Use a trimmed version of README.md for PyPI

.pre-commit-config.yaml

@@ -761,6 +761,12 @@ repos:
         exclude: ^tests/system/providers/google/cloud/bigquery/example_bigquery_queries\.py$
         pass_filenames: true
         additional_dependencies: ['rich>=12.4.4']
+      - id: generate-pypi-readme
+        name: Generate PyPI README
+        entry: ./scripts/ci/pre_commit/pre_commit_generate_pypi_readme.py
+        language: python
+        files: ^README\.md$
+        pass_filenames: false
       - id: lint-markdown
         name: Run markdownlint
         description: Checks the style of Markdown files.

README.md

@@ -17,6 +17,7 @@
  under the License.
 -->
 
+<!-- START Apache Airflow, please keep comment here to allow auto update of PyPI readme.md -->
 # Apache Airflow
 
 [![PyPI version](https://badge.fury.io/py/apache-airflow.svg)](https://badge.fury.io/py/apache-airflow)
@@ -40,6 +41,7 @@ When workflows are defined as code, they become more maintainable, versionable,
 
 Use Airflow to author workflows as directed acyclic graphs (DAGs) of 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.
 
+<!-- END Apache Airflow, please keep comment here to allow auto update of PyPI readme.md -->
 <!-- START doctoc generated TOC please keep comment here to allow auto update -->
 <!-- DON'T EDIT THIS SECTION, INSTEAD RE-RUN doctoc TO UPDATE -->
 **Table of contents**
@@ -59,7 +61,7 @@ Use Airflow to author workflows as directed acyclic graphs (DAGs) of tasks. The
 - [Approach to dependencies of Airflow](#approach-to-dependencies-of-airflow)
 - [Contributing](#contributing)
 - [Who uses Apache Airflow?](#who-uses-apache-airflow)
-- [Who Maintains Apache Airflow?](#who-maintains-apache-airflow)
+- [Who maintains Apache Airflow?](#who-maintains-apache-airflow)
 - [Can I use the Apache Airflow logo in my presentation?](#can-i-use-the-apache-airflow-logo-in-my-presentation)
 - [Airflow merchandise](#airflow-merchandise)
 - [Links](#links)
@@ -82,6 +84,7 @@ Airflow is not a streaming solution, but it is often used to process real-time d
 - **Elegant**: Airflow pipelines are lean and explicit. Parameterizing your scripts is built into the core of Airflow using the powerful **Jinja** templating engine.
 - **Scalable**: Airflow has a modular architecture and uses a message queue to orchestrate an arbitrary number of workers.
 
+<!-- START Requirements, please keep comment here to allow auto update of PyPI readme.md -->
 ## Requirements
 
 Apache Airflow is tested with:
@@ -114,6 +117,8 @@ as this is the only environment that is supported. The only distro that is used
 is used in the [Community managed DockerHub image](https://hub.docker.com/p/apache/airflow) is
 `Debian Bullseye`.
 
+<!-- END Requirements, please keep comment here to allow auto update of PyPI readme.md -->
+<!-- START Getting started, please keep comment here to allow auto update of PyPI readme.md -->
 ## Getting started
 
 Visit the official Airflow website documentation (latest **stable** release) for help with
@@ -128,6 +133,8 @@ the [Airflow Wiki](https://cwiki.apache.org/confluence/display/AIRFLOW/Airflow+I
 
 Documentation for dependent projects like provider packages, Docker image, Helm Chart, you'll find it in [the documentation index](https://airflow.apache.org/docs/).
 
+<!-- END Getting started, please keep comment here to allow auto update of PyPI readme.md -->
+<!-- START Installing from PyPI, please keep comment here to allow auto update of PyPI readme.md -->
 ## Installing from PyPI
 
 We publish Apache Airflow as `apache-airflow` package in PyPI. Installing it however might be sometimes tricky
@@ -177,6 +184,8 @@ pip install 'apache-airflow[postgres,google]==2.7.0' \
 For information on installing provider packages, check
 [providers](http://airflow.apache.org/docs/apache-airflow-providers/index.html).
 
