Cleaner Code for Data Science | Logging in Python

Logging is one of the most useful tools in a code writer's toolkit. All too often, people get in the habit of using print statements to debug their code. While convenient, this causes a few problems. Firstly, what happens when you are done debugging? You now have to go back and remove all these print statements. If you forget one, you could be exposing potentially sensitive information or just generally cluttering up your user's screen with unnecessary information.

In this video, you will learn how to use Python's native logging features to:

1.) Debug your code
2.) Log failed and successful executions
3.) Send logs to different destinations

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Chapters
00:00 Intro
00:28 Understand problem scenario
01:16 Don't use print statements
02:22 Logging Levels
03:42 Root Logger
06:03 Formatting your logs
06:39 Solve problem scenario
07:48 Advanced logging
10:25 Sending logs to different destinations
11:27 Outro

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