---
id: flameprof
version: "0.4"
license: MIT
license_treatment: permissive
maintenance: abandoned
---

# flameprof — cProfile flamegraph generator

License: permissive · Maintenance: abandoned · Downloads: 621.8K/mo

## What it is and what it does

Flameprof reads Python cProfile statistics and generates flamegraph visualizations to help you understand where your code spends time. It addresses a key limitation of cProfile's built-in reporting—which can be verbose and hard to parse—by rendering call stacks as compact, interactive flamegraphs. You profile your script normally using cProfile, then pipe the .prof file through flameprof to get an SVG you can open in a browser and explore by clicking.

The tool offers two output modes: native SVG with interactive features like tooltips showing cumulative and total timings and call counts, or a trace log format that feeds into the flamegraph.pl script. The native SVG mode includes visual cues like green bars to indicate where flameprof estimates timing ratios, and supports an inverted view to show total time across all calls. It's designed for developers, system administrators, and performance engineers who need to profile Python applications and visualize the results clearly.

Use it for:

- Profile a long-running Python service to identify bottlenecks and understand which functions consume the most CPU time.
- Generate an interactive SVG flamegraph from a cProfile dump to share with team members for performance review.
- Replace gprof2dot for Python profiling when you want cleaner, less noisy visualizations of call stacks.
- Export cProfile data as a trace log and process it with flamegraph.pl for further customization or analysis.
- Analyze batch job performance by profiling the script, generating a flamegraph, and drilling into specific call paths.

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

Converts Python cProfile statistics into interactive flamegraph visualizations, either as native SVG or as trace logs compatible with flamegraph.pl.

No. The package is abandoned (last commit 2023-03-23, latest release 2018-12-25) and likely has compatibility issues with modern Python versions. While it solves a real problem—making cProfile output readable—the lack of maintenance, combined with high install friction from a source tarball distribution, makes it a poor choice for new projects. Consider maintained alternatives for production profiling workflows.

## Install

pip install flameprof
uv add flameprof
poetry add flameprof

## Installing flameprof

Before you install: High install friction: the package is archived (last commit 2023-03-23) and abandoned. No runtime dependencies, but the distribution itself is a source tarball, suggesting potential build or extraction steps. Not actively maintained.

License in practice: MIT license is permissive and poses no restrictions on use, modification, or distribution in commercial or private projects.

Quickstart:

pip install flameprof

python -m cProfile -o myscript.prof myscript.py
flameprof myscript.prof > output.svg

Requires a cProfile .prof file as input; the package itself is no longer maintained and may have compatibility issues with modern Python versions.

Verify before relying:

- Whether the package works reliably with Python 3.10+ given its abandonment and last release in 2018.
- Whether the source tarball distribution requires compilation or has undocumented system dependencies.
- Compatibility with modern versions of flamegraph.pl when using --format=log output.

## Package facts

- License: MIT (permissive)
- Python support: unspecified
- Install friction: high
- Maintenance: abandoned
- Downloads: 621.8K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

python profiling visualization, cprofile flamegraph, performance profiling svg, call stack visualization, python cpu profiling, flamegraph generator, profile stat visualization, profiling, performance-analysis, visualization

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