NumPy: array processing for numbers, strings, records, and objects.
Project description
NumPy is a general-purpose array-processing package designed to efficiently manipulate large multi-dimensional arrays of arbitrary records without sacrificing too much speed for small multi-dimensional arrays. NumPy is built on the Numeric code base and adds features introduced by numarray as well as an extended C-API and the ability to create arrays of arbitrary type which also makes NumPy suitable for interfacing with general-purpose data-base applications.
There are also basic facilities for discrete fourier transform, basic linear algebra and random number generation.
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 Distributions
Built Distributions
Hashes for numpy-1.9.2-cp35-cp35m-manylinux1_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 776c4df79ffac22801eb17f1119088f56b652ed01b41deefe14911d66d95a04d |
|
MD5 | 7e859a7804467882eada09f724d3bae4 |
|
BLAKE2b-256 | a0436dbb2f0d89c98f90e9851cbba712ff8afbaf699b243447566c50aa56420c |
Hashes for numpy-1.9.2-cp34-cp34m-manylinux1_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 811dec937131a554e0ace8dfa6b0919ae1b47e376901eb65bf9b1f99f35efbff |
|
MD5 | 8b534c57e23f05bda86603c6a0a96ef2 |
|
BLAKE2b-256 | cbe0e8a2ae5130db93472fac4dff0211b5fb4f580b0dcd399584290c7664d5d0 |
Hashes for numpy-1.9.2-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 | c8ec2900b86d5579023cfe0ae3d6211253e3812171b718c416c584832b439c8b |
|
MD5 | 1df533f72f8c9eab956017da349579e5 |
|
BLAKE2b-256 | e1153b6edf45429063b233a296dea9e5ab408152168d395033006c8b7799944e |
Hashes for numpy-1.9.2-cp33-cp33m-manylinux1_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 9f37f271049451033d3458f80f411ff1f59177ffd6cbb10a3ffc80af84da2149 |
|
MD5 | 46c2f8a57776808b36068f282507280c |
|
BLAKE2b-256 | 0539673f4e48993a397f64c8e8798e8df26446027194346a013af556eeac9093 |
Hashes for numpy-1.9.2-cp33-cp33m-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 | 25bb6805253e390ca85d3fc990be0ec6527d19e0968de1af7accc5c8e45d5c72 |
|
MD5 | d2d8fb9161e662e0b04c32458b2e1ba7 |
|
BLAKE2b-256 | c7c7178ea881b18c27f60a6765aa4ab964a604d7aed86523b4e603a216c3d03c |
Hashes for numpy-1.9.2-cp27-none-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 | ad83e22634e1a34a00d1809a0bd69d04eca68d5c975a1f298c6cead191420071 |
|
MD5 | 296f576bb648b8195b379b0bf39791ce |
|
BLAKE2b-256 | d1e4268d113fae408ce7f49f4c9c9cacc543d85a29a09058c496f38073fbdbae |
Hashes for numpy-1.9.2-cp27-cp27mu-manylinux1_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 425cc2d1f8326e281db328fdddfdbaaee8c907c375cbe9664cc85276f4a05db8 |
|
MD5 | 0da340e64f1aa9736fbef6000beea7ed |
|
BLAKE2b-256 | 474634a876b2ef1e9048df8c678a246aae8c727f025fd907451b6a75dd0cea1f |
Hashes for numpy-1.9.2-cp27-cp27m-manylinux1_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 5026382cc5feb674d13e13da6f4b1fe6db800be9887cc7e93fb8a4db2d11d9bd |
|
MD5 | 4e1ce604b8a619e04fcdfdc32dab2d9a |
|
BLAKE2b-256 | fd4770fe002303661db1a87293244c15ac5d066ed0c2b352ac1ec5f739318f63 |
Hashes for numpy-1.9.2-cp26-cp26mu-manylinux1_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 247aa9efcc1a279b7251a9e9e6d95c6d1e860e461b9bec502765e26b4e9edd1f |
|
MD5 | 13aadb18f61bccf3763c2180a35eceea |
|
BLAKE2b-256 | b28493e97806357fc0bdfe4a9fc88e35f2e47bf94dbd0e062891b7e2a6984213 |
Hashes for numpy-1.9.2-cp26-cp26m-manylinux1_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | b7a2439a390f702de036597c0dee92fb3333a7f9b4607aa256a21f087297e936 |
|
MD5 | 2f0025f9840bb87095db1e156350e970 |
|
BLAKE2b-256 | 6d6f84d83f96e445fe814d3cc593a1b0b0f1e17c3a33a0577413037058574973 |