Fuzzy finding algorithm
npm install fzy.js
!Build Size
!0 Dependencies
``
npm i --save fzy.js
score(needle, haystack)
` javascript
var fzy = require('fzy.js')
fzy.score("amuser", "app/models/user.rb") // 5.595
fzy.score("amuser", "app/models/customer.rb") // 3.655
`
positions(needle, haystack)
` javascript`
fzy.positions("amuser", "app/models/user.rb") // [ 0, 4, 11, 12, 13, 14 ]
fzy.positions("amuser", "app/models/customer.rb") // [ 0, 4, 12, 13, 17, 18 ]
NB: score and positions must be called with matching needle and haystack,
doing otherwise is undefined. The caller needs to check that there is a match.
` javascript
var { sortBy, escapeRegExp } = require("lodash");
var fzy = require("fzy.js");
// List of candidate strings
// Often generated by something like require("glob")("*/")
var list = [
"app/models/user.rb",
"app/models/order.rb",
"app/models/customer.rb"
];
// Usually this is input from the user
var query = "amuser";
// fzy.js doesn't implement filtering, only scoring, but it is simple enough with a regexp
var regex = new RegExp(query.split('').map(escapeRegExp).join(".*"));
list = list.filter((s) => s.match(regex));
// Sort by fzy's scoring, descending (higher scores are better matches)
list = sortBy(list, (s) => -fzy.score(query, s));
// Select only the first 10 results
list.slice(0, 10);
// Print out our results with matched positions
list.forEach((s) => {
var padded = "";
var p = fzy.positions(query, s);
for(var i = 0; i < query.length; i++) {
padded = padded.padEnd(p[i], ' ') + query[i];
}
console.log(s);
console.log(padded);
console.log("");
});
// Output:
//
// app/models/user.rb
// a m user
//
// app/models/customer.rb
// a m us er
``