BREEZE.rst

• Airflow Breeze CI environment
• Prerequisites
  • Docker Desktop
  • Docker Compose
  • Docker in WSL 2
  • The pipx tool
• Resources required
  • Memory
  • Disk
  • Cleaning the environment
• Installation
• Running Breeze for the first time
  • Customize your environment
• Running tests in the CI interactive environment
• Choosing different Breeze environment configuration
• Starting complete Airflow installation
• Troubleshooting
• Uses of the Airflow Breeze environment
  • Development tasks
  • Tests
  • Kubernetes tests
  • CI Image tasks
  • PROD Image tasks
  • Configuration and maintenance
  • Release tasks
• Details of Breeze usage
  • Database volumes in Breeze
  • Image cleanup
  • Launching multiple terminals
  • Additional tools
  • Launching Breeze integrations
  • Managing CI images
  • Verifying providers
  • Preparing packages
  • Managing Production images
  • Releasing Production images to DockerHub
  • Running static checks
  • Building the Documentation
  • Generating constraints
  • Using local virtualenv environment in Your Host IDE
  • Running docker-compose tests
  • Running Kubernetes tests
  • Stopping the interactive environment
• Resource check
• Freeing the space
• Tracking backtracking issues for CI builds
• Internal details of Breeze
  • Airflow directory structure inside container
  • Running Arbitrary commands in the Breeze environment
  • Running "Docker Compose" commands
  • Setting default answers for user interaction
  • Fixing File/Directory Ownership
  • Mounting Local Sources to Breeze
  • Port Forwarding
  • Managing Dependencies
    • Installing Dependencies for a Single Breeze Session
    • Adding Dependencies Permanently
    • Incremental apt Dependencies in the Dockerfile.ci during development
• Recording command output
• Uninstalling Breeze

Airflow Breeze CI environment

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 call 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.

Note

We are currently migrating old Bash-based ./breeze-legacy to the Python-based breeze. Some of the commands are already converted to breeze, but some old commands should use breeze-legacy. The documentation mentions when ./breeze-legacy is involved.

The new breeze after installing is available on your PATH and you should launch it simply as breeze <COMMAND> <FLAGS>. Previously you had to prepend breeze with ./ but this is not needed any more. For convenience, we will keep ./breeze script for a while to run the new breeze and you can still use the legacy Breeze with ./breeze-legacy.

Watch the video below about Airflow Breeze. It explains the motivation for Breeze and screencast all its uses. The video describes old ./breeze-legacy (in video it still called ./breeze ).

Prerequisites

Docker Desktop

• Version: Install the latest stable Docker Desktop and add make sure it is in your PATH. Breeze detects if you are using version that is too old and warns you to upgrade.
• 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 20 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 command. Also see pruning instructions from Docker.

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

Docker Compose

• Version: Install the latest stable `Docker Compose<https://docs.docker.com/compose/install/>`_ and add it to the PATH. Breeze detects if you are using version that is too old and warns you to upgrade.
• Permissions: Configure permission to be able to run the docker-compose command by your user.

Docker in WSL 2

• WSL 2 installation :

  Install WSL 2 and a Linux Distro (e.g. Ubuntu) see WSL 2 Installation Guide for details.

• Docker Desktop installation :

  Install Docker Desktop for Windows. For Windows Home follow the Docker Windows Home Installation Guide. For Windows Pro, Enterprise, or Education follow the Docker Windows Installation Guide.

• Docker setting :

  WSL integration needs to be enabled

• 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.

The pipx tool

We are using pipx tool to install and manage Breeze. The pipx tool is created by the creators of pip from Python Packaging Authority

Install pipx

pip install --user pipx

Breeze, is not globally accessible until your PATH is updated. Add <USER FOLDER>.localbin as a variable environments. This can be done automatically by the following command (follow instructions printed).

pipx ensurepath

Resources required

Memory

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.

Disk

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 breeze cleanup 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

There is a command breeze resource-check that you can run to check available resources. See below for details.

Cleaning the environment

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

To clean up the Docker environment:

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

2. Run the breeze cleanup 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

Run this command to install Breeze (make sure to use -e flag):

pipx install -e ./dev/breeze

Once this is complete, you should have breeze binary on your PATH and available to run by breeze command.

