ProcessPoolExecutormaxworkersnumworkers

ProcessPoolExecutor max_workers refers to the maximum number of worker processes that can run tasks concurrently in Python’s ProcessPoolExecutor. This executor, part of the concurrent.futures module, uses separate processes to execute calls, which helps bypass the Global Interpreter Lock for CPU-bound workloads.

If max_workers is None, the executor defaults to os.cpu_count() or 1, effectively tying the pool size to the number of CPU cores available. This makes the pool size align with the machine’s parallel processing capability in typical scenarios.

The max_workers setting governs how many tasks can run in parallel. When more tasks are submitted than there are available workers, the extra tasks are queued until a worker becomes free. If a worker terminates due to an exception, the pool may replace it to maintain the configured size. In practice, choosing the right number of workers involves balancing CPU utilization against the overhead of multiprocessing; too few workers underutilize hardware, while too many can incur diminishing returns and increased interprocess communication overhead.

Usage notes: Create the executor within a with statement to ensure orderly shutdown. Tasks are submitted with submit or mapped with map, and results are retrieved by calling result() on futures. Arguments and return values must be picklable to transfer between processes. On Windows, code that creates new processes should be protected by an if __name__ == '__main__' guard to avoid recursive process spawning when the module is imported.