How to Install and Uninstall python-mako.noarch Package on Amazon Linux 2
Last updated: January 04,2025
1. Install "python-mako.noarch" package
In this section, we are going to explain the necessary steps to install python-mako.noarch on Amazon Linux 2
$
sudo yum makecache
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$
sudo yum install
python-mako.noarch
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2. Uninstall "python-mako.noarch" package
This guide let you learn how to uninstall python-mako.noarch on Amazon Linux 2:
$
sudo yum remove
python-mako.noarch
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$
sudo yum autoremove
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3. Information about the python-mako.noarch package on Amazon Linux 2
Loaded plugins: ovl, priorities
Available Packages
Name : python-mako
Arch : noarch
Version : 0.8.1
Release : 2.amzn2
Size : 307 k
Repo : amzn2-core/2/x86_64
Summary : Mako template library for Python
URL : http://www.makotemplates.org/
License : (MIT and Python) and (BSD or GPLv2)
Description : Mako is a template library written in Python. It provides a
: familiar, non-XML syntax which compiles into Python modules for
: maximum performance. Mako's syntax and API borrows from the best
: ideas of many others, including Django templates, Cheetah, Myghty,
: and Genshi. Conceptually, Mako is an embedded Python (i.e. Python
: Server Page) language, which refines the familiar ideas of
: componentized layout and inheritance to produce one of the most
: straightforward and flexible models available, while also
: maintaining close ties to Python calling and scoping semantics.
Available Packages
Name : python-mako
Arch : noarch
Version : 0.8.1
Release : 2.amzn2
Size : 307 k
Repo : amzn2-core/2/x86_64
Summary : Mako template library for Python
URL : http://www.makotemplates.org/
License : (MIT and Python) and (BSD or GPLv2)
Description : Mako is a template library written in Python. It provides a
: familiar, non-XML syntax which compiles into Python modules for
: maximum performance. Mako's syntax and API borrows from the best
: ideas of many others, including Django templates, Cheetah, Myghty,
: and Genshi. Conceptually, Mako is an embedded Python (i.e. Python
: Server Page) language, which refines the familiar ideas of
: componentized layout and inheritance to produce one of the most
: straightforward and flexible models available, while also
: maintaining close ties to Python calling and scoping semantics.