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.
All numpy wheels distributed from pypi are BSD licensed.
Windows wheels are linked against the ATLAS BLAS / LAPACK library, restricted to SSE2 instructions, so may not give optimal linear algebra performance for your machine. See http://docs.scipy.org/doc/numpy/user/install.html for alternatives.
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Release files for numpy 1.13.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| numpy-1.13.1.zip | 5.0 MB | Without provenance | Details |
Built distributions (wheels)
| File | Reset | |||
|---|---|---|---|---|
| numpy-1.13.1-cp36-none-win_amd64.whl | CPython 3.6 | none | Windows x86-64 | Details |
| numpy-1.13.1-cp36-none-win32.whl | CPython 3.6 | none | Windows x86-32 | Details |
| numpy-1.13.1-cp36-cp36m-manylinux1_x86_64.whl | CPython 3.6 | CPython 3.6 pymalloc | Linux glibc 2.5+ x86-64 | Details |
| numpy-1.13.1-cp36-cp36m-manylinux1_i686.whl | CPython 3.6 | CPython 3.6 pymalloc | Linux glibc 2.5+ x86-32 | Details |
| numpy-1.13.1-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 | CPython 3.6 | CPython 3.6 pymalloc | macOS 10.9+ Intel (x86-64, i386), macOS 10.6+ Intel (x86-64, i386), macOS 10.10+ Intel (x86-64, i386), macOS 10.10+ x86-64, macOS 10.9+ x86-64 | Details |
| numpy-1.13.1-cp35-none-win_amd64.whl | CPython 3.5 | none | Windows x86-64 | Details |
| numpy-1.13.1-cp35-none-win32.whl | CPython 3.5 | none | Windows x86-32 | Details |
| numpy-1.13.1-cp35-cp35m-manylinux1_x86_64.whl | CPython 3.5 | CPython 3.5 pymalloc | Linux glibc 2.5+ x86-64 | Details |
| numpy-1.13.1-cp35-cp35m-manylinux1_i686.whl | CPython 3.5 | CPython 3.5 pymalloc | Linux glibc 2.5+ x86-32 | Details |
| numpy-1.13.1-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 | CPython 3.5 | CPython 3.5 pymalloc | macOS 10.9+ Intel (x86-64, i386), macOS 10.10+ Intel (x86-64, i386), macOS 10.6+ Intel (x86-64, i386), macOS 10.9+ x86-64, macOS 10.10+ x86-64 | Details |
| numpy-1.13.1-cp34-none-win_amd64.whl | CPython 3.4 | none | Windows x86-64 | Details |
| numpy-1.13.1-cp34-none-win32.whl | CPython 3.4 | none | Windows x86-32 | Details |
| numpy-1.13.1-cp34-cp34m-manylinux1_x86_64.whl | CPython 3.4 | CPython 3.4 pymalloc | Linux glibc 2.5+ x86-64 | Details |
| numpy-1.13.1-cp34-cp34m-manylinux1_i686.whl | CPython 3.4 | CPython 3.4 pymalloc | Linux glibc 2.5+ x86-32 | Details |
| numpy-1.13.1-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 | CPython 3.4 | CPython 3.4 pymalloc | macOS 10.10+ x86-64, macOS 10.6+ Intel (x86-64, i386), macOS 10.9+ Intel (x86-64, i386), macOS 10.10+ Intel (x86-64, i386), macOS 10.9+ x86-64 | Details |
| numpy-1.13.1-cp27-none-win_amd64.whl | CPython 2.7 | none | Windows x86-64 | Details |
| numpy-1.13.1-cp27-none-win32.whl | CPython 2.7 | none | Windows x86-32 | Details |
| numpy-1.13.1-cp27-cp27mu-manylinux1_x86_64.whl | CPython 2.7 | CPython 2.7 pymalloc wide-unicode | Linux glibc 2.5+ x86-64 | Details |
| numpy-1.13.1-cp27-cp27mu-manylinux1_i686.whl | CPython 2.7 | CPython 2.7 pymalloc wide-unicode | Linux glibc 2.5+ x86-32 | Details |
| numpy-1.13.1-cp27-cp27m-manylinux1_x86_64.whl | CPython 2.7 | CPython 2.7 pymalloc | Linux glibc 2.5+ x86-64 | Details |
| numpy-1.13.1-cp27-cp27m-manylinux1_i686.whl | CPython 2.7 | CPython 2.7 pymalloc | Linux glibc 2.5+ x86-32 | Details |
| numpy-1.13.1-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 | CPython 2.7 | CPython 2.7 pymalloc | macOS 10.10+ x86-64, macOS 10.9+ x86-64, macOS 10.9+ Intel (x86-64, i386), macOS 10.10+ Intel (x86-64, i386), macOS 10.6+ Intel (x86-64, i386) | Details |
Total release size: 228.7 MB
Release files / numpy-1.13.1.zip
| Download URL | numpy-1.13.1.zip |
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| Size | 5.0 MB |
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Release files / numpy-1.13.1-cp36-none-win_amd64.whl
| Download URL | numpy-1.13.1-cp36-none-win_amd64.whl |
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| Size | 7.8 MB |
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Release files / numpy-1.13.1-cp36-none-win32.whl
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Release files / numpy-1.13.1-cp36-cp36m-manylinux1_x86_64.whl
| Download URL | numpy-1.13.1-cp36-cp36m-manylinux1_x86_64.whl |
