NumPy is the fundamental package for array computing with Python.
Project description
It provides:
a powerful N-dimensional array object
sophisticated (broadcasting) functions
tools for integrating C/C++ and Fortran code
useful linear algebra, Fourier transform, and random number capabilities
and much more
Besides its obvious scientific uses, NumPy can also be used as an efficient multi-dimensional container of generic data. Arbitrary data-types can be defined. This allows NumPy to seamlessly and speedily integrate with a wide variety of databases.
All NumPy wheels distributed on PyPI are BSD licensed.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
numpy-1.20.0.zip
(8.0 MB
view hashes)
Built Distributions
numpy-1.20.0-cp39-cp39-win32.whl
(11.4 MB
view hashes)
numpy-1.20.0-cp38-cp38-win32.whl
(11.4 MB
view hashes)
numpy-1.20.0-cp37-cp37m-win32.whl
(11.3 MB
view hashes)
Close
Hashes for numpy-1.20.0-pp37-pypy37_pp73-manylinux2010_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 4d592264d2a4f368afbb4288b5ceb646d4cbaf559c0249c096fbb0a149806b90 |
|
MD5 | 66ea4e7911de7fdce688c1b69f9c7c54 |
|
BLAKE2b-256 | 675b54d14318e8bd1fe1e1b2be498e7aaa883766b7d8d5d5c98371a2447748de |
Close
Hashes for numpy-1.20.0-cp39-cp39-win_amd64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | e3db646af9f6a145f0c57202f4b55d4a33f975e395e78fb7b394644c17c1a3a6 |
|
MD5 | 663428d8bedc5785041800ce098368cd |
|
BLAKE2b-256 | ccbd5779abe299afb562cdd434e8229a69a71802cc131ea6d811a8bf05937745 |
Close
Hashes for numpy-1.20.0-cp39-cp39-win32.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | d1bc331e1706fd1809a1bc8a31205329e5b30cf5ba50461c624da267e99f6ae6 |
|
MD5 | 796b273028c7724a855214ae9a83e4f8 |
|
BLAKE2b-256 | fc9d3845dab2da70d54f29973bc071117bd5b05b818621b5ebc384c4c3f2a1aa |
Close
Hashes for numpy-1.20.0-cp39-cp39-manylinux2014_aarch64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 0d28a54afcf46f1f9ebd163e49ad6b49087f22986fefd01a23ca0c1cdda25ca6 |
|
MD5 | 52a78d15f15959003047ccb6b66a0ee7 |
|
BLAKE2b-256 | e1ce3f26bb881ed3b6540923cb162e4ea2ba66ffd4cadc994c660ecb219ee520 |
Close
Hashes for numpy-1.20.0-cp39-cp39-manylinux2010_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 93c2abea7bb69f47029b84ceac30ab46dfcfdb99b671ad850a333ff794a765e4 |
|
MD5 | 4979a98a2cf0a1b14a82630b717aa12b |
|
BLAKE2b-256 | 5f7ce27404f1650923650c418a961d9ccb22134926c88d61a09c3fdfe576bf82 |
Close
Hashes for numpy-1.20.0-cp39-cp39-manylinux2010_i686.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | cf5d9dcbdbe523fa665c5309cce5f144648d94a7fddbf5a40f8e0d5c9f5b596d |
|
MD5 | e36e7e259bb38ccd2320f88a137115e0 |
|
BLAKE2b-256 | ef48de374754b58c6ac4b167537f3aabf3c1ba366d51ebce9c6f0d9e7cb3a58b |
Close
Hashes for numpy-1.20.0-cp39-cp39-macosx_10_9_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | cb257bb0c0a3176c32782a63cfab2eace7eabfa2a3b2dfd85a13700617ccaf28 |
|
MD5 | 749cca75b33849a78e7238aeb09baded |
|
BLAKE2b-256 | 1865b7bc93a0096349f827ecb56f7b98370e704c8a1883c552505d8cf478f741 |
Close
Hashes for numpy-1.20.0-cp38-cp38-win_amd64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | f1e9424e9aa3834ea27cc12f9c6ea8ace5da18ee60a720bb3a85b2f733f41782 |
|
MD5 | 93ebb884970cf7292778cb19e9f27596 |
|
BLAKE2b-256 | 46488b2e5104bfb68e2b8723fbfb402ed0816066e5249735d6591c74b9849fc7 |
Close
Hashes for numpy-1.20.0-cp38-cp38-win32.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | abdfa075e293d73638ece434708aa60b510dc6e70d805f57f481a0f550b25a9e |
|
MD5 | 0e0e4bf53dd8ea4e232083e788419f30 |
|
BLAKE2b-256 | e5e94ec4b349afdcb629943a1bbba22847222cdf3d9ad16670793d6ec92744c7 |
Close
Hashes for numpy-1.20.0-cp38-cp38-manylinux2014_aarch64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | eee454d3aa3955d0c0069a0f265fea47f1e1384c35a110a95efed358eb6e1562 |
|
MD5 | 2282da14106cb52bbf9c8c0b847c3480 |
|
BLAKE2b-256 | 3de356781e03ba3f7eb713af03ad8050957d357fd31685b356c446626436ff3e |
Close
