Shahar Epstein
f92281e1d0
* Drop Python 3.10 from CI, Breeze and the container images Python 3.10 reaches end of life in October 2026 and more and more of Airflow's dependencies have already dropped it, which makes the 3.10 leg the slowest and most fragile part of CI. This is the first layer of the stack that moves the baseline to Python 3.11: Breeze stops offering 3.10, the default Python for CI, Breeze and the images moves to 3.11, and the PGP path for verifying the Python tarball goes away because every remaining version ships Sigstore bundles. Python 3.10 stays in the historical version lists that Breeze uses to reason about older Airflow releases, and in the CI image restore action that release branches still rely on. The distributions still declare Python 3.10 in this layer; layer 7 bumps them once the code no longer carries 3.10-only constructs. Until then the provider metadata generator keeps its own 3.10-inclusive version list, and the prek minimum-Python check keeps 3.10 because its script header still pins it to a 3.10 interpreter until layer 2. The shared-distribution and scripts test jobs run uv without an interpreter pin, so uv picks the runner's system Python, which is 3.10 on the current images. Pinning them to the default CI Python keeps them on a supported interpreter regardless of the runner image. The image build speed check builds the CI image from the registry cache within a fixed budget. A PR that changes install_os_dependencies.sh or the embedded GPG keys misses the cache for the layer that compiles Python from source. That compile took about 4.5 minutes for Python 3.10 but 11 to 18 minutes for 3.11 and newer on hosted runners, so the budget is raised to fit a cold Python 3.11+ build. * Explain when to drop a Python version from the CI version list The comment above ALL_PYTHON_MAJOR_MINOR_VERSIONS described only keeping dropped versions so cherry-picks to older branches stay tested. Python 3.10 is removed from the list because the 3.10 drop is also cherry-picked to v3-4-test, so no release branch that still receives cherry-picks from main supports 3.10. The comment now spells out both phases so the next version drop follows the same rule. The Docker image changelog gets its Python 3.10 entry under Airflow 3.4.0 here, next to the image change itself, as was done for Python 3.9.
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Apache Airflow
| Category | Badges |
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| License |  |
| PyPI |    |
| Containers |    |
| Community |    |
| Dev tools |  |
| Version | Build Status |
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| Main |   |
| 3.x |   |
Apache Airflow (or simply Airflow) is a platform to programmatically author, schedule, and monitor workflows.
When workflows are defined as code, they become more maintainable, versionable, testable, and collaborative.
Use Airflow to author workflows (Dags) that orchestrate tasks. The Airflow scheduler executes your tasks on an array of workers while following the specified dependencies. Rich command line utilities make performing complex surgeries on Dags a snap. The rich user interface makes it easy to visualize pipelines running in production, monitor progress, and troubleshoot issues when needed.
Requirements
Apache Airflow is tested with:
| Main version (dev) | Stable version (3.3.2) | Deprecate version (2.11.2) | |
|---|---|---|---|
| Python | 3.11, 3.12, 3.13, 3.14 | 3.10, 3.11, 3.12, 3.13, 3.14 | 3.10, 3.11, 3.12 |
| Platform | AMD64/ARM64 | AMD64/ARM64 | AMD64/ARM64(*) |
| Kubernetes | 1.31, 1.32, 1.33, 1.34, 1.35, 1.36, 1.37 | 1.30, 1.31, 1.32, 1.33, 1.34, 1.35 | 1.26, 1.27, 1.28, 1.29, 1.30 |
| PostgreSQL | 14, 15, 16, 17, 18 | 14, 15, 16, 17, 18 | 12, 13, 14, 15, 16 |
| MySQL | 8.0, 8.4, Innovation | 8.0, 8.4, Innovation | 8.0, Innovation |
| SQLite | 3.15.0+ | 3.15.0+ | 3.15.0+ |
* Experimental
Note: MariaDB is not tested/recommended.
Note: SQLite is used in Airflow tests. Do not use it in production. We recommend using the latest stable version of SQLite for local development.
