airflow to it.
       This enables you to run tests inside the breeze environment with latest airflow images.
       Note that in case of deploying airflow, the first step is to rebuild the image and loading it
       to the cluster so you can also pass appropriate build image flags that will influence
       rebuilding the production image. Operation is one of:

                start stop restart status deploy test shell k9s

       The last two operations - shell and k9s allow you to perform interactive testing with
       kubernetes tests. You can enter the shell from which you can run kubernetes tests and in
       another terminal you can start the k9s CLI to debug kubernetes instance. It is an easy
       way to debug the kubernetes deployments.

       You can read more about k9s at https://k9scli.io/

 Flags:

 -p, --python PYTHON_MAJOR_MINOR_VERSION
         Python version used for the image. This is always major/minor version.

         One of:

                3.7 3.8 3.9

 -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 GitHub Container Registry 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.

 --check-if-base-python-image-updated
         Checks if Python base image from DockerHub has been updated vs the current python base
         image we store in GitHub Container Registry. Python images are updated regularly with
         security fixes, this switch will check if a new one has been released and will pull and
         prepare a new base python based on the latest one.

 --cleanup-docker-context-files
         Removes whl and tar.gz files created in docker-context-files before running the command.
         In case there are some files there it unnecessarily increases the context size and
         makes the COPY . always invalidated - if you happen to have those files when you build your
         image.

 Customization options:

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

         CI image:
                devel_ci

         Production image:
                amazon,async,celery,cncf.kubernetes,dask,docker,elasticsearch,ftp,google,google_auth,
                grpc,hashicorp,http,ldap,microsoft.azure,mysql,odbc,pandas,postgres,redis,sendgrid,
                sftp,slack,ssh,statsd,virtualenv

 --image-tag TAG
         Additional tag in the image.

 --skip-installing-airflow-providers-from-sources
         By default 'pip install' in Airflow 2.0 installs only the provider packages that
         are needed by the extras. When you build image during the development (which is
         default in Breeze) all providers are installed by default from sources.
         You can disable it by adding this flag but then you have to install providers from
         wheel packages via --use-packages-from-dist flag.

 --disable-pypi-when-building
         Disable installing Airflow from pypi when building. If you use this flag and want
         to install Airflow, you have to install it from packages placed in
         'docker-context-files' and use --install-from-docker-context-files flag.

 --additional-extras ADDITIONAL_EXTRAS
         Additional extras to pass to build images The default is no additional extras.

 --additional-python-deps ADDITIONAL_PYTHON_DEPS
         Additional python dependencies to use when building the images.

 --dev-apt-command DEV_APT_COMMAND
         The basic command executed before dev apt deps are installed.

 --additional-dev-apt-command ADDITIONAL_DEV_APT_COMMAND
         Additional command executed before dev apt deps are installed.

 --additional-dev-apt-deps ADDITIONAL_DEV_APT_DEPS
         Additional apt dev dependencies to use when building the images.

 --dev-apt-deps DEV_APT_DEPS
         The basic apt dev dependencies to use when building the images.

 --additional-dev-apt-deps ADDITIONAL_DEV_DEPS
         Additional apt dev dependencies to use when building the images.

 --additional-dev-apt-envs ADDITIONAL_DEV_APT_ENVS
         Additional environment variables set when adding dev dependencies.

 --runtime-apt-command RUNTIME_APT_COMMAND
         The basic command executed before runtime apt deps are installed.

 --additional-runtime-apt-command ADDITIONAL_RUNTIME_APT_COMMAND
         Additional command executed before runtime apt deps are installed.

 --runtime-apt-deps ADDITIONAL_RUNTIME_APT_DEPS
         The basic apt runtime dependencies to use when building the images.

 --additional-runtime-apt-deps ADDITIONAL_RUNTIME_DEPS
         Additional apt runtime dependencies to use when building the images.

 --additional-runtime-apt-envs ADDITIONAL_RUNTIME_APT_DEPS
         Additional environment variables set when adding runtime dependencies.

