Skip to main content

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.

Metadata

Release files for numpy 1.17.4

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for numpy 1.17.4
File Size Uploaded
numpy-1.17.4.zip 6.4 MB Details

Built distributions (wheels)

Table of built distributions (wheels) for numpy 1.17.4
File
numpy-1.17.4-cp38-cp38-win_amd64.whl CPython 3.8 CPython 3.8 Windows x86-64 Details
numpy-1.17.4-cp38-cp38-win32.whl CPython 3.8 CPython 3.8 Windows x86-32 Details
numpy-1.17.4-cp38-cp38-manylinux1_x86_64.whl CPython 3.8 CPython 3.8 Linux glibc 2.5+ x86-64 Details
numpy-1.17.4-cp38-cp38-manylinux1_i686.whl CPython 3.8 CPython 3.8 Linux glibc 2.5+ x86-32 Details
numpy-1.17.4-cp38-cp38-macosx_10_9_x86_64.whl CPython 3.8 CPython 3.8 macOS 10.9+ x86-64 Details
numpy-1.17.4-cp37-cp37m-win_amd64.whl CPython 3.7 CPython 3.7 pymalloc Windows x86-64 Details
numpy-1.17.4-cp37-cp37m-win32.whl CPython 3.7 CPython 3.7 pymalloc Windows x86-32 Details
numpy-1.17.4-cp37-cp37m-manylinux1_x86_64.whl CPython 3.7 CPython 3.7 pymalloc Linux glibc 2.5+ x86-64 Details
numpy-1.17.4-cp37-cp37m-manylinux1_i686.whl CPython 3.7 CPython 3.7 pymalloc Linux glibc 2.5+ x86-32 Details
numpy-1.17.4-cp37-cp37m-macosx_10_9_x86_64.whl CPython 3.7 CPython 3.7 pymalloc macOS 10.9+ x86-64 Details
numpy-1.17.4-cp36-cp36m-win_amd64.whl CPython 3.6 CPython 3.6 pymalloc Windows x86-64 Details
numpy-1.17.4-cp36-cp36m-win32.whl CPython 3.6 CPython 3.6 pymalloc Windows x86-32 Details
numpy-1.17.4-cp36-cp36m-manylinux1_x86_64.whl CPython 3.6 CPython 3.6 pymalloc Linux glibc 2.5+ x86-64 Details
numpy-1.17.4-cp36-cp36m-manylinux1_i686.whl CPython 3.6 CPython 3.6 pymalloc Linux glibc 2.5+ x86-32 Details
numpy-1.17.4-cp36-cp36m-macosx_10_9_x86_64.whl CPython 3.6 CPython 3.6 pymalloc macOS 10.9+ x86-64 Details
numpy-1.17.4-cp35-cp35m-win_amd64.whl CPython 3.5 CPython 3.5 pymalloc Windows x86-64 Details
numpy-1.17.4-cp35-cp35m-win32.whl CPython 3.5 CPython 3.5 pymalloc Windows x86-32 Details
numpy-1.17.4-cp35-cp35m-manylinux1_x86_64.whl CPython 3.5 CPython 3.5 pymalloc Linux glibc 2.5+ x86-64 Details
numpy-1.17.4-cp35-cp35m-manylinux1_i686.whl CPython 3.5 CPython 3.5 pymalloc Linux glibc 2.5+ x86-32 Details
numpy-1.17.4-cp35-cp35m-macosx_10_6_intel.whl CPython 3.5 CPython 3.5 pymalloc macOS 10.6+ Intel (x86-64, i386) Details

Total release size: 309.9 MB

Release files / numpy-1.17.4.zip

Download URL numpy-1.17.4.zip
Size 6.4 MB
Tags Source
SHA-256 checksum
How to use checksums
f58913e9227400f1395c7b800503ebfdb0772f1c33ff8cb4d6451c06cabdf316
BLAKE2b-256 checksum
How to use checksums
ff59d3f6d46aa1fd220d020bdd61e76ca51f6548c6ad6d24ddb614f4037cf49d
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/1.11.0 pkginfo/1.4.2 requests/2.18.4 setuptools/38.5.1 requests-toolbelt/0.8.0 tqdm/4.23.4 CPython/2.7.16