Those are all available commands for Breeze and details about the commands are described below:

Breeze installed this way is linked to your checked out sources of Airflow so Breeze will automatically use latest version of sources from ./dev/breeze. Sometimes, when dependencies are updated breeze commands with offer you to self-upgrade (you just need to answer y when asked).

You can always run such self-upgrade at any time:

breeze self-upgrade

Those are all available flags of self-upgrade command:

If you have several checked out Airflow sources, Breeze will warn you if you are using it from a different source tree and will offer you to re-install from those sources - to make sure that you are using the right version.

You can skip Breeze's upgrade check by setting SKIP_BREEZE_UPGRADE_CHECK variable to non empty value.

By default Breeze works on the version of Airflow that you run it in - in case you are outside of the sources of Airflow and you installed Breeze from a directory - Breeze will be run on Airflow sources from where it was installed.

You can run breeze version command to see where breeze installed from and what are the current sources that Breeze works on

Those are all available flags of version command:

Running Breeze for the first time

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. The breeze command comes with a built-in bash/zsh/fish 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 (follow the instructions printed). The command will warn you and not reinstall autocomplete if you already did, but you can also force reinstalling the autocomplete via:

breeze setup-autocomplete --force

Those are all available flags of setup-autocomplete command:

Customize your environment

When you enter the Breeze environment, automatically an environment file is sourced from files/airflow-breeze-config/variables.env.

You can also add files/airflow-breeze-config/init.sh and the script will be sourced always when you enter Breeze. For example you can add pip install commands if you want to install custom dependencies - but there are no limits to add your own customizations.

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 copy any .whl or .sdist packages to dist and when you pass --use-packages-from-dist flag as wheel or sdist line parameter, breeze will automatically install the packages found there when you enter Breeze.

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.

Running tests in the CI interactive environment

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

Here is the part of Breeze video which is relevant (note that it refers to the old ./breeze-legacy command and it is not yet available in the new breeze command):

Choosing different Breeze environment configuration

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 3.7 tests with MySQL as backend and with mysql version 8 as follows:

breeze --python 3.7 --backend mysql --mysql-version 8

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.

You can see which value of the parameters that can be stored persistently in cache marked with >VALUE< in the help of the commands.

Another part of configuration is enabling/disabling cheatsheet, asciiart. The cheatsheet and asciiart can be disabled - they are "nice looking" and cheatsheet contains useful information for first time users but eventually you might want to disable both if you find it repetitive and annoying.

With the config setting colour-blind-friendly communication for Breeze messages. By default we communicate with the users about information/errors/warnings/successes via colour-coded messages, but we can switch it off by passing --no-colour to config in which case the messages to the user printed by Breeze will be printed using different schemes (italic/bold/underline) to indicate different kind of messages rather than colours.

Here is the part of Breeze video which is relevant (note that it refers to the old ./breeze-legacy command but it is very similar to current breeze command):

Those are all available flags of config command:

You can also dump hash of the configuration options used - this is mostly use to generate the dump of help of the commands only when they change.

Starting complete Airflow installation

For testing Airflow oyou often want to start multiple components (in multiple terminals). Breeze has built-in start-airflow command that start breeze container, launches multiple terminals using tmux and launches all Airflow necessary components in those terminals.

You can also use it to start any released version of Airflow from PyPI with the --use-airflow-version flag.

breeze --python 3.7 --backend mysql --use-airflow-version 2.2.5 start-airflow

Those are all available flags of start-airflow command:

Troubleshooting

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

1. If you are on macOS, check if you have enough disk space for Docker (Breeze will warn you if not).
2. Stop Breeze with breeze stop.
3. Delete the .build directory and run breeze build-image.
4. Clean up Docker images via breeze cleanup command.
5. Restart your Docker Engine and try again.
6. Restart your machine and try again.
7. Re-install Docker Desktop 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.

Uses of the Airflow Breeze environment

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

Development tasks

Those are commands mostly used by contributors:

• Execute arbitrary command in the test environment with breeze shell command
• Enter interactive shell in CI container when shell (or no command) is specified
• Start containerised, development-friendly airflow installation with breeze start-airflow command
• Build documentation with breeze build-docs command
• Initialize local virtualenv with ./scripts/tools/initialize_virtualenv.py command
• Run static checks with autocomplete support breeze static-checks command
• Run test specified with breeze tests command
• Build CI docker image with breeze build-image command
• Cleanup breeze with breeze cleanup command

Additional management tasks:

• Join running interactive shell with breeze exec command
• Stop running interactive environment with breeze stop command
• Execute arbitrary docker-compose command with ./breeze-legacy docker-compose command

Tests

• Run docker-compose tests with breeze docker-compose-tests command.
• Run test specified with breeze tests command.

