The Real Python Podcast

Discover how Python is transforming bioinformatics & lab work with automation, DNA sequencing, & gut microbe research. Learn about using Python in lab robotics, DNA manipulation, and techniques for measurements. Also, explore a course spotlight on building Python project documentation using MkDocs.

Topics discussed include duck typing in Python, benefits and drawbacks, monkey patching for runtime behavior modification, Python community articles, becoming a senior developer, data exploration challenges, Python evaluation game, and regex testing with a terminal UI.

Bob Belderbos from Pybites discusses building a positive developer mindset while learning Python, sharing tips on overcoming coding blocks and delivering projects. Course spotlight on 13 intermediate project ideas. Topics cover community building, mindset definition, learning outside classroom, clean code writing, and moving from challenges to projects.

Discussion on automating tasks with Python scripts, building a micro-search engine from scratch, Python data analysis, open-source licensing, Python version changes, command line interfaces with argparse, operating systems, and IBIS data processing tool

Creator of pandas, Wes McKinney, discusses improving the data stack with Apache Arrow and composable systems. He talks about decoupling storage and computation, collaboration in the data science community, and the benefits of Arrow in tools like Polars and DuckDB. Wes also advocates for composable data systems and introduces Ibis, a portable dataframe API for data manipulation and exploration in Python.

The podcast discusses practical uses of Python decorators and common pitfalls of the Python datetime library. They also cover topics such as Python string formatting, falsehoods programmers believe, exploring decorators in Django and Flask, the potential of Rust in Python projects, and a replacement for the Requests library.

Savin Goyal returns to discuss updates to the open-source framework Metaflow, including capturing project snapshots and managing dependencies. He talks about starting a new company, Outerbounds, to build the Metaflow platform. The podcast also explores challenges of building AI apps, infrastructure requirements, and the scalability and flexibility of using Metaflow.

Stefanie Molin, a data scientist and software engineer at Bloomberg, discusses starting to contribute to open-source projects. Topics include finding ways to contribute, participating in community sprints, benefits of contributing, and finding beginner-friendly projects. The chapter also touches on the process of contributing, documenting Python projects, and the importance of organization in writing.

Christopher Trudeau, Python developer and author, shares a tutorial on building a debugger in Python. They also discuss preparing for changes to NumPy, transitioning from R to Python, and optimizing font files and physical quantities in Python.

Jodie Burchell, developer advocate for data science at JetBrains, discusses techniques and tools for evaluating large language models (LLMs) using Python. They explore measuring bias, toxicity, and truthfulness in LLMs, the challenges and limitations of AI language models, the role of Python packages like Hugging Face, and the concept of grouping and acronyms. Jodie also shares benchmarking datasets and resources available on Hugging Face for evaluating LLMs.