Advice on Beginning to Learn Python
What's changed about learning Python over the last few years? What new techniques and updated advice should beginners have as they start their journey? This week on the show, Stephen Gruppetta and Martin Breuss return to discuss beginning to learn Python.
3 Loka 52min
Managing Feature Flags & Comparing Python Visualization Libraries
What's a good way to enable or disable code paths without redeploying the software? How can you use feature flags to toggle functionality for specific users of your application? Christopher Trudeau is back on the show this week, bringing another batch of PyCoder's Weekly articles and projects.
26 Syys 42min
Dangers of Automatically Converting a REST API to MCP
When converting an existing REST API to the Model Context Protocol, what should you consider? What anti-patterns should you avoid to keep an AI agent’s context clean? This week on the show, Kyle Stratis returns to discuss his upcoming book, "AI Agents with MCP".
19 Syys 1h 24min
Python App Hosting Choices & Documenting Python's History
What are your options for hosting your Python application or scripts? What are the advantages of a platform as a service, container-based hosts, or setting up a virtual machine? Christopher Trudeau is back on the show this week, bringing another batch of PyCoder's Weekly articles and projects.
12 Syys 43min
Large Language Models on the Edge of the Scaling Laws
What's happening with the latest releases of large language models? Is the industry hitting the edge of the scaling laws, and do the current benchmarks provide reliable performance assessments? This week on the show, Jodie Burchell returns to discuss the current state of LLM releases.
5 Syys 1h 28min
Exploring Mixin Classes in Python
What is a good way to add isolated, reusable functionality to Python classes? Christopher Trudeau is back on the show this week, bringing another batch of PyCoder's Weekly articles and projects.
29 Elo 50min
Travis Oliphant: SciPy, NumPy, and Fostering Scientific Python
What went into developing the open-source Python tools data scientists use every day? This week on the show, we talk with Travis Oliphant about his work on SciPy, NumPy, Numba, and many other contributions to the Python scientific community.
22 Elo 1h 11min
