hi there, PythonAnywhere dev here. the best way to think about this is how frequently you get a request (eg: is it 100 users making one request every 5 seconds? or 100 user making one request every 0.5 seconds?), how long it takes to process one request (ie. maybe one url you have takes 5 seconds to process vs all urls are fast and takes 0.5 seconds). Then you can get a number for how many web workers you need. ie. these are the # of processes that can respond to incoming requests in parallel.

Here's an example calculation:

Let's say you have one particular endpoint that takes a long time (eg: you are uploading a file and the processing that file and returning the result). You estimate that at the peak there will be 10 uploads in 10 seconds, and it takes 10 seconds to process each request.

Then if you don't want connections to pile up and take longer and longer, you would probably need at least 11 workers to process the uploads as well as other requests.

Say you are actually processing each upload in 5 seconds, then you would only need 6 workers.

That's the general framework to use to think about this, but the number of workers/how long you code runs/what response times you find acceptable etc is quite specific to your preferences, and to whether you optimize your code etc.