Anyone waiting for the docker images is going to have to wait until tomorrow, (or perhaps even Monday) as the build isn’t currently behaving itself after the split of airflow-core and the new meta package airflow
#95 5.136 The conflict is caused by: #95 5.136 The user requested apache-airflow-core==3.0.0rc1.post1 #95 5.136 apache-airflow 3.0.0rc1.post1 depends on apache-airflow-core==3.0.0.rc1 It’s a quirk of the RC naming, we’ll fix it and get the docker images build. -ash > On 3 Apr 2025, at 22:12, Vikram Koka <vik...@astronomer.io.INVALID> wrote: > > Awesome! > Thank you Kaxil for all your work and also thank you to all the > contributors whose hard work and dedication made this release a reality. > > Best regards, > Vikram > > > On Thu, Apr 3, 2025 at 2:08 PM Kaxil Naik <kaxiln...@gmail.com> wrote: > >> Docker images will be out soon too. >> >> On Fri, 4 Apr 2025 at 02:35, Kaxil Naik <kaxiln...@gmail.com> wrote: >> >>> Hey fellow Airflowers, >>> >>> I am thrilled to announce the availability of Apache Airflow 3.0.0rc1 & >> *Task >>> SDK 1.0.0rc1* for testing! Airflow 3.0 marks a significant milestone as >>> the first major release in over four years, introducing improvements that >>> enhance user experience, task execution, and system scalability. >>> >>> This email is calling for a vote on the release, >>> which will last at least 7 days until 10th April. >>> and until 3 binding +1 votes have been received. >>> >>> Consider this my (non-binding) +1. >>> >>> Airflow 3.0.0rc1 is available at: >>> https://dist.apache.org/repos/dist/dev/airflow/3.0.0rc1/ >>> >>> >>> "apache-airflow" Meta package: >>> >>> >>> - *apache-airflow-3.0.0-source.tar.gz* is a source release that comes >>> with INSTALL instructions. >>> - *apache-airflow-3.0.0.tar.gz* is the binary Python "sdist" release. >>> - *apache_airflow-3.0.0-py3-none-any.whl* is the binary Python >>> wheel "binary" release. >>> >>> "apache-airflow-core" package >>> >>> >>> - *apache_airflow_core-3.0.0.tar.gz* is the binary Python "sdist" >>> release. >>> - *apache_airflow_3.0.0-py3-none-any.whl* is the binary Python >>> wheel "binary" release. >>> >>> >>> Task SDK 1.0.0rc1 is available at: >>> https://dist.apache.org/repos/dist/dev/airflow/task-sdk/1.0.0rc1/ >>> >>> >>> "apache-airflow-task-sdk" package >>> >>> - *apache-airflow-task-sdk-1.0.0-source.tar.gz* is a source release >>> - *apache_airflow_task_sdk-1.0.0.tar.gz* is the binary Python "sdist" >>> release. >>> - *apache_airflow_task_sdk-1.0.0-py3-none-any.whl* is the binary >>> Python wheel "binary" release. >>> >>> >>> >>> Public keys are available at: >>> https://dist.apache.org/repos/dist/release/airflow/KEYS >>> >>> Please vote accordingly: >>> >>> [ ] +1 approve >>> [ ] +0 no opinion >>> [ ] -1 disapprove with the reason >>> >>> Only votes from PMC members are binding, but all members of the community >>> are encouraged to test the release and vote with "(non-binding)". >>> >>> The test procedure for PMC members is described in: >>> >>> >> https://github.com/apache/airflow/blob/main/dev/README_RELEASE_AIRFLOW.md\#verify-the-release-candidate-by-pmc-members >>> >>> The test procedure for contributors and members of the community who >> would >>> like to test this RC is described in: >>> >>> >> https://github.com/apache/airflow/blob/main/dev/README_RELEASE_AIRFLOW.md\#verify-the-release-candidate-by-contributors >>> >>> Please note that the version number excludes the 'rcX' string, so it's >> now >>> simply 3.0.0 for Airflow package and 1.0.0 for Task SDK. This will allow >>> us to rename the artifact without modifying >>> the artifact checksums when we actually release. >>> >>> Release Notes: >>> https://github.com/apache/airflow/blob/3.0.0rc1/RELEASE_NOTES.rst >>> >>> >>> *Testing Instructions using PyPI*: >>> >>> You can build a virtualenv that installs this, and other required >> packages >>> (e.g. task sdk), like this: >>> >>> ``` >>> >>> uv venv >>> >>> uv pip install apache-airflow apache-airflow-providers-standard==0.3.0rc1 >>> --pre >>> >>> ``` >>> >>> Get Involved >>> >>> We encourage the community to test this release and report any issues or >>> feedback. Your contributions help us ensure a stable and reliable Airflow >>> 3.0.0 release. Please report issues using Github at >>> https://github.com/apache/airflow/issues and mark that this is an issue >>> in 3.0.0. For an updated list of all known issues in the beta can also be >>> found in the above link with the label “affected_version:3.0.0rc” >>> >>> A huge thank you to all the contributors who have worked on this >> milestone >>> release! >>> Best, >>> Kaxil >>> >>> --- >>> What's new in 3.0.0? >>> >>> Notable Features >>> >>> DAG versioning & Bundles >>> >>> Airflow now tracks DAG versions, offering better visibility into >>> historical DAG changes and execution states. The introduction of DAG >>> Bundles ensures tasks run with the correct code version, even as DAGs >>> evolve. >>> >>> Modern Web Application >>> >>> The UI has been rebuilt using React and a complete API-driven structure, >>> improving maintainability and extensibility. It includes a new >>> component-based design system and an enhanced information architecture. A >>> new React-based plugin system supports custom widgets, improved workflow >>> visibility, and integration with external tools. >>> >>> Task Execution Interface >>> >>> Airflow 3.0 adopts a client / server architecture, decoupling task >>> execution from the internal meta-database via API-based interaction. This >>> allows for remote execution across networks, multi-language support, >>> enhanced security, and better dependency management. The Edge Executor >>> further enables seamless remote task execution without direct database >>> connections. >>> >>> Data Assets & Asset-Centric Syntax >>> >>> Airflow 3.0 enhances dataset management by introducing Data Assets, >>> expanding beyond tables and files to include ML models and more. Assets >> can >>> be explicitly defined using the @asset decorator, simplifying tracking >> and >>> dependencies. >>> >>> External Event-Driven Scheduling >>> >>> Airflow now supports event-driven DAG triggers from external sources like >>> message queues and blob stores. This builds upon dataset scheduling and >>> enhances integration with the external data ecosystem. >>> >>> >> --------------------------------------------------------------------- To unsubscribe, e-mail: dev-unsubscr...@airflow.apache.org For additional commands, e-mail: dev-h...@airflow.apache.org
