How do you write a production data science code?

The ability to write a production-level code is one of the most sought-after skills for a data scientist role.

100% agree. Most posts on this subject don't actually help data scientists think about how to write better code; instead, they give some easy answer like "use XYZ product" or "wrap your code behind a RESTful API". These suggestions are not wrong, per se, but they're certainly inadequate.

The correct answer to "how do you write production code?" is: write better code. Modularize and organize your components. Document well. Focus on readability. Discuss integration requirements with consumers of your algorithms.

This post tackles the subject head-on. While this is not a topic that a single blog post can fully address, this is the best overview that I've seen.


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