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Release files / numpy-1.13.1-cp36-cp36m-manylinux1_i686.whl
| Download URL | numpy-1.13.1-cp36-cp36m-manylinux1_i686.whl |
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Release files / numpy-1.13.1-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
| Download URL | numpy-1.13.1-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 |
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| Size | 4.5 MB |
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Release files / numpy-1.13.1-cp35-none-win_amd64.whl
| Download URL | numpy-1.13.1-cp35-none-win_amd64.whl |
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Release files / numpy-1.13.1-cp35-none-win32.whl
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Release files / numpy-1.13.1-cp35-cp35m-manylinux1_x86_64.whl
| Download URL | numpy-1.13.1-cp35-cp35m-manylinux1_x86_64.whl |
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Release files / numpy-1.13.1-cp35-cp35m-manylinux1_i686.whl
| Download URL | numpy-1.13.1-cp35-cp35m-manylinux1_i686.whl |
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| Size | 12.8 MB |
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Release files / numpy-1.13.1-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
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| Size | 4.5 MB |
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Release files / numpy-1.13.1-cp34-none-win_amd64.whl
| Download URL | numpy-1.13.1-cp34-none-win_amd64.whl |
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Release files / numpy-1.13.1-cp34-none-win32.whl
| Download URL | numpy-1.13.1-cp34-none-win32.whl |
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Release files / numpy-1.13.1-cp34-cp34m-manylinux1_x86_64.whl
| Download URL | numpy-1.13.1-cp34-cp34m-manylinux1_x86_64.whl |
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| Size | 16.9 MB |
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Release files / numpy-1.13.1-cp34-cp34m-manylinux1_i686.whl
| Download URL | numpy-1.13.1-cp34-cp34m-manylinux1_i686.whl |
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Release files / numpy-1.13.1-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
| Download URL | numpy-1.13.1-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 |
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| Size | 4.5 MB |
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Release files / numpy-1.13.1-cp27-none-win_amd64.whl
| Download URL | numpy-1.13.1-cp27-none-win_amd64.whl |
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Release files / numpy-1.13.1-cp27-none-win32.whl
| Download URL | numpy-1.13.1-cp27-none-win32.whl |
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Release files / numpy-1.13.1-cp27-cp27mu-manylinux1_x86_64.whl
| Download URL | numpy-1.13.1-cp27-cp27mu-manylinux1_x86_64.whl |
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Release files / numpy-1.13.1-cp27-cp27mu-manylinux1_i686.whl
| Download URL | numpy-1.13.1-cp27-cp27mu-manylinux1_i686.whl |
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Release files / numpy-1.13.1-cp27-cp27m-manylinux1_x86_64.whl
| Download URL | numpy-1.13.1-cp27-cp27m-manylinux1_x86_64.whl |
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Release files / numpy-1.13.1-cp27-cp27m-manylinux1_i686.whl
| Download URL | numpy-1.13.1-cp27-cp27m-manylinux1_i686.whl |
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| Size | 12.6 MB |
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Release files / numpy-1.13.1-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
| Download URL | numpy-1.13.1-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 |
|---|---|
| Size | 4.6 MB |
| Tags | CPython 2.7 CPython 2.7 pymalloc macOS 10.10+ Intel (x86-64, i386) macOS 10.10+ x86-64 macOS 10.6+ Intel (x86-64, i386) macOS 10.9+ Intel (x86-64, i386) macOS 10.9+ x86-64 |
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SHA-256 checksum How to use checksums |
91a4f5c6594a61b57b0ab6031a084fa3686b1e847cc2215983e444583594b529
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BLAKE2b-256 checksum How to use checksums |
dddb3807a832fabfb105498a860b8f5908c90b9812ed86ed76e17658fe8a0ff6
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
Security for numpy 1.13.1
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