scipy

SciPy: Scientific Library for Python

These details have been verified by PyPI

Maintainers

matthew.brett pv rgommers rkern teoliphant treddy

These details have not been verified by PyPI

Project links

Project description

SciPy (pronounced “Sigh Pie”) is open-source software for mathematics, science, and engineering. The SciPy library depends on NumPy, which provides convenient and fast N-dimensional array manipulation. The SciPy library is built to work with NumPy arrays, and provides many user-friendly and efficient numerical routines such as routines for numerical integration and optimization. Together, they run on all popular operating systems, are quick to install, and are free of charge. NumPy and SciPy are easy to use, but powerful enough to be depended upon by some of the world’s leading scientists and engineers. If you need to manipulate numbers on a computer and display or publish the results, give SciPy a try!

Project details

These details have been verified by PyPI

Maintainers

matthew.brett pv rgommers rkern teoliphant treddy

These details have not been verified by PyPI

Project links

Release history Release notifications | RSS feed

1.14.1

Aug 21, 2024

1.14.0

Jun 24, 2024

1.14.0rc2 pre-release

Jun 15, 2024

1.14.0rc1 pre-release yanked

May 30, 2024

Reason this release was yanked:

macOS wheels are broken

1.13.1

May 23, 2024

1.13.0

Apr 2, 2024

1.13.0rc1 pre-release

Mar 19, 2024

1.12.0

Jan 20, 2024

1.12.0rc2 pre-release

Jan 12, 2024

1.12.0rc1 pre-release

Dec 20, 2023

1.11.4

Nov 18, 2023

1.11.3

Sep 27, 2023

1.11.2

Aug 17, 2023

1.11.1

Jun 28, 2023

1.11.0 yanked

Jun 25, 2023

Reason this release was yanked:

