# csurfer/pyheatmagic

IPython magic command to profile and view your python code as a heat map.

Repository: https://github.com/csurfer/pyheatmagic
Canonical: https://ross.abutalabs.com/products/pyheatmagic
Language: Python
License: MIT
License Family: permissive
Topics: ipython, ipython-magic, profiler, heatmap
Last push: 2024-07-14T18:30:54+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3302, "days_push": 780, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1029, forks 22 (observed 2026-08-28T04:03:17.575715+00:00)

## What it is
An IPython magic extension that profiles Python code and renders the results as a heat map, wrapping the py-heat library. It exposes a %%heat cell magic that displays or saves the annotated heatmap as an image.

## Use cases
- profile python code in a jupyter notebook and visualize hotspots as a heatmap
- find slow lines in a python function from ipython
- save a profiling heatmap to a png file
- visualize line-by-line execution time of notebook code

## When to choose
- you work in IPython or Jupyter and want quick visual profiling of a code cell
- you prefer heatmaps over text-based profiler output

## When to avoid
- you need profiling outside IPython/Jupyter notebooks
- you need advanced profiling features like call graphs or statistical aggregation

## Facets
- artifact type: plugin
- maturity: maintenance
- function: benchmarking, data-visualization, developer-tools
- domain: developer-tools, data-visualization, performance
- platform: python, cli
- tags: ipython-magic, profiler, heatmap, jupyter, line-profiler

## Member repositories
- csurfer/pyheatmagic (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:17.575715+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 2026-08-30T07:07:38.603972+00:00, confidence not recorded.
  - readme: https://github.com/csurfer/pyheatmagic (fetched 2026-08-28T04:03:17.575715+00:00, sha a9822859a648)
- Data as of 2026-08-30T08:39:29.467469+00:00.