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original maintainer doesn't support this package anymore, we forked it\nand maintain it for the needs of [Seald](https://www.seald.io).\n\n**Embedded persistent or in memory database for Node.js, Electron and browsers,\n100% JavaScript, no binary dependency**. API is a subset of MongoDB's and it's\n[plenty fast](#speed).\n\n## Installation\n\nModule name on npm is [`@seald-io/nedb`](https://www.npmjs.com/package/@seald-io/nedb).\n\n```\nnpm install @seald-io/nedb\n```\n\nThen to import, you just have to:\n\n```js\nconst Datastore = require('@seald-io/nedb')\n```\n\n## Documentation\nThe API is a subset of MongoDB's API (the most used operations).\n\nSince version [3.0.0](./CHANGELOG.md#300---2022-03-16), NeDB provides a Promise-based equivalent for each function\nwhich is suffixed with `Async`, for example `loadDatabaseAsync`.\n\nThe original callback-based interface is still available, fully retro-compatible\n(as far as the test suites can tell) and are a shim to this Promise-based\nversion.\n\nDon't hesitate to open an issue if it breaks something in your project.\n\nThe rest of the readme will only show the Promise-based API, the full\ndocumentation is available in the [`API.md`](./API.md) file at the root of the\nrepository. It is generated by running `npm run generateDocs:markdown`.\n\n* [Creating/loading a database](#creatingloading-a-database)\n* [Dropping a database](#dropping-a-database)\n* [Persistence](#persistence)\n* [Inserting documents](#inserting-documents)\n* [Finding documents](#finding-documents)\n  * [Basic Querying](#basic-querying)\n  * [Operators ($lt, $lte, $gt, $gte, $in, $nin, $ne, $exists, $regex)](#operators-lt-lte-gt-gte-in-nin-ne-stat-regex)\n  * [Array fields](#array-fields)\n  * [Logical operators $or, $and, $not, $where](#logical-operators-or-and-not-where)\n  * [Sorting and paginating](#sorting-and-paginating)\n  * [Projections](#projections)\n* [Counting documents](#counting-documents)\n* [Updating documents](#updating-documents)\n* [Removing documents](#removing-documents)\n* [Indexing](#indexing)\n* [Other environments](#other-environments)\n\n### Creating/loading a database\n\nYou can use NeDB as an in-memory only datastore or as a persistent datastore.\nOne datastore is the equivalent of a MongoDB collection. The constructor is used\nas follows [`new Datastore(options)` where `options` is an object](./API.md#new_Datastore_new).\n\nIf the Datastore is persistent (if you give it [`options.filename`](./API.md#Datastore+filename),\nyou'll need to load the database using [Datastore#loadDatabaseAsync](./API.md#Datastore+loadDatabaseAsync),\nor using [`options.autoload`](./API.md#Datastore+autoload).\n\n```javascript\n// Type 1: In-memory only datastore (no need to load the database)\nconst Datastore = require('@seald-io/nedb')\nconst db = new Datastore()\n\n// Type 2: Persistent datastore with manual loading\nconst Datastore = require('@seald-io/nedb')\nconst db = new Datastore({ filename: 'path/to/datafile' })\ntry {\n  await db.loadDatabaseAsync()\n} catch (error) {\n  // loading has failed\n}\n// loading has succeeded\n \n// Type 3: Persistent datastore with automatic loading\nconst Datastore = require('@seald-io/nedb')\nconst db = new Datastore({ filename: 'path/to/datafile', autoload: true }) // You can await db.autoloadPromise to catch a potential error when autoloading.\n// You can issue commands right away\n\n// Of course you can create multiple datastores if you need several\n// collections. In this case it's usually a good idea to use autoload for all collections.\ndb = {}\ndb.users = new Datastore('path/to/users.db')\ndb.robots = new Datastore('path/to/robots.db')\n\n// You need to load each database\nawait db.users.loadDatabaseAsync()\nawait db.robots.loadDatabaseAsync()\n```\n\n### Dropping a database\n\nSince v3.0.0, you can drop the database by using [`Datastore#dropDatabaseAsync`](./API.md#Datastore+dropDatabaseAsync):\n```js\nconst Datastore = require('@seald-io/nedb')\nconst db = new Datastore()\nawait d.insertAsync({ hello: 'world' })\nawait d.dropDatabaseAsync()\nassert.equal(d.getAllData().length, 0)\nassert.equal(await exists(testDb), false)\n```\n\nIt is not recommended to keep using an instance of Datastore when its database\nhas been dropped as it may have some unintended side effects.\n\n### Persistence\n\nUnder the hood, NeDB's [persistence](./API.md#Persistence) uses an append-only\nformat, meaning that all updates and deletes actually result in lines added at\nthe end of the datafile, for performance reasons. The database is automatically\ncompacted (i.e. put back in the one-line-per-document format) every time you\nload each database within your application.