A2 Review article, Literature review, Systematic review
SciPy 1.0 : fundamental algorithms for scientific computing in Python (2020)
Virtanen, Pauli, Gommers, Ralf, Oliphant, Travis E., Haberland, Matt, Reddy, Tyler, Cournapeau, David, Burovski, Evgeni, Peterson, Pearu, Weckesser, Warren, Bright, Jonathan, van der Walt, Stéfan J., Brett, Matthew, Wilson, Joshua, Millman, K. Jarrod, Mayorov, Nikolay, Nelson, Andrew R. J., Jones, Eric, Kern, Robert, Larson, Eric, Carey, C. J., Polat, İlhan, Feng, Yu, Moore, Eric W., VanderPlas, Jake, Laxalde, Denis, Perktold, Josef, Cimrman, Robert, Henriksen, Ian, Quintero, E. A., Harris, Charles R., Archibald, Anne M., Ribeiro, Antônio H., Pedregosa, Fabian, van Mulbregt, Paul, SciPy 1.0 Contributors. (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
JYU authors or editors
Publication details
All authors or editors: Virtanen, Pauli; Gommers, Ralf; Oliphant, Travis E.; Haberland, Matt, Reddy, Tyler; Cournapeau, David; Burovski, Evgeni; Peterson, Pearu; Weckesser, Warren; Bright, Jonathan; van der Walt, Stéfan J.; et al.
Journal or series: Nature Methods
ISSN: 1548-7091
eISSN: 1548-7105
Publication year: 2020
Volume: 17
Issue number: 3
Pages range: 261-272
Publisher: Nature Publishing Group
Publication country: United Kingdom
Publication language: English
DOI: https://doi.org/10.1038/s41592-019-0686-2
Publication open access: Openly available
Publication channel open access: Partially open access channel
Publication is parallel published (JYX): https://jyx.jyu.fi/handle/123456789/67875
Web address of parallel published publication (pre-print): https://arxiv.org/abs/1907.10121
Additional information: Perspective. Author correction: https://www.nature.com/articles/s41592-020-0772-5
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: computational science; algorithms; open source code; Python (programming languages)
Free keywords: SciPy
Contributing organizations
Ministry reporting: Yes
Reporting Year: 2020
JUFO rating: 3