# hepdata_lib
[](https://doi.org/10.5281/zenodo.1217998)
[](https://badge.fury.io/py/hepdata-lib)
[](https://prefix.dev/channels/conda-forge/packages/hepdata-lib)
[](https://github.com/HEPData/hepdata_lib/actions)
[](https://codecov.io/gh/HEPData/hepdata_lib?branch=main)
[](http://hepdata-lib.readthedocs.io/)
[](https://github.com/HEPData/hepdata_lib/pkgs/container/hepdata_lib)
Library for getting your data into HEPData
- Documentation: https://hepdata-lib.readthedocs.io
This code works with Python 3.6, 3.7, 3.8, 3.9, 3.10, 3.11 or 3.12.
## Installation
It is highly recommended you install `hepdata_lib` into a [virtual environment](https://packaging.python.org/guides/installing-using-pip-and-virtual-environments/).
```shell
python -m pip install hepdata_lib
```
Alternatively, install from [conda-forge](https://anaconda.org/conda-forge/hepdata-lib) using a `conda` ecosystem package manager:
```console
conda install --channel conda-forge hepdata-lib
```
If you are not sure about your Python environment, please also see below how to use `hepdata_lib` in a Docker or Apptainer container.
The use of Apptainer is recommended when working on typical HEP computing clusters such as CERN LXPLUS.
## Getting started
For using `hepdata_lib`, you don't even need to install it, but can use the [binder](https://mybinder.org/) or [SWAN](https://swan.cern.ch/) (CERN-only) services using one of the buttons below:
[](https://mybinder.org/v2/gh/HEPData/hepdata_lib/main?filepath=examples/Getting_started.ipynb)
[](https://cern.ch/swanserver/cgi-bin/go/?projurl=https://github.com/HEPData/hepdata_lib.git)
You can also use the Docker image (recommended when working on local machine):
```shell
docker run --rm -it -p 8888:8888 -v ${PWD}:/home/hepdata ghcr.io/hepdata/hepdata_lib:latest
```
And then point your browser to [http://localhost:8888](http://localhost:8888) and use the token that is printed out. The output will end up in your current working directory (`${PWD}`).
If you prefer a shell, instead run:
```shell
docker run --rm -it -p 8888:8888 -v ${PWD}:/home/hepdata ghcr.io/hepdata/hepdata_lib:latest bash
```
If on CERN LXPLUS or anywhere else where there is Apptainer available but not Docker, you can still use the docker image.
If CVMFS (specifically `/cvmfs/unpacked.cern.ch/`) is available:
```shell
export APPTAINER_CACHEDIR="/tmp/$(whoami)/apptainer"
apptainer shell -B /afs -B /eos /cvmfs/unpacked.cern.ch/ghcr.io/hepdata/hepdata_lib:latest
```
If CVMFS is not available:
```shell
export APPTAINER_CACHEDIR="/tmp/$(whoami)/apptainer"
apptainer shell -B /afs -B /eos docker://ghcr.io/hepdata/hepdata_lib:latest 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](https://mybinder.org/) links below or using [SWAN](https://swan.cern.ch/) (CERN-only, please use LCG release LCG_94 or later) and selecting the corresponding notebook manually:
- [Reading in text files](https://github.com/HEPData/hepdata_lib/blob/main/examples/Getting_started.ipynb)
[](https://mybinder.org/v2/gh/HEPData/hepdata_lib/main?filepath=examples/Getting_started.ipynb)
<br/><br/>
- [Reading in a CMS combine ntuple](https://github.com/HEPData/hepdata_lib/blob/main/examples/combine_limits.ipynb)
[](https://mybinder.org/v2/gh/HEPData/hepdata_lib/main?filepath=examples/combine_limits.ipynb)
<br/><br/>
- [Reading in ROOT histograms](https://github.com/HEPData/hepdata_lib/blob/main/examples/reading_histograms.ipynb)
[](https://mybinder.org/v2/gh/HEPData/hepdata_lib/main?filepath=examples/reading_histograms.ipynb)
<br/><br/>
- [Reading a correlation matrix](https://github.com/HEPData/hepdata_lib/blob/main/examples/correlation.ipynb)
[](https://mybinder.org/v2/gh/HEPData/hepdata_lib/main?filepath=examples/correlation.ipynb)
<br/><br/>
- [Reading TGraph and TGraphError from '.C' files](https://github.com/HEPData/hepdata_lib/blob/main/examples/read_c_file.ipynb)
[](https://mybinder.org/v2/gh/HEPData/hepdata_lib/main?filepath=examples/read_c_file.ipynb)
<br/><br/>
- [Preparing scikit-hep histograms](https://github.com/HEPData/hepdata_lib/blob/main/examples/reading_scikithep_histograms.ipynb)
[](https://mybinder.org/v2/gh/HEPData/hepdata_lib/main?filepath=examples/reading_scikihep_histograms.ipynb)
<br/><br/>
## External dependencies
- [ROOT](https://root.cern.ch)
- [ImageMagick](https://www.imagemagick.org)
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.
A ROOT installation is not strictly required if your input data is not in a ROOT format, for example, if
your input data is provided as text files or `scikit-hep/hist` histograms. Most of the `hepdata_lib`
functionality can be used without a ROOT installation, other than the `RootFileReader` and `CFileReader` classes,
and other functions of the `hepdata_lib.root_utils` module.