\n\n**Breaking change**: [since v3.0.0](./CHANGELOG.md#300---unreleased), calling methods of `yourDatabase.persistence`\nis deprecated. The same functions exists directly on the `Datastore`.\n\nYou can manually call the compaction function\nwith [`yourDatabase#compactDatafileAsync`](./API.md#Datastore+compactDatafileAsync).\n\nYou can also set automatic compaction at regular intervals\nwith [`yourDatabase#setAutocompactionInterval`](./API.md#Datastore+setAutocompactionInterval),\nand stop automatic compaction with [`yourDatabase#stopAutocompaction`](./API.md#Datastore+stopAutocompaction).\n\n### Inserting documents\n\nThe native types are `String`, `Number`, `Boolean`, `Date` and `null`. You can\nalso use arrays and subdocuments (objects). If a field is `undefined`, it will\nnot be saved (this is different from MongoDB which transforms `undefined`\nin `null`, something I find counter-intuitive).\n\nIf the document does not contain an `_id` field, NeDB will automatically\ngenerate one for you (a 16-characters alphanumerical string). The `_id` of a\ndocument, once set, cannot be modified.\n\nField names cannot start with '$' or contain the characters '.' and ','.\n\n```javascript\nconst doc = {\n  hello: 'world',\n  n: 5,\n  today: new Date(),\n  nedbIsAwesome: true,\n  notthere: null,\n  notToBeSaved: undefined,  // Will not be saved\n  fruits: ['apple', 'orange', 'pear'],\n  infos: { name: '@seald-io/nedb' }\n}\n\ntry {\n  const newDoc = await db.insertAsync(doc)\n  // newDoc is the newly inserted document, including its _id\n  // newDoc has no key called notToBeSaved since its value was undefined\n} catch (error) {\n  // if an error happens\n}\n```\n\nYou can also bulk-insert an array of documents. This operation is atomic,\nmeaning that if one insert fails due to a unique constraint being violated, all\nchanges are rolled back.\n\n```javascript\nconst newDocs = await db.insertAsync([{ a: 5 }, { a: 42 }])\n// Two documents were inserted in the database\n// newDocs is an array with these documents, augmented with their _id\n\n\n// If there is a unique constraint on field 'a', this will fail\ntry {\n  await db.insertAsync([{ a: 5 }, { a: 42 }, { a: 5 }])\n} catch (error) {\n  // err is a 'uniqueViolated' error\n  // The database was not modified\n}\n```\n\n### Finding documents\n\nUse `findAsync` to look for multiple documents matching you query, or `findOneAsync` to\nlook for one specific document. You can select documents based on field equality\nor use comparison operators (`$lt`, `$lte`, `$gt`, `$gte`, `$in`, `$nin`, `$ne`)\n. You can also use logical operators `$or`, `$and`, `$not` and `$where`. See\nbelow for the syntax.\n\nYou can use regular expressions in two ways: in basic querying in place of a\nstring, or with the `$regex` operator.\n\nYou can sort and paginate results using the cursor API (see below).\n\nYou can use standard projections to restrict the fields to appear in the\nresults (see below).\n\n#### Basic querying\n\nBasic querying means are looking for documents whose fields match the ones you\nspecify. You can use regular expression to match strings. You can use the dot\nnotation to navigate inside nested documents, arrays, arrays of subdocuments and\nto match a specific element of an array.\n\n```javascript\n// Let's say our datastore contains the following collection\n// { _id: 'id1', planet: 'Mars', system: 'solar', inhabited: false, satellites: ['Phobos', 'Deimos'] }\n// { _id: 'id2', planet: 'Earth', system: 'solar', inhabited: true, humans: { genders: 2, eyes: true } }\n// { _id: 'id3', planet: 'Jupiter', system: 'solar', inhabited: false }\n// { _id: 'id4', planet: 'Omicron Persei 8', system: 'futurama', inhabited: true, humans: { genders: 7 } }\n// { _id: 'id5', completeData: { planets: [ { name: 'Earth', number: 3 }, { name: 'Mars', number: 2 }, { name: 'Pluton', number: 9 } ] } }\n\n// Finding all planets in the solar system\nconst docs = await db.findAsync({ system: 'solar' })\n// docs is an array containing documents Mars, Earth, Jupiter\n// If no document is found, docs is equal to []\n\n\n// Finding all planets whose name contain the substring 'ar' using a regular expression\nconst docs = await db.findAsync({ planet: /ar/ })\n// docs contains Mars and Earth\n\n// Finding all inhabited planets in the solar system\nconst docs = await db.findAsync({ system: 'solar', inhabited: true })\n// docs is an array containing document Earth only\n\n// Use the dot-notation to match fields in subdocuments\nconst docs = await db.findAsync({ 'humans.genders': 2 })\n// docs contains Earth\n\n\n// Use the dot-notation to navigate arrays of subdocuments\nconst docs = await db.findAsync({ 'completeData.planets.name': 'Mars' })\n// docs contains document 5\n\nconst docs = await db.findAsync({ 'completeData.planets.name': 'Jupiter' })\n// docs is empty\n\nconst docs = await db.findAsync({ 'completeData.planets.0.name': 'Earth' })\n// docs contains document 5\n// If we had tested against 'Mars' docs would be empty because we are matching against a specific array element\n\n\n// You can also deep-compare objects. Don't confuse this with dot-notation!