SciPy 1.0: fundamental algorithms for scientific computing in Python
- PMID: 32015543
- PMCID: PMC7056644
- DOI: 10.1038/s41592-019-0686-2
SciPy 1.0: fundamental algorithms for scientific computing in Python
Erratum in
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Author Correction: SciPy 1.0: fundamental algorithms for scientific computing in Python.Nat Methods. 2020 Mar;17(3):352. doi: 10.1038/s41592-020-0772-5. Nat Methods. 2020. PMID: 32094914 Free PMC article.
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.
Conflict of interest statement
The following statements indicate industry affiliations for authors in the main author list, but not for authors in the SciPy 1.0 Contributor group beyond that. These affiliations may have since changed. R.G. was employed by Quansight LLC. T.E.O., E.J. and R.K. were employed by Enthought, Inc. T.E.O. and I.H. were employed by Anaconda Inc. N.M. was employed by WayRay LLC. E.W.M. was employed by Bruker Biospin Corp. F.P. and P.v.M. were employed by Google LLC.
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