Python Memory Management and Tips Course

Python memory management is often a black box to most developers. You probably know that Python uses reference counting, but how can you write code most efficiently to work with it? Did you know it also uses garbage collection? Do you know when that kicks it and its performance implications? With this course, you'll learn all of these concepts and more. You will explore them with concrete code examples, not just theories. And you will learn to optimize your code to both use less memory and to run faster.

This very unique course will teach not just how Python memory management works and how to create code that functions well within that world, it will provide many concrete techniques, tools, design patterns, and more to make your programs more memory efficient and computationally faster to boot.

If Python memory (allocations, clean up, and so on) has always felt like a weird black box that you have had to take for granted, join this course and open that box. There are many beautiful and interesting aspects of Python's runtime behavior making your code run. You should understand what's happening on your behalf.

What topics are covered

In this course, you will:

• Learn how Python variables and data structures actually look in the CPython layer
• See how the small object allocator treats most objects differently than your intuition
• Understand Python's memory allocation primitives: blocks, pools, and arenas
• Locate the elements on C code responsible for Python memory behavior
• See reference counting in action with live code explorations
• Discover why reference counting alone is not enough for memory cleanup
• Work with Python's GC and see when it's needed, and when it's not
• Compare different data structures to get a sense of their relative size
• Use multiple clever but simple techniques to massively reduce memory during function calls
• Lighten up your classes with properties
• Leverage multiple memory profilers to investigate memory usage line by line and over time
• And lots more