 Build options:

 --disable-mysql-client-installation
         Disables installation of the mysql client which might be problematic if you are building
         image in controlled environment. Only valid for production image.

 --disable-mssql-client-installation
         Disables installation of the mssql client which might be problematic if you are building
         image in controlled environment. Only valid for production image.

 --constraints-location
         Url to the constraints file. In case of the production image it can also be a path to the
         constraint file placed in 'docker-context-files' folder, in which case it has to be
         in the form of '/docker-context-files/<NAME_OF_THE_FILE>'

 --disable-pip-cache
         Disables GitHub PIP cache during the build. Useful if GitHub is not reachable during build.

 --install-from-docker-context-files
         This flag is used during image building. If it is used additionally to installing
         Airflow from PyPI, the packages are installed from the .whl and .tar.gz packages placed
         in the 'docker-context-files' folder. The same flag can be used during entering the image in
         the CI image - in this case also the .whl and .tar.gz files will be installed automatically

 -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.

 -r, --skip-rebuild-check
         Skips checking image for rebuilds. It will use whatever image is available locally/pulled.

 -L, --build-cache-local
         Uses local cache to build images. No pulled images will be used, but results of local
         builds in the Docker cache are used instead. This will take longer than when the pulled
         cache is used for the first time, but subsequent '--build-cache-local' builds will be
         faster as they will use mostly the locally build cache.

         This is default strategy used by the Production image builds.

 -U, --build-cache-pulled
         Uses images pulled from GitHub Container Registry to build images.
         Those builds are usually faster than when ''--build-cache-local'' with the exception if
         the registry images are not yet updated. The images are updated after successful merges
         to main.

         This is default strategy used by the CI image builds.

 -X, --build-cache-disabled
         Disables cache during docker builds. This is useful if you want to make sure you want to
         rebuild everything from scratch.

         This strategy is used by default for both Production and CI images for the scheduled
         (nightly) builds in CI.


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


 Detailed usage for command: prepare-provider-documentation


 breeze prepare-provider-documentation [FLAGS] [PACKAGE_ID ...]

       Prepares documentation files for provider packages.

       The command is optionally followed by the list of packages to generate readme for.
       If the first parameter is not formatted as a date, then today is regenerated.
       If no packages are specified, readme for all packages are generated.
       If no date is specified, current date + 3 days is used (allowing for PMC votes to pass).

       Examples:

       'breeze prepare-provider-documentation' or
       'breeze prepare-provider-documentation --version-suffix-for-pypi rc1'

       General form:

       'breeze prepare-provider-documentation <PACKAGE_ID> ...'

       * <PACKAGE_ID> is usually directory in the airflow/providers folder (for example
         'google' but in several cases, it might be one level deeper separated with
         '.' for example 'apache.hive'

 Flags:

 -S, --version-suffix-for-pypi SUFFIX
         Adds optional suffix to the version in the generated provider package. It can be used
         to generate rc1/rc2 ... versions of the packages to be uploaded to PyPI.

 -N, --version-suffix-for-svn SUFFIX
         Adds optional suffix to the generated names of package. It can be used to generate
         rc1/rc2 ... versions of the packages to be uploaded to SVN.

 --package-format PACKAGE_FORMAT

         Chooses format of packages to prepare.

         One of:

                both,sdist,wheel

         Default: both

 --non-interactive

         Runs the command in non-interactive mode.

 --generate-providers-issue

         Generate providers issue that should be created.

 -v, --verbose
         Show verbose information about executed docker, kind, kubectl, helm commands. Useful for
         debugging - when you run breeze with --verbose flags you will be able to see the commands
         executed under the hood and copy&paste them to your terminal to debug them more easily.

         Note that you can further increase verbosity and see all the commands executed by breeze
         by running 'export VERBOSE_COMMANDS="true"' before running breeze.

 --dry-run-docker
         Only show docker commands to execute instead of actually executing them. The docker
         commands are printed in yellow color.


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


 Detailed usage for command: prepare-provider-packages


 breeze prepare-provider-packages [FLAGS] [PACKAGE_ID ...]