License Violation

1.11.0rc2 pre-release

Jun 16, 2023

1.11.0rc1 pre-release

May 31, 2023

1.10.1

Feb 19, 2023

1.10.0

Jan 3, 2023

1.10.0rc2 pre-release

Dec 25, 2022

1.10.0rc1 pre-release

Dec 11, 2022

1.9.3

Oct 20, 2022

1.9.2

Oct 8, 2022

1.9.1

Aug 27, 2022

1.9.0

Jul 29, 2022

1.9.0rc3 pre-release

Jul 23, 2022

1.9.0rc2 pre-release

Jul 5, 2022

1.9.0rc1 pre-release

Jun 24, 2022

1.8.1

May 18, 2022

1.8.0

Feb 5, 2022

1.8.0rc4 pre-release

Jan 30, 2022

1.8.0rc3 pre-release

Jan 22, 2022

1.8.0rc2 pre-release

Dec 21, 2021

1.8.0rc1 pre-release

Dec 11, 2021

1.7.3

Nov 24, 2021

1.7.2

Nov 6, 2021

1.7.1

Aug 2, 2021

1.7.0

Jun 20, 2021

1.6.3

Apr 26, 2021

1.6.2

Mar 25, 2021

1.6.1

Feb 18, 2021

1.6.0

Dec 31, 2020

1.5.4

Nov 5, 2020

1.5.3

Oct 17, 2020

1.5.2

Jul 24, 2020

This version

1.5.1

Jul 4, 2020

1.5.0

Jun 21, 2020

1.4.1

Dec 19, 2019

1.4.0

Dec 16, 2019

1.3.3

Nov 23, 2019

1.3.2

Nov 9, 2019

1.3.1

Aug 9, 2019

1.3.0

May 17, 2019

1.2.3

Jan 21, 2020

1.2.2

Jun 7, 2019

1.2.1

Feb 9, 2019

1.2.0

Dec 18, 2018

1.1.0

May 5, 2018

1.0.1

Mar 24, 2018

1.0.0

Oct 25, 2017

0.19.1

Jun 23, 2017

0.19.0

Mar 9, 2017

0.18.1

Sep 19, 2016

0.18.0

Jul 25, 2016

0.17.1

May 12, 2016

0.17.0

Jan 23, 2016

0.16.1

Oct 24, 2015

0.16.0

Jul 24, 2015

0.15.1

Jan 18, 2015

0.15.0

Jan 11, 2015

0.14.1

Dec 30, 2014

0.14.0

May 3, 2014

0.13.3

Feb 4, 2014

0.13.2

Dec 8, 2013

0.13.1

Nov 17, 2013

0.13.0

Oct 19, 2013

0.12.1

Oct 12, 2013

0.12.0

Apr 9, 2013

0.11.0

Sep 29, 2012

0.10.1

Feb 28, 2012

0.10.0

Nov 13, 2011

0.9.0

Feb 28, 2011

0.8.0

Jul 27, 2010

0.7.2

Apr 22, 2010

0.7.0

Feb 11, 2009

0.6.0

Oct 17, 2007

0.5.2

Dec 8, 2006

0.4.4

Jan 9, 2006

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

scipy-1.5.1.tar.gz (25.6 MB view hashes)

Uploaded Jul 4, 2020 Source

Built Distributions

scipy-1.5.1-cp38-cp38-win_amd64.whl (31.4 MB view hashes)

Uploaded Jul 4, 2020 CPython 3.8 Windows x86-64

scipy-1.5.1-cp38-cp38-win32.whl (28.4 MB view hashes)

Uploaded Jul 4, 2020 CPython 3.8 Windows x86

scipy-1.5.1-cp38-cp38-manylinux1_x86_64.whl (25.8 MB view hashes)

Uploaded Jul 4, 2020 CPython 3.8

scipy-1.5.1-cp38-cp38-manylinux1_i686.whl (22.7 MB view hashes)

Uploaded Jul 4, 2020 CPython 3.8

scipy-1.5.1-cp38-cp38-macosx_10_9_x86_64.whl (28.9 MB view hashes)

Uploaded Jul 4, 2020 CPython 3.8 macOS 10.9+ x86-64

scipy-1.5.1-cp37-cp37m-win_amd64.whl (31.2 MB view hashes)

Uploaded Jul 4, 2020 CPython 3.7m Windows x86-64

scipy-1.5.1-cp37-cp37m-win32.whl (28.2 MB view hashes)

Uploaded Jul 4, 2020 CPython 3.7m Windows x86

scipy-1.5.1-cp37-cp37m-manylinux1_x86_64.whl (25.9 MB view hashes)

Uploaded Jul 4, 2020 CPython 3.7m

scipy-1.5.1-cp37-cp37m-manylinux1_i686.whl (22.8 MB view hashes)

Uploaded Jul 4, 2020 CPython 3.7m

scipy-1.5.1-cp37-cp37m-macosx_10_9_x86_64.whl (28.7 MB view hashes)

Uploaded Jul 4, 2020 CPython 3.7m macOS 10.9+ x86-64

scipy-1.5.1-cp36-cp36m-win_amd64.whl (31.2 MB view hashes)

Uploaded Jul 4, 2020 CPython 3.6m Windows x86-64

scipy-1.5.1-cp36-cp36m-win32.whl (28.2 MB view hashes)

Uploaded Jul 4, 2020 CPython 3.6m Windows x86

scipy-1.5.1-cp36-cp36m-manylinux1_x86_64.whl (25.9 MB view hashes)

Uploaded Jul 4, 2020 CPython 3.6m

scipy-1.5.1-cp36-cp36m-manylinux1_i686.whl (22.8 MB view hashes)

Uploaded Jul 4, 2020 CPython 3.6m

scipy-1.5.1-cp36-cp36m-macosx_10_9_x86_64.whl (28.8 MB view hashes)

Uploaded Jul 4, 2020 CPython 3.6m macOS 10.9+ x86-64

Hashes for scipy-1.5.1.tar.gz

Hashes for scipy-1.5.1.tar.gz
Algorithm	Hash digest
SHA256	`039572f0ca9578a466683558c5bf1e65d442860ec6e13307d528749cfe6d07b8`
MD5	`f6986798b7d22ffc5f80b749d7ec27ca`
BLAKE2b-256	`8a6c7777c60626cf620ce24d6349af69f3d2a4f298729d688cc4cd9528ae3c61`

