Python in 2026 is the lingua franca of working-with-data: spreadsheets, science, scripts, ML. For the non-engineers — analysts, scientists, writers, lawyers using it for one specific task — the learning resources have stratified into beginner tutorials that don't transfer, books that assume you want to be a software engineer, and a handful of genuinely useful guides for your specific job. This page is a syllabus for someone who wants Python as a tool rather than as a profession, organized by what each part of the practice does: the starter resources that respect your time, the libraries you'll actually use, the environment-setup choices that prevent painful detours, and the writers worth following to deepen the practice. One deliberate omission: pure software-engineering Python (web frameworks, devops, async runtimes) is not covered — that's a different career path with its own canon.

A Python syllabus for non-engineers — researchers, analysts, scientists, curious adults.