How to Install and Uninstall python3-cytoolz.x86_64 Package on CentOS Stream 8

Last updated: October 05,2024

1. Install "python3-cytoolz.x86_64" package

This tutorial shows how to install python3-cytoolz.x86_64 on CentOS Stream 8


    
        
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                sudo dnf update
            
                    
    
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                sudo dnf install
            
                        
                python3-cytoolz.x86_64
            
                    
    
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2. Uninstall "python3-cytoolz.x86_64" package

This guide let you learn how to uninstall python3-cytoolz.x86_64 on CentOS Stream 8:


    
        
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                sudo dnf remove
            
                        
                python3-cytoolz.x86_64
            
                    
    
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                sudo dnf autoremove
            
                    
    
    Copied

3. Information about the python3-cytoolz.x86_64 package on CentOS Stream 8

Last metadata expiration check: 1:05:47 ago on Sun Feb 25 03:03:59 2024.
Available Packages
Name : python3-cytoolz
Version : 0.11.0
Release : 1.el8
Architecture : x86_64
Size : 319 k
Source : python-cytoolz-0.11.0-1.el8.src.rpm
Repository : epel
Summary : Cython implementation of the toolz package
URL : http://github.com/pytoolz/cytoolz/
License : BSD
Description : Cython implementation of the toolz package, which provides high performance
: utility functions for iterables, functions, and dictionaries.
:
: toolz is a pure Python package that borrows heavily from contemporary
: functional languanges. It is designed to interoperate seamlessly with other
: libraries including itertools, functools, and third party libraries. High
: performance functional data analysis is possible with builtin types like list
: and dict, and user-defined data structures; and low memory usage is achieved
: by using the iterator protocol and returning iterators whenever possible.
:
: cytoolz implements the same API as toolz. The main differences are that
: cytoolz is faster (typically 2-5x faster with a few spectacular exceptions)
: and cytoolz offers a C API that is accessible to other projects developed in
: Cython. Since toolz is able to process very large (potentially infinite) data
: sets, the performance increase gained by using cytoolz can be significant.
:
: See the PyToolz documentation at http://toolz.readthedocs.org.