flask-app | Example app for demonstrating CI/CD workflows | Continous Integration library

This is somewhat odd behaviour but I think it might be because you are using the global python interpreter. I would recommend creating a virtual environment like python -m venv env and then .\env\Scripts\activate

and then install all the packages there and try running flask again.

You could look into flask-httpauth. I used this a while back on one of my projects to add a layer of security to some API's running on flask. Keep in mind that this is only a basic authentication (base-64 encoded strings).

yes, you can. you just have to put them in different variables.

in $docker inspect --format '{{json .State.Health }}' flask-app

remove the extra space after the word json on ({{json .State.Health }})

Just use a regular Python module-level variable.

You don't need to install the driver for the Azure file share. You just need to set the azure_file as you showed when you follow the steps to install the Docker Desktop for Windows. It will create the storage file share for you in the resource group.

And if you use the ACR to store your custom image, then you need to log in the ACR like this:

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.

After much trial end error I've finally figured out what the problem was.

The redirect problem in the original question was solved by setting OVERWRITE_REDIRECT_URI:

Not enough for comment so this is why: From what it seems it could be either firewall rule in your host running the container or one between the host to your house. To test which on between the two I'd try to use nmap with --reason and --tracerout options, since we have connectivity in another port it's unlikely that there is a complete block between your home and the container so the traceroute wouldn't give much info but just in case. Also if you have root access to the host machine or just to the iptables service try to stop it to check if that's the root cause for the block.

also check with docker ps if the port is bound to the port on the machine, should look something like this:

0.0.0.0:port --> tcp\port

where instead of port you have the port number

If it doesn't maybe it's due to some problem with the docker-compose up command so try to run the service with a simple docker run command