typings-tests.ts

/**
 * Created by stefansteinhart on 31.01.15.
 * Modified my arantes555 on 19.10.2021.
 */

import Datastore from './'
import { mkdirSync } from 'fs'

mkdirSync('./workspace/typings/', { recursive: true })
process.chdir('./workspace/typings/')

// Type 1: In-memory only datastore (no need to load the database)
let db = new Datastore()

// Type 2: Persistent datastore with manual loading
db = new Datastore({ filename: 'path/to/datafile' })
db.loadDatabase()

// Type 2 bis: Persistent datastore with manual loading with a callback
db = new Datastore({ filename: 'path/to/datafile' })
db.loadDatabase((err: Error | null) => {
  // should not fail
})

// Type 3: Persistent datastore with automatic loading
db = new Datastore({ filename: 'path/to/datafile_2', autoload: true, modes: {fileMode: 0o644, dirMode: 0o755} })
// You can issue commands right away

// Of course you can create multiple datastores if you need several
// collections. In this case it's usually a good idea to use autoload for all collections.
const dbContainer: any = {}
dbContainer.users = new Datastore('path/to/users.db')
dbContainer.robots = new Datastore('path/to/robots.db')

// You need to load each database (here we do it asynchronously)
dbContainer.users.loadDatabase()
dbContainer.robots.loadDatabase()

type Schema = {
  hello: string,
  n: number,
  today: Date,
  nedbIsAwesome: boolean,
  notthere: null,
  notToBeSaved: undefined,
  fruits:  string[];
  infos: { name: string }
}

const doc: Schema = {
  hello: 'world',
  n: 5,
  today: new Date(),
  nedbIsAwesome: true,
  notthere: null,
  notToBeSaved: undefined,  // Will not be saved
  fruits: ['apple', 'orange', 'pear'],
  infos: { name: 'nedb' }
}

db.insert(doc, (err: Error | null, newDoc: any) => {   // Callback is optional
  // newDoc is the newly inserted document, including its _id
  // newDoc has no key called notToBeSaved since its value was undefined
})

db.insert([{ a: 5 }, { a: 42 }], (err: Error | null, newdocs) => {
  // Two documents were inserted in the database
  // newDocs is an array with these documents, augmented with their _id
})

// If there is a unique constraint on field 'a', this will fail
db.insert([{ a: 5 }, { a: 42 }, { a: 5 }], (err: Error | null) => {
  // err is a 'uniqueViolated' error
  // The database was not modified
})

// Finding all planets in the solar system
db.find({ system: 'solar' }, (err: Error | null, docs: any[]) => {
  // docs is an array containing documents Mars, Earth, Jupiter
  // If no document is found, docs is equal to []
})

// Finding all planets whose name contain the substring 'ar' using a regular expression
db.find({ planet: /ar/ }, (err: Error | null, docs: any[]) => {
  // docs contains Mars and Earth
})

// Finding all inhabited planets in the solar system
db.find({ system: 'solar', inhabited: true }, (err: Error | null, docs: any[]) => {
  // docs is an array containing document Earth only
})

// Use the dot-notation to match fields in subdocuments
db.find({ 'humans.genders': 2 }, (err: Error | null, docs: any[]) => {
  // docs contains Earth
})

// Use the dot-notation to navigate arrays of subdocuments
db.find({ 'completeData.planets.name': 'Mars' }, (err: Error | null, docs: any[]) => {
  // docs contains document 5
})

db.find({ 'completeData.planets.name': 'Jupiter' }, (err: Error | null, docs: any[]) => {
  // docs is empty
})

db.find({ 'completeData.planets.0.name': 'Earth' }, (err: Error | null, docs: any[]) => {
  // docs contains document 5
  // If we had tested against "Mars" docs would be empty because we are matching against a specific array element
})

// You can also deep-compare objects. Don't confuse this with dot-notation!
db.find({ humans: { genders: 2 } }, (err: Error | null, docs: any[]) => {
  // docs is empty, because { genders: 2 } is not equal to { genders: 2, eyes: true }
})

