Using ROOT with python

Last updated on 2024-07-26 | Edit this page

Estimated time: 5 minutes

Overview

Questions

  • Can I call ROOT from python?

Objectives

  • Find resources for PyROOT
  • Find resources for Scikit-HEP

PyROOT

The PyROOT project started with Wim Lavrijsen in the late `00s and became very popular, paralleling the rise of more general python tools within the community. Python has become the primary analysis language for the majority of HEP experimentalists. It has a rich ecosystem that is constantly evolving. This is a good thing because it means that improvements and new tools are always being developed, but it can sometimes be a challenge to keep up with the latest and greatest projects! :)

If you want to learn how to use PyROOT, you can go through some individual examples here, or a more guided tutorial here.

Feel free to challenge yourself to rewrite the previous C++ code using PyROOT!

Scikit-HEP libraries

Over the past several years, an effort has developed to provide more python tools that can interface with CMS ROOT file formats as well as typical scientific python tools used widely beyond particle physics. We will use several of the Scikit-HEP libraries to analyze NanoAOD: uproot, awkward, and vector. As CMS datasets grow larger, we increasingly rely on tools for array-based data processing in python, and the scikit-HEP tools are very important for that task.

You can check out a tutorial for many of their tools here.

Using the Python docker container

The tools in the Python docker container will allow you to can easily open and analyze ROOT files. This is useful for when you make use of the CMS open data tools to skim some subset of the open data and then copy it to your local laptop, desktop, or perhaps an HPC cluster at your home institution.

If you completed the Docker pre-exercises you should already have worked through this episode, under Download the docker images for ROOT and python tools and start container, and you will have

  • a working directory cms_open_data_python on your local computer
  • a docker container with name my_python created with the working directory cms_open_data_python mounted into the /code directory of the container.

Start your python container with

BASH 

docker start -i my_python

In the container, you will be in the /code directory and it shares the files with your local cms_open_data_python directory.

If you’re using apptainer:

Whenever you see a docker start instruction, replace it with apptainer shell to open either the ROOT or Python container image. The specific commands in this pre-exercise and during the live workshop will be given for docker, since that is the most common application. As a general rule, editing of files will be done in the standard terminal (the containers do not have all text editors!) or via the jupyter-lab interface, and then commands will be executed inside the container shell. If you see Singularity> on your command line, you are ready to run a ROOT or python script.

If you want to test out the installation, from within Docker you can launch and interactive python session by typing python (in Docker) and then trying

PYTHON 

import uproot
import awkward as ak

If you don’t get any errors then congratulations! You have a working environment and you are ready to perform some HEP analysis with your new python environment!

Key Points

  • PyROOT is a complete interface to the ROOT libraries
  • Scikit-HEP provides tools to interface between ROOT and global scientific python tools
  • We will use uproot, awkward, and vector in our NanoAOD analysis