\nconst docs = await db.findAsync({ humans: { genders: 2 } })\n// docs is empty, because { genders: 2 } is not equal to { genders: 2, eyes: true }\n\n\n// Find all documents in the collection\nconst docs = await db.findAsync({})\n\n// The same rules apply when you want to only find one document\nconst doc = await db.findOneAsync({ _id: 'id1' })\n// doc is the document Mars\n// If no document is found, doc is null\n```\n\n#### Operators ($lt, $lte, $gt, $gte, $in, $nin, $ne, $exists, $regex)\n\nThe syntax is `{ field: { $op: value } }` where `$op` is any comparison\noperator:\n\n* `$lt`, `$lte`: less than, less than or equal\n* `$gt`, `$gte`: greater than, greater than or equal\n* `$in`: member of. `value` must be an array of values\n* `$ne`, `$nin`: not equal, not a member of\n* `$exists`: checks whether the document posses the property `field`. `value`\n  should be true or false\n* `$regex`: checks whether a string is matched by the regular expression.\n  Contrary to MongoDB, the use of `$options` with `$regex` is not supported,\n  because it doesn't give you more power than regex flags. Basic queries are\n  more readable so only use the `$regex` operator when you need to use another\n  operator with it (see example below)\n\n```javascript\n// $lt, $lte, $gt and $gte work on numbers and strings\nconst docs = await db.findAsync({ 'humans.genders': { $gt: 5 } })\n// docs contains Omicron Persei 8, whose humans have more than 5 genders (7).\n\n// When used with strings, lexicographical order is used\nconst docs = await db.findAsync({ planet: { $gt: 'Mercury' } })\n// docs contains Omicron Persei 8\n\n// Using $in. $nin is used in the same way\nconst docs = await db.findAsync({ planet: { $in: ['Earth', 'Jupiter'] } })\n// docs contains Earth and Jupiter\n\n// Using $exists\nconst docs = await db.findAsync({ satellites: { $exists: true } })\n// docs contains only Mars\n\n// Using $regex with another operator\nconst docs = await db.findAsync({\n  planet: {\n    $regex: /ar/,\n    $nin: ['Jupiter', 'Earth']\n  }\n})\n// docs only contains Mars because Earth was excluded from the match by $nin\n```\n\n#### Array fields\n\nWhen a field in a document is an array, NeDB first tries to see if the query\nvalue is an array to perform an exact match, then whether there is an\narray-specific comparison function (for now there is only `$size`\nand `$elemMatch`) being used. If not, the query is treated as a query on every\nelement and there is a match if at least one element matches.\n\n* `$size`: match on the size of the array\n* `$elemMatch`: matches if at least one array element matches the query entirely\n\n```javascript\n// Exact match\nconst docs = await db.findAsync({ satellites: ['Phobos', 'Deimos'] })\n// docs contains Mars\n\nconst docs = await db.findAsync({ satellites: ['Deimos', 'Phobos'] })\n// docs is empty\n\n// Using an array-specific comparison function\n// $elemMatch operator will provide match for a document, if an element from the array field satisfies all the conditions specified with the `$elemMatch` operator\nconst docs = await db.findAsync({\n  completeData: {\n    planets: {\n      $elemMatch: {\n        name: 'Earth',\n        number: 3\n      }\n    }\n  }\n})\n// docs contains documents with id 5 (completeData)\n\nconst docs = await db.findAsync({\n  completeData: {\n    planets: {\n      $elemMatch: {\n        name: 'Earth',\n        number: 5\n      }\n    }\n  }\n})\n// docs is empty\n\n// You can use inside #elemMatch query any known document query operator\nconst docs = await db.findAsync({\n  completeData: {\n    planets: {\n      $elemMatch: {\n        name: 'Earth',\n        number: { $gt: 2 }\n      }\n    }\n  }\n})\n// docs contains documents with id 5 (completeData)\n\n// Note: you can't use nested comparison functions, e.g. { $size: { $lt: 5 } } will throw an error\nconst docs = await db.findAsync({ satellites: { $size: 2 } })\n// docs contains Mars\n\nconst