Efficiently utilize system resources in Python

Description:

Background / Problem Statement

Global Interpreter Lock(GIL) is quite infamous in Python. Whenever anyone compares Python with other languages like Java, they always point out you can't achieve true multithreading in Python. Besides there are ways to go beyond GIL. This talk will be focused on presenting different solutions that can be considered to solve this problem.

Solutions considering different kind of workloads

1. multithreading
2. multiprocessing
3. asyncio
4. Combination of above mentioned solutions.

Take Aways

This thing might be known to many. But this talk will make the audience more informed and bring clarity to their thoughts on GIL and different concurrency and parallelism model in Python. What should be the way to go with given task at hand.

Prerequisites:

Basic Python

Content URLs:

https://www.slideshare.net/NitinBhojwani/srecon19-asia-enhance-your-python-code-beyond-gil

Speaker Info:

Nitin Bhojwani has experience of around 5 years working in Python, in which he has worked on various scalable web applications. He likes Python and keeps exploring better ways of getting things done in Python. He is learning Machine Learning using Python.

Apart from Python, he has experience on SRE and UI development as well.

Speaker Links:

http://nitinbhojwani-tech-talk.blogspot.com

https://github.com/jsocol/django-ratelimit/pull/100

https://github.com/jsocol/django-jsonview/pull/32