Introduction to Python’s Multiprocessing Module
Python’s multiprocessing module is a powerful tool that allows for the creation of process-based parallel programs. This enables developers to take full advantage of multiple processors and cores, resulting in significant speed-ups for computation-heavy tasks.
Creating a Multiprocessing Program
To create a multiprocessing program in Python, you first need to import the multiprocessing module. You can then create processes using the Process class, which takes a target function and optional arguments.
import multiprocessingdef worker(): print('Worker')if __name__ == '__main__': jobs = [] for i in range(5): p = multiprocessing.Process(target=worker) jobs.append(p) p.start()Synchronizing Processes
Synchronization between processes can be achieved using locks, conditions, events, or semaphores, all of which are provided by the multiprocessing module.
Sharing State Between Processes
State can be shared between processes using shared memory or server process. The multiprocessing module provides Value or Array classes for sharing state using shared memory.
Conclusion
Python’s multiprocessing module is a powerful tool for creating parallel programs that can leverage the full power of your machine’s hardware. By understanding how to create processes, synchronize them, and share state between them, you can create efficient, computation-heavy programs that are significantly faster than their single-process counterparts.