Python’s Global Interpreter Lock (GIL) is often portrayed as a limitation but it doesn’t have to be a blocker. In this talk, we will discuss the core concepts behind Python concurrency and explore practical ways to work with GIL rather than working against it. From threading to multiprocessing, async IO to real-world patterns, we will break down what’s really going on under the hood and when to use which approach.

Whether you are building data pipelines, web backends, or automating workflows, understanding concurrency is key to writing responsive and efficient Python code. I will use simple examples and real life scenarios to show how concurrency works in modern Python and share some hard earned lessons from debugging slow, blocking code in production systems.