Release files / numpy-1.17.4-cp38-cp38-win_amd64.whl

Download URL numpy-1.17.4-cp38-cp38-win_amd64.whl
Size 12.7 MB
Tags CPython 3.8 Windows x86-64
SHA-256 checksum
How to use checksums
ada4805ed51f5bcaa3a06d3dd94939351869c095e30a2b54264f5a5004b52170
BLAKE2b-256 checksum
How to use checksums
ca11c81d07e47d197634ac175941bf0de5add37d40a6b9e9a79723fae7380e56
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/1.11.0 pkginfo/1.4.2 requests/2.18.4 setuptools/38.5.1 requests-toolbelt/0.8.0 tqdm/4.23.4 CPython/2.7.16

Release files / numpy-1.17.4-cp38-cp38-win32.whl

Download URL numpy-1.17.4-cp38-cp38-win32.whl
Size 10.8 MB
Tags CPython 3.8 Windows x86-32
SHA-256 checksum
How to use checksums
0a7a1dd123aecc9f0076934288ceed7fd9a81ba3919f11a855a7887cbe82a02f
BLAKE2b-256 checksum
How to use checksums
5c2832ca028c2dcaa3f180dcc59266d6856d3e24f63ca96b8fc4af9bdbd4ae04
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/1.11.0 pkginfo/1.4.2 requests/2.18.4 setuptools/38.5.1 requests-toolbelt/0.8.0 tqdm/4.23.4 CPython/2.7.16

Release files / numpy-1.17.4-cp38-cp38-manylinux1_x86_64.whl

Download URL numpy-1.17.4-cp38-cp38-manylinux1_x86_64.whl
Size 20.5 MB
Tags CPython 3.8 Linux glibc 2.5+ x86-64
SHA-256 checksum
How to use checksums
a8f67ebfae9f575d85fa859b54d3bdecaeece74e3274b0b5c5f804d7ca789fe1
BLAKE2b-256 checksum
How to use checksums
d76a3fed132c846d1e47963f30376cc041e9dd586d286d931055ad06ff65c6c7
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/1.11.0 pkginfo/1.4.2 requests/2.18.4 setuptools/38.5.1 requests-toolbelt/0.8.0 tqdm/4.23.4 CPython/2.7.16

Release files / numpy-1.17.4-cp38-cp38-manylinux1_i686.whl

Download URL numpy-1.17.4-cp38-cp38-manylinux1_i686.whl
Size 17.7 MB
Tags CPython 3.8 Linux glibc 2.5+ x86-32
SHA-256 checksum
How to use checksums
e2e9d8c87120ba2c591f60e32736b82b67f72c37ba88a4c23c81b5b8fa49c018
BLAKE2b-256 checksum
How to use checksums
bcf97fd1368393a561d68efc248c1dfba1c877c65290cabd4f55ad31c43db93b
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/1.11.0 pkginfo/1.4.2 requests/2.18.4 setuptools/38.5.1 requests-toolbelt/0.8.0 tqdm/4.23.4 CPython/2.7.16

Release files / numpy-1.17.4-cp38-cp38-macosx_10_9_x86_64.whl

Download URL numpy-1.17.4-cp38-cp38-macosx_10_9_x86_64.whl
Size 15.1 MB
Tags CPython 3.8 macOS 10.9+ x86-64
SHA-256 checksum
How to use checksums
683828e50c339fc9e68720396f2de14253992c495fdddef77a1e17de55f1decc
BLAKE2b-256 checksum
How to use checksums
9ecf7cea38d32df6087d7c15bca8edef0be82e0d957119e9dafd7052dc6192f0
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/1.11.0 pkginfo/1.4.2 requests/2.18.4 setuptools/38.5.1 requests-toolbelt/0.8.0 tqdm/4.23.4 CPython/2.7.16

Release files / numpy-1.17.4-cp37-cp37m-win_amd64.whl

Download URL numpy-1.17.4-cp37-cp37m-win_amd64.whl
Size 12.7 MB
Tags CPython 3.7 CPython 3.7 pymalloc Windows x86-64
SHA-256 checksum
How to use checksums
0c0763787133dfeec19904c22c7e358b231c87ba3206b211652f8cbe1241deb6
BLAKE2b-256 checksum
How to use checksums
3440c6eae19892551ff91bdb15f884fef2d42d6f58da55ab18fa540851b48a32
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/1.11.0 pkginfo/1.4.2 requests/2.18.4 setuptools/38.5.1 requests-toolbelt/0.8.0 tqdm/4.23.4 CPython/2.7.16

