katydid: A haskell implementation of Katydid

[ bsd3, data, library, program ] [ Propose Tags ] [ Report a vulnerability ]
Versions [RSS] 0.1.0.0, 0.1.1.0, 0.2.0.1, 0.3.0.0, 0.3.0.1, 0.3.1.0, 0.4.0.1, 0.4.0.2
Change log Changelog.md
Dependencies base (>=4.7 && <5), bytestring, containers, deepseq, either, extra, hxt, ilist, json, katydid, mtl, parsec, regex-tdfa, text, transformers [details]
License BSD-3-Clause
Copyright Walter Schulze
Author Walter Schulze
Maintainer awalterschulze@gmail.com
Category Data
Home page https://github.com/katydid/katydid-haskell#readme
Bug tracker https://github.com/katydid/katydid-haskell/issues
Source repo head: git clone https://github.com/katydid/katydid-haskell
Uploaded by awalterschulze at 2018-09-10T09:28:05Z
Distributions
Executables katydid-exe
Downloads 4359 total (27 in the last 30 days)
Rating (no votes yet) [estimated by Bayesian average]
Your Rating
  • λ
  • λ
  • λ
Status Docs available [build log]
Last success reported on 2018-09-10 [all 1 reports]

Readme for katydid-0.4.0.2

[back to package description]

Katydid

Build Status

A Haskell implementation of Katydid.

Katydid Logo

This includes:

Documentation for katydid

Documentation for katydid-haskell

Documentation for katydid-haskell/Relapse

All JSON and XML tests from the language agnostic test suite [passes].

Hackage

Example

Validating a single structure can be done using the validate function:

validate :: Tree t => Grammar -> [t] -> Bool

, where a tree is a class in the Parsers module:

class Tree a where
    getLabel :: a -> Label
    getChildren :: a -> [a]

Here is an example that validates a single JSON tree:

main = either 
    (\err -> putStrLn $ "error:" ++ err) 
    (\valid -> if valid 
        then putStrLn "dragons exist" 
        else putStrLn "dragons are fictional"
    ) $
    Relapse.validate <$> 
        Relapse.parse ".DragonsExist == true" <*> 
        Json.decodeJSON "{\"DragonsExist\": false}"

Efficiency

If you want to validate multiple trees using the same grammar then the filter function does some internal memoization, which makes a huge difference.

filter :: Tree t => Grammar -> [[t]] -> [[t]]

User Defined Functions

If you want to create your own extra functions for operating on the leaves, then you can inject them into the parse function:

main = either
    (\err -> putStrLn $ "error:" ++ err)
    (\valid -> if valid
        then putStrLn "prime birthday !!!"
        else putStrLn "JOMO"
    ) $
    Relapse.validate <$>
        Relapse.parseWithUDFs userLib ".Survived->isPrime($int)" <*>
        Json.decodeJSON "{\"Survived\": 104743}"

Defining your own user library to inject is easy. The Expr library provides many useful helper functions:

import Data.Numbers.Primes (isPrime)
import Data.Katydid.Relapse.Expr

userLib :: String -> [AnyExpr] -> Either String AnyExpr
userLib "isPrime" args = mkIsPrime args
userLib n _ = throwError $ "undefined function: " ++ n

mkIsPrime :: [AnyExpr] -> Either String AnyExpr
mkIsPrime args = do {
    arg <- assertArgs1 "isPrime" args;
    mkBoolExpr . isPrimeExpr <$> assertInt arg;
}

isPrimeExpr :: Integral a => Expr a -> Expr Bool
isPrimeExpr numExpr = trimBool Expr {
    desc = mkDesc "isPrime" [desc numExpr]
    , eval = \fieldValue -> isPrime <$> eval numExpr fieldValue
}

Roadmap

  • Protobuf parser
  • Profile and Optimize (bring up to par with Go version)
  • Typed DSL (Combinator)