How to Install and Uninstall perl-Parallel-Iterator.noarch Package on Fedora 36
Last updated: November 27,2024
1. Install "perl-Parallel-Iterator.noarch" package
This is a short guide on how to install perl-Parallel-Iterator.noarch on Fedora 36
$
sudo dnf update
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$
sudo dnf install
perl-Parallel-Iterator.noarch
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2. Uninstall "perl-Parallel-Iterator.noarch" package
Please follow the guidelines below to uninstall perl-Parallel-Iterator.noarch on Fedora 36:
$
sudo dnf remove
perl-Parallel-Iterator.noarch
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$
sudo dnf autoremove
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3. Information about the perl-Parallel-Iterator.noarch package on Fedora 36
Last metadata expiration check: 1:20:00 ago on Thu Sep 8 08:04:50 2022.
Available Packages
Name : perl-Parallel-Iterator
Version : 1.00
Release : 31.fc36
Architecture : noarch
Size : 24 k
Source : perl-Parallel-Iterator-1.00-31.fc36.src.rpm
Repository : fedora
Summary : Simple parallel execution
URL : https://metacpan.org/release/Parallel-Iterator
License : GPL+ or Artistic
Description : The map function applies a user supplied transformation function to
: each element in a list, returning a new list containing the
: transformed elements.
:
: This module provides a 'parallel map'. Multiple worker processes are forked so
: that many instances of the transformation function may be executed
: simultaneously.
:
: For time consuming operations, particularly operations that spend most of their
: time waiting for I/O, this is a big performance win. It also provides a simple
: idiom to make effective use of multi CPU systems.
Available Packages
Name : perl-Parallel-Iterator
Version : 1.00
Release : 31.fc36
Architecture : noarch
Size : 24 k
Source : perl-Parallel-Iterator-1.00-31.fc36.src.rpm
Repository : fedora
Summary : Simple parallel execution
URL : https://metacpan.org/release/Parallel-Iterator
License : GPL+ or Artistic
Description : The map function applies a user supplied transformation function to
: each element in a list, returning a new list containing the
: transformed elements.
:
: This module provides a 'parallel map'. Multiple worker processes are forked so
: that many instances of the transformation function may be executed
: simultaneously.
:
: For time consuming operations, particularly operations that spend most of their
: time waiting for I/O, this is a big performance win. It also provides a simple
: idiom to make effective use of multi CPU systems.