Talk Python To Me

Larry Ogrodnek, software developer and creator of PyView, brings Phoenix LiveView style real-time patterns to Python. He explains server-managed state with WebSocket diffs and how templates map to render trees. They explore event handling, JS hooks for rich front-end libs, T-Strings and Pythonic APIs, and deployment and scaling trade-offs for real-time Python web apps.

Vincent Warmerdam, a skilled data scientist and developer at Marimo, delves into the world of caching with DiskCache. He discusses the significance of caching in ML workflows, explaining how it saves time and costs. The conversation explores comparing traditional systems like Redis to SQLite’s innovative usage for persistent caches. Vincent shares insights on advanced features like sharding, memoization, and custom serialization, providing practical advice on designing effective cache keys. Tune in for practical tips and the future of caching in Python.

Join experts from the Python web framework universe: Carlton Gibson (Django core contributor), Sebastián Ramírez (creator of FastAPI), David Lord (lead maintainer of Flask), Janek Nouvertné, and Cody Fincher (Litestar maintainers). They dive into deploying applications in production, discussing everything from optimal database choices, like when to use SQLite versus Postgres, to deployment patterns with Kubernetes and Docker. Expect insights on avoiding blocking in async code, the performance boosts of upgrading Python, and deploying efficiently with FastAPI Cloud.

Join a powerhouse panel featuring Gregory Kapfhammer, an expert in software engineering, Thomas Wouters, a key figure in Python's core development, Jodie Burchell, a data scientist at JetBrains, Brett Cannon, a seasoned Python developer at Microsoft, Reuven Lerner, a Python trainer, and Barry Warsaw, a veteran core contributor. They discuss the future of Python in 2025, exploring AI's evolving role, the impact of lazy imports and free-threading, and the need for improved community funding. Get insights on user experience enhancements and the balance between simplicity and debugging challenges.

In this discussion, Michael Kennedy, an influential Python educator and author, shares insights from his latest book, Talk Python in Production. He delves into the pitfalls of over-architecting and emphasizes pragmatic solutions for deploying web apps affordably. Michael also highlights the human side of open source and how AI tools can enhance productivity, sharing his own experience of using AI for site improvement. Additionally, he contrasts major cloud providers with smaller options, advocating for predictable costs and better user experiences.

Trevor Manz, a software engineer and anywidget creator with a PhD from Harvard focused on data visualization, dives into revolutionizing Jupyter widgets. He discusses the challenges of integrating front-end UI with Python and how anywidget simplifies this by minimizing JavaScript usage. Trevor highlights its role in enabling interactive visualizations and data exploration. He also covers the importance of cross-platform functionality and using AI to streamline widget development, making advanced data interactions accessible for all Python users.

David Kopec, a computer science professor and author, discusses rebuilding CS education for self-taught programmers. He emphasizes the importance of teaching low-level concepts through Python for better understanding. David highlights curriculum innovations blending liberal arts with careers, and the growing relevance of AI and cybersecurity majors. They also tackle challenges posed by AI tools in education, advocate for fundamental learning despite advancements, and explore practical projects like NES emulators and simple algorithms for art, illustrating the depth of CS concepts.

Vincent Warmerdam, a Python developer and educator behind CalmCode and Marimo, dives into the practical integration of LLMs into Python apps. He emphasizes treating LLMs as just another API, with specific boundaries and focused monitoring to enhance reliability. Topics include efficient caching of LLM responses, the benefits of using structured outputs with Pydantic, and the contrasting advantages of Marimo over Jupyter. Vincent also explores ways to improve productivity through ergonomic workflows and local model experimentation.

Den Delimarsky, a Principal Product Engineer at Microsoft and a key figure behind the Model Context Protocol (MCP), dives into the revolutionary potential of MCP for Python developers. He explains how MCP serves as a universal adapter for LLMs to access dynamic data across applications. The conversation includes practical insights on using MCP for podcast workflows, securing local servers with Tailscale, and programming with Python decorators. Delimarsky emphasizes the importance of prudently exploring public MCP servers while providing a roadmap for getting started with the Python MCP SDK.

Hugo Bowne-Anderson, a seasoned data scientist and educator, dives into the practicalities of building AI products with foundation models. He shares insights on the shift from analyst to AI app builder, emphasizing evaluation-driven development and the importance of proper data workflows. Hugo explores modern data tools like Marimo and DuckDB, and discusses the impact of AI on programming practices, including agentic coding. He also provides valuable advice for new data scientists to focus on delivering business value.