Release files / numpy-1.17.4-cp37-cp37m-win32.whl

Download URL numpy-1.17.4-cp37-cp37m-win32.whl
Size 10.7 MB
Tags CPython 3.7 CPython 3.7 pymalloc Windows x86-32
SHA-256 checksum
How to use checksums
475963c5b9e116c38ad7347e154e5651d05a2286d86455671f5b1eebba5feb76
BLAKE2b-256 checksum
How to use checksums
cead2e88f36b56f64f70c081b32fa5512dacedf12005ccb0c2d300d44dcc1215
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/1.11.0 pkginfo/1.4.2 requests/2.18.4 setuptools/38.5.1 requests-toolbelt/0.8.0 tqdm/4.23.4 CPython/2.7.16

Release files / numpy-1.17.4-cp37-cp37m-manylinux1_x86_64.whl

Download URL numpy-1.17.4-cp37-cp37m-manylinux1_x86_64.whl
Size 20.0 MB
Tags CPython 3.7 CPython 3.7 pymalloc Linux glibc 2.5+ x86-64
SHA-256 checksum
How to use checksums
3d52298d0be333583739f1aec9026f3b09fdfe3ddf7c7028cb16d9d2af1cca7e
BLAKE2b-256 checksum
How to use checksums
9baf4fc72f9d38e43b092e91e5b8cb9956d25b2e3ff8c75aed95df5569e4734e
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/1.11.0 pkginfo/1.4.2 requests/2.18.4 setuptools/38.5.1 requests-toolbelt/0.8.0 tqdm/4.23.4 CPython/2.7.16

Release files / numpy-1.17.4-cp37-cp37m-manylinux1_i686.whl

Download URL numpy-1.17.4-cp37-cp37m-manylinux1_i686.whl
Size 17.3 MB
Tags CPython 3.7 CPython 3.7 pymalloc Linux glibc 2.5+ x86-32
SHA-256 checksum
How to use checksums
acbf5c52db4adb366c064d0b7c7899e3e778d89db585feadd23b06b587d64761
BLAKE2b-256 checksum
How to use checksums
0816cc53a5d61c2db6f6134c72d52d3dec0de44fd4e642ad217bea33fd2cfa16
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/1.11.0 pkginfo/1.4.2 requests/2.18.4 setuptools/38.5.1 requests-toolbelt/0.8.0 tqdm/4.23.4 CPython/2.7.16

Release files / numpy-1.17.4-cp37-cp37m-macosx_10_9_x86_64.whl

Download URL numpy-1.17.4-cp37-cp37m-macosx_10_9_x86_64.whl
Size 15.1 MB
Tags CPython 3.7 CPython 3.7 pymalloc macOS 10.9+ x86-64
SHA-256 checksum
How to use checksums
9679831005fb16c6df3dd35d17aa31dc0d4d7573d84f0b44cc481490a65c7725
BLAKE2b-256 checksum
How to use checksums
609aa6b3168f2194fb468dcc4cf54c8344d1f514935006c3347ede198e968cb0
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/1.11.0 pkginfo/1.4.2 requests/2.18.4 setuptools/38.5.1 requests-toolbelt/0.8.0 tqdm/4.23.4 CPython/2.7.16

Release files / numpy-1.17.4-cp36-cp36m-win_amd64.whl

Download URL numpy-1.17.4-cp36-cp36m-win_amd64.whl
Size 12.7 MB
Tags CPython 3.6 CPython 3.6 pymalloc Windows x86-64
SHA-256 checksum
How to use checksums
8d0af8d3664f142414fd5b15cabfd3b6cc3ef242a3c7a7493257025be5a6955f
BLAKE2b-256 checksum
How to use checksums
b0ee5ff445dd43b9820e5494d21240e689d3b7cb52bc93f4f164eba84206cd0d
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/1.11.0 pkginfo/1.4.2 requests/2.18.4 setuptools/38.5.1 requests-toolbelt/0.8.0 tqdm/4.23.4 CPython/2.7.16

