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Example\n\n```js\nimport { createIndex, indexAdd } from \"ndx\";\nimport { indexQuery } from \"ndx/query\";\n\nconst termFilter = (term) => term.toLowerCase();\n\nfunction createDocumentIndex(fields) {\n  // `createIndex()` creates an index data structure.\n  // First argument specifies how many different fields we want to index.\n  const index = createIndex(\n    fields.length,\n    // Tokenizer is a function that breaks text into words, phrases, symbols,\n    // or other meaningful elements called tokens.\n    (s) => s.split(\" \"),\n    // Filter is a function that processes tokens and returns terms, terms are\n    // used in Inverted Index to index documents.\n    termFilter,\n  );\n  // `fieldGetters` is an array with functions that will be used to retrieve\n  // data from different fields.\n  const fieldGetters = fields.map((f) => (doc) => doc[f.name]);\n  // `fieldBoostFactors` is an array of boost factors for each field, in this\n  // example all fields will have identical weight.\n  const fieldBoostFactors = fields.map(() => 1);\n\n  return {\n    index,\n    // `add()` will add documents to the index.\n    add(doc) {\n      indexAdd(\n        index,\n        fieldGetters,\n        // Docum  ent key, it can be an unique document id or a refernce to a\n        // document if you want to store all documents in memory.\n        doc.id,\n        // Document.\n        doc,\n      );\n    },\n    // `remove()` will remove documents from the index.\n    remove(id) {\n      // When document is removed we are just marking document id as being\n      // removed. Index data structure still contains references to the removed\n      // document.\n      indexRemove(index, removed, id);\n      if (removed.size > 10) {\n        // `indexVacuum()` removes all references to removed documents from the\n        // index.\n        indexVacuum(index, removed);\n      }\n    },\n\n    // `search()` will be used to perform queries.\n    search(q) {\n      return indexQuery(\n        index,\n        fieldBoostFactors,\n        // BM25 ranking function constants:\n        // BM25 k1 constant, controls non-linear term frequency normalization\n        // (saturation).\n        1.2,\n        // BM25 b constant, controls to what degree document length normalizes\n        // tf values.\n        0.75,\n        q,\n      );\n    }\n  };\n}\n\n// Create a document index that will index `content` field.\nconst index = createDocumentIndex([{ name: \"content\" }]);\n\nconst docs = [\n  {\n    \"id\": \"1\",\n    \"content\": \"Lorem ipsum dolor\",\n  },\n  {\n    \"id\": \"2\",\n    \"content\": \"Lorem ipsum\",\n  }\n];\n\n// Add documents to the index.\ndocs.forEach((d) => { index.add(d); });\n\n// Perform a search query.\nindex.search(\"Lorem\");\n// => [{ key: \"2\" , score: ... }, { key: \"1\", score: ... } ]\n//\n// document with an id `\"2\"` is ranked higher because it has a `\"content\"`\n// field with a less number of terms than document with an id `\"1\"`.\n\nindex.search(\"dolor\");\n// => [{ key: \"1\", score: ... }]\n```\n\n### Tokenizers and Filters\n\n`ndx` library doesn't provide any tokenizers or filters. There are other\nlibraries that implement tokenizers, for example\n[Natural](https://github.com/NaturalNode/natural/) has a good collection of\ntokenizers and stemmers.\n\n## License\n\n[MIT](http://opensource.org/licenses/MIT)\n","maintainers":[{"name":"localvoid","email":"localvoid@gmail.com"}],"time":{"modified":"2023-03-14T18:52:56.167Z","created":"2016-10-21T11:12:47.005Z","0.0.1":"2016-10-21T11:12:47.005Z","0.1.0":"2016-10-24T13:12:05.684Z","0.1.1":"2016-10-25T07:46:16.170Z","0.1.2":"2016-10-25T17:36:02.051Z","0.1.3":"2016-10-26T02:17:04.065Z","0.2.0":"2016-10-26T07:58:21.057Z","0.3.0":"2017-04-20T08:40:41.270Z","0.4.1":"2018-05-13T15:38:24.527Z","1.0.0-beta.0":"2019-01-10T12:32:02.981Z","1.0.0-beta.1":"2019-01-10T12:33:30.504Z","1.0.0-beta.2":"2019-01-17T10:53:29.117Z","1.0.0":"2019-02-04T06:49:45.140Z","1.0.1":"2019-02-04T06:52:59.949Z","1.0.2":"2019-06-07T00:18:49.353Z","2.0.0":"2023-03-08T15:47:17.007Z","2.0.1":"2023-03-14T18:52:56.093Z"},"homepage":"https://github.com/localvoid/ndx","keywords":["text","full-text","index","inverted-index","search","relevance"],"repository":{"type":"git","url":"git+https://github.com/localvoid/ndx.git"},"author":{"name":"Boris Kaul","email":"localvoid@gmail.com","url":"https://github.com/localvoid"},"bugs":{"url":"https://github.com/localvoid/ndx/issues"},"license":"MIT","readmeFilename":"README.md"}