docs = await db.findAsync({ satellites: { $size: 1 } })\n// docs is empty\n\n// If a document's field is an array, matching it means matching any element of the array\nconst docs = await db.findAsync({ satellites: 'Phobos' })\n// docs contains Mars. Result would have been the same if query had been { satellites: 'Deimos' }\n\n// This also works for queries that use comparison operators\nconst docs = await db.findAsync({ satellites: { $lt: 'Amos' } })\n// docs is empty since Phobos and Deimos are after Amos in lexicographical order\n\n// This also works with the $in and $nin operator\nconst docs = await db.findAsync({ satellites: { $in: ['Moon', 'Deimos'] } })\n// docs contains Mars (the Earth document is not complete!)\n```\n\n#### Logical operators $or, $and, $not, $where\n\nYou can combine queries using logical operators:\n\n* For `$or` and `$and`, the syntax is `{ $op: [query1, query2, ...] }`.\n* For `$not`, the syntax is `{ $not: query }`\n* For `$where`, the syntax\n  is `{ $where: function () { /* object is 'this', return a boolean */ } }`\n\n```javascript\nconst docs = await db.findAsync({ $or: [{ planet: 'Earth' }, { planet: 'Mars' }] })\n// docs contains Earth and Mars\n\nconst docs = await db.findAsync({ $not: { planet: 'Earth' } })\n// docs contains Mars, Jupiter, Omicron Persei 8\n\nconst docs = await db.findAsync({ $where: function () { return Object.keys(this) > 6 } })\n// docs with more than 6 properties\n\n// You can mix normal queries, comparison queries and logical operators\nconst docs = await db.findAsync({\n  $or: [{ planet: 'Earth' }, { planet: 'Mars' }],\n  inhabited: true\n})\n// docs contains Earth\n```\n\n#### Sorting and paginating\n\n[`Datastore#findAsync`](./API.md#Datastore+findAsync),\n[`Datastore#findOneAsync`](./API.md#Datastore+findOneAsync) and\n[`Datastore#countAsync`](./API.md#Datastore+countAsync) don't\nactually return a `Promise`, but a [`Cursor`](./API.md#Cursor) which is a\n[`Thenable`](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Operators/await#thenable_objects)\nwhich calls [`Cursor#execAsync`](./API.md#Cursor+execAsync) when awaited.\n\nThis pattern allows to chain [`Cursor#sort`](./API.md#Cursor+sort),\n[`Cursor#skip`](./API.md#Cursor+skip), \n[`Cursor#limit`](./API.md#Cursor+limit) and\n[`Cursor#projection`](./API.md#Cursor+projection) and await the result.\n\n```javascript\n// Let's say the database contains these 4 documents\n// doc1 = { _id: 'id1', planet: 'Mars', system: 'solar', inhabited: false, satellites: ['Phobos', 'Deimos'] }\n// doc2 = { _id: 'id2', planet: 'Earth', system: 'solar', inhabited: true, humans: { genders: 2, eyes: true } }\n// doc3 = { _id: 'id3', planet: 'Jupiter', system: 'solar', inhabited: false }\n// doc4 = { _id: 'id4', planet: 'Omicron Persei 8', system: 'futurama', inhabited: true, humans: { genders: 7 } }\n\n// No query used means all results are returned (before the Cursor modifiers)\nconst docs = await db.findAsync({}).sort({ planet: 1 }).skip(1).limit(2)\n// docs is [doc3, doc1]\n\n// You can sort in reverse order like this\nconst docs = await db.findAsync({ system: 'solar' }).sort({ planet: -1 })\n// docs is [doc1, doc3, doc2]\n\n// You can sort on one field, then another, and so on like this:\nconst docs = await db.findAsync({}).sort({ firstField: 1, secondField: -1 })\n// ... You understand how this works!\n```\n\n#### Projections\n\nYou can give `findAsync` and `findOneAsync` an optional second argument, `projections`.\nThe syntax is the same as MongoDB: `{ a: 1, b: 1 }` to return only the `a`\nand `b` fields, `{ a: 0, b: 0 }` to omit these two fields. You cannot use both\nmodes at the time, except for `_id` which is by default always returned and\nwhich you can choose to omit. You can project on nested documents.\n\n```javascript\n// Same database as above\n\n// Keeping only the given fields\nconst docs = await db.findAsync({ planet: 'Mars' }, { planet: 1, system: 1 })\n// docs is [{ planet: 'Mars', system: 'solar', _id: 'id1' }]\n\n// Keeping only the given fields but removing _id\nconst docs = await db.findAsync({ planet: 'Mars' }, {\n  planet: 1,\n  system: 1,\n  _id: 0\n})\n// docs is [{ planet: 'Mars', system: 'solar' }]\n\n// Omitting only the given fields and removing _id\nconst docs = await db.findAsync({ planet: 'Mars' }, {\n  planet: 0,\n  system: 0,\n  _id: 0\n})\n// docs is [{ inhabited: false, satellites: ['Phobos', 'Deimos'] }]\n\n// Failure: using both modes at the same time\nconst docs = await db.findAsync({ planet: 'Mars' }, { planet: 0, system: 1 })\n// err is the error message, docs is undefined\n\n// You can also use it in a Cursor way but this syntax is not compatible with MongoDB\nconst docs = await db.findAsync({ planet: 'Mars' }).projection({\n  planet: 1,\n  system: 1\n})\n// docs is [{ planet: 'Mars', system: 'solar', _id: 'id1' }]\n\n// Project on a nested document\nconst doc = await db.findOneAsync({ planet: 'Earth' }).projection({\n  planet: 1,\n  'humans.genders': 1\n})\n// doc is { planet: 'Earth', _id: 'id2', humans: { genders: 2 } }\n```\n\n### Counting documents\n\nYou can use `countAsync` to count documents. It has the same syntax as `findAsync`.