ROOT I/O in pure Python and Numpy.
uproot (originally μproot, for “micro-Python ROOT”) is a reader and (someday) 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 calls to rapidly cast data blocks in the ROOT file as Numpy arrays.
It is important to note that uproot is not maintained by the ROOT project team, so post bug reports as uproot GitHub issues, not on any ROOT forum.
Install uproot like any other Python package:
pip install uproot
or similar (use
virtualenv, or pip-in-conda if you wish).
- Python (2.7+, 3.4+)
The following are installed automatically when you install uproot with pip:
- Numpy (1.13.1+)
- awkward-array to manipulate data from non-flat TTrees, such as jagged arrays (part of Scikit-HEP)
- uproot-methods (0.2.0+) for histogram and physics object methods, such as TLorentzVector (part of Scikit-HEP)
- cachetools for dict-like caches (replaces uproot 2’s custom caches)
- lz4 to read lz4-compressed ROOT files (now ROOT’s default compression method)
- lzma to read lzma-compressed ROOT files in Python 2 (not needed for Python 3 or if your ROOT files aren’t lzma-compressed)
- futures for parallel processing in Python 2 (not needed for Python 3 or if you don’t plan to use parallel processing)
- XRootD to access remote files; get version 4 or later for pyxrootd to be included in the package (unfortunately, you have to compile it manually with CMake)
Reminder: you do not need C++ ROOT to run uproot.
- Opening files
- ROOT I/O
- TTree Handling
- Parallel I/O