How to Install and Uninstall python39-cloudpickle Package on openSuSE Tumbleweed
Last updated: November 26,2024
1. Install "python39-cloudpickle" package
Here is a brief guide to show you how to install python39-cloudpickle on openSuSE Tumbleweed
$
sudo zypper refresh
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$
sudo zypper install
python39-cloudpickle
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2. Uninstall "python39-cloudpickle" package
Please follow the guidelines below to uninstall python39-cloudpickle on openSuSE Tumbleweed:
$
sudo zypper remove
python39-cloudpickle
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3. Information about the python39-cloudpickle package on openSuSE Tumbleweed
Information for package python39-cloudpickle:
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Repository : openSUSE-Tumbleweed-Oss
Name : python39-cloudpickle
Version : 2.2.1-2.4
Arch : noarch
Vendor : openSUSE
Installed Size : 151.8 KiB
Installed : No
Status : not installed
Source package : python-cloudpickle-2.2.1-2.4.src
Upstream URL : https://github.com/cloudpipe/cloudpickle
Summary : Extended pickling support for Python objects
Description :
The cloudpickle package makes it possible to serialize Python constructs
not supported by the default pickle module from the Python standard
library.
cloudpickle is especially useful for cluster computing where Python
expressions are shipped over the network to execute on remote hosts,
possibly close to the data.
Among other things, cloudpickle supports pickling for lambda expressions,
functions and classes defined interactively in the __main__ module.
---------------------------------------------
Repository : openSUSE-Tumbleweed-Oss
Name : python39-cloudpickle
Version : 2.2.1-2.4
Arch : noarch
Vendor : openSUSE
Installed Size : 151.8 KiB
Installed : No
Status : not installed
Source package : python-cloudpickle-2.2.1-2.4.src
Upstream URL : https://github.com/cloudpipe/cloudpickle
Summary : Extended pickling support for Python objects
Description :
The cloudpickle package makes it possible to serialize Python constructs
not supported by the default pickle module from the Python standard
library.
cloudpickle is especially useful for cluster computing where Python
expressions are shipped over the network to execute on remote hosts,
possibly close to the data.
Among other things, cloudpickle supports pickling for lambda expressions,
functions and classes defined interactively in the __main__ module.