Description
Python is a dynamically typed language. Applications leave task of object memory management to Python VM. Python automatically manages memory using reference counting and garbage collection. But, Python memory manager may bloat the VM size, and sometimes it may consume complete main memory. It causes applications to deliver low performance and encounter unexpected memory errors.
This talk dissects the internals of CPython memory manager, its limitations and negative impact on application behavior. We demonstrate the problem of memory leaks by learning Python heap pattern, object graphs and memory profiling. Next, we suggest solutions to reduce memory footprints of applications, tools to diagnose and fix memory leaks and lesson learned as best development practices.