Awkward Array is a library for nested, variable-sized data, including arbitrary-length lists, records, mixed types, and missing data, using NumPy-like idioms.

Arrays are dynamically typed, but operations on them are compiled and fast. Their behavior coincides with NumPy when array dimensions are regular and generalizes when they're not.

How-to documentation for data analysts

How-it-works tutorials for developers

C++ API reference Python API reference

Awkward Array can be installed from PyPI using pip:

pip install awkward1

Most users will get a precompiled binary (wheel) for your operating system and Python version. If not, the above attempts to compile from source.

Be sure to clone this repository recursively to get the header-only C++ dependencies.

git clone --recursive https://github.com/scikit-hep/awkward-1.0.git

You can install it on your system with pip, which uses exactly the same procedure as deployment:

pip install .[test,dev]

Or you can build it locally for incremental development. The following reuses a local directory so that you only recompile what you've changed:

python localbuild.py --pytest tests

Continuous integration and continuous deployment are hosted by Azure Pipelines.

Python projects can simply import awkward1.

C++ projects can link against the shared libraries libawkward-cpu-kernels.so and libawkward.so or their static library equivalents. These libraries are shipped, along with the include files, as part of pip's installation.

See the dependent-project directory for examples.

• The original motivations document from July 2019, now a little out-of-date.
• My StrangeLoop talk on September 14, 2019.
• My PyHEP talk on October 17, 2019.
• My CHEP talk on November 7, 2019.
• My CHEP 2019 proceedings (to be published in EPJ Web of Conferences).
• Demo for Coffea developers on December 20, 2019.
• Demo for Numba developers on January 22, 2020.
• A summary poster that I presented on February 27, 2020.