---
id: snakeviz
version: "2.2.2"
license: Copyright (c) 2012, Matt Davis All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: -… (full text in the JSON record)
license_treatment: permissive
maintenance: active
---

# snakeviz — A web-based viewer for Python profiler output

License: permissive · Maintenance: active · Downloads: 2.7M/mo

## What it is and what it does

SnakeViz is a web application that visualizes Python profiling output in your browser. It takes profiling data generated by Python's standard cProfile or profile module and renders it as an interactive hierarchy showing which functions consumed the most time and how they called one another. The tool runs a local web server (powered by tornado) and displays the call tree in a format inspired by RunSnakeRun, making it easy to spot performance bottlenecks without leaving your browser.

The package is designed for developers who need to understand where their Python code spends execution time. You generate a profile using Python's built-in profiling tools, then point SnakeViz at the output file. It handles the visualization and interaction, letting you drill down into call stacks and compare time spent across different code paths.

Use it for:

- Identify performance bottlenecks in a Python application by visualizing which functions consume the most CPU time.
- Explore call hierarchies interactively to understand how functions call one another and where time is actually spent.
- Compare profiling runs across different code versions to see if optimizations had the intended effect.
- Debug slow batch jobs or data processing pipelines by profiling them and examining the results in a browser.
- Share profiling results with team members by exporting or viewing the web interface on a shared machine.

## Worth the install?

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

SnakeViz is a web-based viewer for Python profiling data that displays call stacks and execution time hierarchies in an interactive browser interface.

Yes. SnakeViz is a mature, actively maintained tool with low install friction, no security vulnerabilities, and a permissive license. It solves a real problem—making Python profiling data readable—and integrates seamlessly with Python's standard profiling workflow. Install it if you regularly profile Python code and want a better way to explore the results than command-line tools.

## Install

pip install snakeviz
uv add snakeviz
poetry add snakeviz

## Installing snakeviz

Before you install: Low install friction with a single runtime dependency (tornado). Actively maintained with recent commits and broad Python version support (3.9–3.13). Repository is not archived and has accumulated 2568 stars.

License in practice: BSD License (permissive). You may use, modify, and distribute the software freely in source or binary form, provided you retain the copyright notice and disclaimer; you cannot use the author's name to endorse derived products.

Quickstart:

pip install snakeviz

# After profiling with cProfile or profile module:
snakeviz profile_output.prof

Requires Python 3.9 or later. Profiling data must be generated separately using Python's built-in cProfile or profile module before visualization.

Verify before relying:

- Whether the web interface requires a specific browser or has known compatibility constraints.
- Whether snakeviz can handle very large profiling datasets without performance degradation.

## Package facts

- License: Copyright (c) 2012, Matt Davis All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: -… (full text in the JSON record) (permissive)
- Python support: supports_current
- Install friction: low
- Maintenance: active
- Downloads: 2.7M/month (top 5,000 on PyPI)
- Known vulnerabilities: none known

## Tags

python profiler visualization, profile output viewer, call stack explorer, python performance analysis, web-based profiling tool, flame graph alternative, runtime profiler browser, profiling, performance-analysis, web-ui

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