Kubernetes tests

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

CI Image tasks

The image building is usually run for users automatically when needed, but sometimes Breeze users might want to manually build, pull or verify the CI images.

• Build CI docker image with breeze build-image command
• Pull CI images in parallel breeze pull-image command
• Verify CI image breeze verify-image command

PROD Image tasks

Users can also build Production images when they are developing them. However when you want to use the PROD image, the regular docker build commands are recommended. See building the image

• Build PROD image with breeze build-prod-image command
• Pull PROD image in parallel breeze pull-prod-image command
• Verify CI image breeze verify-prod-image command

Configuration and maintenance

• Cleanup breeze with breeze cleanup command
• Self-upgrade breeze with breeze self-upgrade command
• Setup autocomplete for Breeze with breeze setup-autocomplete command
• Checking available resources for docker with breeze resource-check command
• Freeing space needed to run CI tests with breeze free-space command
• Fixing ownership of files in your repository with breeze fix-ownership command
• Print Breeze version with breeze version command
• Outputs hash of commands defined by breeze with command-hash-export (useful to avoid needless regeneration of Breeze images)

Release tasks

Maintainers also can use Breeze for other purposes (those are commands that regular contributors likely do not need or have no access to run). Those are usually connected with releasing Airflow:

• Prepare cache for CI: breeze build-image --prepare-build-cache and ``breeze build-prod image --prepare-build-cache``(needs buildx plugin and write access to registry ghcr.io)
• Generate constraints with breeze generate-constraints (needed when conflicting changes are merged)
• Prepare airflow packages: breeze prepare-airflow-package (when releasing Airflow)
• Verify providers: breeze verify-provider-packages (when releasing provider packages) - including importing the providers in an earlier airflow version.
• Prepare provider documentation breeze prepare-provider-documentation and prepare provider packages breeze prepare-provider-packages (when releasing provider packages)
• Finding the updated dependencies since the last successful build when we have conflict with breeze find-newer-dependencies command
• Release production images to DockerHub with breeze release-prod-images command

Details of Breeze usage

Database volumes in Breeze

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. You can also preserve the volumes by adding flag --preserve-volumes when you run the command. Then, next time when you start Breeze, it will have the data pre-populated.

Those are all available flags of stop command:

Image cleanup

Breeze uses docker images heavily and those images are rebuild periodically. This might cause extra disk usage by the images. If you need to clean-up the images periodically you can run breeze cleanup command (by default it will skip removing your images before cleaning up but you can also remove the images to clean-up everything by adding --all).

Those are all available flags of cleanup command:

Launching multiple terminals

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

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

Here is the part of Breeze video which is relevant:

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.

Here is the part of Breeze video which is relevant:

Those are all available flags of exec command:

Additional tools

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:

• install_aws.sh - installs the AWS CLI including
• install_az.sh - installs the Azure CLI including
• install_gcloud.sh - installs the Google Cloud SDK including gcloud, gsutil.
• install_imgcat.sh - installs imgcat - Inline Images Protocol for iTerm2 (Mac OS only)
• install_java.sh - installs the OpenJDK 8u41
• install_kubectl.sh - installs the Kubernetes command-line tool, kubectl
• install_snowsql.sh - installs SnowSQL
• install_terraform.sh - installs Terraform

Launching Breeze integrations

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

Here is the part of Breeze video which is relevant (note that it refers to the old ./breeze-legacy command but it is very similar to current breeze command):

Managing CI images

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

Here is the part of Breeze video which is relevant (note that it refers to the old ./breeze-legacy command but it is very similar to current breeze command):

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.

Those are all available flags of build-image command:

You can also pull the CI images locally in parallel with optional verification.

Those are all available flags of pull-image command:

Finally, you can verify CI image by running tests - either with the pulled/built images or with an arbitrary image.

