How do you prepare your Python data science projects for production? What are the essential tools and techniques to make your code reproducible, organized, and testable? This week on the show, Khuyen Tran from CodeCut discusses her new book, “Production Ready Data Science.” Khuyen shares how she got into blogging and what motivated her to write a book. She shares tips on how to create repeatable workflows. We delve into modern Python tools that will help you bring your projects to production. Topics: 00:00:00 – Introduction 00:01:27 – Recent article about top six visualization libraries 00:02:19 – How long have you been blogging? 00:03:55 – What do you cover in your book? 00:07:07 – Potential issues with notebooks 00:11:40 – Structuring data science projects 00:15:12 – Reproducibility and sharing notebooks 00:20:33 – Using Polars 00:26:03 – Advantages of marimo notebooks 00:34:21 – Video Course Spotlight 00:35:44 – Shipping a project in data science 00:42:10 – Advice on testing 00:49:50 – Creating importable parameter values 00:53:55 – Seeing the commit diff of a notebook 00:55:12 – What are you excited about in the world of Python? 00:56:04 – What do you want to learn next? 00:56:52 – What’s the best way to follow your work online? 00:58:28 – Thanks and goodbye Show Links: Production Ready Data Science by Khuyen Tran - CodeCut CodeCut Top 6 Python Libraries for Visualization: Which One to Use? - CodeCut Ruff uv Cookiecutter marimo - a next-generation Python notebook Episode #230: marimo: Reactive Notebooks and Deployable Web Apps in Python Polars — DataFrames for the new era Episode #260: Harnessing the Power of Python Polars Narwhals Episode #224: Narwhals: Expanding DataFrame Compatibility Between Libraries pytest documentation nbdime: Tools for diffing and merging of Jupyter notebooks. LangChain Build Production-Ready LLM Agents with LangChain 1.0 Middleware - CodeCut Build an LLM RAG Chatbot With LangChain Khuyen Tran - LinkedIn Khuyen Tran (@KhuyenTran16) - X Level up your Python skills with our expert-led courses: Working With Python Polars Getting Started With marimo Notebooks Python Project Management With uv Suppor