How to Install and Uninstall python2-numpy Package on openSUSE Leap
Last updated: November 26,2024
Deprecated! Installation of this package may no longer be supported.
1. Install "python2-numpy" package
This is a short guide on how to install python2-numpy on openSUSE Leap
$
sudo zypper refresh
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$
sudo zypper install
python2-numpy
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2. Uninstall "python2-numpy" package
This guide covers the steps necessary to uninstall python2-numpy on openSUSE Leap:
$
sudo zypper remove
python2-numpy
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3. Information about the python2-numpy package on openSUSE Leap
Information for package python2-numpy:
--------------------------------------
Repository : Main Repository
Name : python2-numpy
Version : 1.16.5-1.40
Arch : x86_64
Vendor : SUSE LLC
Installed Size : 14,6 MiB
Installed : No
Status : not installed
Source package : python2-numpy-1.16.5-1.40.src
Summary : NumPy array processing for numbers, strings, records and objects
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.
--------------------------------------
Repository : Main Repository
Name : python2-numpy
Version : 1.16.5-1.40
Arch : x86_64
Vendor : SUSE LLC
Installed Size : 14,6 MiB
Installed : No
Status : not installed
Source package : python2-numpy-1.16.5-1.40.src
Summary : NumPy array processing for numbers, strings, records and objects
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.