Those are all available flags of verify-image command:

Verifying providers

Breeze can also be used to verify if provider classes are importable and if they are following the right naming conventions. This happens automatically on CI but you can also run it manually.

breeze verify-provider-packages

You can also run the verification with an earlier airflow version to check for compatibility.

breeze verify-provider-packages --use-airflow-version 2.1.0

All the command parameters are here:

Preparing packages

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 documentation files
• preparing Airflow packages
• preparing Provider packages

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

The below example perform documentation preparation for provider packages.

breeze prepare-provider-documentation

By default, the documentation preparation runs package verification to check if all packages are importable, but you can add --skip-package-verification to skip it.

breeze prepare-provider-documentation --skip-package-verification

You can also add --answer yes to perform non-interactive build.

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 prepare airflow packages using breeze:

breeze prepare-airflow-package

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-package --package-format=wheel

Managing Production images

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 using build-prod-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-prod-image --help, but here typical examples are presented:

breeze build-prod-image --additional-extras "jira"

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

breeze build-prod-image --additional-python-deps "torchio==0.17.10"

This install additional pypi dependency - torchio in specified version.

breeze build-prod-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-prod-image --python 3.7 --additional-dev-deps "libasound2-dev" \
   --additional-runtime-apt-deps "libasound2"

Same as above but uses python 3.7.

Those are all available flags of build-prod-image command:

Here is the part of Breeze video which is relevant (note that it refers to the old ./breeze-legacy command but it is very similar to current breeze command):

You can also pull PROD images in parallel with optional verification.

Those are all available flags of pull-prod-image command:

Finally, you can verify PROD image by running tests - either with the pulled/built images or with an arbitrary image.

Those are all available flags of verify-prod-image command:

Releasing Production images to DockerHub

The Production image can be released by release managers who have permissions to push the image. This happens only when there is an RC candidate or final version of Airflow released.

You release "regular" and "slim" images as separate steps.

Releasing "regular" images:

breeze release-prod-images --airflow-version 2.4.0

Or "slim" images:

breeze release-prod-images --airflow-version 2.4.0 --slim-images

By default when you are releasing the "final" image, we also tag image with "latest" tags but this step can be skipped if you pass the --skip-latest flag.

These are all of the available flags for the release-prod-images command:

Running static checks

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-checks -t mypy

The above will run mypy check for currently staged files.

You can also pass specific pre-commit flags for example --all-files :

breeze static-checks -t mypy --all-files

The above will run mypy check for all files.

There is a convenience --last-commit flag that you can use to run static check on last commit only:

breeze static-checks -t mypy --last-commit

The above will run mypy check for all files in the last commit.

There is another convenience --commit-ref flag that you can use to run static check on specific commit:

breeze static-checks -t mypy --commit-ref 639483d998ecac64d0fef7c5aa4634414065f690

The above will run mypy check for all files in the 639483d998ecac64d0fef7c5aa4634414065f690 commit. Any commit-ish reference from Git will work here (branch, tag, short/long hash etc.)

If you ever need to get a list of the files that will be checked (for troubleshooting) use these commands:

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

Those are all available flags of static-checks command:

Here is the part of Breeze video which is relevant (note that it refers to the old ./breeze-legacy command but it is very similar to current breeze command):

Note

When you run static checks, some of the artifacts (mypy_cache) is stored in docker-compose volume so that it can speed up static checks execution significantly. However, sometimes, the cache might get broken, in which case you should run breeze stop to clean up the cache.

Building the Documentation

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

breeze build-docs

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

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.

Those are all available flags of build-docs command:

Here is the part of Breeze video which is relevant (note that it refers to the old ./breeze-legacy command but it is very similar to current breeze command):

Generating constraints

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 all or selected python version and single constraint mode like this:

Warning

In order to generate constraints, you need to build all images with --upgrade-to-newer-dependencies flag - for all python versions.

breeze generate-constraints --airflow-constraints-mode constraints

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.

• "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.
• "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.

Those are all available flags of generate-constraints command:

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 Refreshing CI Cache 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.

Using local virtualenv environment in Your Host IDE

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

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:

./scripts/tools/initialize_virtualenv.py

Warning

Make sure that you use the right Python version in this command - matching the Python version you have in your local virtualenv. If you don't, you will get strange conflicts.

4. 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.

