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What are the key characteristics of complex systems, and what are practical patterns for tackling complex coding problems? Christopher Trudeau is back
Check your understanding of building a command line rock paper scissors game in Python, from player input and loops to enums and dictionary rules.
Test your Claude Code basics: install it, set it up, work with CLAUDE.md, and use Git to stay in control of your changes.
Explore Python 3.15's new sampling profiler and learn low-overhead profiling of scripts, threads, and live production processes.
Test your understanding of Python 3.15's new sampling profiler, from CPU and GIL modes to flame graphs, heatmaps, and attaching to a live process.
Learn about Python's print() function, discover its lesser-known features, avoid common mistakes, and know when to use a better alternative.
Test your grasp of Python 3.12 static typing. Practice the new type variable syntax, the @override decorator, and typed dictionaries.
Check what you know about Python's print() function, including string formatting, escape sequences, file streams, and when to reach for logging instea
Learn how to write an AGENTS.md file so your AI coding agent produces idiomatic Python code that fits your project on the first try.
Check your understanding of how an AGENTS.md file gives your AI coding agent the project context it needs to write code that fits your project.
Test your understanding of Git basics for Python projects, including commits, the staging area, branches, merges, and working with remote repos.
Why do AI systems silently fail? How can you set up a system that produces results while also reviewing and validating the work? This week on the show
Test your grasp of the CPython source code, from bytecode and memory management to frames and generators. Based on the CPython 3.8 walkthrough.
Learn how to use Claude Code to build and debug Python projects with natural-language commands right from your terminal.
Test your understanding of Claude Code by working through installation, plan mode, diff review, and debugging a Python project.
Test your understanding of how to review AI-generated Python code, from automated checks to the bugs that coding agents get wrong most often.
Learn how to use Python's deque to efficiently append and pop items from both ends, build queues and stacks, and set maxlen for bounded history.
Test your understanding of Python's deque. Practice fast appends and pops at both ends, building queues and stacks, and setting maxlen.
Check your understanding of using Arduino with Python. Practice setting up circuits, using the Firmata protocol, and controlling inputs and outputs.
Learn AI debugging by pairing with an AI coding agent: reproduce the bug with a failing test, give your agent context, then verify the fix.