// Find all documents in the collection
db.find({}, (err: Error | null, docs: any[]) => {
})

// The same rules apply when you want to only find one document
db.findOne({ _id: 'id1' }, (err: Error | null, doc: any) => {
  // doc is the document Mars
  // If no document is found, doc is null
})

// $lt, $lte, $gt and $gte work on numbers and strings
db.find({ 'humans.genders': { $gt: 5 } }, (err: Error | null, docs: any[]) => {
  // docs contains Omicron Persei 8, whose humans have more than 5 genders (7).
})

// When used with strings, lexicographical order is used
db.find({ planet: { $gt: 'Mercury' } }, (err: Error | null, docs: any[]) => {
  // docs contains Omicron Persei 8
})

// Using $in. $nin is used in the same way
db.find({ planet: { $in: ['Earth', 'Jupiter'] } }, (err: Error | null, docs: any[]) => {
  // docs contains Earth and Jupiter
})

// Using $exists
db.find({ satellites: { $exists: true } }, (err: Error | null, docs: any[]) => {
  // docs contains only Mars
})

// Using $regex with another operator
db.find({ planet: { $regex: /ar/, $nin: ['Jupiter', 'Earth'] } }, (err: Error | null, docs: any[]) => {
  // docs only contains Mars because Earth was excluded from the match by $nin
})

// Using an array-specific comparison function
// Note: you can't use nested comparison functions, e.g. { $size: { $lt: 5 } } will throw an error
db.find({ satellites: { $size: 2 } }, (err: Error | null, docs: any[]) => {
  // docs contains Mars
})

db.find({ satellites: { $size: 1 } }, (err: Error | null, docs: any[]) => {
  // docs is empty
})

// If a document's field is an array, matching it means matching any element of the array
db.find({ satellites: 'Phobos' }, (err: Error | null, docs: any[]) => {
  // docs contains Mars. Result would have been the same if query had been { satellites: 'Deimos' }
})

// This also works for queries that use comparison operators
db.find({ satellites: { $lt: 'Amos' } }, (err: Error | null, docs: any[]) => {
  // docs is empty since Phobos and Deimos are after Amos in lexicographical order
})

// This also works with the $in and $nin operator
db.find({ satellites: { $in: ['Moon', 'Deimos'] } }, (err: Error | null, docs: any[]) => {
  // docs contains Mars (the Earth document is not complete!)
})

db.find({ $or: [{ planet: 'Earth' }, { planet: 'Mars' }] }, (err: Error | null, docs: any[]) => {
  // docs contains Earth and Mars
})

db.find({ $not: { planet: 'Earth' } }, (err: Error | null, docs: any[]) => {
  // docs contains Mars, Jupiter, Omicron Persei 8
})

db.find({
  $where () {
    return parseInt(Object.keys(this)[0], 10) > 6
  }
}, (err: Error | null, docs: any[]) => {
  // docs with more than 6 properties
})

// You can mix normal queries, comparison queries and logical operators
db.find({ $or: [{ planet: 'Earth' }, { planet: 'Mars' }], inhabited: true }, (err: Error | null, docs: any[]) => {
  // docs contains Earth
})

// No query used means all results are returned (before the Cursor modifiers)
db.find({}).sort({ planet: 1 }).skip(1).limit(2).exec((err: Error | null, docs: any[]) => {
  // docs is [doc3, doc1]
})

// You can sort in reverse order like this
db.find({ system: 'solar' }).sort({ planet: -1 }).exec((err: Error | null, docs: any[]) => {
  // docs is [doc1, doc3, doc2]
})

// You can sort on one field, then another, and so on like this:
db.find({}).sort({ firstField: 1, secondField: -1 })

// Same database as above

// Keeping only the given fields
db.find({ planet: 'Mars' }, { planet: 1, system: 1 }, (err: Error | null, docs: any[]) => {
  // docs is [{ planet: 'Mars', system: 'solar', _id: 'id1' }]
})

