marshmallow-sqlalchemy | SQLAlchemy integration with marshmallow | Reactive Programming library

Look at constraint files. You do not have to think about the right versions of dependencies as long as you use golden set of constraints which are generated by Airflow maintainers with every release.

See Airflow documentation about this:

https://airflow.apache.org/docs/apache-airflow/stable/installation/installing-from-pypi.html

You should use constraints when you install airflow - this way the right versions will be automatically found and installed by PIP.

But you can also - if you want manually set those dependencies or even automate version retrieval. For example here you have the set of "golden" constraints for Airflow 2.2.2 and Python 3.7:

https://raw.githubusercontent.com/apache/airflow/constraints-2.2.3/constraints-3.7.txt

Are you sourcing your venv before running test.py?

If so, then try this,

Searching for the exception, leads to the corresponding eventlet issue: https://github.com/eventlet/eventlet/issues/687

The summary is that eventlet (0.32.0) is currently not compatible with Python 3.10 because it tries to patch types that have become immutable in Python 3.10.

Like with your requirements, it is good practice to be more specific with your Docker dependencies too. Today using the tag 3 for the Python Docker image will give you 3.10.0, unless it is using a cache. In the future it could be a different version. Since there is a compatibility issue with Python 3.10, use Python 3.9 - the currently latest Python 3.9 Docker tag is 3.9.7.

i.e. it should work once you change your first line of the Dockerfile to:

If you have a look for the base image, you could see it just be updated 27hours ago.

It seems that you are confusing the use-cases for PythonVirtualenvOperator and PythonOperator.

If you simply want to run a Python callable in a task (callable_virtualenv() in your case) you can use PythonOperator. In this case, it does not matter if you installed Airflow in a virtual environment, system wide, or using Docker.

What happens in your code is the following: PythonVirtualenvOperator creates another virtual environment (which is completely unrelated to the one in which you run Airflow), installs Airflow into it, and tries to import Variable. But this another Airflow installation is not configured and that is why you get those exceptions. You could set the AIRFLOW_HOME environment variable for this second Airflow installation to the same directory as used by the first Airflow installation, and this should actually work, but it looks like an overkill to me.

So, what you can do is install colorama into the same environment in which you installed Airflow and replace PythonVirtualenvOperator by PythonOperator.

BTW, those print() inside the callable would be redirected into a log file and not printed to terminal, so it probably does not make much sense to use colorama with them.

Try creating Inventory objects:

Maybe I shouldn't have posted the question so early, since it was a very simple error ...

The OAUTH_PROVIDERS variable should be an array!

I see that you can try two different strategies:

Add this config line to your code after the app definition:

The problem is a known issue in flask-sqlalchemy, caused by changes in SQLAchemy 1.4. Flask-sqlalchemy attempts to modify the SQLALchemy engine's URL, but these URLs are immutable in SQLAlchemy 1.4.

The problem is fixed in Flask-SQLAlchemy 2.5+ (changelog).

If upgrading Flask-SQLAlchemy is not possible, the issue can be worked around by specifying the SQLAlchemy version passed to pip, either via the command line