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A fast and memory efficient implementation of aho-corasick algorithm based on double-array trie (cedar), supports visualizing structure via graphviz.

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ahocorasick

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Package ahocorasick implementes fast, compact and low memory used aho-corasick algorithm based on double-array trie. and also supports visualizing inner data structures by graphviz

cedar-go is a Golang port of cedar which is written in C++ by Naoki Yoshinaga. cedar-go currently implements the reduced verion of cedar. This package is not thread safe if there is one goroutine doing insertions or deletions.

Visualize

Install graphviz

# for mac os
brew install graphviz
# for ubuntu
sudo apt-get install graphviz

Dump structure in golang

m := cedar.NewMatcher()
m.Insert...
m.Compile...
// dump trie graph in double array trie
m.Cedar().DumpGraph("trie.gv")
// dump aho-corasick dfa graph in double array trie
m.DumpGraph("dfa.gv")

Generate png

dot -Tpng -o out.png trie.gv
# example: words {"she", "he", "her", "hers"}
  • trie

GitHub

  • aho-corasick

GitHub

Install

go get github.com/iohub/ahocorasick

Usage

  • aho-corasick
package main

import (
	"fmt"

	"github.com/iohub/ahocorasick"
)

func main() {
	fmt.Printf("\ntesting in simple case...\n")
	m := cedar.NewMatcher()
	words := []string{
		"she", "he", "her", "hers",
	}
	for i, word := range words {
		m.Insert([]byte(word), i)
	}
	// visualize trie 
	m.Cedar().DumpGraph("trie.gv")
	m.Compile()
	// visualize aho-corasick
	m.DumpGraph("dfa.gv")
	seq := []byte("hershertongher")
	fmt.Printf("searching %s\n", string(seq))
        resp := m.Match(seq)
        for resp.HasNext() {
            items := resp.NextMatchItem(seq)
            for _, itr := range items {
                key := m.Key(seq, itr)
                fmt.Printf("key:%s value:%d\n", key, itr.Value.(int))
            }
        }
	// release buffer to sync.Pool
	resp.Release()
}

​ output

testing in simple case...
searching hershertongher
key:he value:1
key:her value:2
key:hers value:3
key:he value:1
key:she value:0
key:her value:2
key:he value:1
key:her value:2
  • trie
package main

import (
	"fmt"

	"github.com/iohub/ahocorasick"
)

func main() {
	fmt.Printf("\ntesting int float32 value...\n")
	cd := NewCedar()
	words := []string{
		"she", "hers", "her", "he",
	}
	for i, word := range words {
		v := float32(i) + 1.880001
		cd.Insert([]byte(word), v)
	}
	ids := cd.PrefixMatch([]byte("hers"), 0)
	for _, id := range ids {
		k, _ := cd.Key(id)
		v, _ := cd.Get(k)
		fmt.Printf("key:%s val:%f\n", string(k), v.(float32))
	} 
}

​ output

testing int float32 value...
key:he val:4.880001
key:her val:3.880001
key:hers val:2.880001

Chinese words segment demo

Build demo test

go test -run TestMatcher

demo output

Searching 一丁点C++的T桖中华人民共和国人民解放军军队看守南京长江大桥

key: value:7
key:一丁 value:17
key: value:3317
key:一丁点 value:19
key:丁点 value:3519
key: value:214913
key:C++ value:5
key: value:233716
key: value:13425
key:中华 value:13663
key: value:63497
key:华人 value:63545
key: value:25372
key:中华人民 value:13667
key:人民 value:25881
key: value:195603
key:中华人民共和国 value:13668
key:人民共和国 value:25891
key:共和国 value:44163
key: value:88227
key:国人 value:88295
key: value:25372
key:人民 value:25881
key: value:195603
key: value:287247
key:解放 value:287374
key: value:160645
key:人民解放军 value:25927
key:解放军 value:287381
key: value:46587
key:军军 value:46669
key: value:46587
key:军队 value:46885
key: value:323587
key: value:236540
key:看守 value:236604
key: value:108752
key: value:64826
key:南京 value:64860
key: value:24978
key: value:321363
key:长江 value:321685
key: value:198725
key:南京长江大桥 value:64899
key:长江大桥 value:321699
key:大桥 value:98737
key: value:187704
PASS
ok  	github.com/iohub/ahocorasick	0.402s

Benchmark

ahocorasick golang implementation: cloudflare anknown iohub

image

How to run benchmark

git clone https://github.com/iohub/ahocorasick
cd benchmark
go get -u -v
go build .
./benchmark

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A fast and memory efficient implementation of aho-corasick algorithm based on double-array trie (cedar), supports visualizing structure via graphviz.

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