5-Steps Guide to Parallel Processing in Python
It’s time to go deep with Python. Who wouldn’t want to be faster!
Published in
6 min readSep 9, 2020
The idea of creating a practical guide for Python parallel processing with examples is actually not that old for me. We know that this is not really one of the main contents for Python. However, when the time comes to work with big data, we cannot be very patient about the time. And at this point, it’s no secret that we need new equipment to take on big tasks.
This article will help you understand:
- Why is parallel processing and what is parallel processing?
- Which function is used and how many processors can be used?
- What should I know before starting parallelization?
- How is any function parallelization?
- How to parallelize Pandas DataFrame?
1. Why and What?
Why do i need parallel processing?
- A single process covers a separately executable piece of code
- Some sections of code can be run simultaneously and allow, in principle, parallelization
- Using the features of modern processors and operating systems, we can shorten the total execution time of a…
