SciPy 1.0: fundamental algorithms for scientific computing in Python

doi:10.1038/s41592-019-0686-2

Review

. 2020 Mar;17(3):261-272.

doi: 10.1038/s41592-019-0686-2. Epub 2020 Feb 3.

SciPy 1.0: fundamental algorithms for scientific computing in Python

Pauli Virtanen¹, Ralf Gommers², Travis E Oliphant^{3

4

5

6

7}, Matt Haberland^{8

9}, Tyler Reddy¹⁰, David Cournapeau¹¹, Evgeni Burovski¹², Pearu Peterson^{13

14}, Warren Weckesser¹⁵, Jonathan Bright¹⁶, Stéfan J van der Walt¹⁵, Matthew Brett¹⁷, Joshua Wilson¹⁸, K Jarrod Millman^{15

19}, Nikolay Mayorov²⁰, Andrew R J Nelson²¹, Eric Jones⁶, Robert Kern⁶, Eric Larson²², C J Carey²³, İlhan Polat²⁴, Yu Feng²⁵, Eric W Moore²⁶, Jake VanderPlas²⁷, Denis Laxalde²⁸, Josef Perktold²⁹, Robert Cimrman³⁰, Ian Henriksen^{7

31

32}, E A Quintero³³, Charles R Harris^{34

35}, Anne M Archibald³⁶, Antônio H Ribeiro³⁷, Fabian Pedregosa³⁸, Paul van Mulbregt³⁹; SciPy 1.0 Contributors

Collaborators, Affiliations

Collaborators

SciPy 1.0 Contributors:
Aditya Vijaykumar, Alessandro Pietro Bardelli, Alex Rothberg, Andreas Hilboll, Andreas Kloeckner, Anthony Scopatz, Antony Lee, Ariel Rokem, C Nathan Woods, Chad Fulton, Charles Masson, Christian Häggström, Clark Fitzgerald, David A Nicholson, David R Hagen, Dmitrii V Pasechnik, Emanuele Olivetti, Eric Martin, Eric Wieser, Fabrice Silva, Felix Lenders, Florian Wilhelm, G Young, Gavin A Price, Gert-Ludwig Ingold, Gregory E Allen, Gregory R Lee, Hervé Audren, Irvin Probst, Jörg P Dietrich, Jacob Silterra, James T Webber, Janko Slavič, Joel Nothman, Johannes Buchner, Johannes Kulick, Johannes L Schönberger, José Vinícius de Miranda Cardoso, Joscha Reimer, Joseph Harrington, Juan Luis Cano Rodríguez, Juan Nunez-Iglesias, Justin Kuczynski, Kevin Tritz, Martin Thoma, Matthew Newville, Matthias Kümmerer, Maximilian Bolingbroke, Michael Tartre, Mikhail Pak, Nathaniel J Smith, Nikolai Nowaczyk, Nikolay Shebanov, Oleksandr Pavlyk, Per A Brodtkorb, Perry Lee, Robert T McGibbon, Roman Feldbauer, Sam Lewis, Sam Tygier, Scott Sievert, Sebastiano Vigna, Stefan Peterson, Surhud More, Tadeusz Pudlik, Takuya Oshima, Thomas J Pingel, Thomas P Robitaille, Thomas Spura, Thouis R Jones, Tim Cera, Tim Leslie, Tiziano Zito, Tom Krauss, Utkarsh Upadhyay, Yaroslav O Halchenko, Yoshiki Vázquez-Baeza