\nFor example:\n\n```javascript\n// Count all planets in the solar system\nconst count = await db.countAsync({ system: 'solar' })\n// count equals to 3\n\n// Count all documents in the datastore\nconst count = await db.countAsync({})\n// count equals to 4\n```\n\n### Updating documents\n\n[`db.updateAsync(query, update, options)`](./API.md#Datastore+updateAsync)\nwill update all documents matching `query` according to the `update` rules.\n\n`update` specifies how the documents should be modified. It is either a new \ndocument or a set of modifiers (you cannot use both together):\n* A new document will replace the matched docs;\n* Modifiers create the fields they need to modify if they don't exist,\n  and you can apply them to subdocs (see [the API reference]((./API.md#Datastore+updateAsync)))\n\n`options` is an object with three possible parameters:\n* `multi` which allows the modification of several documents if set to true.\n* `upsert` will insert a new document corresponding if it doesn't exist (either\nthe `update` is a simple object with no modifiers, or the `query` modified by\nthe modifiers in the `update`) if set to `true`.\n* `returnUpdatedDocs` will return the array of documents matched by the find\nquery and updated (updated documents will be returned even if the update did not\nactually modify them) if set to `true`.\n\nIt resolves into an  Object with the following properties:\n- `numAffected`: how many documents were affected by the update;\n- `upsert`: if a document was actually upserted (not always the same as `options.upsert`;\n- `affectedDocuments`: \n  - if `upsert` is `true` the document upserted;\n  - if `options.returnUpdatedDocs` is `true` either the affected document or, if `options.multi` is `true` an Array of the affected documents, else `null`;\n\n**Note**: you can't change a document's _id.\n\n```javascript\n// Let's use the same example collection as in the 'finding document' part\n// { _id: 'id1', planet: 'Mars', system: 'solar', inhabited: false }\n// { _id: 'id2', planet: 'Earth', system: 'solar', inhabited: true }\n// { _id: 'id3', planet: 'Jupiter', system: 'solar', inhabited: false }\n// { _id: 'id4', planet: 'Omicron Persia 8', system: 'futurama', inhabited: true }\n\n// Replace a document by another\nconst { numAffected } = await db.updateAsync({ planet: 'Jupiter' }, { planet: 'Pluton' }, {})\n// numAffected = 1\n// The doc #3 has been replaced by { _id: 'id3', planet: 'Pluton' }\n// Note that the _id is kept unchanged, and the document has been replaced\n// (the 'system' and inhabited fields are not here anymore)\n\n\n// Set an existing field's value\nconst { numAffected } = await db.updateAsync({ system: 'solar' }, { $set: { system: 'solar system' } }, { multi: true })\n// numAffected = 3\n// Field 'system' on Mars, Earth, Jupiter now has value 'solar system'\n\n\n// Setting the value of a non-existing field in a subdocument by using the dot-notation\nawait db.updateAsync({ planet: 'Mars' }, {\n  $set: {\n    'data.satellites': 2,\n    'data.red': true\n  }\n}, {})\n// Mars document now is { _id: 'id1', system: 'solar', inhabited: false\n//                      , data: { satellites: 2, red: true }\n//                      }\n// Not that to set fields in subdocuments, you HAVE to use dot-notation\n// Using object-notation will just replace the top-level field\nawait db.updateAsync({ planet: 'Mars' }, { $set: { data: { satellites: 3 } } }, {})\n// Mars document now is { _id: 'id1', system: 'solar', inhabited: false\n//                      , data: { satellites: 3 }\n//                      }\n// You lost the 'data.red' field which is probably not the intended behavior\n\n\n// Deleting a field\nawait db.updateAsync({ planet: 'Mars' }, { $unset: { planet: true } }, {})\n// Now the document for Mars doesn't contain the planet field\n// You can unset nested fields with the dot notation of course\n\n\n// Upserting a document\nconst { numAffected, affectedDocuments, upsert } = await db.updateAsync({ planet: 'Pluton' }, {\n  planet: 'Pluton',\n  inhabited: