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S³ School 2026 — Debugger & Unit Tests (Build and Code) Speaker: Maximilian Linhoff (CTAO ERIC) Testing isn’t “extra work” — it’s the foundation of sustainable and reproducible research software. In this session, you’ll learn how to write solid unit tests in Python with pytest, measure coverage, and use debugging techniques to investigate failing tests efficiently. What you’ll learn: • Unit tests vs integration vs performance tests (and when to use each) • pytest essentials: test discovery, assertions, expected exceptions • Floating-point pitfalls: approximate comparisons + NumPy testing helpers • Fixtures & scopes (session vs function), temp directories, capturing output/logs • Mocking / monkeypatching external services & hard-to-test dependencies • Coverage (line + branch) with pytest-cov + HTML reports • Doctests and test-driven debugging (turning bugs into tests) 📚 Slides & materials (course page): https://s3-school.github.io/s3-2026-l... 📑 Slides (PDF): https://indico.in2p3.fr/event/36319/c... 🔗 Resources (all sessions): • S3 2026 Lectures (all notes/materials): https://s3-school.github.io/s3-2026-l... • GitHub organization (exercises & repositories): https://github.com/s3-school • Event page (Indico): https://indico.in2p3.fr/event/36319/ Tags (YouTube): pytest, unit testing, python testing, debugging, pdb, pytest fixtures, monkeypatch, mocking, pytest-cov, test coverage, branch coverage, doctest, tdd, floating point precision, numpy testing, software quality, research software, research software engineering, rse, reproducible research, open science, sustainable software, s3 school, s3 school 2026, build and code 🔔 If this helped: like, subscribe, and watch the next session in the S³ School 2026 series!