       Prepares provider packages. You can provide (after --) optional list of packages to prepare.
       If no packages are specified, readme for all packages are generated. You can specify optional
       --version-suffix-for-svn flag to generate rc candidate packages to upload to SVN or
       --version-suffix-for-pypi flag to generate rc candidates for PyPI packages. You can also
       provide both suffixes in case you prepare alpha/beta versions. The packages are prepared in
       dist folder. Note that this command also cleans up dist folder before generating the packages
       so that you do not have accidental files there. This will delete airflow package if it is
       prepared there so make sure you run prepare-provider-packages first,
       and prepare-airflow-packages second.

       Examples:

       'breeze prepare-provider-packages' or
       'breeze prepare-provider-packages google' or
       'breeze prepare-provider-packages --package-format wheel google' or
       'breeze prepare-provider-packages --version-suffix-for-svn rc1 http google amazon' or
       'breeze prepare-provider-packages --version-suffix-for-pypi rc1 http google amazon'
       'breeze prepare-provider-packages --version-suffix-for-pypi a1
                                             --version-suffix-for-svn a1 http google amazon'

       General form:

       'breeze prepare-provider-packages [--package-format PACKAGE_FORMAT] \
             [--version-suffix-for-svn|--version-suffix-for-pypi] <PACKAGE_ID> ...'

       * <PACKAGE_ID> is usually directory in the airflow/providers folder (for example
         'google'), but in several cases, it might be one level deeper separated with '.'
         for example 'apache.hive'

 Flags:

 --package-format PACKAGE_FORMAT

         Chooses format of packages to prepare.

         One of:

                both,sdist,wheel

         Default: both

 -S, --version-suffix-for-pypi SUFFIX
         Adds optional suffix to the version in the generated provider package. It can be used
         to generate rc1/rc2 ... versions of the packages to be uploaded to PyPI.

 -N, --version-suffix-for-svn SUFFIX
         Adds optional suffix to the generated names of package. It can be used to generate
         rc1/rc2 ... versions of the packages to be uploaded to SVN.

 -v, --verbose
         Show verbose information about executed docker, kind, kubectl, helm commands. Useful for
         debugging - when you run breeze with --verbose flags you will be able to see the commands
         executed under the hood and copy&paste them to your terminal to debug them more easily.

         Note that you can further increase verbosity and see all the commands executed by breeze
         by running 'export VERBOSE_COMMANDS="true"' before running breeze.

 --dry-run-docker
         Only show docker commands to execute instead of actually executing them. The docker
         commands are printed in yellow color.


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


 Detailed usage for command: static-check


 breeze static-check [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 airflow-config-yaml airflow-providers-available airflow-provider-yaml-files-ok
                autoflake base-operator bats-tests bats-in-container-tests black blacken-docs
                boring-cyborg build build-providers-dependencies chart-schema-lint
                capitalized-breeze changelog-duplicates check-apache-license check-builtin-literals
                check-executables-have-shebangs check-extras-order check-hooks-apply
                check-integrations check-merge-conflict check-xml daysago-import-check
                debug-statements detect-private-key doctoc dont-use-safe-filter end-of-file-fixer
                fix-encoding-pragma flake8 flynt codespell forbid-tabs helm-lint identity
                incorrect-use-of-LoggingMixin insert-license isort json-schema language-matters
                lint-dockerfile lint-openapi markdownlint mermaid mixed-line-ending mypy mypy-helm
                no-providers-in-core-examples no-relative-imports persist-credentials-disabled
                pre-commit-descriptions pre-commit-hook-names pretty-format-json
                provide-create-sessions providers-changelogs providers-init-file
                providers-subpackages-init-file provider-yamls pydevd pydocstyle python-no-log-warn
                pyupgrade restrict-start_date rst-backticks setup-order setup-extra-packages
                shellcheck sort-in-the-wild sort-spelling-wordlist stylelint trailing-whitespace
                ui-lint update-breeze-file update-extras update-local-yml-file update-setup-cfg-file
                update-supported-versions update-versions vendor-k8s-json-schema
                verify-db-migrations-documented version-sync www-lint yamllint yesqa

