tenacity | Dropwizard Hystrix Module | Analytics library

So in my case I've previously ran Airflow locally directly on my machine and now I'm trying to run it through containers using docker while also keeping the history of my previous dags. However I've been having some issues.
A slight bit of background ... when I first used docker-compose to bring up my containers airflow was sending an error message saying that the column dag_has_import_errors doesn't exist. So I just went ahead and created it and everything seemed to work fine.
Now however my dags are all broken and when I modify one without fixing the issue I can see see the updated line of code in the brief error information that shows up at the top of the webserver.
However when I resolve the issue the code doesn't change and DAG remains broken. I'll provide
this image of the error
this is the image of the code\

also the following is my docker-compose file (I commented out airflow db init but may I should have kept it with the db upgrade parameter as true? My compose file is based on this template\

I'd like to examine the Psychological Capital (a construct consisting of four dimensions, namely hope, optimism, efficacy and resiliency) of founders using computer-aided text analysis in R. So far I have pulled tweets from various users into R. The data frame contains of 2130 tweets from 5 different users in different periods. The dataframe is called before_failure. Picture of original data frame

I have then used the quanteda package to create a corpus, perfomed tokenization on it and removed redundant punctuatio/numbers/symbols:

I have a problem. For my project, I need to move files from the directory to the mega cloud. But when trying to run the code, it gives an error. Also when trying to pip install mega.py it turns out the following:

The code

I’ve been developing a dash app that uses a long_callback, and for development I’ve been using a diskcache backend for my long_callback_manager, as recommended by the guide I found here: https://dash.plotly.com/long-callbacks

When I tried running my app using gunicorn, it failed to start because of something apparently wrong with diskcache. As such, I decided to switch to a celery/redis backend since that’s recommended for production anyway.

I got a redis server running (responds properly to redis-cli ping with PONG), and then started the app again. This time it started up fine, and all of the normal callbacks work, but the long_callback does not work.

Details:

• The page more or less hangs, with the page title flashing between the normal title and the Updating... title, indicating that the app thinks it’s “waiting” for a response/update from the long_callback.
• The values set by the running argument of the long_callback are set to their starting value, indicating that the app recognizes that the long_callback ought to run.
• By placing a print statement as the first line within the long_callback function and seeing that it does not print, I’ve determined that the function never starts.
• The failure happens both with gunicorn and without gunicorn.

These details all point to the problem being the celery/redis backend. No errors are shown, neither on the client/browser nor on the server’s stdout/sterr.

How do I get a celery/redis backend working?

UPDATE: After realizing that the __name__ variable is being used and that its value changes depending on the file from which it is referenced, I've also tried moving the code which creates celery_app and LONG_CALLBACK_MANAGER into app.py, to no avail. The exact same thing happens.

I keep seeing an error message during my docker build, at the part where docker tries to install my requirements.txt file that says Module Not Found. However, half of the time the version of the module it says it can't find is in the list of versions available.

I keep trying older versions and eventually I'll find one that works but then the same thing will happen on the next package. It's taking hours to try and build one container which surely can't be right. I'm assuming it might be something to do with packages might not be passing between different layers of the containers, but I'm new to Docker so can't tell if this is the issue or how to fix it.

I'm using WSL2 (Ubuntu 20.04) to build a flask application in Python (well technically it's a Plotly Dash app but I've read it works the same as flask). I have a Windows 10 machine and I've ensured that Docker is set to be compatible with WSL2 and Ubuntu. I've pasted a few of the many errors I've been getting below, as well as my current requirements.txt, Dockerfile and file structure.

I'd like to know how to prevent this message from keep coming up and how to know which package is compatible with Docker? Any help would be appreciated.

Some of my error messages that I'm seeing are:

I have two Flask apps (A and B). App A is running locally on port 5000 and makes a post request to app B running on port 5002 like such:

I have a request that can only run once. At times, the request takes much longer than it should.

If I were to set a default socket timeout value (using socket.setdefaulttimeout(5)), and it took longer than 5 seconds, will the original request be cancelled so it's safe to retry (see example code below)?

If not, what is the best way to cancel the original request and retry it again ensuring it never runs more than once.

How can I properly install PyCaret in AWS Glue?

Methods I tried:

• --additional-python-modules and --python-modules-installer-option
• Python library path
• easy_install as described in Use AWS Glue Python with NumPy and Pandas Python Packages

I am using Glue Version 2.0. I used --additional-python-modules and set to pycaret as shown in the picture.

Then I got this error log.