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"js-levenshtein-1.1.6.tgz": { "url": "https://registry.npmjs.org/js-levenshtein/-/js-levenshtein-1.1.6.tgz", "sha": "c6cee58eb3550372df8deb85fad5ce66ce01d59d", "registry": "npmjs" } }, "_attachments": { "js-levenshtein-1.1.4.tgz": { "shasum": "3a56e3cbf589ca0081eb22cd9ba0b1290a16d26e" } }, "_rev": "2-5a0a52760156e247", "_id": "js-levenshtein", "readme": "# js-levenshtein [![Build Status](https://travis-ci.org/gustf/js-levenshtein.svg?branch=master)](https://travis-ci.org/gustf/js-levenshtein)\n\nA very efficient JS implementation calculating the Levenshtein distance, i.e. the difference between two strings.\n\nBased on Wagner-Fischer dynamic programming algorithm, optimized for speed and memory\n - use a single distance vector instead of a matrix\n - loop unrolling on the outer loop\n - remove common prefixes/postfixes from the calculation\n - minimize the number of comparisons\n \n## Install\n\n```\n$ npm install --save js-levenshtein\n```\n\n\n## Usage\n\n```js\nconst levenshtein = require('js-levenshtein');\n\nlevenshtein('kitten', 'sitting');\n//=> 3\n```\n\n\n## Benchmark\n\n```\n$ npm run bench\n \n 50 paragraphs, length max=500 min=240 avr=372.5\n 162 op/s » js-levenshtein\n 98 op/s » talisman\n 94 op/s » levenshtein-edit-distance\n 85 op/s » leven\n 39 op/s » fast-levenshtein\n\n 100 sentences, length max=170 min=6 avr=57.5\n 3,076 op/s » js-levenshtein\n 2,024 op/s » talisman\n 1,817 op/s » levenshtein-edit-distance\n 1,633 op/s » leven\n 800 op/s » fast-levenshtein\n\n 2000 words, length max=20 min=3 avr=9.5\n 3,119 op/s » js-levenshtein\n 2,416 op/s » talisman\n 2,141 op/s » levenshtein-edit-distance\n 1,855 op/s » leven\n 1,260 op/s » fast-levenshtein\n```\n\nBenchmarks was performed with node v8.12.0 on a MacBook Pro 15\", 2.9 GHz Intel Core i9\n\n## License\n\nMIT © Gustaf Andersson" }