false\n}, { upsert: true })\n// numAffected = 1, affectedDocuments = { _id: 'id5', planet: 'Pluton', inhabited: false }, upsert = true\n// A new document { _id: 'id5', planet: 'Pluton', inhabited: false } has been added to the collection\n\n\n// If you upsert with a modifier, the upserted doc is the query modified by the modifier\n// This is simpler than it sounds :)\nawait db.updateAsync({ planet: 'Pluton' }, { $inc: { distance: 38 } }, { upsert: true })\n// A new document { _id: 'id5', planet: 'Pluton', distance: 38 } has been added to the collection  \n\n\n// If we insert a new document { _id: 'id6', fruits: ['apple', 'orange', 'pear'] } in the collection,\n// let's see how we can modify the array field atomically\n\n// $push inserts new elements at the end of the array\nawait db.updateAsync({ _id: 'id6' }, { $push: { fruits: 'banana' } }, {})\n// Now the fruits array is ['apple', 'orange', 'pear', 'banana']\n\n\n// $pop removes an element from the end (if used with 1) or the front (if used with -1) of the array\nawait db.updateAsync({ _id: 'id6' }, { $pop: { fruits: 1 } }, {})\n// Now the fruits array is ['apple', 'orange']\n// With { $pop: { fruits: -1 } }, it would have been ['orange', 'pear']\n\n\n// $addToSet adds an element to an array only if it isn't already in it\n// Equality is deep-checked (i.e. $addToSet will not insert an object in an array already containing the same object)\n// Note that it doesn't check whether the array contained duplicates before or not\nawait db.updateAsync({ _id: 'id6' }, { $addToSet: { fruits: 'apple' } }, {})\n// The fruits array didn't change\n// If we had used a fruit not in the array, e.g. 'banana', it would have been added to the array\n\n// $pull removes all values matching a value or even any NeDB query from the array\nawait db.updateAsync({ _id: 'id6' }, { $pull: { fruits: 'apple' } }, {})\n// Now the fruits array is ['orange', 'pear']\n\nawait db.updateAsync({ _id: 'id6' }, { $pull: { fruits: { $in: ['apple', 'pear'] } } }, {})\n// Now the fruits array is ['orange']\n\n\n// $each can be used to $push or $addToSet multiple values at once\n// This example works the same way with $addToSet\nawait db.updateAsync({ _id: 'id6' }, { $push: { fruits: { $each: ['banana', 'orange'] } } }, {})\n// Now the fruits array is ['apple', 'orange', 'pear', 'banana', 'orange']\n\n\n// $slice can be used in cunjunction with $push and $each to limit the size of the resulting array.\n// A value of 0 will update the array to an empty array. A positive value n will keep only the n first elements\n// A negative value -n will keep only the last n elements.\n// If $slice is specified but not $each, $each is set to []\nawait db.updateAsync({ _id: 'id6' }, {\n  $push: {\n    fruits: {\n      $each: ['banana'],\n      $slice: 2\n    }\n  }\n})\n// Now the fruits array is ['apple', 'orange']\n\n\n// $min/$max to update only if provided value is less/greater than current value\n// Let's say the database contains this document\n// doc = { _id: 'id', name: 'Name', value: 5 }\nawait db.updateAsync({ _id: 'id1' }, { $min: { value: 2 } }, {})\n// The document will be updated to { _id: 'id', name: 'Name', value: 2 }\n\n\nawait db.updateAsync({ _id: 'id1' }, { $min: { value: 8 } }, {})\n// The document will not be modified\n```\n\n### Removing documents\n\n[`db.removeAsync(query, options)`](./API.md#Datastore#removeAsync)\nwill remove documents matching `query`. Can remove multiple documents if\n`options.multi` is set. Returns the `Promise<numRemoved>`.\n\n```javascript\n// Let's use the same example collection as in the \"finding document\" part\n// { _id: 'id1', planet: 'Mars', system: 'solar', inhabited: false }\n// { _id: 'id2', planet: 'Earth', system: 'solar', inhabited: true }\n// { _id: 'id3', planet: 'Jupiter', system: 'solar', inhabited: false }\n// { _id: 'id4', planet: 'Omicron Persia 8', system: 'futurama', inhabited: true }\n\n// Remove one document from the collection\n// options set to {} since the default for multi is false\nconst { numRemoved } = await db.removeAsync({ _id: 'id2' }, {})\n// numRemoved = 1\n\n\n// Remove multiple documents\nconst { numRemoved } = await db.removeAsync({ system: 'solar' }, { multi: true })\n// numRemoved = 3\n// All planets from the solar system were removed\n\n\n// Removing all documents with the 'match-all' query\nconst { numRemoved } = await db.removeAsync({}, { multi: true })\n```\n\n### Indexing\n\nNeDB supports indexing. It gives a very nice speed boost and can be used to\nenforce a unique constraint on a field. You can index any field, including\nfields in nested documents using the dot notation. For now, indexes are only\nused to speed up basic queries and queries using `$in`, `$lt`, `$lte`, `$gt`\nand `$gte`. The indexed values cannot be of type array of object.