Raw data
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"description": "# hepdata_lib\n\n[](https://doi.org/10.5281/zenodo.1217998)\n[](https://badge.fury.io/py/hepdata-lib)\n[](https://prefix.dev/channels/conda-forge/packages/hepdata-lib)\n[](https://github.com/HEPData/hepdata_lib/actions)\n[](https://codecov.io/gh/HEPData/hepdata_lib?branch=main)\n[](http://hepdata-lib.readthedocs.io/)\n[](https://github.com/HEPData/hepdata_lib/pkgs/container/hepdata_lib)\n\nLibrary for getting your data into HEPData\n\n- Documentation: https://hepdata-lib.readthedocs.io\n\nThis code works with Python 3.6, 3.7, 3.8, 3.9, 3.10, 3.11 or 3.12.\n\n## Installation\n\nIt is highly recommended you install `hepdata_lib` into a [virtual environment](https://packaging.python.org/guides/installing-using-pip-and-virtual-environments/).\n\n```shell\npython -m pip install hepdata_lib\n```\n\nAlternatively, install from [conda-forge](https://anaconda.org/conda-forge/hepdata-lib) using a `conda` ecosystem package manager:\n\n```console\nconda install --channel conda-forge hepdata-lib\n```\n\nIf you are not sure about your Python environment, please also see below how to use `hepdata_lib` in a Docker or Apptainer container.\nThe use of Apptainer is recommended when working on typical HEP computing clusters such as CERN LXPLUS.\n\n## Getting started\n\nFor using `hepdata_lib`, you don't even need to install it, but can use the [binder](https://mybinder.org/) or [SWAN](https://swan.cern.ch/) (CERN-only) services using one of the buttons below:\n\n[](https://mybinder.org/v2/gh/HEPData/hepdata_lib/main?filepath=examples/Getting_started.ipynb)\n[](https://cern.ch/swanserver/cgi-bin/go/?projurl=https://github.com/HEPData/hepdata_lib.git)\n\nYou can also use the Docker image (recommended when working on local machine):\n\n```shell\ndocker run --rm -it -p 8888:8888 -v ${PWD}:/home/hepdata ghcr.io/hepdata/hepdata_lib:latest\n```\n\nAnd then point your browser to [http://localhost:8888](http://localhost:8888) and use the token that is printed out. The output will end up in your current working directory (`${PWD}`).\n\nIf you prefer a shell, instead run:\n\n```shell\ndocker run --rm -it -p 8888:8888 -v ${PWD}:/home/hepdata ghcr.io/hepdata/hepdata_lib:latest bash\n```\n\nIf on CERN LXPLUS or anywhere else where there is Apptainer available but not Docker, you can still use the docker image.\n\nIf CVMFS (specifically `/cvmfs/unpacked.cern.ch/`) is available:\n\n```shell\nexport APPTAINER_CACHEDIR=\"/tmp/$(whoami)/apptainer\"\napptainer shell -B /afs -B /eos /cvmfs/unpacked.cern.ch/ghcr.io/hepdata/hepdata_lib:latest\n```\n\nIf CVMFS is not available:\n\n```shell\nexport APPTAINER_CACHEDIR=\"/tmp/$(whoami)/apptainer\"\napptainer shell -B /afs -B /eos docker://ghcr.io/hepdata/hepdata_lib:latest bash\n```\n\nUnpacking 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.\n\n## Further examples\n\nThere are a few more examples available that can directly be run using the [binder](https://mybinder.org/) links below or using [SWAN](https://swan.cern.ch/) (CERN-only, please use LCG release LCG_94 or later) and selecting the corresponding notebook manually:\n\n- [Reading in text files](https://github.com/HEPData/hepdata_lib/blob/main/examples/Getting_started.ipynb)\n[](https://mybinder.org/v2/gh/HEPData/hepdata_lib/main?filepath=examples/Getting_started.ipynb)\n<br/><br/>\n- [Reading in a CMS combine ntuple](https://github.com/HEPData/hepdata_lib/blob/main/examples/combine_limits.ipynb)\n[](https://mybinder.org/v2/gh/HEPData/hepdata_lib/main?filepath=examples/combine_limits.ipynb)\n<br/><br/>\n- [Reading in ROOT histograms](https://github.com/HEPData/hepdata_lib/blob/main/examples/reading_histograms.ipynb)\n[](https://mybinder.org/v2/gh/HEPData/hepdata_lib/main?filepath=examples/reading_histograms.ipynb)\n<br/><br/>\n- [Reading a correlation matrix](https://github.com/HEPData/hepdata_lib/blob/main/examples/correlation.ipynb)\n[](https://mybinder.org/v2/gh/HEPData/hepdata_lib/main?filepath=examples/correlation.ipynb)\n<br/><br/>\n- [Reading TGraph and TGraphError from '.C' files](https://github.com/HEPData/hepdata_lib/blob/main/examples/read_c_file.ipynb)\n[](https://mybinder.org/v2/gh/HEPData/hepdata_lib/main?filepath=examples/read_c_file.ipynb)\n<br/><br/>\n- [Preparing scikit-hep histograms](https://github.com/HEPData/hepdata_lib/blob/main/examples/reading_scikithep_histograms.ipynb)\n[](https://mybinder.org/v2/gh/HEPData/hepdata_lib/main?filepath=examples/reading_scikihep_histograms.ipynb)\n<br/><br/>\n\n## External dependencies\n\n- [ROOT](https://root.cern.ch)\n- [ImageMagick](https://www.imagemagick.org)\n\nMake sure that you have `ROOT` in your `$PYTHONPATH` and that the `convert` command is available by adding its location to your `$PATH` if needed.\n\nA ROOT installation is not strictly required if your input data is not in a ROOT format, for example, if\nyour input data is provided as text files or `scikit-hep/hist` histograms. 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