+<!-- END Installing from PyPI, please keep comment here to allow auto update of PyPI readme.md -->
+<!-- START Official source code, please keep comment here to allow auto update of PyPI readme.md -->
 ## Official source code
 
 Apache Airflow is an [Apache Software Foundation](https://www.apache.org) (ASF) project,
@@ -191,6 +200,7 @@ and our official source code releases:
 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.
 
+<!-- END Official source code, please keep comment here to allow auto update of PyPI readme.md -->
 ## Convenience packages
 
 There are other ways of installing and using Airflow. Those are "convenience" methods - they are
@@ -409,25 +419,31 @@ Those `extras` and `providers` dependencies are maintained in `provider.yaml` of
 By default, we should not upper-bound dependencies for providers, however each provider's maintainer
 might decide to add additional limits (and justify them with comment).
 
+<!-- START Contributing, please keep comment here to allow auto update of PyPI readme.md -->
 ## Contributing
 
 Want to help build Apache Airflow? Check out our [contributing documentation](https://github.com/apache/airflow/blob/main/CONTRIBUTING.rst).
 
 Official Docker (container) images for Apache Airflow are described in [IMAGES.rst](https://github.com/apache/airflow/blob/main/IMAGES.rst).
 
+<!-- END Contributing, please keep comment here to allow auto update of PyPI readme.md -->
+<!-- START Who uses Apache Airflow, please keep comment here to allow auto update of PyPI readme.md -->
 ## Who uses Apache Airflow?
 
 More than 400 organizations are using Apache Airflow
 [in the wild](https://github.com/apache/airflow/blob/main/INTHEWILD.md).
 
-## Who Maintains Apache Airflow?
+<!-- END Who uses Apache Airflow, please keep comment here to allow auto update of PyPI readme.md -->
+<!-- START Who maintains Apache Airflow, please keep comment here to allow auto update of PyPI readme.md -->
+## Who maintains Apache Airflow?
 
 Airflow is the work of the [community](https://github.com/apache/airflow/graphs/contributors),
 but the [core committers/maintainers](https://people.apache.org/committers-by-project.html#airflow)
 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](https://github.com/apache/airflow/blob/main/COMMITTERS.rst#guidelines-to-become-an-airflow-committer).
 
+<!-- END Who maintains Apache Airflow, please keep comment here to allow auto update of PyPI readme.md -->
 ## Can I use the Apache Airflow logo in my presentation?
 
 Yes! Be sure to abide by the Apache Foundation [trademark policies](https://www.apache.org/foundation/marks/#books) and the Apache Airflow [Brandbook](https://cwiki.apache.org/confluence/display/AIRFLOW/Brandbook). The most up-to-date logos are found in [this repo](https://github.com/apache/airflow/tree/main/docs/apache-airflow/img/logos/) and on the Apache Software Foundation [website](https://www.apache.org/logos/about.html).

STATIC_CODE_CHECKS.rst

@@ -265,6 +265,8 @@ require Breeze Docker image to be built locally.
 +-----------------------------------------------------------+--------------------------------------------------------------+---------+
 | flynt                                                     | Run flynt string format converter for Python                 |         |
 +-----------------------------------------------------------+--------------------------------------------------------------+---------+
+| generate-pypi-readme                                      | Generate PyPI README                                         |         |
++-----------------------------------------------------------+--------------------------------------------------------------+---------+
 | identity                                                  | Print input to the static check hooks for troubleshooting    |         |
 +-----------------------------------------------------------+--------------------------------------------------------------+---------+
 | insert-license                                            | * Add license for all SQL files                              |         |

dev/breeze/src/airflow_breeze/pre_commit_ids.py

@@ -86,6 +86,7 @@
     "end-of-file-fixer",
     "fix-encoding-pragma",
     "flynt",
+    "generate-pypi-readme",
     "identity",
     "insert-license",
     "lint-chart-schema",