\n\n**Breaking change**: [since v4.0.0](./CHANGELOG.md#400---2023-01-20), commas (`,`) can no longer be used in indexed field names.\n\nThe following is illegal:\n```javascript\ndb.ensureIndexAsync({ fieldName: 'some,field' })\ndb.ensureIndexAsync({ fieldName: ['some,field', 'other,field'] })\n```\nThis is a side effect of the compound index implementation.\n\nTo create an index, use [`datastore#ensureIndexAsync(options)`](./API.md#Datastore+ensureIndexAsync).\nIt resolves when the index is persisted on disk (if the database is persistent)\nand may throw an Error (usually a unique constraint that was violated). It can\nbe called when you want, even after some data was inserted, though it's best to\ncall it at application startup. The options are:\n\n* **fieldName** (required): name of the field to index. Use the dot notation to\n  index a field in a nested document. For a compound index, use an array of field names.\n* **unique** (optional, defaults to `false`): enforce field uniqueness.\n* **sparse** (optional, defaults to `false`): don't index documents for which\n  the field is not defined.\n* **expireAfterSeconds** (number of seconds, optional): if set, the created\n  index is a TTL (time to live) index, that will automatically remove documents\n  when the indexed field value is older than `expireAfterSeconds`.\n\nNote: the `_id` is automatically indexed with a unique constraint.\n\nYou can remove a previously created index with\n[`datastore#removeIndexAsync(fieldName)`](./API.md#Datastore+removeIndexAsync).\n\n```javascript\ntry {\n  await db.ensureIndexAsync({ fieldName: 'somefield' })\n} catch (error) {\n  // If there was an error, error is not null\n}\n\n// Using a unique constraint with the index\nawait db.ensureIndexAsync({ fieldName: 'somefield', unique: true })\n\n// Using a sparse unique index\nawait db.ensureIndexAsync({\n  fieldName: 'somefield',\n  unique: true,\n  sparse: true\n})\n\n// Using a compound index\nawait db.ensureIndexAsync({ fieldName: [\"field1\", \"field2\"] });\n\ntry {\n  // Format of the error message when the unique constraint is not met\n  await db.insertAsync({ somefield: '@seald-io/nedb' })\n  // works\n  await db.insertAsync({ somefield: '@seald-io/nedb' })\n  //rejects\n} catch (error) {\n  // error is { errorType: 'uniqueViolated',\n  //            key: 'name',\n  //            message: 'Unique constraint violated for key name' }\n}\n\n\n// Remove index on field somefield\nawait db.removeIndexAsync('somefield')\n\n// Example of using expireAfterSeconds to remove documents 1 hour\n// after their creation (db's timestampData option is true here)\nawait db.ensureIndex({\n  fieldName: 'createdAt',\n  expireAfterSeconds: 3600\n})\n\n// You can also use the option to set an expiration date like so\nawait db.ensureIndex({\n  fieldName: 'expirationDate',\n  expireAfterSeconds: 0\n})\n// Now all documents will expire when system time reaches the date in their\n// expirationDate field\n```\n\n## Other environments\nNeDB runs on Node.js (it is tested on Node 12, 14 and 16), the browser (it is\ntested on the latest version of Chrome) and React-Native using\n[@react-native-async-storage/async-storage](https://github.com/react-native-async-storage/async-storage).\n\n### Browser bundle\nThe npm package contains a bundle and its minified counterpart for the browser.\nThey are located in the `browser-version/out` directory. You only need to require `nedb.js`\nor `nedb.min.js` in your HTML file and the global object `Nedb` can be used\nright away, with the same API as the server version:\n\n```\n<script src=\"nedb.min.js\"></script>\n<script>\n  var db = new Nedb();   // Create an in-memory only datastore\n  \n  db.insert({ planet: 'Earth' }, function (err) {\n   db.find({}, function (err, docs) {\n     // docs contains the two planets Earth and Mars\n   });\n  });\n</script>\n```\n\nIf you specify a `filename`, the database will be persistent, and automatically\nselect the best storage method available using [localforage](https://github.com/localForage/localForage)\n(IndexedDB, WebSQL or localStorage) depending on the browser. In most cases that\nmeans a lot of data can be stored, typically in hundreds of MB.\n\n**WARNING**: the storage system changed between\nv1.3 and v1.4 and is NOT back-compatible! Your application needs to resync\nclient-side when you upgrade NeDB.