Memory Problems, Did Collector Forgot to Clean the Garbage?
2022-07-14 , Liffey B

Memory Problems are the worst nightmare of every developer whose code is serving large files in a production environment. If you ever faced issues of memory leaking in application or if frequent unexpected Out of Memory Exception is raising your anxiety levels, then this talk is for you. This talk aims to summarize the common Memory issues in Python. It is overwhelming to see them even when logic in code is properly optimized. However it is more scary that some of these errors are hard to find and harder to fix.


In recent years, we have seen many improvements in Python Garbage Collection but there are some instances when it doesn’t work as expected. This results in memory crunch for the application leading it to crash. Although there are multiple ways to overcome the memory challenges, sometimes it is difficult to find what we can improve in our code and infrastructure that can make them memory efficient. In such cases, it helps to have an understanding of what is going on behind the curtains at a low level where memory is being managed.

This presentation aims to give a quick overview of

  1. How CPython manages the Memory allocation
  2. Common memory errors we see in day to day production code and how we can improve them

We will share what we have learned so far and encourage you to try it with your own projects. We'll walk through a simple example, with screenshots and code wherever required.


Expected audience expertise: Domain:

some

Expected audience expertise: Python:

some

Abstract as a tweet:

This talk aims to summarize the common Memory issues in Python. It is overwhelming to see them even when logic in code is properly optimized. However it is more scary that some of these errors are hard to find and harder to fix.

Pratibha is an enthusiast Pythoniasta, passionate for coding and books. Through her PyCon talks, she love to explore and share new things she learn in Python.