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SciPy 1.0: fundamental algorithms for scientific computing in Python.

Published version
Peer-reviewed

Repository URI

https://www.repository.cam.ac.uk/handle/1810/326191

Repository DOI

https://doi.org/10.17863/CAM.73648
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 Published version (135.54 KB)
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Type

Article

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Authors

Gommers, Ralf  ORCID logo  https://orcid.org/0000-0002-0300-3333
Haberland, Matt  ORCID logo  https://orcid.org/0000-0003-4806-3601
Reddy, Tyler  ORCID logo  https://orcid.org/0000-0003-2364-6157

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.

Description

Keywords

Algorithms, Computational Biology, Computer Simulation, History, 20th Century, History, 21st Century, Linear Models, Models, Biological, Nonlinear Dynamics, Programming Languages, Signal Processing, Computer-Assisted, Software

Journal Title

Nat Methods

Conference Name

Journal ISSN

1548-7091
1548-7105

Volume Title

17

Publisher

Springer Nature

Publisher DOI

https://doi.org/10.1038/s41592-019-0686-2

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Except where otherwised noted, this item's license is described as http://creativecommons.org/licenses/by/4.0/

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