How to Install and Uninstall golang-github-willf-bloom-dev Package on Kali Linux

Last updated: September 20,2024

1. Install "golang-github-willf-bloom-dev" package

This tutorial shows how to install golang-github-willf-bloom-dev on Kali Linux


    
        
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                sudo apt update
            
                    
    
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                sudo apt install
            
                        
                golang-github-willf-bloom-dev
            
                    
    
    Copied

2. Uninstall "golang-github-willf-bloom-dev" package

This is a short guide on how to uninstall golang-github-willf-bloom-dev on Kali Linux:


    
        
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                sudo apt remove
            
                        
                golang-github-willf-bloom-dev
            
                    
    
    Copied


    
        
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                sudo apt autoclean && sudo apt autoremove
            
                    
    
    Copied

3. Information about the golang-github-willf-bloom-dev package on Kali Linux

Package: golang-github-willf-bloom-dev
Source: golang-github-willf-bloom
Version: 3.3.1-1
Installed-Size: 56
Maintainer: Debian Go Packaging Team
Architecture: all
Depends: golang-github-bits-and-blooms-bitset-dev
Size: 12516
SHA256: b57d482f17389511d8317071171766ca6d0d96d82c0b0428ec53fb6c8b4621ec
SHA1: a3fd7f8de5385feedf11058570d1c5663fc3187b
MD5sum: 6f0f8c9c6058e349a15c7c3afe80bca1
Description: Go package implementing Bloom filters
A Bloom filter is a representation of a set of n items, where the main
requirement is to make membership queries; i.e., whether an item is a
member of a set.
.
A Bloom filter has two parameters: m, a maximum size (typically a
reasonably large multiple of the cardinality of the set to represent)
and k, the number of hashing functions on elements of the set. (The
actual hashing functions are important, too, but this is not a
parameter for this implementation). A Bloom filter is backed by a BitSet
(https://github.com/willf/bitset); a key is represented in the filter
by setting the bits at each value of the hashing functions (modulo
m). Set membership is done by testing whether the bits at each value of
the hashing functions (again, modulo m) are set. If so, the item is in
the set. If the item is actually in the set, a Bloom filter will never
fail (the true positive rate is 1.0); but it is susceptible to false
positives. The art is to choose k and m correctly.
.
In this implementation, the hashing functions used is murmurhash
(github.com/spaolacci/murmur3), a non-cryptographic hashing function.
Description-md5:
Homepage: https://github.com/willf/bloom
Section: golang
Priority: optional
Filename: pool/main/g/golang-github-willf-bloom/golang-github-willf-bloom-dev_3.3.1-1_all.deb