Multithreading in Python

In this video, we’ll dive deep into the concept of Multithreading — from theory to practical implementation. Here’s what we’ll cover 👇 ▶️ What are Threads? We’ll understand what threads are, their advantages, and in which scenarios using threads is the best approach. ▶️ Multithreading vs Multiprocessing: We’ll explore the difference between processes and threads, looking at execution, memory sharing, and performance from both perspectives. ▶️ Practical Implementation: We’ll implement real examples of both multithreading and multiprocessing, to clearly understand the differences. ▶️ Ways to Implement Multithreading: We’ll cover two important approaches to implement multithreading in Python: - Class-level multithreading - Function-level multithreading Both will be explained step-by-step. ▶️ Thread Creation Syntax: We’ll explore the syntax for creating threads using Python’s built-in threading tools. ▶️ Thread Scheduling & Execution: We’ll understand how the scheduler decides which thread to execute and how multiple threads run concurrently. ▶️ join() Method: We’ll see how to use the join() method to synchronize threads and join them with the main thread. ▶️ GIL (Global Interpreter Lock): We’ll discuss what the GIL is and its actual impact on multithreading in Python. ▶️ GIL, Memory & Execution Comparison: Lastly, we’ll compare the memory model of threads vs processes and understand how GIL affects execution in real scenarios. By the end of this video, you’ll have a complete understanding of multithreading, multiprocessing, GIL, and how they affect performance in Python — explained with practical coding examples. Check out our courses: Mastering Agentic AI with Java: Spring AI, LangChain4j, MCP & ADK: https://go.telusko.com/agentic-ai Coupon: TELUSKO10 (10% Discount) DevOps Bootcamp: https://go.telusko.com/complete-devops Coupon: TELUSKO10 (10% Discount) Master Java Spring Development : https://go.telusko.com/learn-master