The difference between Multithreading and Multiprocessing in Python and when to use them

As a high-level language, Python has a Global Interpreter Lock (GIL) that ensures that only one thread executes Python bytecode at once. This means that, by default, multithreading in Python is not a good choice for CPU-bound tasks, as the GIL limits the performance benefits of multithreading. However, multithreading can still be useful for I/O-bound and concurrent tasks, as it allows multiple threads to run in parallel and perform different tasks simultaneously.

In addition to multithreading, Python provides a multiprocessing module that allows you to run multiple processes in parallel, each with its own memory space and CPU resources. This is a great solution for CPU-bound tasks, as it allows you to take advantage of multiple CPU cores and improve the performance of your code.

In this blog post, we'll explore the differences between multithreading and multiprocessing, and when it is appropriate to use each in Python.

The main difference between multiprocessing and multithreading in Python is the way they allow you to run multiple tasks simultaneously.

Multithreading is a way to run multiple threads within a single process. Each thread has its own stack and local variables, but they share the same memory space and global variables with the main thread and other threads. Multithreading is useful for I/O-bound tasks, such as waiting for data from a network or a database, as it allows multiple threads to perform different I/O operations simultaneously and make better use of available CPU resources. However, the Global Interpreter Lock (GIL) in Python limits the performance benefits of multithreading for CPU-bound tasks.

Multiprocessing, on the other hand, allows you to run multiple processes in parallel, each with its own memory space and CPU resources. This is a great solution for CPU-bound tasks, as it allows you to take advantage of multiple CPU cores and improve the performance of your code. Each process is isolated from the others, so there is no need to worry about thread-safety issues or the GIL.

In summary, multithreading is best suited for I/O-bound tasks, while multiprocessing is best suited for CPU-bound tasks. The choice between the two depends on the specific requirements of your application and the type of tasks you want to run simultaneously.