Python quant guides launched
Two practical resources dropped Mar 15: a Medium guide on building a hedge‑fund style quant system in Python published and a PyQuant News starter stack course for finance pros new to Python promoted. Both promise hands‑on code for backtests, data handling and prototype workflows that junior quants can add to a GitHub portfolio.
A step‑by‑step guide by Bhaskar Das — the Medium author behind practical trading and tech posts — publishes a hands‑on blueprint for building a Python quant system. (medium.com) That Medium blueprint maps an end‑to‑end pipeline from data ingestion through backtesting to live execution and risk controls, and the syndicated copy of the piece describes modular, code‑first sections and risk‑management checkpoints. (blog.www2.ro) PyQuant News’ course "Getting Started With Python for Quant Finance" is packaged as roughly 20 hours of instruction split across 13 modules with 40+ ready‑to‑use code templates and over 1,740 alumni. (pyquantnews.com) PyQuant’s ecosystem includes a large Substack archive and claims a newsletter audience in the hundreds of thousands plus a community of ~1,500–1,700 finance practitioners; its lessons explicitly cover automated databases, broker integration and real market data workflows. (pyquantnews.substack.com) Both the Medium guide and PyQuant push tangible, GitHub‑friendly outputs: the PyQuant course advertises copy‑paste templates and project workflows, while the Medium article’s step‑by‑step narrative is presented alongside code examples intended for prototyping. (pyquantnews.com) The two releases together foreground the same practical building blocks employers expect from junior quants—data pipelines, reproducible backtests, and broker‑connected prototypes—and each resource points students to reusable codebases and templates for portfolio pieces. (blog.www2.ro)
