Building your own minimalist NumPy like, ArryPy, it reveals the secret sauce behind high-performance array computing.

In this hands-on workshop, you’ll start with a naïve Python loop, then progressively supercharge it: first pure-Python ufuncs, next Cython-typed memoryviews, and finally native C with SIMD via pybind11.

Along the way, you’ll benchmark each stage in a live leaderboard, turning optimization into a competition. You’ll leave equipped with concrete skills in profiling, vectorization, and extension modules—and a clear roadmap for writing faster Python code in any project.