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SciPy 1.0 — Fundamental Algorithms for Scientific Computing in Python

Paper · 2019 · Pauli Virtanen, Ralf Gommers, Travis E. Oliphant et al.

Summary

The paper describes SciPy, the open-source Python library that collects core numerical algorithms: optimization, integration, interpolation, linear algebra, signal and image processing, sparse matrices, spatial structures such as k-d trees, statistics and more. It marks the 1.0 release in late 2017, about 16 years after version 0.1. It treats that milestone as a statement that the API is stable enough for production pipelines.

The authors trace SciPy's origins in the late 1990s. A shared array object emerged from the Matrix-SIG mailing list, and graduate students wrapped proven Fortran and C codes for Python. These packages were merged into one library in 2001.

The paper then covers how the project runs: release cadence, maintainers, a community roadmap, and exchange with downstream libraries. Its main evidence is adoption. SciPy is a de facto standard, with hundreds of contributors, millions of yearly downloads, and use in gravitational-wave analysis and the M87 black hole image. This matters because large parts of scientific and machine-learning software depend on SciPy, so its quality and governance spread across the whole ecosystem.

Key points

  • SciPy 1.0 came out in late 2017, roughly 16 years after the 0.1 release. The library builds on NumPy and in turn underlies scikit-learn and scikit-image.
  • Early components wrapped established libraries such as ODEPACK, QUADPACK and MINPACK (via Multipack). F2PY was built to bind Fortran to Python.
  • In 2018 there were 610 unique code contributors and more than 19,000 accepted commits. GitHub recorded about 20,000 unique visitors and 721 clones between May 14 and May 27, 2018.
  • Downloads in 2017 were 13,096,468 from PyPI and 5,776,017 from the default conda channel, which the authors treat as a lower bound. SciPy is used by 47% of machine-learning projects on GitHub, and its website has been cited more than 3,000 times.
  • The project follows a 6-monthly release cycle and has 15 active maintainers chosen from proven contributors. A living roadmap (Table 2) lists planned work, for example new global optimizers, new spline routines and PROPACK wrappers for faster SVD.

Interesting ideas

  • I1. Agreeing early on one shared core data object, the array, let many independent packages interoperate instead of fragmenting.
  • I2. Wrapping mature, well-tested Fortran and C libraries was preferred over rewriting them, which gave reliable algorithms quickly behind a friendlier interface.
  • I3. Bumping to version 1.0 is treated as a public promise of API stability, a promise that downstream pipelines can rely on.
  • I4. Code often grows in a domain-specific downstream package and is later promoted into the base library, as happened with binned statistics from an Astropy-affiliated package.
  • I5. Usage counts are framed explicitly as lower bounds, because they cover only some install channels, which keeps the claims honest.

For Mova

How these ideas could serve Mova, our small open language model — its files, stages and tests:

  • I1 (tree): Fix one canonical UD tree structure that the perceptron parser, gparse and the dialect converters all read and write, so every downstream stage consumes the same object.
  • I2 (world): Wrap existing resources such as WordNet, FrameNet and Wikidata behind thin explainable adapters rather than re-deriving that knowledge by hand.
  • I3 (frames): Declare a versioned, frozen interface for the frame and semantic-role output of crate prag, so readers and generators can depend on it without breaking.
  • I4 (learn): Let repair rules or heuristics first prove themselves inside one task-specific reader, then promote the ones that generalize into the shared core.
  • I5 (learn): Report silver-data agreement and test scores together with what they fail to cover, such as missing genres or untested constructions, so the evaluation is read correctly.

Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.