Affiliations

¹ University of Jyväskylä, Jyväskylä, Finland.
² Quansight LLC, Austin, TX, USA. scipy.articles@gmail.com.
³ Quansight LLC, Austin, TX, USA.
⁴ Ultrasound Imaging, Mayo Clinic, Rochester, MN, USA.
⁵ Electrical Engineering, Brigham Young University, Provo, UT, USA.
⁶ Enthought, Inc., Austin, TX, USA.
⁷ Anaconda Inc., Austin, TX, USA.
⁸ BioResource and Agricultural Engineering Department, California Polytechnic State University, San Luis Obispo, CA, USA. scipy.articles@gmail.com.
⁹ Department of Mathematics, University of California Los Angeles, Los Angeles, CA, USA. scipy.articles@gmail.com.
¹⁰ Los Alamos National Laboratory, Los Alamos, NM, USA. scipy.articles@gmail.com.
¹¹ Independent researcher, Tokyo, Japan.
¹² National Research University Higher School of Economics, Moscow, Russia.
¹³ Independent researcher, Saue, Estonia.
¹⁴ Department of Mechanics and Applied Mathematics, Institute of Cybernetics at Tallinn Technical University, Tallinn, Estonia.
¹⁵ Berkeley Institute for Data Science, University of California Berkeley, Berkeley, CA, USA.
¹⁶ Independent researcher, New York, NY, USA.
¹⁷ School of Psychology, University of Birmingham, Edgbaston, Birmingham, UK.
¹⁸ Independent researcher, San Francisco, CA, USA.
¹⁹ Division of Biostatistics, University of California Berkeley, Berkeley, CA, USA.
²⁰ WayRay LLC, Skolkovo Innovation Center, Moscow, Russia.
²¹ Australian Nuclear Science and Technology Organisation, Lucas Heights, NSW, Australia.
²² Institute for Learning and Brain Sciences, University of Washington, Seattle, WA, USA.
²³ College of Information and Computing Sciences, University of Massachusetts Amherst, Amherst, MA, USA.
²⁴ Independent researcher, Amsterdam, the Netherlands.
²⁵ Berkeley Center for Cosmological Physics, University of California Berkeley, Berkeley, CA, USA.
²⁶ Bruker Biospin Corp., Billerica, MA, USA.
²⁷ University of Washington, Seattle, WA, USA.
²⁸ Independent researcher, Toulouse, France.
²⁹ Independent researcher, Montreal, Quebec, Canada.
³⁰ New Technologies Research Centre, University of West Bohemia, Plzeň, Czech Republic.
³¹ Department of Mathematics, Brigham Young University, Provo, UT, USA.
³² Oden Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, TX, USA.
³³ Independent researcher, Belmont, Massachusetts, USA.
³⁴ Space Dynamics Laboratory, North Logan, UT, USA.
³⁵ Independent researcher, Logan, Utah, USA.
³⁶ Anton Pannekoek Institute, Amsterdam, The Netherlands.
³⁷ Graduate Program in Electrical Engineering, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.
³⁸ Google LLC, Montreal, Quebec, Canada.
³⁹ Google LLC, Cambridge, MA, USA.

PMID: 32015543
PMCID: PMC7056644
DOI: 10.1038/s41592-019-0686-2

Review

SciPy 1.0: fundamental algorithms for scientific computing in Python

Pauli Virtanen et al. Nat Methods. 2020 Mar.

. 2020 Mar;17(3):261-272.

doi: 10.1038/s41592-019-0686-2. Epub 2020 Feb 3.

Authors

Collaborators

SciPy 1.0 Contributors:
Aditya Vijaykumar, Alessandro Pietro Bardelli, Alex Rothberg, Andreas Hilboll, Andreas Kloeckner, Anthony Scopatz, Antony Lee, Ariel Rokem, C Nathan Woods, Chad Fulton, Charles Masson, Christian Häggström, Clark Fitzgerald, David A Nicholson, David R Hagen, Dmitrii V Pasechnik, Emanuele Olivetti, Eric Martin, Eric Wieser, Fabrice Silva, Felix Lenders, Florian Wilhelm, G Young, Gavin A Price, Gert-Ludwig Ingold, Gregory E Allen, Gregory R Lee, Hervé Audren, Irvin Probst, Jörg P Dietrich, Jacob Silterra, James T Webber, Janko Slavič, Joel Nothman, Johannes Buchner, Johannes Kulick, Johannes L Schönberger, José Vinícius de Miranda Cardoso, Joscha Reimer, Joseph Harrington, Juan Luis Cano Rodríguez, Juan Nunez-Iglesias, Justin Kuczynski, Kevin Tritz, Martin Thoma, Matthew Newville, Matthias Kümmerer, Maximilian Bolingbroke, Michael Tartre, Mikhail Pak, Nathaniel J Smith, Nikolai Nowaczyk, Nikolay Shebanov, Oleksandr Pavlyk, Per A Brodtkorb, Perry Lee, Robert T McGibbon, Roman Feldbauer, Sam Lewis, Sam Tygier, Scott Sievert, Sebastiano Vigna, Stefan Peterson, Surhud More, Tadeusz Pudlik, Takuya Oshima, Thomas J Pingel, Thomas P Robitaille, Thomas Spura, Thouis R Jones, Tim Cera, Tim Leslie, Tiziano Zito, Tom Krauss, Utkarsh Upadhyay, Yaroslav O Halchenko, Yoshiki Vázquez-Baeza

