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README.md

perf.html

slack-badge

perf.html visualizes performance data recorded from web browsers. It is a tool designed to consume performance profiles from the Gecko Profiler but can visualize data from any profiler able to output in JSON. The interface is a web application built using React and Redux and runs entirely client-side.

Mozilla develops this tool to help make Firefox silky smooth and fast for millions of its users, and to help make sites and apps faster across the web.

Screenshot of perf.html

This project was previously called Cleopatra.

Usage

Visit perf-html.io 🚀

This project is live on https://perf-html.io/. The website includes instructions on how to get going to start recording and viewing performance profiles.

Development

You will need a recent enough version of Yarn, version 1.0.1 is known to work correctly. You can install it into your home directory on Linux and probably OS X with:

cd /tmp
wget https://yarnpkg.com/install.sh
chmod a+x install.sh
./install.sh

To download and build perf.html run:

git clone git@github.com:devtools-html/perf.html.git
cd perf.html
yarn install
yarn start

For more detailed information on getting started contributing. We have plenty of docs available to get you started.

Contributing Find out in detail how to get started and get your local development environment configured.
Code of Conduct We want to create an open and inclusive community, we have a few guidelines to help us out.
Developer Documentation Want to know how this whole thing works? Get started here.
Roadmap Get more information about why we are building this tool, and what we have planned.
Source Files Dive into the inner workings of the code. Most folders have a README.md providing more information.
Gecko Profiler Addon perf.html can record profiles directly in the browser using an add-on, development takes place in another repo.

Discussion

Say hello on slack in the #perf channel.

License

MPL v2

Some permissive software licenses request but do not require an acknowledgement of the use of their software. We are very grateful to the following people and projects for their contributions to this product:

  • The zlib compression library (Jean-loup Gailly, Mark Adler and team)