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https://github.com/llnl/hatchet-tutorial

Live interactive tutorial for Hatchet
https://github.com/llnl/hatchet-tutorial

binderhub comparative-analysis data-analytics docs documentation graphs hatchet hierarchical-data hpc pandas performance performance-analysis python radiuss trees tutorial

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Live interactive tutorial for Hatchet

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README

          

# hatchet Hatchet Tutorial

[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/llnl/hatchet-tutorial/main)

[Hatchet](https://github.com/llnl/hatchet) is a Python-based library that allows [Pandas](https://pandas.pydata.org) 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](https://llnl-hatchet.readthedocs.io/en/latest/).

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](https://mybinder.org) to create a shareable and interactive
environment of the notebooks within a live JupyterHub instance.

You can access the interactive environment at this
[link](https://mybinder.org/v2/gh/llnl/hatchet-tutorial/main)
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](https://github.com/hatchet/hatchet-tutorial/blob/main/LICENSE).

SPDX-License-Identifier: MIT

LLNL-CODE-741008