Release files / numpy-1.17.4-cp36-cp36m-win32.whl

Download URL numpy-1.17.4-cp36-cp36m-win32.whl
Size 10.7 MB
Tags CPython 3.6 CPython 3.6 pymalloc Windows x86-32
SHA-256 checksum
How to use checksums
e467c57121fe1b78a8f68dd9255fbb3bb3f4f7547c6b9e109f31d14569f490c3
BLAKE2b-256 checksum
How to use checksums
44dd45a5965b3406b39d0537a1de89727879f356db984fe82e918bfb9327aa04
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/1.11.0 pkginfo/1.4.2 requests/2.18.4 setuptools/38.5.1 requests-toolbelt/0.8.0 tqdm/4.23.4 CPython/2.7.16

Release files / numpy-1.17.4-cp36-cp36m-manylinux1_x86_64.whl

Download URL numpy-1.17.4-cp36-cp36m-manylinux1_x86_64.whl
Size 20.0 MB
Tags CPython 3.6 CPython 3.6 pymalloc Linux glibc 2.5+ x86-64
SHA-256 checksum
How to use checksums
fe39f5fd4103ec4ca3cb8600b19216cd1ff316b4990f4c0b6057ad982c0a34d5
BLAKE2b-256 checksum
How to use checksums
d2ab43e678759326f728de861edbef34b8e2ad1b1490505f20e0d1f0716c3bf4
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/1.11.0 pkginfo/1.4.2 requests/2.18.4 setuptools/38.5.1 requests-toolbelt/0.8.0 tqdm/4.23.4 CPython/2.7.16

Release files / numpy-1.17.4-cp36-cp36m-manylinux1_i686.whl

Download URL numpy-1.17.4-cp36-cp36m-manylinux1_i686.whl
Size 17.3 MB
Tags CPython 3.6 CPython 3.6 pymalloc Linux glibc 2.5+ x86-32
SHA-256 checksum
How to use checksums
7d81d784bdbed30137aca242ab307f3e65c8d93f4c7b7d8f322110b2e90177f9
BLAKE2b-256 checksum
How to use checksums
15bbeeebd50d401b976127f37567567bf1336edddb09e2551bfdaff844371bcf
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/1.11.0 pkginfo/1.4.2 requests/2.18.4 setuptools/38.5.1 requests-toolbelt/0.8.0 tqdm/4.23.4 CPython/2.7.16

Release files / numpy-1.17.4-cp36-cp36m-macosx_10_9_x86_64.whl

Download URL numpy-1.17.4-cp36-cp36m-macosx_10_9_x86_64.whl
Size 15.1 MB
Tags CPython 3.6 CPython 3.6 pymalloc macOS 10.9+ x86-64
SHA-256 checksum
How to use checksums
75fd817b7061f6378e4659dd792c84c0b60533e867f83e0d1e52d5d8e53df88c
BLAKE2b-256 checksum
How to use checksums
229936e3408ae2cb8b72260de4e538196d17736d7fb82a1086cb2c21ee156ddc
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/1.11.0 pkginfo/1.4.2 requests/2.18.4 setuptools/38.5.1 requests-toolbelt/0.8.0 tqdm/4.23.4 CPython/2.7.16

Release files / numpy-1.17.4-cp35-cp35m-win_amd64.whl

Download URL numpy-1.17.4-cp35-cp35m-win_amd64.whl
Size 12.7 MB
Tags CPython 3.5 CPython 3.5 pymalloc Windows x86-64
SHA-256 checksum
How to use checksums
6ca4000c4a6f95a78c33c7dadbb9495c10880be9c89316aa536eac359ab820ae
BLAKE2b-256 checksum
How to use checksums
257137628d7654da4a539f33497c9d9d6713d2bb3c9e35638776b3eea38ca04a
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/1.11.0 pkginfo/1.4.2 requests/2.18.4 setuptools/38.5.1 requests-toolbelt/0.8.0 tqdm/4.23.4 CPython/2.7.16

