scipy

SciPy: Scientific Library for Python

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

Release history Release notifications | RSS feed

1.5.3

Oct 17, 2020

1.5.2

Jul 24, 2020

1.5.1

Jul 4, 2020

1.5.0

Jun 21, 2020

1.5.0rc2 pre-release

Jun 14, 2020

1.5.0rc1 pre-release

May 30, 2020

1.4.1

Dec 19, 2019

1.4.0

Dec 16, 2019

1.4.0rc2 pre-release

Dec 8, 2019

1.4.0rc1 pre-release

Nov 22, 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

1.3.0rc2 pre-release

May 9, 2019

1.3.0rc1 pre-release

Apr 27, 2019

1.2.3

Jan 21, 2020

1.2.2

Jun 7, 2019

1.2.1

Feb 9, 2019

This version

1.2.0

Dec 18, 2018

1.2.0rc2 pre-release

Dec 5, 2018

1.2.0rc1 pre-release

Nov 26, 2018

1.1.0

May 5, 2018

1.1.0rc1 pre-release

Apr 15, 2018

1.0.1

Mar 24, 2018

1.0.0

Oct 25, 2017

1.0.0rc2 pre-release

Oct 18, 2017

1.0.0rc1 pre-release

Sep 27, 2017

1.0.0b1 pre-release

Sep 18, 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

0.18.0rc2 pre-release

Jul 10, 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

0.14.1rc1 pre-release

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

0.14.1rc1.dev-205726a pre-release

Dec 30, 2014

0.14.1rc1.dev-52fb336 pre-release

Dec 30, 2014

Download files

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

Files for scipy, version 1.2.0
Filename, size	File type	Python version	Upload date	Hashes
Filename, size scipy-1.2.0-cp27-cp27m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl (28.8 MB)	File type Wheel	Python version cp27	Upload date Dec 18, 2018	Hashes View
Filename, size scipy-1.2.0-cp27-cp27m-manylinux1_i686.whl (21.4 MB)	File type Wheel	Python version cp27	Upload date Dec 18, 2018	Hashes View
Filename, size scipy-1.2.0-cp27-cp27m-manylinux1_x86_64.whl (26.6 MB)	File type Wheel	Python version cp27	Upload date Dec 18, 2018	Hashes View
Filename, size scipy-1.2.0-cp27-cp27mu-manylinux1_i686.whl (21.4 MB)	File type Wheel	Python version cp27	Upload date Dec 18, 2018	Hashes View
Filename, size scipy-1.2.0-cp27-cp27mu-manylinux1_x86_64.whl (26.6 MB)	File type Wheel	Python version cp27	Upload date Dec 18, 2018	Hashes View
Filename, size scipy-1.2.0-cp27-cp27m-win32.whl (27.3 MB)	File type Wheel	Python version cp27	Upload date Dec 18, 2018	Hashes View
Filename, size scipy-1.2.0-cp27-cp27m-win_amd64.whl (32.2 MB)	File type Wheel	Python version cp27	Upload date Dec 18, 2018	Hashes View
Filename, size scipy-1.2.0-cp34-cp34m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl (28.6 MB)	File type Wheel	Python version cp34	Upload date Dec 18, 2018	Hashes View
Filename, size scipy-1.2.0-cp34-cp34m-manylinux1_i686.whl (21.3 MB)	File type Wheel	Python version cp34	Upload date Dec 18, 2018	Hashes View
Filename, size scipy-1.2.0-cp34-cp34m-manylinux1_x86_64.whl (26.5 MB)	File type Wheel	Python version cp34	Upload date Dec 18, 2018	Hashes View
Filename, size scipy-1.2.0-cp34-cp34m-win32.whl (26.6 MB)	File type Wheel	Python version cp34	Upload date Dec 18, 2018	Hashes View
Filename, size scipy-1.2.0-cp34-cp34m-win_amd64.whl (31.3 MB)	File type Wheel	Python version cp34	Upload date Dec 18, 2018	Hashes View
Filename, size scipy-1.2.0-cp35-cp35m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl (28.6 MB)	File type Wheel	Python version cp35	Upload date Dec 18, 2018	Hashes View
Filename, size scipy-1.2.0-cp35-cp35m-manylinux1_i686.whl (21.3 MB)	File type Wheel	Python version cp35	Upload date Dec 18, 2018	Hashes View
Filename, size scipy-1.2.0-cp35-cp35m-manylinux1_x86_64.whl (26.5 MB)	File type Wheel	Python version cp35	Upload date Dec 18, 2018	Hashes View
Filename, size scipy-1.2.0-cp35-cp35m-win32.whl (26.9 MB)	File type Wheel	Python version cp35	Upload date Dec 18, 2018	Hashes View
Filename, size scipy-1.2.0-cp35-cp35m-win_amd64.whl (31.8 MB)	File type Wheel	Python version cp35	Upload date Dec 18, 2018	Hashes View
Filename, size scipy-1.2.0-cp36-cp36m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl (28.8 MB)	File type Wheel	Python version cp36	Upload date Dec 18, 2018	Hashes View
Filename, size scipy-1.2.0-cp36-cp36m-manylinux1_i686.whl (21.4 MB)	File type Wheel	Python version cp36	Upload date Dec 18, 2018	Hashes View
Filename, size scipy-1.2.0-cp36-cp36m-manylinux1_x86_64.whl (26.6 MB)	File type Wheel	Python version cp36	Upload date Dec 18, 2018	Hashes View
Filename, size scipy-1.2.0-cp36-cp36m-win32.whl (26.9 MB)	File type Wheel	Python version cp36	Upload date Dec 18, 2018	Hashes View
Filename, size scipy-1.2.0-cp36-cp36m-win_amd64.whl (31.9 MB)	File type Wheel	Python version cp36	Upload date Dec 18, 2018	Hashes View
Filename, size scipy-1.2.0-cp37-cp37m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl (28.7 MB)	File type Wheel	Python version cp37	Upload date Dec 18, 2018	Hashes View
Filename, size scipy-1.2.0-cp37-cp37m-manylinux1_i686.whl (21.4 MB)	File type Wheel	Python version cp37	Upload date Dec 18, 2018	Hashes View
Filename, size scipy-1.2.0-cp37-cp37m-manylinux1_x86_64.whl (26.6 MB)	File type Wheel	Python version cp37	Upload date Dec 18, 2018	Hashes View
Filename, size scipy-1.2.0-cp37-cp37m-win32.whl (26.8 MB)	File type Wheel	Python version cp37	Upload date Dec 18, 2018	Hashes View
Filename, size scipy-1.2.0-cp37-cp37m-win_amd64.whl (31.7 MB)	File type Wheel	Python version cp37	Upload date Dec 18, 2018	Hashes View
Filename, size scipy-1.2.0.tar.gz (23.3 MB)	File type Source	Python version None	Upload date Dec 18, 2018	Hashes View

