Lecture 40: Concurrency in Python: Multithreading and Async

In this tutorial, you will learn about concurrency in Python, a concept that allows multiple tasks to be executed simultaneously. Concurrency helps improve the performance of programs by efficiently utilizing system resources. Python provides several ways to achieve concurrency, including threading, multiprocessing, and asyncio.

Topics Covered:
Introduction to Concurrency: Understand what concurrency is and how it allows multiple tasks to run at the same time. Learn why concurrency is essential for improving the performance of Python programs.
Threading in Python: Explore how threading enables multiple threads to run concurrently within the same process, sharing memory space. You'll see how to create threads to execute functions simultaneously.
Multiprocessing in Python: Learn how multiprocessing allows independent processes to run concurrently, each with its own memory space. Understand how to use processes for parallel execution.
Asyncio in Python: Discover how asyncio provides support for writing asynchronous code, allowing concurrent execution of tasks without using threads or processes. Learn how to use asyncio for handling asynchronous tasks.

Personalized Learning
This tutorial is perfect for those looking to enhance the performance of their Python applications by incorporating concurrency for tasks that can run simultaneously.

Certification
Complete this tutorial to earn a certificate demonstrating your understanding of concurrency techniques in Python.

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