pidly | A super simple daemon library

I have a large Python service that runs on a desktop PC, and I need to have it run as part of a K8S deployment. I expect that I will have to make several small changes to make the service run in a deployment/pod before it will work.

So far, if I encounter an issue in the Python code, it takes a while to update the code, and get it deployed for another round of testing. For example, I have to:

• Modify my Python code.
• Rebuild the Docker container (which includes my Python service).
• scp the Docker container over to the Docker Registry server.
• docker load the image, update tags, and push it to the Registry back-end DB.
• Manually kill off currently-running pods so the deployment restarts all pods with the new Docker image.

This involves a lot of lead time each time I need to debug a minor issue. Ideally, I've prefer being able to just modify the copy of my Python code already running on a pod, but I can't kill it (since the Python service is the default app that is launched, with PID=1), and K8S doesn't support restarting a pod (to my knowledge). Alternately, if I kill/start another pod, it won't have my local changes from the pod I was previously working on (which is by design, of course; but doesn't help with my debug efforts).

Is there a better/faster way to rapidly deploy (experimental/debug) changes to the container I'm testing, without having to spend several minutes recreating container images, re-deploying/tagging/pushing them, etc? If I could find and mount (read-write) the Docker image, that might help, as I could edit the data within it directly (i.e. new Python changes), and just kill pods so the deployment re-creates them.

I don't know how to word this issue properly as English being my second language but essentially I am trying to create new table forEach results property in the array. Here is what my response from API looks like.

I'm running a Django app on uwsgi with an average of 110 concurrent users and 5 requests per second during peak hours. I'm finding that when I deploy with uwsgi reload during these peak hours I am starting to run into an issue where workers keep getting slowly killed and restarted, and then the uwsgi logs begin to throw an error:

I occasionally need to extract data from a large XML database export. The file size is between 600 and 700 MBs. With a few days of research I concluded that XML::Twig is the way to go, because its handlers allow me to process the file chunk-by-chunk.

I followed the examples, and with some hours of trial and error I wrote the Perl code that performed the job I needed to do. The code worked, it extracted the data I wanted and calculated the details I needed. But while running the script (took about 15 minutes to process the 620MBs XML) I noticed in Activity Monitor that towards the end the memory usage quickly increases to an unreasonably high level.

I removed the Perl code that processes the XML tag I was interested in and replaced it with a single instruction to increment a variable, simply counting how many of product elements had been found. The memory usage was similar. First normal, then towards the final few elements it started to rapidly increase and eat up everything I have.

I added some code to monitor time, the number of items processed, and how much memory my Perl process is using. This code is shown here: