Multiprocessing vs Multithreading In Python

In this tutorial, we will learn the difference between Multiprocessing vs Multithreading In Python where there are two techniques that are used for achieving parallel processing and concurrency in software.



Muti processing refers to the situation when multiple processes are executed at some point in time. where every process running at the moment has its own memory and CPU Such approaches are used for data processing and tasks which are CPU bound.

Moreover, multi processing modules in python make python manage multiple processes at the same time enhance productivity and make python more efficient and utilize CPU up to maximum capacity.

Although multi processing uses a little more memory which leads it more expensive as compared to multi threading.


It is a way of running a number of threads at the same time but within the same process to share the same memory location. that means multiple threads of the single process are executed simultaneously. It is said to be more suitable for input/output- bound tasks, which could be communication, where threads can run concurrently without affecting the flow of each other.

The selection of multi processing or multi threads purely depends upon the requirement of the task that we are performing at moment.

If we talk about multi threading it is operated for a single process holding multiple threads. There might be an accurate deadlock situation when more than one thread required the same resource.


To learn more about Multiprocessing vs Multithreading In Python Multi processing Vs Multi Threading.

To learn more about python programming problems and the solutions related to them visit What are Variables in Python | Rules for Naming Variables | Local vs Global Variables and to learn more about different solutions of programming languages and concepts related to them to keep on learning and growing the knowledge.

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