SciPy 1.0: fundamental algorithms for scientific computing in Python

202036,069 citationsJournal Articlehybrid Open Access

Authors

Pauli Virtanen · University of Jyväskylä

Ralf Gommers · Quansight (United States)

Travis E. Oliphant · Brigham Young University

Matt Haberland · California Polytechnic State University

Tyler Reddy · Los Alamos National Laboratory

David Cournapeau

Evgeni Burovski · National Research University Higher School of Economics

Pearu Peterson · Tallinn University of Technology

Abstract

SciPy is an open-source scientific computing library for the Python programming language. Since its initial release in 2001, SciPy has become a de facto standard for leveraging scientific algorithms in Python, with over 600 unique code contributors, thousands of dependent packages, over 100,000 dependent repositories and millions of downloads per year. In this work, we provide an overview of the capabilities and development practices of SciPy 1.0 and highlight some recent technical developments.

Topics & Keywords

Computational Physics and Python Applications Scientific Computing and Data Management Genetics, Bioinformatics, and Biomedical Research

Publication Details

Published in: Nature Methods

Volume 17, Issue 3, pp. 261-272

DOI: 10.1038/s41592-019-0686-2

Field-Weighted Citation Impact: 2455.85

Command Palette

SciPy 1.0: fundamental algorithms for scientific computing in Python

Authors

Abstract

Topics & Keywords

Publication Details