Release files / numpy-1.17.4-cp35-cp35m-win32.whl

Download URL numpy-1.17.4-cp35-cp35m-win32.whl
Size 10.7 MB
Tags CPython 3.5 CPython 3.5 pymalloc Windows x86-32
SHA-256 checksum
How to use checksums
64874913367f18eb3013b16123c9fed113962e75d809fca5b78ebfbb73ed93ba
BLAKE2b-256 checksum
How to use checksums
20dc20048d495faabd2b542b52025c5c227d41b7e75db12bc5f8c3fa8be0b12a
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/1.11.0 pkginfo/1.4.2 requests/2.18.4 setuptools/38.5.1 requests-toolbelt/0.8.0 tqdm/4.23.4 CPython/2.7.16

Release files / numpy-1.17.4-cp35-cp35m-manylinux1_x86_64.whl

Download URL numpy-1.17.4-cp35-cp35m-manylinux1_x86_64.whl
Size 19.8 MB
Tags CPython 3.5 CPython 3.5 pymalloc Linux glibc 2.5+ x86-64
SHA-256 checksum
How to use checksums
c7354e8f0eca5c110b7e978034cd86ed98a7a5ffcf69ca97535445a595e07b8e
BLAKE2b-256 checksum
How to use checksums
abe92561dbfbc05146bffa02167e09b9902e273decb2dc4cd5c43314ede20312
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/1.11.0 pkginfo/1.4.2 requests/2.18.4 setuptools/38.5.1 requests-toolbelt/0.8.0 tqdm/4.23.4 CPython/2.7.16

Release files / numpy-1.17.4-cp35-cp35m-manylinux1_i686.whl

Download URL numpy-1.17.4-cp35-cp35m-manylinux1_i686.whl
Size 17.2 MB
Tags CPython 3.5 CPython 3.5 pymalloc Linux glibc 2.5+ x86-32
SHA-256 checksum
How to use checksums
43bb4b70585f1c2d153e45323a886839f98af8bfa810f7014b20be714c37c447
BLAKE2b-256 checksum
How to use checksums
47ec8fef81b736eff0f65b9ab03519e7c584f904222dce6b7d2dd08c13ba5ef7
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/1.11.0 pkginfo/1.4.2 requests/2.18.4 setuptools/38.5.1 requests-toolbelt/0.8.0 tqdm/4.23.4 CPython/2.7.16

Release files / numpy-1.17.4-cp35-cp35m-macosx_10_6_intel.whl

Download URL numpy-1.17.4-cp35-cp35m-macosx_10_6_intel.whl
Size 14.8 MB
Tags CPython 3.5 CPython 3.5 pymalloc macOS 10.6+ Intel (x86-64, i386)
SHA-256 checksum
How to use checksums
ede47b98de79565fcd7f2decb475e2dcc85ee4097743e551fe26cfc7eb3ff143
BLAKE2b-256 checksum
How to use checksums
4dd6b5a915da06c98a3d992b7ad730bc3c16d735d0a25540962aa1c35a1ecd24
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/1.11.0 pkginfo/1.4.2 requests/2.18.4 setuptools/38.5.1 requests-toolbelt/0.8.0 tqdm/4.23.4 CPython/2.7.16

Release history Release notifications | RSS feed

2.5.0

44 release files

2.4.6

72 release files

2.4.5

72 release files

2.4.4

72 release files

2.4.2

72 release files

2.4.1

72 release files

2.4.0

72 release files

2.3.5

74 release files

2.3.4

74 release files

2.3.2

74 release files

2.3.1

51 release files

2.2.6

55 release files

2.2.5

55 release files

2.2.4

55 release files

2.2.3

55 release files

2.2.2

55 release files

2.2.1

55 release files

2.1.0

52 release files

2.0.2

45 release files

2.0.1

45 release files

2.0.0

45 release files

This release

1.17.4 This release

21 release files

1.9.3

13 release files

1.8.1

11 release files

1.8.0

8 release files

1.7.2

8 release files

1.7.0

14 release files

1.6.2

12 release files

1.6.1

12 release files

1.6.0

12 release files

1.5.1

6 release files

1.5.0

2 release files

1.4.1

1 release file

1.4.0

1.3.0

2 release files

1.2.1

1.2.0

1.1.1

1.0.4

1.0.3

1.0

1 release file

1.0rc3

1.0rc2

1.0rc1

1.0b5

1.0b4

1.0b1

0.9.8

0.9.6

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page