Affiliations

¹ University of Jyväskylä, Jyväskylä, Finland.
² Quansight LLC, Austin, TX, USA. scipy.articles@gmail.com.
³ Quansight LLC, Austin, TX, USA.
⁴ Ultrasound Imaging, Mayo Clinic, Rochester, MN, USA.
⁵ Electrical Engineering, Brigham Young University, Provo, UT, USA.
⁶ Enthought, Inc., Austin, TX, USA.
⁷ Anaconda Inc., Austin, TX, USA.
⁸ BioResource and Agricultural Engineering Department, California Polytechnic State University, San Luis Obispo, CA, USA. scipy.articles@gmail.com.
⁹ Department of Mathematics, University of California Los Angeles, Los Angeles, CA, USA. scipy.articles@gmail.com.
¹⁰ Los Alamos National Laboratory, Los Alamos, NM, USA. scipy.articles@gmail.com.
¹¹ Independent researcher, Tokyo, Japan.
¹² National Research University Higher School of Economics, Moscow, Russia.
¹³ Independent researcher, Saue, Estonia.
¹⁴ Department of Mechanics and Applied Mathematics, Institute of Cybernetics at Tallinn Technical University, Tallinn, Estonia.
¹⁵ Berkeley Institute for Data Science, University of California Berkeley, Berkeley, CA, USA.
¹⁶ Independent researcher, New York, NY, USA.
¹⁷ School of Psychology, University of Birmingham, Edgbaston, Birmingham, UK.
¹⁸ Independent researcher, San Francisco, CA, USA.
¹⁹ Division of Biostatistics, University of California Berkeley, Berkeley, CA, USA.
²⁰ WayRay LLC, Skolkovo Innovation Center, Moscow, Russia.
²¹ Australian Nuclear Science and Technology Organisation, Lucas Heights, NSW, Australia.
²² Institute for Learning and Brain Sciences, University of Washington, Seattle, WA, USA.
²³ College of Information and Computing Sciences, University of Massachusetts Amherst, Amherst, MA, USA.
²⁴ Independent researcher, Amsterdam, the Netherlands.
²⁵ Berkeley Center for Cosmological Physics, University of California Berkeley, Berkeley, CA, USA.
²⁶ Bruker Biospin Corp., Billerica, MA, USA.
²⁷ University of Washington, Seattle, WA, USA.
²⁸ Independent researcher, Toulouse, France.
²⁹ Independent researcher, Montreal, Quebec, Canada.
³⁰ New Technologies Research Centre, University of West Bohemia, Plzeň, Czech Republic.
³¹ Department of Mathematics, Brigham Young University, Provo, UT, USA.
³² Oden Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, TX, USA.
³³ Independent researcher, Belmont, Massachusetts, USA.
³⁴ Space Dynamics Laboratory, North Logan, UT, USA.
³⁵ Independent researcher, Logan, Utah, USA.
³⁶ Anton Pannekoek Institute, Amsterdam, The Netherlands.
³⁷ Graduate Program in Electrical Engineering, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.
³⁸ Google LLC, Montreal, Quebec, Canada.
³⁹ Google LLC, Cambridge, MA, USA.

