Exception Handling in Methods of the Multiprocessing Pool Class in Python

Working with the map, imap, and imap_unordered methods

Introduction

When working with big data, it is often necessary to parallelize calculations. In python, the standard multiprocessing module is usually used for tasks that require a lot of computing resources. In DS, we constantly have to solve problems that can be easily parallelized. Examples could be bootstrap, multiple predictions (model prediction for multiple examples), data preprocessing, etc.

In this article, I would like …

data engineering error-handling multiprocessing programming python