#522: Data Sci Tips and Tricks from CodeCut.ai

Today we’re turning tiny tips into big wins. Khuyen Tran, creator of CodeCut.ai, has shipped hundreds of bite-size Python and data science snippets across four years. We dig into open-source tools you can use right now, cleaner workflows, and why notebooks and scripts don’t have to be enemies. If you want faster insights with fewer yak-shaves, this one’s packed with takeaways you can apply before lunch. Let’s get into it.

Episode sponsors

Sentry Error Monitoring, Code talkpython26
Agntcy
Talk Python Courses

Links from the show

Khuyen Tran (LinkedIn): linkedin.com
Khuyen Tran (GitHub): github.com

CodeCut: codecut.ai
Production-ready Data Science Book (discount code TalkPython): codecut.ai

Why UV Might Be All You Need: codecut.ai
How to Structure a Data Science Project for Readability and Transparency: codecut.ai
Stop Hard-coding: Use Configuration Files Instead: codecut.ai
Simplify Your Python Logging with Loguru: codecut.ai
Git for Data Scientists: Learn Git Through Practical Examples: codecut.ai
Marimo (A Modern Notebook for Reproducible Data Science): codecut.ai
Text Similarity & Fuzzy Matching Guide: codecut.ai
Loguru (Python logging made simple): github.com
Hydra: hydra.cc
Marimo: marimo.io
Quarto: quarto.org
Show Your Work! Book: austinkleon.com

Watch this episode on YouTube: youtube.com
Episode #522 deep-dive: talkpython.fm/522
Episode transcripts: talkpython.fm

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