Hashes for scipy-1.2.0-cp27-cp27m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl

Hashes for scipy-1.2.0-cp27-cp27m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl
Algorithm	Hash digest
SHA256	`d1ae77b79fd5e27a10ba7c4e7c3a62927b9d29a4dccf28f6905c25d983aaf183`
MD5	`0bb53a49e77bca11fb26698744c60f97`
BLAKE2-256	`014a686c5b7a7b94ca55f06f8c5992ebd3db0ddb4691ec97d8125f5a5b55eaae`

Hashes for scipy-1.2.0-cp27-cp27m-manylinux1_i686.whl

Hashes for scipy-1.2.0-cp27-cp27m-manylinux1_i686.whl
Algorithm	Hash digest
SHA256	`4b1f0883cb9d8ee963cf0a31c87341e9e758abb2cf1e5bcc0d7b066ef6b17573`
MD5	`39e215ac7e8d6de33d939486987dcba4`
BLAKE2-256	`e92383128a859e22c5036934fe9697a1dbedae2a45c14fb4e76e7aae009920e7`

Hashes for scipy-1.2.0-cp27-cp27m-manylinux1_x86_64.whl

Hashes for scipy-1.2.0-cp27-cp27m-manylinux1_x86_64.whl
Algorithm	Hash digest
SHA256	`c5eae911cf26b3c7eda889ec98d3c226f312c587acfaaf02602473f98b4c16d6`
MD5	`d6e33b2c05ffbcf9790628d656c8e61f`
BLAKE2-256	`2c9a8cfd681d4a970ff0174dcb93d16c70103c430c64264a9d9078c8abda2b9f`

