Building a Scientific Computing Platform (Quantum, ML, Math) in Pure Python Without NumPy

A developer has built a scientific computing platform called Cognitive Discovery System entirely in pure Python without NumPy, achieving O(N log N) FFT, O(N³) LU decomposition, and a quantum state-vector simulator with O(1) sampling. The platform includes linear algebra, machine learning, signal processing, and statistics modules, all implemented using only the Python Standard Library.

Hi everyone, We rely so heavily on tools like NumPy, SciPy, and PyTorch that most of us treat them like black magic. I wanted to break that illusion. My goal was to see if I could build a professional-grade computational science platform using nothing but the Python Standard Library. It turned into an obsessive deep dive into algorithmic optimization, memory management, and raw math. I've just released v0.6.0, and here is what it currently handles natively in Pure Python: Linear Algebra & Calculus: I had to scrap naive 0 N determinants for an O N3 Partial Pivoting LU decomposition to stop my machine from melting. Also includes an Adaptive Newton Method. Quantum Mechanics: A complete state-vector simulator. Instead of calculating matrices thousands of times for measurements, I implemented an 0 1 probabilistic sampling algorithm with true state collapse. Machine Learning from Scratch: A fully functioning Neural Network MLP trained by a custom-built Adam optimizer that features full momentum state persistence. Signal Processing: An O N log N zero-padded 1D/2D FFT and Convolution Theorem implementation. Statistics: An autonomous hypothesis engine that takes generated ideas and tests them against datasets using ANOVA and Welch's t-tests. The Ecosystem Upgrade: To prove it wasn't just a toy, I made sure the engineering standards were flawless: If you are a student who wants to read the actual math behind an FFT or a Quantum Gate without getting lost in C/C++ source code, or if you're just curious about how far vanilla Python can be pushed, I'd love for you to explore it. Feedback, code reviews, and stars are highly appreciated GitHub Repo: https://github.com/Furox88/cognitive-discovery-system https://github.com/Furox88/cognitive-discovery-system Documentation & Tutorials: https://furox88.github.io/cognitive-discovery-system/ https://furox88.github.io/cognitive-discovery-system/ PyPI Installation: pip install cognitive-discovery-platform