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1: Create a virtual environment (recommended)

to avoid permission issues and library versions:

$ python3 -m venv airflow_env && source airflow_env/bin/activate

and to update Pip and tools

$ pip install --upgrade pip setuptools wheel

2: Install Airflow base, without extras or constraints (just to be able to generate versions):

$ pip install "apache-airflow==3.1.0"

This installs the Airflow core with versions that Pip considers compatible with Python 3.10, in my case.

3: Generate the constraints file using "pip freeze" to capture the exact versions of all installed dependencies:

$ pip freeze > my_constraints.txt

This creates a my_constraints.txt file with a listing like this:

...
apache-airflow==3.1.0
click==8.1.3
jinja2==3.1.2
sqlalchemy==2.1.0
etc...

This file will serve as constraints, and future installations will use exactly those versions.

4: Install Airflow with extras using our brand new constraints file

Now with the custom constraints, install Airflow with the extras you want (AWS, Celery, etc.):

$ pip install "apache-airflow[amazon]==3.1.0" --constraint ./my_constraints.txt

pip will take the versions from the my_constraints.txt file, won't try to download constraints from GitHub, and obviously won't give a 429 error.

So now I have:

• Airflow 3.1.0 working on Python 3.10
• AWS extras installed, and
• A local constraints file that I can always use to reproduce installations

TATÁÁÁÁ!

Let me know how it goes!