Hashes for scipy-1.2.0-cp27-cp27mu-manylinux1_i686.whl

Hashes for scipy-1.2.0-cp27-cp27mu-manylinux1_i686.whl
Algorithm	Hash digest
SHA256	`02cb79ea38114dc480e9b08d6b87095728e8fb39b9a49b449ee443d678001611`
MD5	`82b1ecbecadfeddd2be1c6d616491029`
BLAKE2-256	`7ad2a1fa98b87a481a767fc6439185611be50df84d730431173d8d78954abaa5`

Hashes for scipy-1.2.0-cp27-cp27mu-manylinux1_x86_64.whl

Hashes for scipy-1.2.0-cp27-cp27mu-manylinux1_x86_64.whl
Algorithm	Hash digest
SHA256	`7dc4002f0a0a688774ef04878afe769ecd1ac21fe9b4b1d7125e2cf16170afd3`
MD5	`65021ade783f1416b1920d2a2cc39d4d`
BLAKE2-256	`45d17c2b33a5daee3d67752d043fe7e1476c4465788b0b6e59367fd71fdf684a`

Hashes for scipy-1.2.0-cp27-cp27m-win32.whl

Hashes for scipy-1.2.0-cp27-cp27m-win32.whl
Algorithm	Hash digest
SHA256	`58f0435f052cb60f1472c77f52a8f6642f8877b70559e5e0b9a1744f33f5cbe5`
MD5	`a463a12d77b87df0a2d202323771a908`
BLAKE2-256	`8d3e8b832f5df4d06190c280585278886ecda99ff10d25be0a685f78f79009a0`

Hashes for scipy-1.2.0-cp27-cp27m-win_amd64.whl

Hashes for scipy-1.2.0-cp27-cp27m-win_amd64.whl
Algorithm	Hash digest
SHA256	`4cce25c6e7ff7399c67dfe1b5423c36c391cf9b4b2be390c1675ab410f1ef503`
MD5	`3dc17a11c7dd211ce51a338cfe30eb48`
BLAKE2-256	`4b49caac539e47294049b4dbbd1e4c80e8df6fa70a84ebea12cda4e77253e46d`

Hashes for scipy-1.2.0-cp34-cp34m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl

Hashes for scipy-1.2.0-cp34-cp34m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl
Algorithm	Hash digest
SHA256	`7994c044bf659b0a24ad7673ec7db85c2fadb87e4980a379a9fd5b086fe3649a`
MD5	`7cc2cdbc9b421ef10695b898cdc241e7`
BLAKE2-256	`f7c2d5ab01720a360af9d65d1b58eb53798dd78e1fe17391818a1123dde3992c`

Hashes for scipy-1.2.0-cp34-cp34m-manylinux1_i686.whl

Hashes for scipy-1.2.0-cp34-cp34m-manylinux1_i686.whl
Algorithm	Hash digest
SHA256	`72bd766f753fd32f072d30d7bc2ad492d56dbcbf3e13764e27635d5c41079339`
MD5	`2a4ccbfcccb9395fa7554a82db40e454`
BLAKE2-256	`633a7303014067b0fa8bd9b27dbb6c8b07a4e83db31bf5983bf3910863e3103a`

Hashes for scipy-1.2.0-cp34-cp34m-manylinux1_x86_64.whl

Hashes for scipy-1.2.0-cp34-cp34m-manylinux1_x86_64.whl
Algorithm	Hash digest
SHA256	`3132a9fab3f3545c8b0ba15688d11857efdd4a58d388d3785dc474f56fea7138`
MD5	`662dc35acd6f588565cd6467465fc742`
BLAKE2-256	`bf476e6b4136e1ca4729f67b0ef45b93dcf7523c33c95050a2bc75f8f26c4199`

Hashes for scipy-1.2.0-cp34-cp34m-win32.whl

Hashes for scipy-1.2.0-cp34-cp34m-win32.whl
Algorithm	Hash digest
SHA256	`7413080b381766a22d52814edb65631f0e323a7cea945c70021a672f38acc73f`
MD5	`a19bd9969bb5b92595e82d924b8272f9`
BLAKE2-256	`cb64c006e1f6a418f74cadc03910b2bea3034c1f8ccb45303612a6b8889a97d7`

