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matching","reverse match","geofencing"],"repository":{"url":"git://github.com/kuzzleio/koncorde.git","type":"git"},"description":"Supersonic reverse matching engine","maintainers":[{"name":"kuzzle-ricky","email":"nriquelmebareiro@kuzzle.io"},{"name":"eric-kuzzle","email":"etrousset@kuzzle.io"},{"name":"abouthinon","email":"abouthinon@kuzzle.io"}],"readme":"[![Codecov](http://codecov.io/github/kuzzleio/koncorde/coverage.svg?branch=master)](http://codecov.io/github/kuzzleio/koncorde?branch=master)\n[![Code Quality: Javascript](https://img.shields.io/lgtm/grade/javascript/g/kuzzleio/koncorde.svg?logo=lgtm&logoWidth=18)](https://lgtm.com/projects/g/kuzzleio/koncorde/context:javascript)\n[![Total Alerts](https://img.shields.io/lgtm/alerts/g/kuzzleio/koncorde.svg?logo=lgtm&logoWidth=18)](https://lgtm.com/projects/g/kuzzleio/koncorde/alerts)\n\n# Koncorde\n\nThis module is a reverse-search engine.\n\nInstead of indexing data and searching for them using filters, Koncorde does the opposite: it indexes search filters, and returns the corresponding ones when presented with data.\n\n* an arbitrary large number of filters can be registered and indexed;\n* whenever data are submitted to Koncorde, it returns the list of indexed filters matching them;\n* Koncorde's [filter syntax](https://github.com/kuzzleio/koncorde/wiki/Filter-Syntax) supports a variety of different matchers, and ways to combine them.\n\nKoncorde can be used in a variety of ways. For instance:\n\n* as a base of a notification system, where indexed filters are used as user subscriptions: Koncorde tells which JSON objects verify what subscriptions, making it easy to send events to listening users; \n* to verify if JSON objects comply to filters used as validation rules.\n\nCheck our [full documentation](https://github.com/kuzzleio/koncorde/wiki) to know more about Koncorde's API, filter syntax, and more.\n\n\n# Quick start example\n\nIn the following example, we'll listen to objects containing a `position` property, describing a geopoint. We want that geopoint to be 500 meters around a pre-defined starting position.\n\nThis can be described by the following Koncorde filter:\n\n```json\n{\n    \"geoDistance\": {\n        \"position\": {\n            \"lat\": 43.6073913,\n            \"lon\": 3.9109057\n        },\n        \"distance\": \"500m\"\n    }\n}\n```\n\nAll you need to do now is to register this filter to the engine, and use it to test data:\n\n```js\nimport { Koncorde } from 'koncorde';\n\nconst engine = new Koncorde();\n\nconst filter = {\n    geoDistance: {\n        position: {\n            lat: 43.6073913,\n            lon: 3.9109057\n        },\n        distance: \"500m\"\n    }\n};\n\nconst filterId = engine.register(filter);\n\n// Filter Identifiers are seeded. Given the same seed (to be provided to the\n// constructor), then the filter IDs stay stable.\nconsole.log(`Filter identifier: ${filterId}`);\n\n// No match found, returns an empty array (distance is greater than 500m)\nconsole.log(engine.test({ position: { lat: 43.6073913, lon: 5.7 } }));\n\n// Point within the filter's scope: returns the list of matched filters\n// Here we registered just one of them, so the array contains only 1 filter ID\nconsole.log(engine.test({ position: { lat: 43.608, lon: 3.905 } }));\n\n// No match found, returns an empty array \n// (the geopoint in the provided data is not stored in the tested field)\nconsole.log(engine.test({ not_position: { lat: 43.608, lon: 3.905 } }));\n```\n\n# Install\n\nThis library is compatible with Node.js version 12.x or higher.\nBoth a C and a C++ compilers are needed to install its dependencies: Koncorde cannot be used in a browser.\n\nKoncorde is compatible with either Javascript or Typescript projects.\n\nTo install:\n\n```\nnpm install koncorde\n```\n\n\n## Benchmarks\n\nThe following results are obtained running `node benchmark.js` at the root of the projet.\n\n```\nFilter count per tested keyword: 10000\n\n> Benchmarking keyword: equals\n  Indexation: time = 0.255s, mem = +39MB\n  Matching x 10,320,209 ops/sec ±0.70% (95 runs sampled)\n  Filters removal: time = 0.018s\n\n> Benchmarking keyword: exists\n  Indexation: time = 0.285s, mem = +20MB\n  Matching x 5,047,932 ops/sec ±0.23% (97 runs sampled)\n  Filters removal: time = 0.021s\n\n> Benchmarking keyword: geoBoundingBox\n  Indexation: time = 0.685s, mem = +-8MB\n  Matching x 1,322,528 ops/sec ±0.52% (94 runs sampled)\n  Filters removal: time = 0.092s\n\n> Benchmarking keyword: geoDistance\n  Indexation: time = 1.052s, mem = +3MB\n  Matching x 1,656,882 ops/sec ±0.65% (96 runs sampled)\n  Filters removal: time = 0.094s\n\n> Benchmarking keyword: geoDistanceRange\n  Indexation: time = 1.551s, mem = +20MB\n  Matching x 1,344,257 ops/sec ±2.83% (90 runs sampled)\n  Filters removal: time = 0.101s\n\n> Benchmarking keyword: geoPolygon (5 vertices)\n  Indexation: time = 0.818s, mem = +-74MB\n  Matching x 112,091 ops/sec ±0.54% (97 runs sampled)\n  Filters removal: time = 0.098s\n\n> Benchmarking keyword: in (5 random values)\n  Indexation: time = 0.974s, mem = +90MB\n  Matching x 3,579,507 ops/sec ±2.93% (92 runs sampled)\n  Filters removal: time = 0.058s\n\n> Benchmarking keyword: range (random bounds)\n  Indexation: time = 0.276s, mem = +-72MB\n  Matching x 122,311 ops/sec ±1.28% (96 runs sampled)\n  Filters removal: time = 0.074s\n```\n\n_(results obtained with node v16.2.0)_\n","readmeFilename":"README.md","users":{"chirag8642":true}}