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<img src="https://raw.githubusercontent.com/llnl/hatchet/develop/logo-hex.png" width="64" valign="middle" alt="hatchet"/> Hatchet Tutorial

Hatchet is a Python-based library that allows Pandas dataframes to be indexed by structured tree and graph data. It is intended for analyzing performance data that has a hierarchy (for example, serial or parallel profiles that represent calling context trees, call graphs, nested regions’ timers, etc.). Hatchet implements various operations to analyze a single hierarchical data set or compare multiple data sets, and its API facilitates analyzing such data programmatically.

If you are new to hatchet and want to start using it, please check out the documentation here.

This repository contains materials for Hatchet's hands-on tutorial. You can do all of the exercises on your own laptop using BinderHub.

Running the notebooks online

We use BinderHub to create a shareable and interactive environment of the notebooks within a live JupyterHub instance.

You can access the interactive environment at this link or by clicking the badge at the top of this file.

License

This repository is distributed under the terms of the MIT license.

All contributions must be made under the MIT license. Copyrights are retained by contributors. No copyright assignment is required to contribute to this project.

See LICENSE.

SPDX-License-Identifier: MIT

LLNL-CODE-741008