Hashes for scipy-1.5.1-cp38-cp38-win_amd64.whl

Hashes for scipy-1.5.1-cp38-cp38-win_amd64.whl
Algorithm	Hash digest
SHA256	`c06e731aa46c0dfc563cc636155758178ebc019ef78b9b0f4370effe2ac0f0e6`
MD5	`a626585d08b0991c8f2df0caacdf9997`
BLAKE2b-256	`e3ddc6b603e261c828c38ad95b6e902abb27e1797e3bc7a10b92e389bd57eb5a`

Hashes for scipy-1.5.1-cp38-cp38-win32.whl

Hashes for scipy-1.5.1-cp38-cp38-win32.whl
Algorithm	Hash digest
SHA256	`57a0f2be3063dbe1e3daf31ec9005576e8fd1022a28159d0db71d14566899d16`
MD5	`2aa8b6ddceaebe7b33d71dbad0e208cc`
BLAKE2b-256	`7b22015683f075ec6db529ab6450e9cd5cd14abd8c5277fa14d89ba81aabb817`

Hashes for scipy-1.5.1-cp38-cp38-manylinux1_x86_64.whl

Hashes for scipy-1.5.1-cp38-cp38-manylinux1_x86_64.whl
Algorithm	Hash digest
SHA256	`06b19a650471781056c1a2172eeeeb777b8b516e9434005dd392a4559e0938b9`
MD5	`00181f52a7917d1c3d50e42a76a6df96`
BLAKE2b-256	`e5dc33034dee168361cdd99c712a6492e68ff782eaa9c6b2c1b9137f38439864`

Hashes for scipy-1.5.1-cp38-cp38-manylinux1_i686.whl

Hashes for scipy-1.5.1-cp38-cp38-manylinux1_i686.whl
Algorithm	Hash digest
SHA256	`9323d268775991b79690f7b9a28a4e8b8c4f2b160ed9f8a90123127314e2d3c1`
MD5	`8a65b30ccd72409704d3300922da2b7f`
BLAKE2b-256	`b833805d77e1ded9400a222b7b58c516b7f0300adea2b9b34bc5840ad715457a`

Hashes for scipy-1.5.1-cp38-cp38-macosx_10_9_x86_64.whl

Hashes for scipy-1.5.1-cp38-cp38-macosx_10_9_x86_64.whl
Algorithm	Hash digest
SHA256	`71742889393a724dfce755b6b61228677873d269a4234e51ddaf08b998433c91`
MD5	`cceb059d0cf6a70e62452deb5571ba00`
BLAKE2b-256	`640362dd5df2216486be69beae8071ba1a8663361e2fb86abd22563aa03e2dee`

Hashes for scipy-1.5.1-cp37-cp37m-win_amd64.whl

Hashes for scipy-1.5.1-cp37-cp37m-win_amd64.whl
Algorithm	Hash digest
SHA256	`c05c6fe76228cc13c5214e9faf5f2a871a1da54473bc417ab9da310d0e5fff8b`
MD5	`2ca8c59a6712e91ac78b8540ab694b53`
BLAKE2b-256	`60ade08d41cd6a7d34d60b524fb5e59c020a560199cbc32462576e85fea5c68a`

Hashes for scipy-1.5.1-cp37-cp37m-win32.whl

Hashes for scipy-1.5.1-cp37-cp37m-win32.whl
Algorithm	Hash digest
SHA256	`81859ed3aad620752dd2c07c32b5d3a80a0d47c5e3813904621954a78a0ae899`
MD5	`5da68faf5b32c539d1cb5390df010cc8`
BLAKE2b-256	`cef97920c03d993ca63de15fb817ef9b049da7649f03d9821f5f41195e952bee`

Hashes for scipy-1.5.1-cp37-cp37m-manylinux1_x86_64.whl

Hashes for scipy-1.5.1-cp37-cp37m-manylinux1_x86_64.whl
Algorithm	Hash digest
SHA256	`fff15df01bef1243468be60c55178ed7576270b200aab08a7ffd5b8e0bbc340c`
MD5	`6a18a9636342574ae55d3a80136c550c`
BLAKE2b-256	`3045ff9df4beceab76f979ee0ea7f5d248596aa5b0c179aa3d30589a3f4549eb`

