User guide

pybench ships two example benchmarks you can run yourself.

Start with the synthetic example — a fast, dependency-light loss-curve benchmark that runs in seconds. It is the quickest way to watch pybench save a baseline and then report a PASS or a FAIL, and it doubles as a hands-on demonstration of why pybench’s statistics hold up where simpler tests don’t.

Then see the MNIST example — a real neural-network training run, where pybench catches a regression in a genuinely noisy metric and walks through the full baseline → regression → re-baseline lifecycle.

• Synthetic example
• MNIST example