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Creating a new Python process will still have a memory footprint measured in tens of megabytes. We can try to reduce that footprint by switching to forking (as in os.fork()) and rely on COW memory, but it would still be hard to control memory usage.
As an alternative, I can suggest switching to concurrent.futures module with a ProcessPoolExecutor or a ThreadPoolExecutor, which will allow us to control how many tasks can be executed simultaneously.
Later we can also switch to async/await statements to reduce the footprint even more.
@Fillll would love to hear your feedback on this :)
Now it's ~40MB. Which consumes too much memory. Should be much less.
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