Hashes for numpy-1.20.0-cp38-cp38-manylinux2010_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | b66a6c15d793eda7cdad986e737775aa31b9306d588c14dd0277d2dda5546150 |
|
MD5 | c192aeac728a3abfbd16daef87b2a307 |
|
BLAKE2b-256 | cae58abad0d947199a7c66995c710fa8c9fb1de0af6239575f9129d75fa4e9ed |
Close
Hashes for numpy-1.20.0-cp38-cp38-manylinux2010_i686.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 894aaee60043a98b03f0ad992c810f62e3a15f98a701e1c0f58a4f4a0df13429 |
|
MD5 | 0b0a5e36d4b75a00603cec4db09c44d7 |
|
BLAKE2b-256 | c24bc80ff84027fd077bad534b75169c388f63bb45f6b70f0bf375c8c7c811e6 |
Close
Hashes for numpy-1.20.0-cp38-cp38-manylinux1_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 33edfc0eb229f86f539493917b34035054313a11afbed48404aaf9f86bf4b0f6 |
|
MD5 | 83d74204a26e9dd3cb93653818745d09 |
|
BLAKE2b-256 | 4d0b309da6fbfa351de3b72817ecf3b663ca2962d15e60f00b14e6ad3e08bce9 |
Close
Hashes for numpy-1.20.0-cp38-cp38-manylinux1_i686.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 2445a96fbae23a4109c61be0f0af0f3bc273905dc5687a710850c1dfde0fc994 |
|
MD5 | 2ee146bad9aa521d0bdfd7e30e982a80 |
|
BLAKE2b-256 | c1eeb000ac19ea14bdc876d9c697ea5e3f290a80edc1218ec43d27444fd172c1 |
Close
Hashes for numpy-1.20.0-cp38-cp38-macosx_10_9_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 2bf0e68c92ef077fe766e53f8937d8ac341bdbca68ec128ae049b7d5c34e3206 |
|
MD5 | 791cc5086a755929a1140018067c4587 |
|
BLAKE2b-256 | e94fe1ba93fd1d9b72d3b89e2091df522f52edc3a7a8449e3603114f5a5ea19c |
Close
Hashes for numpy-1.20.0-cp37-cp37m-win_amd64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | afeee581b50df20ef07b736e62ca612858f1fcdba96651d26ab44e3d567a4e6e |
|
MD5 | ec8265d429e808d8f92ed46711d66bc7 |
|
BLAKE2b-256 | 4c0e7220e8ed03c55a1c1c2d68bd45fa28c04787477740ad64a918d25f6d0eb9 |
Close
Hashes for numpy-1.20.0-cp37-cp37m-win32.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | b51b9ef0624f4b01b846c981034c10d2e30db33f9f8be71e992f3900741f6f77 |
|
MD5 | e884b218dc2b20895f57fae00534e8ea |
|
BLAKE2b-256 | 8823dc73a55f3887fe65afb11709e41888f2dd58b6c175ce2b8aee32fcc77eb4 |
Close
Hashes for numpy-1.20.0-cp37-cp37m-manylinux2014_aarch64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 5ae765dd29c71a555f8102281f6fb15a3f4dbd35f6e7daf36af9df6d9dd716a5 |
|
MD5 | b2d47be4aa123623b39f18723e0d70b7 |
|
BLAKE2b-256 | 5f5f530f553c7c12fca5a05b389d21251b859e70421a9d667158e96142a11eb0 |
Close
Hashes for numpy-1.20.0-cp37-cp37m-manylinux2010_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 1abc02e30e3efd81a4571e00f8e62bf42e343c76698e0a3e11d9c2b3ee0d77a7 |
|
MD5 | 82211490e9375bdad57592139b49184d |
|
BLAKE2b-256 | 3a6c322f6aa128179d0ea45a543a4e29a74da2317117109899cfd56d09bf3de0 |
Close
Hashes for numpy-1.20.0-cp37-cp37m-manylinux2010_i686.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | db5e69d08756a2fa75a42b4e433880b6187768fe1bc73d21819def893e5128c6 |
|
MD5 | 89c477a3eaf2e3379aa21bf80e2a2812 |
|
BLAKE2b-256 | 58bae7f7b5672e6feb6346ac30f05e5429c3de47f473bc73462d3d5e82f4d1f3 |
Close
Hashes for numpy-1.20.0-cp37-cp37m-manylinux1_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | e9c5fd330d2fedf06051bafb996252de9b032fcb2ec03eefc9a543e56efa66d4 |
|
MD5 | e8f71fdb7e4e837ae79894b621e3ca08 |
|
BLAKE2b-256 | 730d20355061d7c382c973d9c62803c6f1bdb2e2eb9e5f3623dff2f94c0e253c |
Close
Hashes for numpy-1.20.0-cp37-cp37m-manylinux1_i686.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 1264c66129f5ef63187649dd43f1ca59532e8c098723643336a85131c0dcce3f |
|
MD5 | c77f563595ab4bab6185c795c573a26a |
|
BLAKE2b-256 | 732f39288b4a2490779e32c7c8bb0e3f1cde9d5875d15da9c20aa042e158a24b |
Close
Hashes for numpy-1.20.0-cp37-cp37m-macosx_10_9_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 89bd70c9ad540febe6c28451ba225eb4e49d27f64728357f512c808002325dfa |
|
MD5 | 6f43f51475706d8346cee9604ed54e8a |
|
BLAKE2b-256 | efd68f0458d22383a63d953ddfd41444f4c21783d75b0d19e1373d4ab7456add |