How to Install and Uninstall python311-tables Package on openSuSE Tumbleweed
Last updated: November 08,2024
1. Install "python311-tables" package
Learn how to install python311-tables on openSuSE Tumbleweed
$
sudo zypper refresh
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$
sudo zypper install
python311-tables
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2. Uninstall "python311-tables" package
Please follow the guidance below to uninstall python311-tables on openSuSE Tumbleweed:
$
sudo zypper remove
python311-tables
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3. Information about the python311-tables package on openSuSE Tumbleweed
Information for package python311-tables:
-----------------------------------------
Repository : openSUSE-Tumbleweed-Oss
Name : python311-tables
Version : 3.9.2-4.1
Arch : x86_64
Vendor : openSUSE
Installed Size : 10.2 MiB
Installed : No
Status : not installed
Source package : python-tables-3.9.2-4.1.src
Upstream URL : https://github.com/PyTables/PyTables
Summary : Hierarchical datasets for Python
Description :
PyTables is a package for managing hierarchical datasets and
designed to efficently cope with extremely large amounts of
data. PyTables is built on top of the HDF5 library and the
NumPy package and features an object-oriented interface
that, combined with C-code generated from Pyrex sources,
makes of it a fast, yet extremely easy to use tool for
interactively save and retrieve large amounts of data.
-----------------------------------------
Repository : openSUSE-Tumbleweed-Oss
Name : python311-tables
Version : 3.9.2-4.1
Arch : x86_64
Vendor : openSUSE
Installed Size : 10.2 MiB
Installed : No
Status : not installed
Source package : python-tables-3.9.2-4.1.src
Upstream URL : https://github.com/PyTables/PyTables
Summary : Hierarchical datasets for Python
Description :
PyTables is a package for managing hierarchical datasets and
designed to efficently cope with extremely large amounts of
data. PyTables is built on top of the HDF5 library and the
NumPy package and features an object-oriented interface
that, combined with C-code generated from Pyrex sources,
makes of it a fast, yet extremely easy to use tool for
interactively save and retrieve large amounts of data.