Note: Airflow currently can be run on POSIX-compliant Operating Systems. For development, it is regularly
tested on fairly modern Linux Distros and recent versions of macOS.
On Windows you can run it via WSL2 (Windows Subsystem for Linux 2) or via Linux Containers.
The work to add Windows support is tracked via #10388, but
it is not a high priority. You should only use Linux-based distros as "Production" execution environment
as this is the only environment that is supported. The only distro that is used in our CI tests and that
is used in the Community managed DockerHub image is
Debian Bookworm.
Getting started
Visit the official Airflow website documentation (latest stable release) for help with installing Airflow, getting started, or walking through a more complete tutorial.
Note: If you're looking for documentation for the main branch (latest development branch): you can find it on s.apache.org/airflow-docs.
For more information on Airflow Improvement Proposals (AIPs), visit the Airflow Wiki.
Documentation for dependent projects like provider distributions, Docker image, Helm Chart, you'll find it in the documentation index.
Installing from PyPI
We publish Apache Airflow as apache-airflow package in PyPI. Installing it however might be sometimes tricky
because Airflow is a bit of both a library and application. Libraries usually keep their dependencies open, and
applications usually pin them, but we should do neither and both simultaneously. We decided to keep
our dependencies as open as possible (in pyproject.toml) so users can install different versions of libraries
if needed. This means that pip install apache-airflow will not work from time to time or will
produce unusable Airflow installation.
To have repeatable installation, however, we keep a set of "known-to-be-working" constraint
files in the orphan constraints-main and constraints-2-0 branches. We keep those "known-to-be-working"
constraints files separately per major/minor Python version.
You can use them as constraint files when installing Airflow from PyPI. Note that you have to specify
correct Airflow tag/version/branch and Python versions in the URL.
- Installing just Airflow:
Note: Only
pipanduvinstallation is currently officially supported.
While it is possible to install Airflow with tools like Poetry or
pip-tools, they do not share the same workflow as
pip - especially when it comes to constraint vs. requirements management.
Installing via Poetry or pip-tools is not currently supported.
If you wish to install Airflow using those tools, you should use the constraint files and convert them to the appropriate format and workflow that your tool requires.
pip install 'apache-airflow==3.3.2' \
--constraint "https://raw.githubusercontent.com/apache/airflow/constraints-3.3.2/constraints-3.10.txt"
- Installing with extras (i.e., postgres, google)
pip install 'apache-airflow[postgres,google]==3.3.2' \
--constraint "https://raw.githubusercontent.com/apache/airflow/constraints-3.3.2/constraints-3.10.txt"
For information on installing provider distributions, check providers.
Official source code
Apache Airflow is an Apache Software Foundation (ASF) project, and our official source code releases:
- Follow the ASF Release Policy
- Can be downloaded from the ASF Distribution Directory
- Are cryptographically signed by the release manager
- Are officially voted on by the PMC members during the Release Approval Process
Following the ASF rules, the source packages released must be sufficient for a user to build and test the release provided they have access to the appropriate platform and tools.
Contributing
Want to help build Apache Airflow? Check out our contributors' guide for a comprehensive overview of how to contribute, including setup instructions, coding standards, and pull request guidelines.
If you can't wait to contribute, and want to get started asap, check out the contribution quickstart here!
Official Docker (container) images for Apache Airflow are described in images.
Voting Policy
- Commits need a +1 vote from a committer who is not the author
- When we do AIP voting, both PMC member's and committer's
+1sare considered a binding vote.
Who uses Apache Airflow?
We know about around 500 organizations that are using Apache Airflow (but there are likely many more) in the wild.
If you use Airflow - feel free to make a PR to add your organisation to the list.
Who maintains Apache Airflow?
Airflow is the work of the community, but the core committers/maintainers are responsible for reviewing and merging PRs as well as steering conversations around new feature requests. If you would like to become a maintainer, please review the Apache Airflow committer requirements.