Uproot is a library for reading and writing ROOT files in pure 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.
Uproot can be installed from PyPI using pip.
pip install uproot
Uproot is also available using conda.
conda install -c conda-forge uproot
If you have already added conda-forge as a channel, the -c conda-forge is unnecessary. Adding the channel is recommended because it ensures that all of your packages use compatible versions (see conda-forge docs):
conda config --add channels conda-forge
conda update --all
Start with the tutorials and reference documentation.
Uproot is an ordinary Python library; you can get a copy of the code with
git clone https://github.com/scikit-hep/uproot5.git
and install it locally by calling pip install -e . in the repository directory.
If you need to develop Awkward Array as well, see its installation for developers.
Uproot's only strict dependencies are NumPy and packaging. Strict dependencies are automatically installed by pip (or conda).
Awkward Array is highly recommended and is automatically installed by pip (or conda), though it is possible to use Uproot without it. If you need a minimal installation, pass --no-deps to pip and pass library="np" to every array-fetching function, or globally set uproot.default_library to get NumPy arrays instead of Awkward Arrays.
awkward: Uproot 5.x requires Awkward 2.x.The following libraries are also useful in conjunction with Uproot, but are not necessary. If you call a function that needs one, you'll be prompted to install it. (Conda installs most of these automatically.)
For ROOT files, compressed different ways:
lz4 and xxhash: if reading ROOT files that have been LZ4-compressed.zstandard: if reading ROOT files that have been ZSTD-compressed.For accessing remote files:
minio: if reading files with s3:// URIs.xrootd: if reading files with root:// URIs.For distributed computing with Dask:
dask: see uproot.dask.dask-awkward: for data with irregular structure ("jagged" arrays), see dask-awkward.For exporting TTrees to Pandas:
pandas: if library="pd".awkward-pandas: if library="pd" and the data have irregular structure ("jagged" arrays), see awkward-pandas.For exporting histograms:
boost-histogram: if converting histograms to boost-histogram with histogram.to_boost().hist: if converting histograms to hist with histogram.to_hist().Support for this work was provided by NSF cooperative agreements OAC-1836650 and PHY-2323298 (IRIS-HEP), grant OAC-1450377 (DIANA/HEP), and PHY-2121686 (US-CMS LHC Ops).
Thanks especially to the gracious help of Uproot contributors (including the original repository).
💻: code, 📖: documentation, 🚇: infrastructure, 🚧: maintainance, ⚠: tests/feedback, 🤔: foundational ideas.
FAQs
ROOT I/O in pure Python and NumPy.
We found that uproot demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 2 open source maintainers collaborating on the project.
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