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package snap-blaze

blaze-html integration for Snap blaze-html integration for Snap
package snowflake

A loose port of Twitter Snowflake to Haskell. Generates arbitrary precision, unique, time-sortable identifiers. A loose port of Twitter Snowflake to Haskell. Generates arbitrary precision, unique, time-sortable identifiers.
package sort

A Haskell sorting toolkit A library of general-purpose sorting utilities.
package sphinx

Haskell bindings to the Sphinx full-text searching daemon. Haskell bindings to the Sphinx full-text searching daemon. Compatible with Sphinx version 2.0
package splice

Cross-platform Socket to Socket Data Splicing A library that implements most efficient socket to socket data transfer loops for proxy servers on all operating systems. On GNU/Linux, it exports the zero-copy system call c_splice() (http://en.wikipedia.org/wiki/Splice_(system_call)#Requirements) in System.IO.Splice.Linux. On other operating systems, it only exports a portable Haskell implementation. A unified sockets API for all operating systems is available in Network.Socket.Splice.
- Version Scheme Major-R-ewrite . New-F-unctionality . I-mprovementAndBugFixes . P-ackagingOnly
- PackagingOnly changes are made for quality assurance reasons.
package stateref

Abstraction for things that work like IORef. A collection of type-classes generalizing the read/write/modify operations for stateful variables provided by things like IORef, TVar, &c. Note that The interface has changed a bit from the 0.2.* version. "*Ref" functions are now called "*Reference" and new "*Ref" function exist with simpler signatures. The new Ref existential type provides a convenient monad-indexed reference type, and the HasRef class indicates monads for which there is a default reference type for every referent.
package statistics-linreg

Linear regression between two samples, based on the 'statistics' package. Provides functions to perform a linear regression between 2 samples, see the documentation of the linearRegression functions. This library is based on the statistics package.
- 0.3: you can now use all functions on any instance of the Vector class (not just unboxed vectors).
- 0.2.4: added distribution estimations for standard regression parameters.
- 0.2.3: added robust-fit support.
- 0.2.2: added the Total-Least-Squares version and made some refactoring to eliminate code duplication
- 0.2.1: added the r-squared version and improved the performances.
Code sample:
```
import qualified Data.Vector.Unboxed as U

test :: Int -> IO ()
test k = do
let n = 10000000
let a = k*n + 1
let b = (k+1)*n
let xs = U.fromList [a..b]
let ys = U.map (\x -> x*100 + 2000) xs
-- thus 100 and 2000 are the alpha and beta we want
putStrLn "linearRegression:"
print $ linearRegression xs ys
```
The r-squared and Total-Least-Squares versions work the same way.
package stm-extras

Extra STM functions Please see README.md
package stm-split

TMVars, TVars and TChans with distinguished input and output side Transactional MVars, Vars and Channels with distinguished input and output side. When threads communicate via a TMVar, a TVar or a TChan there are often clearly defined roles, which thread is the sender and which one is receiver. We provide wrappers around the standard concurrency communication channels that make the distinction clear and type safe. For example, if a function has a parameter of type TChan.In then it is sure that it will only write to that channel. Additionally if the compiler warns about an unused TChan.Out that was created by TChan.new then you know that the receiver part of your communication is missing. See also package concurrent-split for non-transactional communication. This package follows the same idea as chan-split but is strictly Haskell 98.
package streaming-wai

Streaming Wai utilities Please see README.md

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