# jrfonseca/gprof2dot

Converts profiling output to a dot graph.

Repository: https://github.com/jrfonseca/gprof2dot
Canonical: https://ross.abutalabs.com/products/gprof2dot
Language: Python
License: LGPL-3.0
License Family: copyleft
Topics: profiling, graph, c-plus-plus, python
Last push: 2026-08-05T13:04:28+00:00

## Health v2 (maintenance only)
Score: 66/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 96, release rhythm 8, longevity 100
- inputs: {"age_days": 4191, "days_push": 28, "days_rel": 506, "gap_med": null, "n_releases_24m": 1}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 3454, forks 391 (observed 2026-08-28T04:08:05.450229+00:00)

## What it is
A Python command-line script that converts output from many profilers (perf, callgrind, gprof, Python profilers, etc.) into Graphviz dot call graphs. It prunes low-weight nodes, propagates time through recursion, and highlights hotspots with color.

## Use cases
- visualize perf output as a call graph
- convert valgrind callgrind data to a dot graph
- generate call graphs from Python profiler stats
- find hotspots in a program's call graph
- compare two profiling graphs
- turn gprof output into an image

## When to choose
- you have profiler output and want a visual call graph
- you want a lightweight cross-platform script using Python and Graphviz
- you need to prune noisy profiling data down to hotspots

## When to avoid
- you need an interactive profile viewer (use xdot.py or flamegraph tools)
- you need active development or new features
- you want flame charts rather than dot graphs

## Facets
- artifact type: cli-tool
- maturity: maintenance
- function: developer-tools, data-visualization, charts
- domain: developer-tools, performance
- platform: python, cli, cross-platform
- tags: profiling, graphviz, dot-graph, call-graph, performance-analysis, command-line

## Member repositories
- jrfonseca/gprof2dot (main) score 66

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:08:05.450229+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T18:37:31.399816+00:00, confidence not recorded.
  - readme: https://github.com/jrfonseca/gprof2dot (fetched 2026-08-28T04:08:05.450229+00:00, sha d98d51ca889c)
  - registry_pypi: https://pypi.org/pypi/gprof2dot/json (fetched 2026-08-29T09:31:14.700296+00:00, sha da919c4a787f)
- Data as of 2026-08-30T08:39:29.467469+00:00.