Flask sqlite 3 thread code#

PyPy can really help with CPU bound stuff too, if the code is mostly pure Python. You might benefit from multiprocessing and just use asyncio to coordinate, which is what it excels at. You really have to choose one way or another at the beginning of a project and stick with it.Īnd yeah, async programming (in Python) isn't really for CPU bound stuff. It's super annoying how the python ecosystem has been bifurcated with asyncio. I was disappointed when asyncio came out, as I would have preferred the ecosystem moved in the gevent direction instead but I'm coming around. Gevent makes it so damn easy, I've been spoiled. I imagine the performance would improve quite a bit with pypy, perhaps exceeding that of gevent. I like how I am able to bring non-async code into the async world using threading. It's nice to be able to deploy async microservices without installing gevent, and there's a certain value to the discipline that it imposes. Some tight loop benchmarks for message passing with other processes show it to be about half the speed of gevent in my case, which is fine. As for performance, it's not too bad for mostly io bound tasks, which is why one uses async in the first place. It's getting easier, especially as I build up a collection of in-house async libraries for various things. Part of me enjoys the challenge of learning something new and solving little puzzles. I'm always coming up against little gotchas that take time to debug and fix. If you need performance, then use Java, Rust, Go or C/C++, but for prototyping and tooling I absolutely love this approach with Python.Īfter using gevent for about a decade I have started using asyncio for new projects, just because it's in the standard library and has the official async blessing of the Python gods. This also works very nice with asyncio (like aiohttp) and one ends up with very readable code. server.py defers all the request/response handling to server_handler.py which can be edited on the fly so that the next request executes the new code. Server.py loads reloader.py (which sets up inotify) and that one takes care of reloading server_handler.py whenever it changes. In any case, what keeps me hooked on Python like a junkie is the `reload(module)` which I invoke via an inotify hook every time a file/module changes: I really enjoy using asyncio in Python for things where I have to do a lot of stuff in parallel, like executing remote scripts in a dozen of servers in parallel via AsyncSSH or for low workload servers which query databases. You can wait for result of the thread in the async loop without blocking. In other languages you're basically stepping out of the async paradigm in order to use threading in parallel. In Python there's no benefit in doing this due to the GIL, unless you're using a module which implements its own multithreading (for example in C). But it only does so because you can move out that extra work from the async thread into a thread pool.