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timeit
Python standard-library module for measuring execution time of small code snippets.
Our View
timeit gives researchers a simple, repeatable way to compare small implementation choices before investing in heavier profiling or optimization work.
Provisional positions are editorial proposals awaiting group review.
Teaching — Recorded in topic offerings; consult the dated event links for availability.
1 topics with recorded teaching · 1 past offerings · 1 upcoming offerings
Related themes: Scientific Computing
Related topics: Arrays and Numerical ComputingAutomating Research WorkflowsRobust and Reusable Software
Common use cases
- Benchmark small Python expressions or functions
- Compare alternative implementations before refactoring
- Teach measurement-first performance thinking
Getting started
timeit is part of Python’s standard library. It runs small snippets repeatedly and reports timing measurements that are less noisy than a single manual timestamp around a line of code.
Why It Matters in Research Workflows
Optimization should start with measurement. timeit helps researchers test whether a small change actually improves runtime, and it encourages comparisons that are explicit enough to share or repeat.
In Our Teaching
We use timeit in high-performance Python as the first step in a profiling workflow. The course materials cover measuring and profiling performance in Python code before moving to larger-scale profiling tools.