Here is the part of Breeze video which is relevant (note that it refers to the old ./breeze-legacy but it is not available in the breeze command):

Running docker-compose tests

You can use Breeze to run docker-compose tests. Those tests are run using Production image and they are running test with the Quick-start docker compose we have.

Running Kubernetes tests

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.

Here is the part of Breeze video which is relevant (note that it refers to the old ./breeze-legacy command and it is not yet available in the current breeze command):

Stopping the interactive environment

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

breeze stop

Those are all available flags of stop command:

Here is the part of Breeze video which is relevant (note that it refers to the old ./breeze-legacy command but it is very similar to current breeze command):

Resource check

Breeze requires certain resources to be available - disk, memory, CPU. When you enter Breeze's shell, the resources are checked and information if there is enough resources is displayed. However you can manually run resource check any time by breeze resource-check command.

Those are all available flags of resource-check command:

Freeing the space

When our CI runs a job, it needs all memory and disk it can have. We have a Breeze command that frees the memory and disk space used. You can also use it clear space locally but it performs a few operations that might be a bit invasive - such are removing swap file and complete pruning of docker disk space used.

Those are all available flags of free-space command:

Tracking backtracking issues for CI builds

When our CI runs a job, we automatically upgrade our dependencies in the main build. However, this might lead to conflicts and pip backtracking for a long time (possibly forever) for dependency resolution. Unfortunately those issues are difficult to diagnose so we had to invent our own tool to help us with diagnosing them. This tool is find-newer-dependencies and it works in the way that it helps to guess which new dependency might have caused the backtracking. The whole process is described in tracking backtracking issues.

Those are all available flags of find-newer-dependencies command:

Internal details of Breeze

Airflow directory structure inside container

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.

Running Arbitrary commands in the Breeze environment

To run other commands/executables inside the Breeze Docker-based environment, use the breeze shell command.

breeze shell "ls -la"

Those are all available flags of shell command:

Running "Docker Compose" commands

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

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

Setting default answers for user interaction

Sometimes during the build, you are asked whether to perform an action, skip it, or quit. This happens when rebuilding or removing an image and in few other cases - actions that take a lot of time or could be potentially destructive. You can force answer to the questions by providing an --answer flag in the commands that support it.

For automation scripts, you can export the ANSWER variable (and set it to y, n, q, yes, no, quit - in all case combinations).

export ANSWER="yes"

Fixing File/Directory Ownership

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

breeze fix-ownership

Those are all available flags of fix-ownership command:

Mounting Local Sources to Breeze

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

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

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

Port Forwarding

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

• 12322 -> forwarded to Airflow ssh server -> airflow:22
• 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
• 21433 -> forwarded to MSSQL database -> mssql:1443
• 26379 -> forwarded to Redis broker -> redis:6379

You can connect to these ports/databases using:

• ssh connection for remote debugging: ssh -p 12322 [email protected] pw: airflow
• 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
• MSSQL: jdbc:sqlserver://127.0.0.1:21433;databaseName=airflow;user=sa;password=Airflow123
• Redis: redis://127.0.0.1:26379/0

If you do not use start-airflow command, you can start the webserver manually with the airflow webserver command if you want to run it. 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:

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

• SSH_PORT
• WEBSERVER_HOST_PORT
• POSTGRES_HOST_PORT
• MYSQL_HOST_PORT
• MSSQL_HOST_PORT
• FLOWER_HOST_PORT
• REDIS_HOST_PORT

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

Managing Dependencies

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

Installing Dependencies for a Single Breeze Session

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

Adding Dependencies Permanently

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

Incremental apt Dependencies in the Dockerfile.ci during development

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.

Recording command output

Breeze uses built-in capability of rich to record and print the command help as an svg file. It's enabled by setting RECORD_BREEZE_OUTPUT_FILE to a file name where it will be recorded. By default it records the screenshots with default characters width and with "Breeze screenshot" title, but you can override it with RECORD_BREEZE_WIDTH and RECORD_BREEZE_TITLE variables respectively.

Uninstalling Breeze

Breeze was installed with pipx, with pipx list, you can list the installed packages. Once you have the name of breeze package you can proceed to uninstall it.

pipx list

This will also remove breeze from the folder: ${HOME}.local/bin/

pipx uninstall apache-airflow-breeze