In this article, you will learn

• Difference between Multi-Threading and MultiProcessing and when to use them
• Implement MultiProcessing in Python using multiprocessing and concurrent.futures

What is MultiProcessing?

• Multiprocessing allows you to spawn multiple processes within a program.
• It allows you to leverage multiple CPU cores on your machine
• Multiple processes within a program do not share the memory
• Side steps the GIL(Global Interpreter Lock) limitation of Python which allows only one thread to hold control of the Python interpreter
• Used for computation or CPU intensive programs

then what is Multi-threading and when to use it?

A Thread is the

• Smallest set of independent commands executed in a program
• Multiple threads within an application can execute simultaneously on a CPU referred to as MultiThreading
• Runs always within a program and cannot run on its own
• Used when programs ar network bound or there is heavy I/O operation
• Memory is shared between multiple threads within a process and hence has lower resources consumption

Below is the code to demonstrate that Multiprocessing does not share a memory, whereas Multi-Threading shares memory.

In the piece of code below, we check if the number passed in the list is a prime number or not. We will do this using both Multi-threading as well as using Multiprocessing

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