The Real Python Podcast

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.

Explore the different ways to serialize data in Python beyond XML and JSON. Learn about naming conventions in Python and how to avoid name clashes with keywords. Discover how to build a custom REPL in Python and override the default behavior. Dive into the comprehensive resource on serialization in Python, covering different methods and considerations. Gain insights into the importance of balancing quality and shipping in software development. Hear about frustration with project setups and learn about 'flask muck', a well-documented project for generating RESTful APIs. Finally, discover NH3, a Python wrapper for the ammonia tool, a replacement for the deprecated HTML sanitizer bleach.

Principal Architect John Lam and Sr. Cloud Developer Advocate Sarah Kaiser from Microsoft discuss the journey of adding Python to Excel. They explore data science workflows, interactive visualizations, and resources to learn more. The podcast also touches on the benefits of Python in Excel and the importance of team assembly and security. Additionally, they discuss possibilities in Python with Rust and advancements in AI.

Three members of the Real Python team, Kate Finegan, Tappan Moore, and Philipp Acsany, discuss their year-end wrap-up of tutorials, projects, and video courses. They highlight onboarding new writers and video instructors, the 'Recursion in Python' video course, and various topics including building a Wordle clone with Python and Rich, Python classes, and sorting Unicode strings. They also mention their excitement for future content on the Real Python Podcast.

Python trends of 2023: removing dead batteries from the standard library, speeding up Python, using Rust code in libraries, and moving away from microservices. Recent releases include Python 3.13 alpha 2, Django 5, and Ninja 1.0. Also discussed: JavaScript library, Python video course on object-oriented programming, Mojo programming language for Python's performance in machine learning and AI, and microservices trend with Kraken Technologies' approach to Python monolith structuring.

The podcast explores code reviews in Python, discussing the experiences of developers in different organizations and the importance of constructive feedback. They also delve into the benefits of coding tools like co-pilot for code review and the potential of AI in code development. Additionally, the podcast highlights the impact of code assistance tools on code development and explores developments in Python and AI. The speakers also discuss their website, social media presence, and future plans.

Python language enhancement ideas discussed including simplifying keyword arguments syntax and returning named tuples from functions. Tutorial on building a JSON-like parser in Python. Other topics include upcoming episodes, PyPI security audit, mentoring work impact, Django admin interface, Git terminology confusion, Python Advent of Code video course, using named tuples as function returns, projects 'grab links' and 'Reg X Crossword'

Lawrence Gray, author of “Mastering Python: A Problem Solving Approach,” discusses the future of Python in AI systems and its cognitive benefits. He shares his personal journey of learning Python during a difficult time and how it changed his thinking. The podcast explores Python's uniqueness, its role in computational thinking, and preparing for an AI-driven future. They also touch on critical thinking, problem-solving, and the empowering feeling of fixing coding problems. Plus, they discuss computers' memory capabilities, deep learning, computer vision, and Lawrence's upcoming book release.