 Institutions

🎓University of WashingtonSeattle · United States263 works · 180,581 citations🎓University of California, BerkeleyBerkeley · United States127 works · 212,523 citations🎓Johns Hopkins UniversityBaltimore · United States187 works · 92,194 citations🎓University of CambridgeCambridge · United Kingdom155 works · 115,562 citations🎓University of Illinois Urbana-ChampaignUrbana · United States108 works · 67,432 citations🎓University of OxfordOxford · United Kingdom52 works · 154,829 citations🎓University of AmsterdamAmsterdam · Netherlands89 works · 81,337 citations🎓The University of Texas at AustinAustin · United States72 works · 55,722 citations🎓University of Massachusetts AmherstAmherst Center · United States67 works · 64,591 citations🎓University of StuttgartStuttgart · Germany75 works · 46,113 citations🎓Ludwig-Maximilians-Universität MünchenMunich · Germany44 works · 55,193 citations🎓The University of SydneySydney · Australia31 works · 67,940 citations🎓University of California, Los AngelesLos Angeles · United States54 works · 53,688 citations🎓University of Colorado BoulderBoulder · United States52 works · 49,647 citations🎓University of California San DiegoSan Diego · United States34 works · 51,167 citations🔬Centre National de la Recherche ScientifiqueParis · France104 works · 60,877 citations🎓University of ChicagoChicago · United States28 works · 49,773 citations🎓Monash UniversityMelbourne · Australia31 works · 54,201 citations🎓University of ManchesterManchester · United Kingdom30 works · 43,942 citations🎓University of Wisconsin–MadisonMadison · United States21 works · 46,892 citations🔬Fondazione Bruno KesslerTrento · Italy25 works · 43,498 citations🎓Heidelberg UniversityHeidelberg · Germany27 works · 40,944 citations🎓University of TübingenTübingen · Germany30 works · 40,834 citations🎓Humboldt-Universität zu BerlinBerlin · Germany13 works · 41,845 citations🎓Brigham Young UniversityProvo · United States15 works · 40,065 citations🎓Technical University of MunichMunich · Germany18 works · 48,618 citations🎓Emory UniversityAtlanta · United States16 works · 39,535 citations🎓Virginia TechBlacksburg · United States15 works · 42,600 citations🔬Max Planck SocietyMunich · Germany10 works · 42,142 citations🎓Dartmouth CollegeHanover · United States16 works · 42,313 citations🎓University of California, DavisDavis · United States13 works · 41,713 citations🎓University of Central FloridaOrlando · United States8 works · 39,618 citations🏢IntelSanta Clara · United States6 works · 40,104 citations🎓National Research University Higher School of EconomicsMoscow · Russia16 works · 39,548 citations🎓University of West Bohemia in PilsenPilsen · Czechia10 works · 38,730 citations🔬Chan Zuckerberg Biohub San FranciscoSan Francisco · United States2 works · 41,092 citations🎓University of BirminghamBirmingham · United Kingdom11 works · 62,331 citations🎓Birla Institute of Technology and Science, PilaniPilāni · India8 works · 40,950 citations🎓Tallinn University of TechnologyTallinn · Estonia4 works · 62,003 citations🎓Aix-Marseille UniversitéMarseille · France14 works · 38,957 citations🎓Christian-Albrechts-Universität zu KielKiel · Germany3 works · 38,851 citations🎓University of JyväskyläJyväskylä · Finland3 works · 62,143 citations🏢EnthoughtAustin · United States2 works · 61,908 citations🔬Los Alamos National LaboratoryLos Alamos · United States2 works · 61,908 citations🏢QuansightAustin · United States2 works · 61,908 citations🎓University of MilanMilan · Italy3 works · 38,687 citations🎓Universidade Federal de Minas GeraisBelo Horizonte · Brazil4 works · 38,791 citations🔬Broad InstituteCambridge · United States2 works · 38,884 citations🎓University of LjubljanaLjubljana · Slovenia4 works · 38,642 citations🎓University of ViennaVienna · Austria7 works · 38,636 citations🎓University of BremenBremen · Germany3 works · 38,378 citations🔬Applied Research Laboratories, The University of Texas at AustinAustin · United States2 works · 38,426 citations🔬Mayo ClinicRochester · United States4 works · 38,902 citations🏢Two Sigma InvestmentsNew York · United States2 works · 38,578 citations🎓University of AugsburgAugsburg · Germany2 works · 38,318 citations🎓University of CincinnatiCincinnati · United States2 works · 38,318 citations🎓California Polytechnic State UniversitySan Luis Obispo · United States2 works · 38,552 citations🔬Max Planck Institute for Software SystemsSaarbrücken · Germany2 works · 38,552 citations

