SciPy 1.0: fundamental algorithms for scientific computing in Python

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Authors
Virtanen, Pauli
  Gommers, Ralf
Oliphant, Travis E.
  Haberland, Matt
  Reddy, Tyler
Cournapeau, David
Burovski, Evgeni
Publication Date
2020-02-03
Journal Title
Nature Methods
ISSN
1548-7091
Publisher
Nature Publishing Group US
Volume
17
Issue
3
Pages
261-272
Language
en
Type
Article
This Version
VoR
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Citation
Virtanen, P., Gommers, R., Oliphant, T. E., Haberland, M., Reddy, T., Cournapeau, D., Burovski, E., et al. (2020). SciPy 1.0: fundamental algorithms for scientific computing in Python. Nature Methods, 17 (3), 261-272. https://doi.org/10.1038/s41592-019-0686-2
Abstract
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.
Keywords
Perspective, /631/114, /631/45/56, /706/703/559, perspective
Identifiers
s41592-019-0686-2, 686
External DOI: https://doi.org/10.1038/s41592-019-0686-2
This record's URL: https://www.repository.cam.ac.uk/handle/1810/317023
Rights
Attribution 4.0 International (CC BY 4.0)
Licence URL: https://creativecommons.org/licenses/by/4.0/
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Attribution 4.0 International (CC BY 4.0)
Except where otherwise noted, this item's licence is described as Attribution 4.0 International (CC BY 4.0)