re: How to make Python code concurrent with 3 lines VIEW POST

re: @rhymes , please don't pay too much attention when people with russian names criticise your work. High level of critics is a heritage of a Soviet m...
Sloan, the sloth mascot Comment marked as low quality/non-constructive by the community View code of conduct

Now my name is not western enough. I wonder what would be the next in this ad-hominem hell on this “welcoming” site.

We suffer from self-criticism

Please do not speak for the internets, speak for yourself.

I saw a python code

You seem to be fine in googling titles, unfortunately fair arguing implies reading these texts as well. The link you posted contains “way is just adding some synchronization in your client limiting number of concurrent requests it can process. I’m going to do this by adding asyncio.Semaphore() with max tasks of 1000”—guess what?

in a real app, you will reach [...]

Please tell that to Hadoop engineers, or to WhatsApp (or any other Telecom) team. There are tons of examples, and none is made with python. Twitter escaped Ruby as soon as possible for the exactly same reason.

To be welcomed you shouldn't start to comment python article with something like "python sucks, use Java.

Everybody here knows good and bad sides of Python, and sure it is not 1kk RPS per core language, thank you, K.O.

As for company examples, remember Eve online, running dozens of thousands players in one world using python 2.7

To be welcomed you shouldn't

I never said I want to be welcomed and/or appreciated.

comment python article with something like “python sucks, use Java.”

Please stop putting words in my mouth. I never said that either. What I said was “don’t use python for concurrency,” and this is indeed a good advise.

Wow these guys are rude. As a Python developer (and Telecom employee!), I'm with you. Don't use Python threading or multiprocessing too much if you can avoid it. We definitely prefer a queue/worker model for our async code.

That being said, multiprocessing isn't terrible but you are running full instances of the python interpreter for each process so it's less than friendly on memory and can introduce leakages especially with file descriptors.

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