Hashes for scipy-1.2.0-cp34-cp34m-win_amd64.whl

Hashes for scipy-1.2.0-cp34-cp34m-win_amd64.whl
Algorithm	Hash digest
SHA256	`6f791987899532305126309578727c0197bddbafab9596bafe3e7bfab6e1ce13`
MD5	`5f1eaa3745956db0da724f83dd174559`
BLAKE2-256	`5693114bb24b62dc584c3f6181054ece710ac2366840cb778bf0f93c4074593b`

Hashes for scipy-1.2.0-cp35-cp35m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl

Hashes for scipy-1.2.0-cp35-cp35m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl
Algorithm	Hash digest
SHA256	`937147086e8b4338bf139ca8fa98da650e3a46bf2ca617f8e9dd68c3971ec420`
MD5	`d32a4c31d0a188f3550c1306d20b03c7`
BLAKE2-256	`11ad9d71302bfda15523a7cabb35c26eb41b4c6c8412897b34eca809bcaf709f`

Hashes for scipy-1.2.0-cp35-cp35m-manylinux1_i686.whl

Hashes for scipy-1.2.0-cp35-cp35m-manylinux1_i686.whl
Algorithm	Hash digest
SHA256	`63e1d5ca9e5e1984f1a275276991b036e25d39d37dd7edbb3f4f6165c2da7dbb`
MD5	`34f4a7f04abfda87fac8ab38a9a70a77`
BLAKE2-256	`05814dc54387f6240f0bdcab178770f9121c52901a8afff85e84c521cf34d5ec`

Hashes for scipy-1.2.0-cp35-cp35m-manylinux1_x86_64.whl

Hashes for scipy-1.2.0-cp35-cp35m-manylinux1_x86_64.whl
Algorithm	Hash digest
SHA256	`03c827cdbc584e935264040b958e5fa0570a16095bee23a013482ba3f0e963a2`
MD5	`bd4d56910802870072e3c5ded69a8f08`
BLAKE2-256	`ab19c0ad5b9183ef97030edd6297d1726525ff2c369a09fbb6ea52a1e616ffd6`

Hashes for scipy-1.2.0-cp35-cp35m-win32.whl

Hashes for scipy-1.2.0-cp35-cp35m-win32.whl
Algorithm	Hash digest
SHA256	`bc294841f6c822714af362095b181a853f47ed5ce757354bd2e4776d579ff3a4`
MD5	`cb3fb7ddd3992928f9173e4eb489d23e`
BLAKE2-256	`ed2bdfe43bc35fbeb8ad997f397bb7bcaabe84d9f4ac5ae4c7599ae06f8eadb5`

Hashes for scipy-1.2.0-cp35-cp35m-win_amd64.whl

Hashes for scipy-1.2.0-cp35-cp35m-win_amd64.whl
Algorithm	Hash digest
SHA256	`cca33a01a5987c650b87a1a910aa311ffa44e67cca1ff502ef9efdae5d9a8624`
MD5	`68f5ddcb6e592b1d9cba95f24faee7b5`
BLAKE2-256	`eb065f1123e379e349cd61fe88d98512ac695bf0b41f999ac097747835722d36`

Hashes for scipy-1.2.0-cp36-cp36m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl

Hashes for scipy-1.2.0-cp36-cp36m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl
Algorithm	Hash digest
SHA256	`8608316d0cc01f8b25111c8adfe6efbc959cbba037a62c784551568d7ffbf280`
MD5	`c0e110f3a935731782c96a13cc264ea2`
BLAKE2-256	`c01deef9d7b34ab8b7ee42d570f2e24d58ee0374064c1ca593bdb02914f66a80`

Hashes for scipy-1.2.0-cp36-cp36m-manylinux1_i686.whl

Hashes for scipy-1.2.0-cp36-cp36m-manylinux1_i686.whl
Algorithm	Hash digest
SHA256	`fb36064047e6bf87b6320a9b6eb7f525ef6863c7a4aef1a84a4bbfb043612617`
MD5	`9d898924498abbe2d26dd18b3413fb11`
BLAKE2-256	`807bbb47a983f16da11e170d1504bc6a96bba51de9319d65acabafd9779327e6`

Hashes for scipy-1.2.0-cp36-cp36m-manylinux1_x86_64.whl

Hashes for scipy-1.2.0-cp36-cp36m-manylinux1_x86_64.whl
Algorithm	Hash digest
SHA256	`854bd87cc23824d5db4983956bc30f3790e1c7448f1a9e6a8fb7bff7601aef87`
MD5	`dd9ae664cbe7de54828d83c772e24da3`
BLAKE2-256	`67e66d4edaceee6a110ecf6f318482f5229792f143e468b34a631f5a0899f56d`

