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.
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Release files for numpy 1.17.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| numpy-1.17.2.zip | 6.5 MB | Details |
Built distributions (wheels)
| File | Reset | |||
|---|---|---|---|---|
| numpy-1.17.2-cp37-cp37m-win_amd64.whl | CPython 3.7 | CPython 3.7 pymalloc | Windows x86-64 | Details |
| numpy-1.17.2-cp37-cp37m-win32.whl | CPython 3.7 | CPython 3.7 pymalloc | Windows x86-32 | Details |
| numpy-1.17.2-cp37-cp37m-manylinux1_x86_64.whl | CPython 3.7 | CPython 3.7 pymalloc | Linux glibc 2.5+ x86-64 | Details |
| numpy-1.17.2-cp37-cp37m-manylinux1_i686.whl | CPython 3.7 | CPython 3.7 pymalloc | Linux glibc 2.5+ x86-32 | Details |
| numpy-1.17.2-cp37-cp37m-macosx_10_6_intel.whl | CPython 3.7 | CPython 3.7 pymalloc | macOS 10.6+ Intel (x86-64, i386) | Details |
| numpy-1.17.2-cp36-cp36m-win_amd64.whl | CPython 3.6 | CPython 3.6 pymalloc | Windows x86-64 | Details |
| numpy-1.17.2-cp36-cp36m-win32.whl | CPython 3.6 | CPython 3.6 pymalloc | Windows x86-32 | Details |
| numpy-1.17.2-cp36-cp36m-manylinux1_x86_64.whl | CPython 3.6 | CPython 3.6 pymalloc | Linux glibc 2.5+ x86-64 | Details |
| numpy-1.17.2-cp36-cp36m-manylinux1_i686.whl | CPython 3.6 | CPython 3.6 pymalloc | Linux glibc 2.5+ x86-32 | Details |
| numpy-1.17.2-cp36-cp36m-macosx_10_6_intel.whl | CPython 3.6 | CPython 3.6 pymalloc | macOS 10.6+ Intel (x86-64, i386) | Details |
| numpy-1.17.2-cp35-cp35m-win_amd64.whl | CPython 3.5 | CPython 3.5 pymalloc | Windows x86-64 | Details |
| numpy-1.17.2-cp35-cp35m-win32.whl | CPython 3.5 | CPython 3.5 pymalloc | Windows x86-32 | Details |
| numpy-1.17.2-cp35-cp35m-manylinux1_x86_64.whl | CPython 3.5 | CPython 3.5 pymalloc | Linux glibc 2.5+ x86-64 | Details |
| numpy-1.17.2-cp35-cp35m-manylinux1_i686.whl | CPython 3.5 | CPython 3.5 pymalloc | Linux glibc 2.5+ x86-32 | Details |
| numpy-1.17.2-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: 235.4 MB
Release files / numpy-1.17.2.zip
| Download URL | numpy-1.17.2.zip |
|---|---|
| Size | 6.5 MB |
| Tags | Source |
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Release files / numpy-1.17.2-cp37-cp37m-win_amd64.whl
| Download URL | numpy-1.17.2-cp37-cp37m-win_amd64.whl |
|---|---|
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Release files / numpy-1.17.2-cp37-cp37m-win32.whl
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Release files / numpy-1.17.2-cp37-cp37m-manylinux1_x86_64.whl
| Download URL | numpy-1.17.2-cp37-cp37m-manylinux1_x86_64.whl |
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Release files / numpy-1.17.2-cp37-cp37m-manylinux1_i686.whl
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Release files / numpy-1.17.2-cp37-cp37m-macosx_10_6_intel.whl
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Release files / numpy-1.17.2-cp36-cp36m-win_amd64.whl
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Release files / numpy-1.17.2-cp36-cp36m-win32.whl
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Release files / numpy-1.17.2-cp36-cp36m-manylinux1_x86_64.whl
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Release files / numpy-1.17.2-cp36-cp36m-manylinux1_i686.whl
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Release files / numpy-1.17.2-cp36-cp36m-macosx_10_6_intel.whl
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Release files / numpy-1.17.2-cp35-cp35m-win_amd64.whl
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Release files / numpy-1.17.2-cp35-cp35m-win32.whl
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Release files / numpy-1.17.2-cp35-cp35m-manylinux1_x86_64.whl
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Release files / numpy-1.17.2-cp35-cp35m-manylinux1_i686.whl
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Release files / numpy-1.17.2-cp35-cp35m-macosx_10_6_intel.whl
| Download URL | numpy-1.17.2-cp35-cp35m-macosx_10_6_intel.whl |
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