Abstract¶
NumPy simplifies and accelerates mathematical calculations in Python, but only for rectilinear arrays of numbers. Awkward Array provides a similar interface for JSON-like data: slicing, masking, broadcasting, and performing vectorized math on the attributes of objects, unequal-length nested lists (i.e. ragged/jagged arrays), and heterogeneous data types.
Awkward Arrays are columnar data structures, like (and convertible to/from) Apache Arrow, with a focus on manipulation, rather than serialization/transport. These arrays can be passed between C++ and Python, and they can be used in functions that are JIT-compiled by Numba.
Development of a GPU backend is in progress, which would allow data analyses written in array-programming style to run on GPUs without modification.
