Talk Python To Me

Simon Willison and Adrian Holovaty, co-creators of Django, along with Jeff Triplett from the Django Software Foundation, reflect on the framework's evolution over 20 years. They delve into Django's origins in journalism, its powerful community culture, and the impact of open source. The trio discusses modern enhancements like async features and API development, all while keeping Django's inclusive spirit. They also explore its role in AI, the significance of initiatives like Django Girls, and future challenges for web development. A compelling look at Django’s legacy and what lies ahead!

This discussion features Matt Makai, VP of Developer Relations at DigitalOcean and creator of Full Stack Python, who dives into the world of agentic AI programming. He breaks down how coding assistants are evolving from simple autocomplete tools to collaborative partners. Topics include managing technical debt, the quirks of AI tools like Cursor and Claude Code, and effective git workflows for AI-driven changes. Matt shares insights on why typing less can lead to more bugs and the future of open-source agents, highlighting the shift towards developers as system editors.

Ben Zaitlen, a system software manager at NVIDIA with over 15 years in the Python ecosystem, discusses revolutionary advancements in GPU-accelerated data science. He unpacks RAPIDS, an open-source toolkit that supercharges popular libraries like pandas and scikit-learn. Listeners learn about the challenges and triumphs of GPU integration, including speed boosts that reduce hours of work to mere minutes. The conversation also covers scaling techniques for large datasets and the exciting future of using GPUs to revolutionize AI workloads.

Mason Egger, a developer educator at Temporal and president of the PyTexas Foundation, chats about making Python applications crash-proof with the Temporal framework. He explains how Temporal manages resilient workflows and simplifies error handling, allowing seamless execution during failures. The discussion also touches on organizing Python conferences and the shift in community engagement, especially post-COVID. Plus, he shares insights into managing budgets in data science and the open-source landscape of Temporal, highlighting its benefits for developers.

Seth Michael Larson, a security expert and Python blogger, shares his insights from the closed-door Python Language Summit 2025. He dives into critical discussions about Python's future, covering topics like the need for ARM builders in GitHub CI and the innovative integration of Rust for improved memory safety. Seth also addresses challenges with thread safety, the implications of immutability, and Python's governance dynamics. With excitement for upcoming features in Python 3.14, he provides a glimpse into evolving development opportunities in the community.

Join Python legends Barry Warsaw, Paul Everitt, Carol Willing, and Brett Cannon as they share hilarious and heartfelt stories from Python's colorful history. Discover how the quirky name linked to Monty Python and the evolution from a niche language to an AI powerhouse have shaped the community. Enjoy anecdotes from the very first PyCon and hear about Python's growing presence in the banking sector. Their reflections celebrate the camaraderie that defines the Python community and foster a spirit of mentorship and inclusivity.

Join Brandt Bucher, a Python core developer at Microsoft, as he dives deep into the development of a JIT compiler for CPython. Discover how this initiative differs from JITs in languages like C# and Java. The conversation highlights recent performance advancements and the delicate balance between speed and memory efficiency. Brandt discusses integer performance optimizations, error tracking with Sentry, and the collaborative dynamics between the JIT compiler and the adaptive interpreter, all crucial for modern Python's evolution.

Catherine Nelson, a self-employed data scientist and author of 'Software Engineering for Data Scientists,' discusses vital techniques for transitioning from local data science notebooks to robust production workflows. She shares insights on effective coding practices, the challenges of machine learning integration, and organizing Python projects for scalability. Additionally, Catherine highlights the dual nature of notebooks, emphasizing their role in project exploration versus production needs. Her personal journey reflects a rich intersection between software engineering principles and data science.

Christopher Trudeau, a Python educator and author, dives into the impressive capabilities of the Polars library for data science. He discusses essential tools like Patito for data validation and polars_encryption for adding security. The conversation explores Polars' integration with web frameworks like Django and Flask, its lazy evaluation for optimized performance, and innovative features such as DataFramely. Trudeau emphasizes the importance of data integrity and effective error tracking, providing insights for enhancing data workflows.

Bryce Adelstein Lelbach from NVIDIA, a pioneer in programming language evolution, discusses the transformative use of GPUs in modern computing, moving beyond traditional graphics. He highlights advancements in Python SDKs that allow pure Python coding for GPU programming, making it more accessible. The conversation also delves into the evolution of ARM processors, the implications of Python 3.13's removal of the global interpreter lock, and essential algorithms for high-performance tasks, paving the way for more efficient data science and machine learning applications.