// Keeping only the given fields but removing _id
db.find({ planet: 'Mars' }, { planet: 1, system: 1, _id: 0 }, (err: Error | null, docs: any[]) => {
  // docs is [{ planet: 'Mars', system: 'solar' }]
})

// Omitting only the given fields and removing _id
db.find({ planet: 'Mars' }, { planet: 0, system: 0, _id: 0 }, (err: Error | null, docs: any[]) => {
  // docs is [{ inhabited: false, satellites: ['Phobos', 'Deimos'] }]
})

// Failure: using both modes at the same time
db.find({ planet: 'Mars' }, { planet: 0, system: 1 }, (err: Error | null, docs: any[]) => {
  // err is the error message, docs is undefined
})

// You can also use it in a Cursor way but this syntax is not compatible with MongoDB
// If upstream compatibility is important don't use this method
db.find({ planet: 'Mars' }).projection({ planet: 1, system: 1 }).exec((err: Error | null, docs: any[]) => {
  // docs is [{ planet: 'Mars', system: 'solar', _id: 'id1' }]
})

// Count all planets in the solar system
db.count({ system: 'solar' }, (err: Error | null, count: number) => {
  // count equals to 3
})

// Count all documents in the datastore
db.count({}, (err: Error | null, count: number) => {
  // count equals to 4
})

// Let's use the same example collection as in the "finding document" part
// { _id: 'id1', planet: 'Mars', system: 'solar', inhabited: false }
// { _id: 'id2', planet: 'Earth', system: 'solar', inhabited: true }
// { _id: 'id3', planet: 'Jupiter', system: 'solar', inhabited: false }
// { _id: 'id4', planet: 'Omicron Persia 8', system: 'futurama', inhabited: true }

// Replace a document by another
db.update({ planet: 'Jupiter' }, { planet: 'Pluton' }, {}, (err: Error | null, numReplaced: number) => {
  // numReplaced = 1
  // The doc #3 has been replaced by { _id: 'id3', planet: 'Pluton' }
  // Note that the _id is kept unchanged, and the document has been replaced
  // (the 'system' and inhabited fields are not here anymore)
})

// Set an existing field's value
db.update({ system: 'solar' }, { $set: { system: 'solar system' } }, { multi: true }, (err: Error | null, numReplaced: number) => {
  // numReplaced = 3
  // Field 'system' on Mars, Earth, Jupiter now has value 'solar system'
})

// Setting the value of a non-existing field in a subdocument by using the dot-notation
db.update({ planet: 'Mars' }, { $set: { 'data.satellites': 2, 'data.red': true } }, {}, () => {
  // Mars document now is { _id: 'id1', system: 'solar', inhabited: false
  //                      , data: { satellites: 2, red: true }
  //                      }
  // Not that to set fields in subdocuments, you HAVE to use dot-notation
  // Using object-notation will just replace the top-level field
  db.update({ planet: 'Mars' }, { $set: { data: { satellites: 3 } } }, {}, () => {
    // Mars document now is { _id: 'id1', system: 'solar', inhabited: false
    //                      , data: { satellites: 3 }
    //                      }
    // You lost the "data.red" field which is probably not the intended behavior
  })
})

// Deleting a field
db.update({ planet: 'Mars' }, { $unset: { planet: true } }, {}, () => {
  // Now the document for Mars doesn't contain the planet field
  // You can unset nested fields with the dot notation of course
})

// Upserting a document
db.update({ planet: 'Pluton' }, {
  planet: 'Pluton',
  inhabited: false
}, { upsert: true }, (err: Error | null, numReplaced: number) => {
  // numReplaced = 1, upsert = { _id: 'id5', planet: 'Pluton', inhabited: false }
  // A new document { _id: 'id5', planet: 'Pluton', inhabited: false } has been added to the collection
})

// If you upsert with a modifier, the upserted doc is the query modified by the modifier
// This is simpler than it sounds :)
db.update({ planet: 'Pluton' }, { $inc: { distance: 38 } }, { upsert: true }, () => {
  // A new document { _id: 'id5', planet: 'Pluton', distance: 38 } has been added to the collection
})