       You can pass extra arguments including options 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'
       'breeze static-check mypy -- --all-files'

       To check all files that differ between you current branch and main run:

       'breeze static-check all -- --from-ref $(git merge-base main HEAD) --to-ref HEAD'

       To check all files that are in the HEAD commit run:

       'breeze static-check mypy -- --from-ref HEAD^ --to-ref HEAD'


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

       'breeze static-check mypy -- --help'


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


 Detailed usage for command: tests


 breeze tests [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. You can pass 'tests' as target to
       run all tests. For example:

       'breeze tests tests/core/test_core.py -- --logging-level=DEBUG'
       'breeze tests tests

 Flags:

 --test-type TEST_TYPE
         Type of the test to run. One of:

                All,Always,Core,Providers,API,CLI,Integration,Other,WWW,Postgres,MySQL,Helm,
                Quarantined

         Default: All


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


 Detailed usage for command: flags


       Explains in detail all the flags that can be used with breeze.


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


 Detailed usage for command: help


 breeze help

       Shows general help message for all commands.


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


 Detailed usage for command: help-all


 breeze help-all

       Shows detailed help for all commands and flags.


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


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

 Summary of all 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:

                3.7 3.8 3.9

 ****************************************************************************************************
  Choose backend to run for Airflow

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

                sqlite mysql postgres mssql

         Default: sqlite

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

                10 11 12 13

 --mysql-version MYSQL_VERSION
         MySql version used. One of:

                5.7 8

 --mssql-version MSSQL_VERSION
         MSSql version used. One of:

                2017-latest 2019-latest

 ****************************************************************************************************
  Enable production image

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

 ****************************************************************************************************
  Additional actions executed while entering breeze

 -d, --db-reset
         Resets the database at entry to the environment. 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 pinot rabbitmq redis statsd trino all

 --init-script INIT_SCRIPT_FILE
         Initialization script name - Sourced from files/airflow-breeze-config. Default value
         init.sh. It will be executed after the environment is configured and started.

 ****************************************************************************************************
  Additional actions executed while starting Airflow

 --load-example-dags
         Include Airflow example dags.

 --load-default-connections
         Include Airflow Default Connections.

 ****************************************************************************************************
  Cleanup options when stopping Airflow

 --preserve-volumes
         Use this flag if you would like to preserve data volumes from the databases used
         by the integrations. By default, those volumes are deleted, so when you run 'stop'
         or 'restart' commands you start from scratch, but by using this flag you can
         preserve them. If you want to delete those volumes after stopping Breeze, just
         run the 'breeze stop' again without this flag.

 ****************************************************************************************************
  Kind kubernetes and Kubernetes tests configuration(optional)

 Configuration for the KinD Kubernetes cluster and tests:

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

                image

         Default: image

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

                v1.21.1 v1.20.2

         Default: v1.21.1

 --kind-version KIND_VERSION
         Kind version - only used in case one of kind-cluster commands is used.
         One of:

                v0.11.1

         Default: v0.11.1

 --helm-version HELM_VERSION
         Helm version - only used in case one of kind-cluster commands is used.
         One of:

                v3.6.3

         Default: v3.6.3

 --executor EXECUTOR
         Executor to use in a kubernetes cluster.
         One of:

                KubernetesExecutor CeleryExecutor LocalExecutor CeleryKubernetesExecutor

         Default: KubernetesExecutor

 ****************************************************************************************************
  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.

 ****************************************************************************************************
  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.

 ****************************************************************************************************
  Install different Airflow version during PROD image build

 -a, --install-airflow-version INSTALL_AIRFLOW_VERSION
         Uses different version of Airflow when building PROD image.

                2.0.2 2.0.1 2.0.0 wheel sdist

 -t, --install-airflow-reference INSTALL_AIRFLOW_REFERENCE
         Installs Airflow directly from reference in GitHub when building PROD image.
         This can be a GitHub branch like main or v2-2-test, or a tag like 2.2.0rc1.

