hepdata_lib

Library for getting your data into HEPData

Installation

It is highly recommended you install hepdata_lib into a virtual environment.

pip install hepdata_lib

If you are not sure about your Python environment, please also see below how to use hepdata_lib in a Docker or Singularity container.

Getting started

For using hepdata_lib, you don't even need to install it, but can use the binder or SWAN (CERN-only) services using one of the buttons below and following the instructions in the notebook with name Getting_started:

You can also use the Docker image:

docker run --rm -it -p 8888:8888 -v ${PWD}:/home/hepdata clelange/hepdata_lib

And then point your browser to http://localhost:8888 and use the token that is printed out. The output will end up in your current working directory (${PWD}).

If you prefer a shell, instead run:

docker run --rm -it -p 8888:8888 -v ${PWD}:/home/hepdata clelange/hepdata_lib bash

If on CERN LXPLUS or anywhere else where there is Singularity available but not Docker, you can still use the docker image:

export SINGULARITY_CACHEDIR="/tmp/$(whoami)/singularity"
singularity shell -B /afs -B /eos docker://clelange/hepdata_lib bash

Unpacking the image can take a few minutes the first time you use it. Please be patient. Both EOS and AFS should be available and the output will be in your current working directory.

Further examples

There are a few more examples available that can directly be run using the binder links below or using SWAN (CERN-only, please use LCG release LCG_94 or later) and selecting the corresponding notebook manually:

• Reading in text files
• Reading in a CMS combine ntuple
• Reading in ROOT histograms
• Reading a correlation matrix
• Reading TGraph and TGraphError from '.C' files

External dependencies

• ROOT
• ImageMagick

Make sure that you have ROOT in your $PYTHONPATH and that the convert command is available by adding its location to your $PATH if needed.