joerick/pyinstrument
🚴 Call stack profiler for Python. Shows you why your code is slow! observed · 2026-08-28
Health v2 · maintenance only
92/100
- Activity 96
- Release rhythm 83
- Longevity 100
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.
- gap_med: 77
- age_days: 4556
- days_rel: 35
- days_push: 29
- n_releases_24m: 8
Adoption not part of the score
8006 stars · 299 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded
pyinstrument is a call stack profiler for Python that helps identify why code is slow. It supports profiling scripts, async code, Django apps, and Jupyter notebooks, and renders statistical profiles as text or HTML reports.
Use cases
- profile a slow python script
- find performance bottlenecks in my code
- profile async python code
- profile django request performance
- profile code in a jupyter notebook
- generate an html flame report of a python program
When to choose
- you want a statistical call stack profiler with low overhead
- you need to profile async or Django code
- you want readable text or HTML profile reports
When to avoid
- you need line-level or deterministic tracing detail
- you are profiling inside Docker where timing may be inaccurate
- you need profiling for languages other than Python
Facets
library · maturity active
benchmarking developer-tools developer-tools performance web-development python cross-platform cli profiler call-stack django async jupyter performance-analysis
1 source
- readme: https://github.com/joerick/pyinstrument · fetched 2026-08-28 · 839550c99404
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| joerick/pyinstrument | main | 92 |
For agents
markdown · JSON · MCP: product_card(name="joerick/pyinstrument")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem