loongson/pypi/: numpy-1.10.1 metadata and description

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NumPy: array processing for numbers, strings, records, and objects.

author NumPy Developers
author_email numpy-discussion@scipy.org
classifiers
  • Development Status :: 5 - Production/Stable
  • Intended Audience :: Science/Research
  • Intended Audience :: Developers
  • License :: OSI Approved
  • Programming Language :: C
  • Programming Language :: Python
  • Programming Language :: Python :: 2
  • Programming Language :: Python :: 2.6
  • Programming Language :: Python :: 2.7
  • Programming Language :: Python :: 3
  • Programming Language :: Python :: 3.2
  • Programming Language :: Python :: 3.3
  • Programming Language :: Python :: 3.4
  • Programming Language :: Python :: 3.5
  • Programming Language :: Python :: Implementation :: CPython
  • Topic :: Software Development
  • Topic :: Scientific/Engineering
  • Operating System :: Microsoft :: Windows
  • Operating System :: POSIX
  • Operating System :: Unix
  • Operating System :: MacOS
download_url http://sourceforge.net/projects/numpy/files/NumPy/
license BSD
platform
  • Windows
  • Linux
  • Solaris
  • Mac OS-X
  • Unix

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File Tox results History
numpy-1.10.1-cp36-cp36m-linux_loongarch64.whl
Size
7 MB
Type
Python Wheel
Python
3.6
  • Replaced 1 time(s)
  • Uploaded to loongson/pypi by loongson 2022-08-15 01:19:48
numpy-1.10.1-cp37-cp37m-linux_loongarch64.whl
Size
6 MB
Type
Python Wheel
Python
3.7
numpy-1.10.1-cp38-cp38-linux_loongarch64.whl
Size
7 MB
Type
Python Wheel
Python
3.8
  • Replaced 1 time(s)
  • Uploaded to loongson/pypi by loongson 2022-08-12 02:00:25
numpy-1.10.1.tar.gz
Size
3 MB
Type
Source
  • Replaced 1 time(s)
  • Uploaded to loongson/pypi by loongson 2022-08-15 01:19:50

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.