generated/PYPI_README.md

@@ -0,0 +1,172 @@
+<!--
+Licensed to the Apache Software Foundation (ASF) under one
+or more contributor license agreements.  See the NOTICE file
+distributed with this work for additional information
+regarding copyright ownership.  The ASF licenses this file
+to you under the Apache License, Version 2.0 (the
+"License"); you may not use this file except in compliance
+with the License.  You may obtain a copy of the License at
+
+  http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing,
+software distributed under the License is distributed on an
+"AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+KIND, either express or implied.  See the License for the
+specific language governing permissions and limitations
+under the License.
+-->
+
+<!-- PLEASE DO NOT MODIFY THIS FILE. IT HAS BEEN GENERATED AUTOMATICALLY FROM THE `README.md` FILE OF THE
+PROJECT BY THE `generate-pypi-readme` PRE-COMMIT. YOUR CHANGES HERE WILL BE AUTOMATICALLY OVERWRITTEN.-->
+
+# Apache Airflow
+
+[![PyPI version](https://badge.fury.io/py/apache-airflow.svg)](https://badge.fury.io/py/apache-airflow)
+[![GitHub Build](https://github.com/apache/airflow/workflows/CI%20Build/badge.svg)](https://github.com/apache/airflow/actions)
+[![Coverage Status](https://codecov.io/gh/apache/airflow/graph/badge.svg?token=WdLKlKHOAU)](https://codecov.io/gh/apache/airflow)
+[![License](https://img.shields.io/:license-Apache%202-blue.svg)](https://www.apache.org/licenses/LICENSE-2.0.txt)
+[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/apache-airflow.svg)](https://pypi.org/project/apache-airflow/)
+[![Docker Pulls](https://img.shields.io/docker/pulls/apache/airflow.svg)](https://hub.docker.com/r/apache/airflow)
+[![Docker Stars](https://img.shields.io/docker/stars/apache/airflow.svg)](https://hub.docker.com/r/apache/airflow)
+[![PyPI - Downloads](https://img.shields.io/pypi/dm/apache-airflow)](https://pypi.org/project/apache-airflow/)
+[![Artifact HUB](https://img.shields.io/endpoint?url=https://artifacthub.io/badge/repository/apache-airflow)](https://artifacthub.io/packages/search?repo=apache-airflow)
+[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)
+[![Twitter Follow](https://img.shields.io/twitter/follow/ApacheAirflow.svg?style=social&label=Follow)](https://twitter.com/ApacheAirflow)
+[![Slack Status](https://img.shields.io/badge/slack-join_chat-white.svg?logo=slack&style=social)](https://s.apache.org/airflow-slack)
+[![Contributors](https://img.shields.io/github/contributors/apache/airflow)](https://github.com/apache/airflow/graphs/contributors)
+[![OSSRank](https://shields.io/endpoint?url=https://ossrank.com/shield/6)](https://ossrank.com/p/6)
+
+[Apache Airflow](https://airflow.apache.org/docs/apache-airflow/stable/) (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 as directed acyclic graphs (DAGs) of 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 (2.7.0)    |
+|-------------|------------------------------|---------------------------|
+| Python      | 3.8, 3.9, 3.10, 3.11         | 3.8, 3.9, 3.10, 3.11      |
+| Platform    | AMD64/ARM64(\*)              | AMD64/ARM64(\*)           |
+| Kubernetes  | 1.24, 1.25, 1.26, 1.27, 1.28 | 1.24, 1.25, 1.26, 1.27    |
+| PostgreSQL  | 11, 12, 13, 14, 15           | 11, 12, 13, 14, 15        |
+| MySQL       | 5.7, 8.0, 8.1                | 5.7, 8.0                  |
+| SQLite      | 3.15.0+                      | 3.15.0+                   |
+| MSSQL       | 2017(\*), 2019(\*)           | 2017(\*), 2019(\*)        |
+
+\* Experimental
+
+**Note**: MySQL 5.x versions are unable to or have limitations with
+running multiple schedulers -- please see the [Scheduler docs](https://airflow.apache.org/docs/apache-airflow/stable/administration-and-deployment/scheduler.html).
+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](https://github.com/apache/airflow/issues/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](https://hub.docker.com/p/apache/airflow) is
+`Debian Bullseye`.
+
+## Getting started
+
+Visit the official Airflow website documentation (latest **stable** release) for help with
+[installing Airflow](https://airflow.apache.org/docs/apache-airflow/stable/installation/),
+[getting started](https://airflow.apache.org/docs/apache-airflow/stable/start.html), or walking
