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Literate Haskell support for Markdown Documentation is here: https://github.com/sol/markdown-unlit#readme
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microlens + all batteries included (best for apps) This package exports a module which is the recommended starting point for using microlens if you aren't trying to keep your dependencies minimal. By importing Lens.Micro.Platform you get all functions and instances from microlens, microlens-th, microlens-mtl, microlens-ghc, as well as instances for Vector, Text, and HashMap. The minor and major versions of microlens-platform are incremented whenever the minor and major versions of any other microlens package are incremented, so you can depend on the exact version of microlens-platform without specifying the version of microlens (microlens-mtl, etc) you need. This package is a part of the microlens family; see the readme on Github.
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Type classes for mapping, folding, and traversing monomorphic containers Please see the README at https://www.stackage.org/package/mono-traversable
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POSIX network database (
) API This package provides Haskell bindings to the the POSIX network database (netdb.h) API. Relationship to the network package
The network package version 2.* series provides Network.BSD but it is removed starting with network version 3.0. This package provides the Network.BSD module split off from the network package. If in addition to the network's modules also Network.BSD is necessary, add network-bsd to your dependencies like so:library build-depends: network >= 2.7 && < 3.2 , network-bsd >= 2.7 && < 2.9
I.e. you can control the version of the network package independently. NOTE: Starting with network-bsd-2.8.1.0 the APIs of network and network-bsd evolve differently, and consequently the versioning doesn't match up anymore! Moreover, also starting with version network-bsd-2.8.1.0 this package requires network >= 3 in order to avoid module name clashes with network < 3's Network.BSD module. However, network-bsd-2.7.0.0 and network-bsd-2.8.0.0 passes thru the Network.BSD module from network-2.7.* and network-2.8.* respectively in a non-clashing way via Cabal's reexported-modules feature while ensuring a well-defined API versioning of the observable API of network-bsd. This is why the example above supporting a wide range of network versions works by including version 2.7.0.0 in the required version range of network-bsd. -
Lightweight package providing commonly useful parser combinators Lightweight package providing commonly useful parser combinators.
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Parsing combinators This library provides convenient combinators for working with and building parsing combinator libraries. Given a few simple instances, e.g. for the class Text.Parser.Combinators.Parsing in Text.Parser.Combinators.Parsing you get access to a large number of canned definitions. Instances exist for the parsers provided by parsec, attoparsec and base’s Text.Read.
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Components of paths. Hackage documentation generation is not reliable. For up to date documentation, please see: http://www.stackage.org/package/path-pieces.
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Mid-Level PostgreSQL client library Mid-Level PostgreSQL client library, forked from mysql-simple.
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Automatic derivation of querying functions for servant This library lets you derive automatically Haskell functions that let you query each endpoint of a servant webservice. . See the client section of the tutorial. . CHANGELOG
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Fast Splittable PRNG Pure Haskell implementation of SplitMix described in Guy L. Steele, Jr., Doug Lea, and Christine H. Flood. 2014. Fast splittable pseudorandom number generators. In Proceedings of the 2014 ACM International Conference on Object Oriented Programming Systems Languages & Applications (OOPSLA '14). ACM, New York, NY, USA, 453-472. DOI: https://doi.org/10.1145/2660193.2660195 The paper describes a new algorithm SplitMix for splittable pseudorandom number generator that is quite fast: 9 64 bit arithmetic/logical operations per 64 bits generated. SplitMix is tested with two standard statistical test suites (DieHarder and TestU01, this implementation only using the former) and it appears to be adequate for "everyday" use, such as Monte Carlo algorithms and randomized data structures where speed is important. In particular, it should not be used for cryptographic or security applications, because generated sequences of pseudorandom values are too predictable (the mixing functions are easily inverted, and two successive outputs suffice to reconstruct the internal state).