\n\nNeDB uses modern Javascript features such as `async`, `Promise`, `class`, `const`\n, `let`, `Set`, `Map`, ... The bundle does not polyfill these features. If you\nneed to target another environment, you will need to make your own bundle.\n\n### Using the `browser` and `react-native` fields\nNeDB uses the `browser` and `react-native` fields to replace some modules by an\nenvironment specific shim.\n\nThe way this works is by counting on the bundler that will package NeDB to use\nthis fields. This is [done by default by Webpack](https://webpack.js.org/configuration/resolve/#resolvealiasfields)\nfor the `browser` field. And this is [done by default by Metro](https://github.com/facebook/metro/blob/c21daba415ea26511e157f794689caab9abe8236/packages/metro/src/ModuleGraph/node-haste/Package.js#L108)\nfor the `react-native` field.\n\nThis is done for:\n- the [storage module](./lib/storage.js) which uses Node.js `fs`. It is\n  [replaced in the browser](./browser-version/lib/storage.browser.js) by one that uses\n  [localforage](https://github.com/localForage/localForage), and\n  [in `react-native`](./browser-version/lib/storage.react-native.js)  by one that uses\n  [@react-native-async-storage/async-storage](https://github.com/react-native-async-storage/async-storage)\n- the [customUtils module](./browser-version/lib/customUtils.js) which uses Node.js\n  `crypto` module. It is replaced by a good enough shim to generate ids that uses `Math.random()`.\n- the [byline module](./browser-version/lib/byline.js) which uses Node.js `stream`\n  (a fork of [`node-byline`](https://github.com/jahewson/node-byline) included in\n  the repo because it is unmaintained). It isn't used in the browser nor\n  react-native versions, therefore it is shimmed with an empty object.\n\nHowever, the `browser` and `react-native` versions rely on node native modules and therefore must be polyfilled:\n- `util` with https://github.com/browserify/node-util.\n- `events` with https://github.com/browserify/events.\n\n## Performance\n\n### Speed\n\nNeDB is not intended to be a replacement of large-scale databases such as\nMongoDB, and as such was not designed for speed. That said, it is still pretty\nfast on the expected datasets, especially if you use indexing. On a typical,\nnot-so-fast dev machine, for a collection containing 10,000 documents, with\nindexing:\n\n* Insert: **10,680 ops/s**\n* Find: **43,290 ops/s**\n* Update: **8,000 ops/s**\n* Remove: **11,750 ops/s**\n\nYou can run these simple benchmarks by executing the scripts in the `benchmarks`\nfolder. Run them with the `--help` flag to see how they work.\n\n### Memory footprint\n\nA copy of the whole database is kept in memory. This is not much on the expected\nkind of datasets (20MB for 10,000 2KB documents).\n\n## Use in other services\n\n* An ODM for NeDB: [follicle](https://github.com/seald/follicle)\n* A layer to add a promise-only interface: [nedb-promises](https://www.npmjs.com/package/nedb-promises)\n\n## Modernization\n\nThis fork of NeDB will be incrementally updated to:\n* [ ] cleanup the benchmark and update the performance statistics;\n* [ ] remove deprecated features;\n* [ ] add a way to change the `Storage` module by dependency injection, which will\n  pave the way to cleaner browser react-native versions (cf https://github.com/seald/nedb/pull/19).\n* [x] use `async` functions and `Promises` instead of callbacks with `async@0.2.6`;\n* [x] expose a `Promise`-based interface;\n* [x] remove the `underscore` dependency;\n\n## Pull requests guidelines\nIf you submit a pull request, thanks! There are a couple rules to follow though\nto make it manageable:\n\n* The pull request should be atomic, i.e. contain only one feature. If it\n  contains more, please submit multiple pull requests. Reviewing massive, 1000\n  loc+ pull requests is extremely hard.\n* Likewise, if for one unique feature the pull request grows too large (more\n  than 200 loc tests not included), please get in touch first.\n* Please stick to the current coding style. It's important that the code uses a\n  coherent style for readability (this package uses [`standard`](https://standardjs.com/)).\n* Do not include stylistic improvements ('housekeeping'). If you think one part\n  deserves lots of housekeeping, use a separate pull request so as not to\n  pollute the code.\n* Don't forget tests for your new feature. Also don't forget to run the whole\n  test suite before submitting to make sure you didn't introduce regressions.\n* Update the JSDoc and regenerate [the markdown docs](./API.md).\n* Update the readme accordingly.\n\n## License\n\nSee [License](LICENSE.md)\n","readmeFilename":"README.md"}