semvec/pypi-packages huggingface dataset:
strax 2.2.2
Streaming analysis for xenon TPCs
Requires Python: <3.13,>=3.10

# strax
Streaming analysis for xenon experiments

[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.1340632.svg)](https://doi.org/10.5281/zenodo.1340632)
[![Readthedocs Badge](https://readthedocs.org/projects/strax/badge/?version=latest)](https://strax.readthedocs.io/en/latest/?badge=latest)
[![Coverage Status](https://coveralls.io/repos/github/AxFoundation/strax/badge.svg?branch=master)](https://coveralls.io/github/AxFoundation/strax?branch=master)
[![tests](https://github.com/AxFoundation/strax/actions/workflows/pytest.yml/badge.svg?branch=master)](https://github.com/AxFoundation/strax/actions/workflows/pytest.yml)
[![CodeFactor](https://www.codefactor.io/repository/github/axfoundation/strax/badge)](https://www.codefactor.io/repository/github/axfoundation/strax)
[![pre-commit.ci status](https://results.pre-commit.ci/badge/github/AxFoundation/strax/master.svg)](https://results.pre-commit.ci/latest/github/AxFoundation/strax/master)

[![PyPI version shields.io](https://img.shields.io/pypi/v/strax.svg)](https://pypi.python.org/pypi/strax/)
[![Python Versions](https://img.shields.io/pypi/pyversions/strax.svg)](https://pypi.python.org/pypi/strax)
[![PyPI downloads](https://img.shields.io/pypi/dm/strax.svg)](https://pypistats.org/packages/strax)
[![Join the chat at https://gitter.im/AxFoundation/strax](https://badges.gitter.im/Join%20Chat.svg)](https://gitter.im/AxFoundation/strax?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge)


Strax is an analysis framework for pulse-only digitization data, specialized for live data reduction at speeds of 50-100 MB(raw) / core / sec. For more information, please see the [strax documentation](https://strax.readthedocs.io).

Strax' primary aim is to support noble liquid TPC dark matter searches, such as XENONnT. The XENON-specific algorithms live in the separate package [straxen](https://github.com/XENONnT/straxen). If you want to try out strax, you probably want to start there. This package only contains the core framework and basic algorithms any TPCs would want to use.