3 ms·

Why would the Gil apply to asyncio, which is strictly single threaded?

• zomglings 6y ago
  The post also discusses concurrent.futures.
  • joshuamorton 6y ago
    Which is also single (OS) threaded.
    • devxpy 6y ago
      Why do you say that? I believe concurrent.futures is meant as a way for asyncio to spawn threads or processes -- which lets you essentially call sync code from async and not have it block the event loop. From the docs[1] - The concurrent.futures module provides a high-level interface for asynchronously executing callables. The asynchronous execution can be performed with threads, using ThreadPoolExecutor, or separate processes, using ProcessPoolExecutor. Both implement the same interface, which is defined by the abstract Executor class. [1] https://docs.python.org/3.8/library/concurrent.futures.html https://docs.python.org/3.8/library/concurrent.futures.html
      • joshuamorton 6y ago
        Python's threadpoolexecutor is still single OS-threaded. There will only ever be one thread executing in parallel (due to the GIL). Basically, in python, asyncio and threadpoolexecutor are almost entirely mappable to each other. Neither can accomplish more than the other. Multi-process code can, of course, address some of these issues, but it comes at the cost of spinning up multiple OS processes and costly inter-process communication etc.
        • zomglings 6y ago
          The only issue I see re: the GIL is that ThreadPoolExecutor (by its name) can mislead them into thinking that they are using proper threads when in fact they are still constrained by the GIL. It's a confusion that has been quickly resolved every time a team mate of mine has run into the issue, but I have seen it happen multiple times (at different places).
        • dialamac 6y ago
          This doesn’t sound quite right. Unless they changed something threadpoolexecutor does involve multiple OS threads, and is not single threaded. Sure the GIL puts a big limitation on parallel execution, but it is most definitely different. For one, regardless of the GIL it is still possible to have races in multithreaded python code. You have to worry about RMW because the threads are arbitrarily preemptible at a bytecode boundary. This is not the case with asyncio. Additionally you can release the GIL when making calls to C code. Asyncio is giving you concurrency by using nonblocking calls, you can’t run two CPU bound threads in parallel with it. But you can do this with python threads. So it’s not true that neither can accomplish more than the other.
  • devxpy 6y ago
    Can't you just use the ProcessPoolExecutor[1] for CPU heavy stuff? AFAIK, GIL isn't much of an issue with I/O tasks. [1] https://docs.python.org/3.8/library/concurrent.futures.html#processpoolexecutor-example https://docs.python.org/3.8/library/concurrent.futures.html#...
    • zomglings 6y ago
      You are right, GIL isn't an issue with I/O-bound tasks. The article didn't limit its focus to I/O, though. It felt more like an explanation of modern concurrency and asynchronous options in Python (besides just threading and and multiprocessing). The only practical issue with the GIL in Python is that it forces you to use new (heavy) Python processes to parallelize computationally heavy tasks. Not so much of a concern depending on your application, but it is a gotcha for people new to Python. The real issue, though, as your parent poster mentioned, is the number of different ways to access asynchronicity and concurrency in modern Pythons. It really does run counter to Python PEP20 [0] and can lead to some communication difficulties among developers. [0] https://www.python.org/dev/peps/pep-0020/ https://www.python.org/dev/peps/pep-0020/
      • devxpy 6y ago
        Just an aside from the argument here, I think almost no python API actually follows the zen of python. It's certainly a nice idea, just incredibly hard to actually live upto in the real world.