alfred-margaret: Fast Aho-Corasick string searching

[ bsd3, data, library, program, text ] [ Propose Tags ]

An efficient implementation of the Aho-Corasick string searching algorithm.

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Dependencies aeson (>=1.4.2 && <3), alfred-margaret, base (>=4.7 && <5), containers (>=0.6 && <0.7), deepseq (>=1.4 && <1.5), hashable (>= && <1.5), primitive (>=0.6.4 && <0.8), text (>=2.0 && <2.1), unordered-containers (>=0.2.9 && <0.3), vector (>=0.12 && <0.13) [details]
License BSD-3-Clause
Copyright 2020 Channable
Author The Alfred-Margaret authors
Maintainer Ruud van Asseldonk <>, Fabian Thorand <>
Category Data, Text
Home page
Source repo head: git clone
Uploaded by fatho at 2022-08-31T11:20:48Z
Reverse Dependencies 1 direct, 0 indirect [details]
Executables dump-automaton
Downloads 724 total (23 in the last 30 days)
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Status Docs uploaded by user
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Readme for alfred-margaret-

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Alfred–Margaret is a fast implementation of the Aho–Corasick string searching algorithm in Haskell. It powers many string-related operations in Channable.

The library is designed to work with the text package. It matches directly on the internal UTF-16 representation of Text for efficiency. See the announcement blog post for a deeper dive into Aho–Corasick, and the optimizations that make this library fast.

Alfred–Margaret is named after Alfred Aho and Margaret Corasick.


Running time to count all matches, in a real-world data set, comparing a Java implementation and a Rust implementation against Alfred–Margaret, and against memcopy to establish a lower bound:

For the full details of this benchmark, see our announcement blog post, which includes more details about the data set, the benchmark setup, and a few things to keep in mind when interpreting this graph.


If you are using LLVM instead of the GHC backend, make sure to compare different versions. Using LLVM 9 instead of LLVM 12 with GHC 8.10.7 made a significant dent in benchmark times. For more information, see this issue.


Check if a string contains one of the needles:

import qualified Data.Text.AhoCorasick.Automaton as Aho
import qualified Data.Text.AhoCorasick.Searcher as Searcher

searcher = Aho.CaseSensitive ["tshirt", "shirts", "shorts"]

Searcher.containsAny searcher "short tshirts"
> True

Searcher.containsAny searcher "long shirt"
> False

Searcher.containsAny searcher "Short TSHIRTS"
> False

searcher' = Aho.IgnoreCase ["tshirt", "shirts", "shorts"]

Searcher.containsAny searcher' "Short TSHIRTS"
> True

Sequentially replace many needles:

import Data.Text.AhoCorasick.Automaton (CaseSensitivity (..))
import qualified Data.Text.AhoCorasick.Replacer as Replacer

replacer = CaseSensitive [("tshirt", "banana"), ("shirt", "pear")] replacer "tshirts for sale"
> "bananas for sale" replacer "tshirts and shirts for sale"
> "bananas and pears for sale" replacer "sweatshirts and shirtshirts"
> "sweabananas and shirbananas" replacer "sweatshirts and shirttshirts"
> "sweabananas and pearbananas"

Get all matches, possibly overlapping:

import qualified Data.Text.AhoCorasick.Automaton as Aho

pairNeedleWithSelf text = (Aho.unpackUtf16 text, text)
automaton = $ fmap pairNeedleWithSelf ["tshirt", "shirts", "shorts"]
allMatches = Aho.runText [] (\matches match -> Aho.Step (match : matches))

allMatches automaton "short tshirts"
> [ Match {matchPos = CodeUnitIndex 13, matchValue = "shirts"}
> , Match {matchPos = CodeUnitIndex 12, matchValue = "tshirt"}
> ]

allMatches automaton "sweatshirts and shirtshirts"
> [ Match {matchPos = CodeUnitIndex 27, matchValue = "shirts"}
> , Match {matchPos = CodeUnitIndex 26, matchValue = "tshirt"}
> , Match {matchPos = CodeUnitIndex 22, matchValue = "shirts"}
> , Match {matchPos = CodeUnitIndex 11, matchValue = "shirts"}
> , Match {matchPos = CodeUnitIndex 10, matchValue = "tshirt"}
> ]


Alfred–Margaret is licensed under the 3-clause BSD license.