Work

Awkward Array: JSON-like data, NumPy-like idioms

Year: 2020

Type: conference-paper

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.

Source: Proceedings of the Python in Science Conferences

DOI: 10.25080/majora-342d178e-00b

Authors: Jim Pivarski, Ianna Osborne, Pratyush Das, Anish Biswas, Peter Elmer

Institutions: Princeton University, Manipal Academy of Higher Education

Language: English

Topic: Computational Physics and Python Applications

Subfield: Software

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

Funder: National Science Foundation

Awards: Collaborative Research: Particle Tracking at High Luminosity on Heterogeneous, Parallel Processor Architectures, S2I2: Institute for Research and Innovation in Software for High Energy Physics (IRIS-HEP), Collaborative Research: SI2-SSI: Data-Intensive Analysis for High Energy Physics (DIANA/HEP)