Also on the byline: Tata Institute of Fundamental Research · Université de Bordeaux · Universidade Federal de Campina Grande · Inter-University Centre for Astronomy and Astrophysics · Niigata University · Technische Universität Braunschweig · Lawrence Berkeley National Laboratory · Pontificia Universidad Católica de Chile · Kavli Institute for the Physics and Mathematics of the Universe · Bruker (United States) · Cincinnati Children's Hospital Medical Center · Australian Nuclear Science and Technology Organisation · D. E. Shaw Research · Federal Reserve Board of Governors · International Centre for Theoretical Sciences · Max Planck Institute for Extraterrestrial Physics · Orexplore · Applied BioMath · Anaconda · WayRay · Laboratoire Photonique, Numérique et Nanosciences · Centrale Méditerranée · Excellence Cluster Universe · École nationale supérieure de techniques avancées Bretagne · ABB (Germany) · Utah State University Space Dynamics Laboratory.

📚 Shelves 6 Computer Science · 9,086 works Artificial Intelligence · 8,889 works Mathematics · 140 works Computational Theory and Mathematics · 116 works Decision Sciences · 85 works Information Systems and Management · 18 works

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Cite

Cite as Pauli Virtanen, Ralf Gommers, Travis E. Oliphant, Matt Haberland, Tyler Reddy, David Cournapeau, Evgeni Burovski, Pearu Peterson, Warren Weckesser, Jonathan Bright, Stéfan J. van der Walt, Matthew Brett, Joshua Wilson, K. Jarrod Millman, Nikolay Mayorov, Andrew R. J. Nelson, Eric Jones, Robert Kern, Eric Larson, CJ Carey, İlhan Polat, Yu Feng, Eric W. Moore, Jake VanderPlas, Denis Laxalde, Josef Perktold, Robert Cimrman, Ian Henriksen, E. A. Quintero, Charles R Harris, Anne M. Archibald, Antônio H. Ribeiro, Fabian Pedregosa and Paul van Mulbregt. 2019. SciPy 1.0 — Fundamental Algorithms for Scientific Computing in Python. arXiv:1907.10121 (Nature Methods 17, 261 (2020)).

The paper itself, not this page. BibTeX from the library's record of the work. DOI 10.1038/s41592-019-0686-2 · arXiv 1907.10121

@misc{virtanen2019scipy,
  title = {{SciPy 1.0 — Fundamental Algorithms for Scientific Computing in Python}},
  author = {Pauli Virtanen, Ralf Gommers, Travis E. Oliphant, Matt Haberland, Tyler Reddy, David Cournapeau, Evgeni Burovski, Pearu Peterson, Warren Weckesser, Jonathan Bright, Stéfan J. {van der Walt}, Matthew Brett, Joshua Wilson, K. Jarrod Millman, Nikolay Mayorov, Andrew R. J. Nelson, Eric Jones, Robert Kern, Eric Larson, CJ Carey, İlhan Polat, Yu Feng, Eric W. Moore, Jake VanderPlas, Denis Laxalde, Josef Perktold, Robert Cimrman, Ian Henriksen, E. A. Quintero, Charles R Harris, Anne M. Archibald, Antônio H. Ribeiro, Fabian Pedregosa and Paul {van Mulbregt}},
  year = {2019},
  doi = {10.1038/s41592-019-0686-2},
  eprint = {1907.10121},
  archivePrefix = {arXiv},
  url = {https://doi.org/10.1038/s41592-019-0686-2}
}

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