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.

Sentry Error Monitoring, Code TALKPYTHON

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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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