Hashes for scipy-1.2.0-cp36-cp36m-win32.whl

Hashes for scipy-1.2.0-cp36-cp36m-win32.whl
Algorithm	Hash digest
SHA256	`fc1a19d95649439dbd50baca676bceb29bbfcd600aed2c5bd71d9bad82a87cfe`
MD5	`8dea8432610bb3c63114eb6469c5f99a`
BLAKE2-256	`18d19ed926284d97c12cc4c07b81abce886dd4430c52b8323defc365ed04026e`

Hashes for scipy-1.2.0-cp36-cp36m-win_amd64.whl

Hashes for scipy-1.2.0-cp36-cp36m-win_amd64.whl
Algorithm	Hash digest
SHA256	`8f5fcc87b48fc3dd6d901669c89af4feeb856dffb6f671539a238b7e8af1799c`
MD5	`ebda830aec7b60193772741f85fee28c`
BLAKE2-256	`c40f2bdeab43db2b4a75863863bf7eddda8920b031b0a70494fd2665c73c9aec`

Hashes for scipy-1.2.0-cp37-cp37m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl

Hashes for scipy-1.2.0-cp37-cp37m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl
Algorithm	Hash digest
SHA256	`bc6a88b0009a1b60eab5c22ac3a006f6968d6328de10c6a64ebb0d64a05548d3`
MD5	`0e8b7a7908c50e635e639d2c69901140`
BLAKE2-256	`c27b370891c7686e598c59890588722c1d1c2b485953c4b127b7b752accbddb6`

Hashes for scipy-1.2.0-cp37-cp37m-manylinux1_i686.whl

Hashes for scipy-1.2.0-cp37-cp37m-manylinux1_i686.whl
Algorithm	Hash digest
SHA256	`64b2c35824da3ef6bb1e722216e4ef28802af6413c7586136500e343d34ba179`
MD5	`56719437a821f9f2f98f069225e70c87`
BLAKE2-256	`673b30870e245555479d3ab986fdb9b7495a00705368616435993d373d20c7b7`

Hashes for scipy-1.2.0-cp37-cp37m-manylinux1_x86_64.whl

Hashes for scipy-1.2.0-cp37-cp37m-manylinux1_x86_64.whl
Algorithm	Hash digest
SHA256	`78a67ee4845440e81cfbfabde20537ca12051d0eeac951fe4c6d8751feac3103`
MD5	`93d9d978855516ec38fa08620ef3443c`
BLAKE2-256	`8039066ecde98f373430bf7a39a02d91c7075b01ef4fc928456e8e31577342d6`

Hashes for scipy-1.2.0-cp37-cp37m-win32.whl

Hashes for scipy-1.2.0-cp37-cp37m-win32.whl
Algorithm	Hash digest
SHA256	`04f2b23258139c109d0524f111597dd095a505d9cb2c71e381d688d653877fa3`
MD5	`fff3d66b877b6e6b9984b84ae9e4d76c`
BLAKE2-256	`88f27f16c94e22c9714b0dc417bdaa7d6eb9ec9f90fd5d5c6221769f73b3f5dd`

Hashes for scipy-1.2.0-cp37-cp37m-win_amd64.whl

Hashes for scipy-1.2.0-cp37-cp37m-win_amd64.whl
Algorithm	Hash digest
SHA256	`5706b785ca289fdfd91aa05066619e51d140613b613e35932601f2315f5d8470`
MD5	`3defb2c8b2f69057919ee3b0c92de65c`
BLAKE2-256	`f1b8800d98339427199305f8b4a7f02827ec9bfea438d677aecbe0bd297092d5`

Hashes for scipy-1.2.0.tar.gz

Hashes for scipy-1.2.0.tar.gz
Algorithm	Hash digest
SHA256	`51a2424c8ed80e60bdb9a896806e7adaf24a58253b326fbad10f80a6d06f2214`
MD5	`e57011507865b0b702aff6077d412e03`
BLAKE2-256	`eac8c296904f2c852c5c129962e6ca4ba467116b08cd5b54b7180b2e77fe06b2`