 --installation-method INSTALLATION_METHOD
         Method of installing Airflow in PROD image - either from the sources ('.')
         or from package 'apache-airflow' to install from PyPI.
         Default in Breeze is to install from sources. One of:

                . apache-airflow

 --upgrade-to-newer-dependencies
         Upgrades PIP packages to latest versions available without looking at the constraints.

 ****************************************************************************************************
  Use different Airflow version at runtime in CI image

 --use-airflow-version AIRFLOW_SPECIFICATION
         In CI image, installs Airflow at runtime from PIP released version or using
         the installation method specified (sdist, wheel, none). When 'none' is used,
         airflow is just removed. In this case airflow package should be added to dist folder
         and --use-packages-from-dist flag should be used.

                2.0.2 2.0.1 2.0.0 wheel sdist none

 --use-packages-from-dist
         In CI image, if specified it will look for packages placed in dist folder and
         it will install the packages after entering the image.
         This is useful for testing provider packages.

 ****************************************************************************************************
  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.

 ****************************************************************************************************
  Flags for building Docker images (both CI and production)

 -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 GitHub Container Registry 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.

 --check-if-base-python-image-updated
         Checks if Python base image from DockerHub has been updated vs the current python base
         image we store in GitHub Container Registry. Python images are updated regularly with
         security fixes, this switch will check if a new one has been released and will pull and
         prepare a new base python based on the latest one.

 --cleanup-docker-context-files
         Removes whl and tar.gz files created in docker-context-files before running the command.
         In case there are some files there it unnecessarily increases the context size and
         makes the COPY . always invalidated - if you happen to have those files when you build your
         image.

 Customization options:

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

         CI image:
                devel_ci

         Production image:
                amazon,async,celery,cncf.kubernetes,dask,docker,elasticsearch,ftp,google,google_auth,
                grpc,hashicorp,http,ldap,microsoft.azure,mysql,odbc,pandas,postgres,redis,sendgrid,
                sftp,slack,ssh,statsd,virtualenv

 --image-tag TAG
         Additional tag in the image.

 --skip-installing-airflow-providers-from-sources
         By default 'pip install' in Airflow 2.0 installs only the provider packages that
         are needed by the extras. When you build image during the development (which is
         default in Breeze) all providers are installed by default from sources.
         You can disable it by adding this flag but then you have to install providers from
         wheel packages via --use-packages-from-dist flag.

 --disable-pypi-when-building
         Disable installing Airflow from pypi when building. If you use this flag and want
         to install Airflow, you have to install it from packages placed in
         'docker-context-files' and use --install-from-docker-context-files flag.

 --additional-extras ADDITIONAL_EXTRAS
         Additional extras to pass to build images The default is no additional extras.

 --additional-python-deps ADDITIONAL_PYTHON_DEPS
         Additional python dependencies to use when building the images.

 --dev-apt-command DEV_APT_COMMAND
         The basic command executed before dev apt deps are installed.

 --additional-dev-apt-command ADDITIONAL_DEV_APT_COMMAND
         Additional command executed before dev apt deps are installed.

 --additional-dev-apt-deps ADDITIONAL_DEV_APT_DEPS
         Additional apt dev dependencies to use when building the images.

 --dev-apt-deps DEV_APT_DEPS
         The basic apt dev dependencies to use when building the images.

 --additional-dev-apt-deps ADDITIONAL_DEV_DEPS
         Additional apt dev dependencies to use when building the images.

 --additional-dev-apt-envs ADDITIONAL_DEV_APT_ENVS
         Additional environment variables set when adding dev dependencies.

 --runtime-apt-command RUNTIME_APT_COMMAND
         The basic command executed before runtime apt deps are installed.

 --additional-runtime-apt-command ADDITIONAL_RUNTIME_APT_COMMAND
         Additional command executed before runtime apt deps are installed.

 --runtime-apt-deps ADDITIONAL_RUNTIME_APT_DEPS
         The basic apt runtime dependencies to use when building the images.

 --additional-runtime-apt-deps ADDITIONAL_RUNTIME_DEPS
         Additional apt runtime dependencies to use when building the images.