+through a more complete [tutorial](https://airflow.apache.org/docs/apache-airflow/stable/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](https://s.apache.org/airflow-docs/).
+
+For more information on Airflow Improvement Proposals (AIPs), visit
+the [Airflow Wiki](https://cwiki.apache.org/confluence/display/AIRFLOW/Airflow+Improvement+Proposals).
+
+Documentation for dependent projects like provider packages, Docker image, Helm Chart, you'll find it in [the documentation index](https://airflow.apache.org/docs/).
+
+## 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 `setup.py`) 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.
+
+
+1. Installing just Airflow:
+
+> Note: Only `pip` installation is currently officially supported.
+
+While it is possible to install Airflow with tools like [Poetry](https://python-poetry.org) or
+[pip-tools](https://pypi.org/project/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.
+
+There are known issues with ``bazel`` that might lead to circular dependencies when using it to install
+Airflow. Please switch to ``pip`` if you encounter such problems. ``Bazel`` community works on fixing
+the problem in `this PR <https://github.com/bazelbuild/rules_python/pull/1166>`_ so it might be that
+newer versions of ``bazel`` will handle it.
+
+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.
+
+
+```bash
+pip install 'apache-airflow==2.7.0' \
+ --constraint "https://raw.githubusercontent.com/apache/airflow/constraints-2.7.0/constraints-3.8.txt"
+```
+
+2. Installing with extras (i.e., postgres, google)
+
+```bash
+pip install 'apache-airflow[postgres,google]==2.7.0' \
+ --constraint "https://raw.githubusercontent.com/apache/airflow/constraints-2.7.0/constraints-3.8.txt"
+```
+
+For information on installing provider packages, check
+[providers](http://airflow.apache.org/docs/apache-airflow-providers/index.html).
+
+## Official source code
+
+Apache Airflow is an [Apache Software Foundation](https://www.apache.org) (ASF) project,
+and our official source code releases:
+
+- Follow the [ASF Release Policy](https://www.apache.org/legal/release-policy.html)
+- Can be downloaded from [the ASF Distribution Directory](https://downloads.apache.org/airflow)
+- Are cryptographically signed by the release manager
+- Are officially voted on by the PMC members during the
+  [Release Approval Process](https://www.apache.org/legal/release-policy.html#release-approval)
+
+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 [contributing documentation](https://github.com/apache/airflow/blob/main/CONTRIBUTING.rst).
+
+Official Docker (container) images for Apache Airflow are described in [IMAGES.rst](https://github.com/apache/airflow/blob/main/IMAGES.rst).
+
+## Who uses Apache Airflow?
+
+More than 400 organizations are using Apache Airflow
+[in the wild](https://github.com/apache/airflow/blob/main/INTHEWILD.md).
+
+## Who maintains Apache Airflow?
+
+Airflow is the work of the [community](https://github.com/apache/airflow/graphs/contributors),
+but the [core committers/maintainers](https://people.apache.org/committers-by-project.html#airflow)
+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](https://github.com/apache/airflow/blob/main/COMMITTERS.rst#guidelines-to-become-an-airflow-committer).

generated/README.md

@@ -30,3 +30,9 @@ You can read more about pre-commit hooks [here](../STATIC_CODE_CHECKS.rst#pre-co
   the providers. It contains historical metadata in providers that were released - it is useful to generate
   information in release notes and it is used to generate SBOM information for the providers. It is manually
   regenerated using `breeze release-management generate-providers-metadata` command."
+
+* `PYPI_README.md` - is generated from the comprehensive `README.md` of the project, which contains exhaustive
+  project details. Unlike the full `README.md`, `PYPI_README.md` is a distilled version tailored for PyPI,
+  focusing on select sections. This subset is produced by the `generate-pypi-readme` pre-commit hook specified in
+  the `.pre-commit-config.yaml` file. This hook triggers automatically whenever the related sections in the
+  `README.md` change, ensuring alignment between the two files.