order
Contents
order#
If you’re designing a high-energy physics analysis (e.g. with data recorded by an LHC experiment at CERN, manual bookkeeping of external data can get complicated quite fast. order provides a pythonic class collection that helps you structuring
analyses,
MC campaigns,
datasets,
physics process and cross sections,
channels,
categories,
variables, and
systematic shifts.
Projects using order#
tba
Installation and dependencies#
Install order via pip:
pip install order
The only dependencies are scinum and six (Python 2 support that will be dropped soon), which are installed with the above command.
Contributing and testing#
If you like to contribute, feel free to open a pull request 🎉. Just make sure to add new test cases and run them via:
python -m unittest tests
In general, tests should be run for Python 2.7, 3.6 - 3.11. To run tests in a docker container, do
# run the tests
./tests/docker.sh python:3.9
# or interactively by adding a flag "1" to the command
./tests/docker.sh python:3.9 1
> pip install -r requirements.txt
> python -m unittest tests
In addition, PEP 8 compatibility should be checked with flake8:
flake8 order tests setup.py
Development#
Source hosted at GitHub
Report issues, questions, feature requests on GitHub Issues