4 ms·

can you elaborate?

• jessedhillon 10y ago
  It's the equivalent of: (edit: actually an improvement over) from threading import Thread def blocking_function(arg): .... pool = [] for arg in args[:16]: f = lambda: blocking_function(arg) thread = Thread(target=f) thread.start() pool.append(thread) Edit: see below, this doesn't include job queueing but rather, hard limits your input to maximum 16 args. The point is, the code is a nice, easy way to start a number of threads working on a list of arguments.
  • quinnftw 10y ago
    Not quite. You can submit as many jobs as you'd like to the pool and it will delegate them to 16 threads. The pool maintains a queue of work to be done and the fixed number of threads consume from the queue.
  • rdtsc 10y ago
    Almost but as quinnftw mentioned it does a bit more, specifically it limits the number of threads it runs to 16. I can pass 1000 url or arguments into it and it won't spawn 1000 threads but keep it at 16 max. Also I think it does a bit a better job with exception propagation.
    • deleted 10y ago
      [deleted]
• paulddraper 10y ago
  Multiprocessing offers a ThreadPool for multi-threading.. It doesn't have true CPU parallelism like multiple processes would have, but it works for IO code. It's a little gold nuggest in the multiprocessing lib.