Down with technical debt! Clean Python for data scientists.

I often talk about how critical (and overlooked) code quality is in data science, but I've never before seen a piece that provides such clear tactical guidance on the topic. If you want to immediately level up the quality of your code, focus on your process and tooling: linters, auto-documentation, type checking, etc.

As you incorporate these tools into your production process you'll find your entire team constantly nudged in the direction of writing good code. Improving code quality isn't achieved by a heroic refactoring effort, rather by consistent gradual improvement.


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