How to Install and Uninstall python38-nbval Package on openSuSE Tumbleweed
Last updated: December 25,2024
Deprecated! Installation of this package may no longer be supported.
1. Install "python38-nbval" package
This guide covers the steps necessary to install python38-nbval on openSuSE Tumbleweed
$
sudo zypper refresh
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$
sudo zypper install
python38-nbval
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2. Uninstall "python38-nbval" package
In this section, we are going to explain the necessary steps to uninstall python38-nbval on openSuSE Tumbleweed:
$
sudo zypper remove
python38-nbval
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3. Information about the python38-nbval package on openSuSE Tumbleweed
Information for package python38-nbval:
---------------------------------------
Repository : openSUSE-Tumbleweed-Oss
Name : python38-nbval
Version : 0.9.6-4.2
Arch : noarch
Vendor : openSUSE
Installed Size : 142,2 KiB
Installed : No
Status : not installed
Source package : python-nbval-0.9.6-4.2.src
Summary : A pytest plugin to validate Jupyter notebooks
Description :
The plugin adds functionality to py.test to recognise and collect
Jupyter notebooks. The intended purpose of the tests is to determine
whether execution of the stored inputs match the stored outputs of
the .ipynb file. Whilst also ensuring that the notebooks are running
without errors.
The tests were designed to ensure that Jupyter notebooks (especially
those for reference and documentation), are executing consistently.
Each cell is taken as a test, a cell that doesn't reproduce the
expected output will fail.
---------------------------------------
Repository : openSUSE-Tumbleweed-Oss
Name : python38-nbval
Version : 0.9.6-4.2
Arch : noarch
Vendor : openSUSE
Installed Size : 142,2 KiB
Installed : No
Status : not installed
Source package : python-nbval-0.9.6-4.2.src
Summary : A pytest plugin to validate Jupyter notebooks
Description :
The plugin adds functionality to py.test to recognise and collect
Jupyter notebooks. The intended purpose of the tests is to determine
whether execution of the stored inputs match the stored outputs of
the .ipynb file. Whilst also ensuring that the notebooks are running
without errors.
The tests were designed to ensure that Jupyter notebooks (especially
those for reference and documentation), are executing consistently.
Each cell is taken as a test, a cell that doesn't reproduce the
expected output will fail.