The Trie Tree implementation in Go. It has flexible interface and works fast as Radix Tree implementation.

This is basically an implementation of the algorithm described in 簡単なトライ - LINE ENGINEERING. I really appreciate the amazing ideas and the clear and easy-to-understand explanation.

github.com/acomagu/trie/v2

Run make bench to run it locally. The latest benchmark result is here.

The task is to determine whether a string matches one of all Wikipedia titles.

The task is to answer which of all Wikipedia titles can be the longest prefix of a string.

(dghubble/trie and kkdai/radix don't have way to do.)

The task is to prepare Trie/Radix Tree with all of the Wikipedia titles.

The common preparation for each example:

import (
	"fmt"

	"github.com/acomagu/trie/v2"
)

keys := [][]byte{
	[]byte("ab"),
	[]byte("abc"),
	[]byte("abd"),
}
values := []int{1, 2, 3} // The type of value doesn't have to be int. Can be anything.
t := trie.New(keys, values)

New() takes keys and values as the arguments. values[i] is the value of the corresponding key, keys[i].

v, ok := t.Trace([]byte("abc")).Terminal()
fmt.Println(v, ok) // => 2 true

Playground

var v int
var match bool
for _, c := range []byte("abcxxx") {
	if t = t.TraceOne(c); t == nil {
		break
	}
	if vv, ok := t.Terminal(); ok {
		v = vv
		match = true
	}
}

fmt.Println(v, match) // => 2 true

Playground

No special function to get longest prefix because it can be implemented yourself easily using the existing methods.