Multiprocessing in Python is a powerful technique that allows you to run multiple processes simultaneously, leveraging multiple CPU cores to improve performance, especially for CPU-bound tasks. The multiprocessing module in Python provides a simple interface for creating and managing separate processes, enabling parallel execution of tasks.

One of the key advantages of multiprocessing is that it does not share memory between processes, which helps avoid issues related to data corruption that can occur in multi-threading scenarios. Each process has its own memory space, making it suitable for tasks that require significant computational resources, such as image processing in computer vision projects ².

To get started with multiprocessing, you can use the Process class from the multiprocessing module to create new processes. You can also utilize features like Queue for inter-process communication and Pool for managing a pool of worker processes to handle multiple tasks efficiently ¹⁴.

If you’re interested in learning more about practical examples and visualizations, there are additional resources available that delve deeper into the topic ¹.