 --additional-runtime-apt-envs ADDITIONAL_RUNTIME_APT_DEPS
         Additional environment variables set when adding runtime dependencies.

 Build options:

 --disable-mysql-client-installation
         Disables installation of the mysql client which might be problematic if you are building
         image in controlled environment. Only valid for production image.

 --disable-mssql-client-installation
         Disables installation of the mssql client which might be problematic if you are building
         image in controlled environment. Only valid for production image.

 --constraints-location
         Url to the constraints file. In case of the production image it can also be a path to the
         constraint file placed in 'docker-context-files' folder, in which case it has to be
         in the form of '/docker-context-files/<NAME_OF_THE_FILE>'

 --disable-pip-cache
         Disables GitHub PIP cache during the build. Useful if GitHub is not reachable during build.

 --install-from-docker-context-files
         This flag is used during image building. If it is used additionally to installing
         Airflow from PyPI, the packages are installed from the .whl and .tar.gz packages placed
         in the 'docker-context-files' folder. The same flag can be used during entering the image in
         the CI image - in this case also the .whl and .tar.gz files will be installed automatically

 -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.

 -r, --skip-rebuild-check
         Skips checking image for rebuilds. It will use whatever image is available locally/pulled.

 -L, --build-cache-local
         Uses local cache to build images. No pulled images will be used, but results of local
         builds in the Docker cache are used instead. This will take longer than when the pulled
         cache is used for the first time, but subsequent '--build-cache-local' builds will be
         faster as they will use mostly the locally build cache.

         This is default strategy used by the Production image builds.

 -U, --build-cache-pulled
         Uses images pulled from GitHub Container Registry to build images.
         Those builds are usually faster than when ''--build-cache-local'' with the exception if
         the registry images are not yet updated. The images are updated after successful merges
         to main.

         This is default strategy used by the CI image builds.

 -X, --build-cache-disabled
         Disables cache during docker builds. This is useful if you want to make sure you want to
         rebuild everything from scratch.

         This strategy is used by default for both Production and CI images for the scheduled
         (nightly) builds in CI.

 ****************************************************************************************************
  Flags for pulling/pushing Docker images (both CI and production)

 -g, --github-repository GITHUB_REPOSITORY
         GitHub repository used to pull, push images.
         Default: apache/airflow.




 -s, --github-image-id COMMIT_SHA
         <COMMIT_SHA> of the image. Images in GitHub registry are stored with those
         to be able to easily find the image for particular CI runs. Once you know the
         <COMMIT_SHA>, you can specify it in github-image-id flag and Breeze will
         automatically pull and use that image so that you can easily reproduce a problem
         that occurred in CI.

         Default: latest.

 ****************************************************************************************************
  Flags for running tests

 --test-type TEST_TYPE
         Type of the test to run. One of:

                All,Always,Core,Providers,API,CLI,Integration,Other,WWW,Postgres,MySQL,Helm,
                Quarantined

         Default: All

 ****************************************************************************************************
  Flags for generation of the provider packages

 -S, --version-suffix-for-pypi SUFFIX
         Adds optional suffix to the version in the generated provider package. It can be used
         to generate rc1/rc2 ... versions of the packages to be uploaded to PyPI.

 -N, --version-suffix-for-svn SUFFIX
         Adds optional suffix to the generated names of package. It can be used to generate
         rc1/rc2 ... versions of the packages to be uploaded to SVN.

 ****************************************************************************************************
  Increase verbosity of the scripts

 -v, --verbose
         Show verbose information about executed docker, kind, kubectl, helm commands. Useful for
         debugging - when you run breeze with --verbose flags you will be able to see the commands
         executed under the hood and copy&paste them to your terminal to debug them more easily.

         Note that you can further increase verbosity and see all the commands executed by breeze
         by running 'export VERBOSE_COMMANDS="true"' before running breeze.

 --dry-run-docker
         Only show docker commands to execute instead of actually executing them. The docker
         commands are printed in yellow color.

 ****************************************************************************************************
  Print detailed help message

 -h, --help
         Shows detailed help message for the command specified.

.. END BREEZE HELP MARKER