colorlog | golang彩色日志 - 带有颜色的日志 , 一般应用于console , 命令行使用 | Plugin library

Instead of putting the version of python into the Procfile simply put:

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.

Some tutorials on YouTube are outdated. The problem here is with your requirements.txt. You don't need to include git+https://github.com/Rapptz/discord.py at the beginning of the file. And some modules like pandas and async-timeout are already installed with the python Buildpack. Finally, pip isn't a module, so you don't need to include that as well.

I would change:

I am on MacOS 10.15.7 Python version 3.8.2

I'm guessing you used the Python 3 bundled/pre-installed with macOS Catalina.

My compliments on such an extensive report. Your issue lies probably in this weird setup you've got going on.

We can use os module to create the pip list, then we use pandas.read_csv with \s+ as seperator to read the pip list into a dataframe:

There are 2 types of logs in App Engine :

• Request log: A log of the requests that are sent to your app. App Engine automatically creates entries in the request log.

• App log: log entries that you write to a supported framework or file as described on this page.

The both logs are send to the Cloud Logging Agent automatically by App Engine Standard.

On first request, app logs and request logs are not correlated and that's why there are not shown in a group , this is a known issue stated in App Engine Official Documentation. However in the second request, you can see that the logs are shown in a group.

A feature request in Public Issue Tracker has already been created for this behavior where you will get all the updates regarding the fix.

Config is not a module, it's a python file that is missing from this github repository.

If you go into the repository's .gitignore, you can see Config.py in the last line.

There is two things going on here. First of all there is a misspelling of propagate in the config. It is wrongly spelled propogate: notice the "o" where an "a" should be. That means all the loggers do in fact propagate their logs up the hierarchy.

The second thing is that when propagation is on, the level of the ancestor loggers, in this case the root logger, is ignored and only the level of the handlers is taken into consideration. Since the console_err handler that is added to root has level DEBUG and all logs propagate to root this handler will log every log.

The relevant piece of information can be found the python documentation here:

Messages are passed directly to the ancestor loggers’ handlers - neither the level nor filters of the ancestor loggers in question are considered.