How to Install and Uninstall ghc-tf-random.x86_64 Package on Fedora 34
Last updated: November 27,2024
1. Install "ghc-tf-random.x86_64" package
This is a short guide on how to install ghc-tf-random.x86_64 on Fedora 34
$
sudo dnf update
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$
sudo dnf install
ghc-tf-random.x86_64
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2. Uninstall "ghc-tf-random.x86_64" package
Learn how to uninstall ghc-tf-random.x86_64 on Fedora 34:
$
sudo dnf remove
ghc-tf-random.x86_64
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$
sudo dnf autoremove
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3. Information about the ghc-tf-random.x86_64 package on Fedora 34
Last metadata expiration check: 1:13:08 ago on Tue Sep 6 14:10:38 2022.
Available Packages
Name : ghc-tf-random
Version : 0.5
Release : 21.fc34
Architecture : x86_64
Size : 47 k
Source : ghc-tf-random-0.5-21.fc34.src.rpm
Repository : fedora
Summary : High-quality splittable pseudorandom number generator
URL : https://hackage.haskell.org/package/tf-random
License : BSD and Public Domain
Description : This package contains an implementation of a high-quality splittable
: pseudorandom number generator. The generator is based on a cryptographic hash
: function built on top of the ThreeFish block cipher. See the paper /Splittable
: Pseudorandom Number Generators Using Cryptographic Hashing/ by Claessen, Pałka
: for details and the rationale of the design.
:
: The package provides the following:
:
: * A splittable PRNG that implements the standard 'System.Random.RandomGen'
: class.
:
: * The generator also implements an alternative version of the
: 'System.Random.TF.Gen.RandomGen' class (exported from "System.Random.TF.Gen"),
: which requires the generator to return pseudorandom integers from the full
: 32-bit range, and contains an n-way split function.
:
: * An alternative version of the 'Random' class is provided, which is linked to
: the new 'RandomGen' class, together with 'Random' instances for some integral
: types.
:
: * Two functions for initialising the generator with a non-deterministic seed:
: one using the system time, and one using the '/dev/urandom' UNIX special file.
:
: The package uses an adapted version of the reference C implementation of
: ThreeFish from the reference package of the Skein hash function
: (), originally written by Doug Whiting.
:
: Please note that even though the generator provides very high-quality
: pseudorandom numbers, it has not been designed with cryptographic applications
: in mind.
Available Packages
Name : ghc-tf-random
Version : 0.5
Release : 21.fc34
Architecture : x86_64
Size : 47 k
Source : ghc-tf-random-0.5-21.fc34.src.rpm
Repository : fedora
Summary : High-quality splittable pseudorandom number generator
URL : https://hackage.haskell.org/package/tf-random
License : BSD and Public Domain
Description : This package contains an implementation of a high-quality splittable
: pseudorandom number generator. The generator is based on a cryptographic hash
: function built on top of the ThreeFish block cipher. See the paper /Splittable
: Pseudorandom Number Generators Using Cryptographic Hashing/ by Claessen, Pałka
: for details and the rationale of the design.
:
: The package provides the following:
:
: * A splittable PRNG that implements the standard 'System.Random.RandomGen'
: class.
:
: * The generator also implements an alternative version of the
: 'System.Random.TF.Gen.RandomGen' class (exported from "System.Random.TF.Gen"),
: which requires the generator to return pseudorandom integers from the full
: 32-bit range, and contains an n-way split function.
:
: * An alternative version of the 'Random' class is provided, which is linked to
: the new 'RandomGen' class, together with 'Random' instances for some integral
: types.
:
: * Two functions for initialising the generator with a non-deterministic seed:
: one using the system time, and one using the '/dev/urandom' UNIX special file.
:
: The package uses an adapted version of the reference C implementation of
: ThreeFish from the reference package of the Skein hash function
: (
:
: Please note that even though the generator provides very high-quality
: pseudorandom numbers, it has not been designed with cryptographic applications
: in mind.