Prettify Your Python Logs with Loguru

Note: The following is an objective evaluation of a Python library. I am not associated with nor do I receive any form of compensation from any entity associated with Loguru.

If you’re a data engineer, chances are, you will likely agree with two fundamental truths I’ve discovered about our craft:

• No matter how perfect you make something, it will break at least once.
• Logs are ugly.

Whether writing or interpreting logs locally or on cloud infrastructure, the output is, admittedly, difficult to interpret, especially if you are in a situation where you are diagnosing an error on a system you’re unfamiliar with.

Even if you strategically place logging statements throughout your code, the output will still be blocks of unformatted, dizzying metadata.

Parsing raw data is fine and part of the job. I regularly deal with raw JSON and other messy outputs.

But when that data contains critical information about your infrastructure, it needs to be communicated as clearly, as legibly and as quickly as possible.

There are ways to cleanly format JSON data; there are even platforms that will convert raw JSON files into readable, ‘prettified’ documents.

But there is no equivalent of pretty print for logging statements.

That is, until I began to explore Loguru, based on a colleague’s recommendation.

The library, available for local installation and housed in this repo, outlines how it solves the problem of illegible, overwhelming logs:

This library is intended to make Python logging less painful by adding a bunch of useful functionalities that solve caveats of the standard loggers. Using logs in your application should be an automatism, Loguru tries to make it both pleasant and powerful.

— Loguru GitHub

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