PMID: 32015543
PMCID: PMC7056644
DOI: 10.1038/s41592-019-0686-2

Erratum in

Author Correction: SciPy 1.0: fundamental algorithms for scientific computing in Python.
Virtanen P, Gommers R, Oliphant TE, Haberland M, Reddy T, Cournapeau D, Burovski E, Peterson P, Weckesser W, Bright J, van der Walt SJ, Brett M, Wilson J, Millman KJ, Mayorov N, Nelson ARJ, Jones E, Kern R, Larson E, Carey CJ, Polat İ, Feng Y, Moore EW, VanderPlas J, Laxalde D, Perktold J, Cimrman R, Henriksen I, Quintero EA, Harris CR, Archibald AM, Ribeiro AH, Pedregosa F, van Mulbregt P; SciPy 1.0 Contributors. Virtanen P, et al. 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.

PubMed Disclaimer

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.

Figures

**Fig. 1. Major milestones from SciPy’s initial release in 2001 to the release of SciPy 1.0 in 2017.**
Note that SciKits and GitHub have been introduced in the Background section; more information about Cython and SciPy subpackages (for example, scipy.sparse) is available in the ‘Architecture and implementation choices’ section, BLAS/LAPACK support is detailed in the ‘Key technical improvements’ section, and continuous integration is discussed in the ‘Test and benchmark suite’ section.

**Fig. 2**
Python and compiled code volume in SciPy over time.

**Fig. 3. Results of the **scipy.spatial.cKDTree.query** benchmark from the introduction of **cKDTree** to the release of SciPy 1.0.**
The benchmark generates a k-d tree from uniformly distributed points in an m-dimensional unit hypercube, then finds the nearest (Euclidean) neighbor in the tree for each of 1,000 query points. Each marker in the figure indicates the execution time of the benchmark for a commit in the master branch of SciPy.

See this image and copyright information in PMC

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References

1. Oliphant, T.E. Guide to NumPy 1st edn (Trelgol Publishing USA, 2006).
1. van der Walt S, Colbert SC, Varoquaux G. The NumPy array: a structure for efficient numerical computation. Comput. Sci. Eng. 2011;13:22–30.
1. Pedregosa F, et al. Scikit-learn: machine learning in Python. J. Mach. Learn. Res. 2011;12:2825–2830.
1. van der Walt S, et al. scikit-image: image processing in Python. Peer J. 2014;2:e453. - PMC - PubMed
1. Nitz, A. et al. gwastro/pycbc: PyCBC v1.13.2 release, 10.5281/zenodo.1596771 (27 November 2018).

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[1] Oliphant, T.E. Guide to NumPy 1st edn (Trelgol Publishing USA, 2006).

[2] Oliphant, T.E. Guide to NumPy 1st edn (Trelgol Publishing USA, 2006).

[3] van der Walt S, Colbert SC, Varoquaux G. The NumPy array: a structure for efficient numerical computation. Comput. Sci. Eng. 2011;13:22–30.

[4] van der Walt S, Colbert SC, Varoquaux G. The NumPy array: a structure for efficient numerical computation. Comput. Sci. Eng. 2011;13:22–30.

[5] Pedregosa F, et al. Scikit-learn: machine learning in Python. J. Mach. Learn. Res. 2011;12:2825–2830.

[6] Pedregosa F, et al. Scikit-learn: machine learning in Python. J. Mach. Learn. Res. 2011;12:2825–2830.

[7] van der Walt S, et al. scikit-image: image processing in Python. Peer J. 2014;2:e453. - PMC - PubMed

[8] van der Walt S, et al. scikit-image: image processing in Python. Peer J. 2014;2:e453. - PMC - PubMed

[9] Nitz, A. et al. gwastro/pycbc: PyCBC v1.13.2 release, 10.5281/zenodo.1596771 (27 November 2018).

[10] Nitz, A. et al. gwastro/pycbc: PyCBC v1.13.2 release, 10.5281/zenodo.1596771 (27 November 2018).

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SciPy 1.0: fundamental algorithms for scientific computing in Python

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SciPy 1.0: fundamental algorithms for scientific computing in Python

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