Note
fasthep-toolbench is still in early development, which means it is
incomplete and the API is not yet stable. Please report any issues you find on
the
GitHub issue tracker.
fasthep-toolbench is a collection of tools and utilities for FAST-HEP packages.
This project is in early development. The documentation is available at
fasthep-toolbench.readthedocs.io
and contains mostly fictional features. The most useful information can be found
in the FAST-HEP documentation. It describes the
current status and plans for the FAST-HEP projects, including
fasthep-toolbench (see
Developer's Corner).
You can install fasthep-toolbench using pip:
pip install fasthep-toolbenchYou had a look and are interested to contribute? That's great! There are three main ways to contribute to this project:
- Head to the issues tab and see if there is anything you can help with.
- If you have a new feature in mind, please open an issue first to discuss it. This way we can ensure that your work is not in vain.
- You can also help by improving the documentation or fixing typos.
Once you have something to work on, you can have a look at the contributing guidelines. It contains recommendations for setting up your development environment, testing, and more (compiled by the Scientific Python Community).
Important
How you customise your development environment is up to you. You like
uv? Be our guest. You prefer
nox? That's fine too. You want to use
? Go ahead. We are happy as long as you are happy.
Ideally you should be able to run pylint, pytest, and the pre-commit
hooks. If you can do that, you are good to go.
This project is licensed under the terms of the Apache 2.0 license. See LICENSE for more details.
Special thanks to the gracious help of FAST-HEP contributors:
Luke Kreczko |
This software is a continuation of the work done in the fasthep-toolbench and fast-toolbench repositories. The original code was developed by Ben Krikler and has been adapted and improved by various collaborators. The new version of the software is designed to be more flexible and extensible, allowing users to easily create custom data processing pipelines.
Part of the development of this software was funded by the IRIS Digital Assets grant.