Hashes for scipy-1.5.1-cp37-cp37m-manylinux1_i686.whl

Hashes for scipy-1.5.1-cp37-cp37m-manylinux1_i686.whl
Algorithm	Hash digest
SHA256	`eb46d8b5947ca27b0bc972cecfba8130f088a83ab3d08c1a6033d9070b3046b3`
MD5	`f2d5c8713b087545c5ec19cc8e46212c`
BLAKE2b-256	`72277e87ca166b10acfdd34b7e6d2ff7078c64c5effdadefd15c15c30b328d13`

Hashes for scipy-1.5.1-cp37-cp37m-macosx_10_9_x86_64.whl

Hashes for scipy-1.5.1-cp37-cp37m-macosx_10_9_x86_64.whl
Algorithm	Hash digest
SHA256	`b4858ccbd88f4b53950fb9fc0069c1d9fea83d7cff2382e1d8b023d3f4883014`
MD5	`83479a6de66a6bc2da0990fa71cf3cec`
BLAKE2b-256	`e3e92141008f9f691a40951dd732a0eebf6f37093904a803e1fd1c8807dc0e23`

Hashes for scipy-1.5.1-cp36-cp36m-win_amd64.whl

Hashes for scipy-1.5.1-cp36-cp36m-win_amd64.whl
Algorithm	Hash digest
SHA256	`5e0bb43ff581811ab7f27425f6b96c1ddf7591ccad2e486c9af0b910c18f7185`
MD5	`9edc3a9aedf6bffccb17101c905126d0`
BLAKE2b-256	`12001dc9fec03087160e89fd5a8826fd3191090694b22451c5bd3dda9e9f3d3d`

Hashes for scipy-1.5.1-cp36-cp36m-win32.whl

Hashes for scipy-1.5.1-cp36-cp36m-win32.whl
Algorithm	Hash digest
SHA256	`35d042d6499caf1a5d171baed0ebf01eb665b7af2ad98a8ff1b0e6e783654540`
MD5	`baad02c954e85e7fd3d4a9fd49fc6359`
BLAKE2b-256	`86e8a83e44d9629e9f122acece0b2d2017810db5dd303e404432d091a57414ae`

Hashes for scipy-1.5.1-cp36-cp36m-manylinux1_x86_64.whl

Hashes for scipy-1.5.1-cp36-cp36m-manylinux1_x86_64.whl
Algorithm	Hash digest
SHA256	`8302d69fb1528ea7c7f2a1ea640d354c981b6eb8192d1c175349874209397604`
MD5	`c4dd717a3a0c3fe64380039e4fda663f`
BLAKE2b-256	`abf96eeed6d5cd8dd435bbf105d10d778c2d76de1a5838fdbc315a59fb7fad64`

Hashes for scipy-1.5.1-cp36-cp36m-manylinux1_i686.whl

Hashes for scipy-1.5.1-cp36-cp36m-manylinux1_i686.whl
Algorithm	Hash digest
SHA256	`7908c85854c5b5b6d3ce7fefafac1ca3e23ff9ac41edabc2d46ae5dc9fa070ac`
MD5	`0190c11f75ed28a7e56050182ca95a18`
BLAKE2b-256	`bec09d34c8297de4cfc4db02cc84849807f68ddc2e6cf92a42afa270c93267d2`

Hashes for scipy-1.5.1-cp36-cp36m-macosx_10_9_x86_64.whl

Hashes for scipy-1.5.1-cp36-cp36m-macosx_10_9_x86_64.whl
Algorithm	Hash digest
SHA256	`058e84930407927f71963a4ad8c1dc96c4d2d075636a68578195648c81f78810`
MD5	`b71e8115d61c604cc65e5ecc556131f6`
BLAKE2b-256	`12d8010f2111706a06082c7b8fd8d138a012a3ce95d3f74caeaaa6084fefb479`