Skip to main content

ROOT I/O in pure Python and Numpy.

Project description

uproot

uproot (originally μproot, for “micro-Python ROOT”) is a reader and a writer of the ROOT file format using only Python and Numpy. Unlike the standard C++ ROOT implementation, uproot is only an I/O library, primarily intended to stream data into machine learning libraries in Python. Unlike PyROOT and root_numpy, uproot does not depend on C++ ROOT. Instead, it uses Numpy to cast blocks of data from the ROOT file as Numpy arrays.

Python does not necessarily mean slow. As long as the data blocks (“baskets”) are large, this “array at a time” approach can even be faster than “event at a time” C++. Below, the rate of reading data into arrays with uproot is shown to be faster than C++ ROOT (left) and root_numpy (right), as long as the baskets are tens of kilobytes or larger (for a variable number of muons per event in an ensemble of different physics samples; higher is better).

https://raw.githubusercontent.com/scikit-hep/uproot/master/docs/root-none-muon.png https://raw.githubusercontent.com/scikit-hep/uproot/master/docs/rootnumpy-none-muon.png

uproot is not maintained by the ROOT project team, so post bug reports here as GitHub issues, not on a ROOT forum. Thanks!

Installation

Install uproot like any other Python package:

pip install uproot                        # maybe with sudo or --user, or in virtualenv

or install with conda:

conda config --add channels conda-forge   # if you haven't added conda-forge already
conda install uproot

The pip installer automatically installs strict dependencies; the conda installer installs optional dependencies, too.

Strict dependencies:

Optional dependencies:

  • lz4 to read lz4-compressed ROOT files

  • lzma to read lzma-compressed ROOT files in Python 2

  • xrootd to access remote files through XRootD

  • requests to access remote files through HTTP

Reminder: you do not need C++ ROOT to run uproot.

Tutorial

See the project homepage for a tutorial.

Run that tutorial on Binder.

Reference documentation

Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

uproot-3.4.15.tar.gz (25.9 MB view details)

Uploaded Source

Built Distribution

uproot-3.4.15-py2.py3-none-any.whl (122.7 kB view details)

Uploaded Python 2 Python 3

File details

Details for the file uproot-3.4.15.tar.gz.

File metadata

  • Download URL: uproot-3.4.15.tar.gz
  • Upload date:
  • Size: 25.9 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.13.0 pkginfo/1.5.0.1 requests/2.21.0 setuptools/40.8.0 requests-toolbelt/0.9.1 tqdm/4.31.1 CPython/3.7.1

File hashes

Hashes for uproot-3.4.15.tar.gz
Algorithm Hash digest
SHA256 148966bfafedb104de7baa01595f3e6d977aa28af9368a26876118aa85674f67
MD5 ccb94755d09ae3531ab1a87ffc8b76fe
BLAKE2b-256 19f4a19fdf1d28b8bccb59d64edded06deee8a5471b319f2b3f6666570e45bd4

See more details on using hashes here.

Provenance

File details

Details for the file uproot-3.4.15-py2.py3-none-any.whl.

File metadata

  • Download URL: uproot-3.4.15-py2.py3-none-any.whl
  • Upload date:
  • Size: 122.7 kB
  • Tags: Python 2, Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.13.0 pkginfo/1.5.0.1 requests/2.21.0 setuptools/40.8.0 requests-toolbelt/0.9.1 tqdm/4.31.1 CPython/3.7.1

File hashes

Hashes for uproot-3.4.15-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 634883c53748a9d722ca2c2b071caac594373d72078dab50258e5ed113863b4a
MD5 0848b954c7c83294fa848787c7b5f1e6
BLAKE2b-256 06d6d7f496483c9bbf95d61004edb366ebfc56644788d03fcd259d497b24a1d1

See more details on using hashes here.

Provenance

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page