How to Install and Uninstall python-Shed_Skin Package on openSUSE Leap
Last updated: December 27,2024
Deprecated! Installation of this package may no longer be supported.
1. Install "python-Shed_Skin" package
Please follow the steps below to install python-Shed_Skin on openSUSE Leap
$
sudo zypper refresh
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$
sudo zypper install
python-Shed_Skin
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2. Uninstall "python-Shed_Skin" package
In this section, we are going to explain the necessary steps to uninstall python-Shed_Skin on openSUSE Leap:
$
sudo zypper remove
python-Shed_Skin
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3. Information about the python-Shed_Skin package on openSUSE Leap
Information for package python-Shed_Skin:
-----------------------------------------
Repository : Main Repository
Name : python-Shed_Skin
Version : 0.9.4-bp153.1.12
Arch : noarch
Vendor : openSUSE
Installed Size : 1,6 MiB
Installed : No
Status : not installed
Source package : python-Shed_Skin-0.9.4-bp153.1.12.src
Summary : An Optimizing (restricted) Python-to-C++ Compiler
Description :
Shed Skin is an experimental (restricted) Python-to-C++ compiler. It accepts
pure but implicitly statically typed Python programs and generates optimized
C++ code. The result can be further compiled to stand-alone programs or
extension modules. For a set of 57 non-trivial test programs, at more than
16,000 lines in total (sloccount), measurements show a typical speedup of
2-200 times compared to CPython. Not all Python features are supported, and
only a subset of about 20 library modules, such as re and random. See the
home page for more details.
-----------------------------------------
Repository : Main Repository
Name : python-Shed_Skin
Version : 0.9.4-bp153.1.12
Arch : noarch
Vendor : openSUSE
Installed Size : 1,6 MiB
Installed : No
Status : not installed
Source package : python-Shed_Skin-0.9.4-bp153.1.12.src
Summary : An Optimizing (restricted) Python-to-C++ Compiler
Description :
Shed Skin is an experimental (restricted) Python-to-C++ compiler. It accepts
pure but implicitly statically typed Python programs and generates optimized
C++ code. The result can be further compiled to stand-alone programs or
extension modules. For a set of 57 non-trivial test programs, at more than
16,000 lines in total (sloccount), measurements show a typical speedup of
2-200 times compared to CPython. Not all Python features are supported, and
only a subset of about 20 library modules, such as re and random. See the
home page for more details.