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Solves in O(mn) for now.\r\n\r\n# NOTE: HEAVILY A WORK IN PROGRESS. Subject to change or breaking. NOT STABLE.\r\n\r\n## Use\r\n`npm install @autumnrowan/levensort`\r\n\r\nThen, require the package\r\n\r\n```js\r\nconst { levenshtein, levensearch } = require(\"@autumnrowan/levensort\");\r\n\r\nconst database = [\"julius caeser\", \"julia\", \"july\", \"orange julius\"];\r\n\r\nconst search_results = levensearch(database, \"julio\", 100, 6);\r\n\r\nconsole.log(search_results);\r\n```\r\n\r\n### Output\r\n```js\r\n[\r\n    { value: 'julia', score: 1},\r\n    { value: 'july', score: 2}, \r\n]\r\n```\r\n\r\n## Docs\r\n`levenshtein()` - takes two arguments, `a` (target) `b` (source) as strings.\r\n\r\n`levensearch()` - `arr` array to search `source` source string `limit` limit results `maxTolerance` max distance","readmeFilename":"README.md","description":"A basic Wagner-Fischer implementation of the Levenshtein / Minimum Edit Distance algorithm. Solves in O(mn) for now."}