// If we insert a new document { _id: 'id6', fruits: ['apple', 'orange', 'pear'] } in the collection,
// let's see how we can modify the array field atomically

// $push inserts new elements at the end of the array
db.update({ _id: 'id6' }, { $push: { fruits: 'banana' } }, {}, () => {
  // Now the fruits array is ['apple', 'orange', 'pear', 'banana']
})

// $pop removes an element from the end (if used with 1) or the front (if used with -1) of the array
db.update({ _id: 'id6' }, { $pop: { fruits: 1 } }, {}, () => {
  // Now the fruits array is ['apple', 'orange']
  // With { $pop: { fruits: -1 } }, it would have been ['orange', 'pear']
})

// $addToSet adds an element to an array only if it isn't already in it
// Equality is deep-checked (i.e. $addToSet will not insert an object in an array already containing the same object)
// Note that it doesn't check whether the array contained duplicates before or not
db.update({ _id: 'id6' }, { $addToSet: { fruits: 'apple' } }, {}, () => {
  // The fruits array didn't change
  // If we had used a fruit not in the array, e.g. 'banana', it would have been added to the array
})

// $pull removes all values matching a value or even any NeDB query from the array
db.update({ _id: 'id6' }, { $pull: { fruits: 'apple' } }, {}, () => {
  // Now the fruits array is ['orange', 'pear']
})
db.update({ _id: 'id6' }, { $pull: { fruits: { $in: ['apple', 'pear'] } } }, {}, () => {
  // Now the fruits array is ['orange']
})

// $each can be used to $push or $addToSet multiple values at once
// This example works the same way with $addToSet
db.update({ _id: 'id6' }, { $push: { fruits: { $each: ['banana', 'orange'] } } }, {}, () => {
  // Now the fruits array is ['apple', 'orange', 'pear', 'banana', 'orange']
})

// Let's use the same example collection as in the "finding document" part
// { _id: 'id1', planet: 'Mars', system: 'solar', inhabited: false }
// { _id: 'id2', planet: 'Earth', system: 'solar', inhabited: true }
// { _id: 'id3', planet: 'Jupiter', system: 'solar', inhabited: false }
// { _id: 'id4', planet: 'Omicron Persia 8', system: 'futurama', inhabited: true }

// Remove one document from the collection
// options set to {} since the default for multi is false
db.remove({ _id: 'id2' }, {}, (err: Error | null, numRemoved: number) => {
  // numRemoved = 1
})

// Remove multiple documents
db.remove({ system: 'solar' }, { multi: true }, (err: Error | null, numRemoved: number) => {
  // numRemoved = 3
  // All planets from the solar system were removed
})

db.ensureIndex({ fieldName: 'somefield' }, (err: Error | null) => {
  // If there was an error, err is not null
})

// Using a unique constraint with the index
db.ensureIndex({ fieldName: 'somefield', unique: true }, (err: Error | null) => {
})

// Using a sparse unique index
db.ensureIndex({ fieldName: 'somefield', unique: true, sparse: true }, (err: Error | null) => {
})

// Example of using expireAfterSeconds to remove documents 1 hour
// after their creation (db's timestampData option is true here)
db.ensureIndex({ fieldName: 'somefield', expireAfterSeconds: 3600 }, (err: Error | null) => {
})

// Format of the error message when the unique constraint is not met
db.insert({ somefield: 'nedb' }, (err: Error | null) => {
  // err is null
  db.insert({ somefield: 'nedb' }, (err: Error | null) => {
    // err is { errorType: 'uniqueViolated'
    //        , key: 'name'
    //        , message: 'Unique constraint violated for key name' }
  })
})

// Remove index on field somefield
db.removeIndex('somefield', (err: Error | null) => {
})

db.addListener('compaction.done', () => {})
db.on('compaction.done', () => {})
db.once('compaction.done', () => {})
db.prependListener('compaction.done', () => {})
db.prependOnceListener('compaction.done', () => {})
db.removeListener('compaction.done', () => {})
db.off('compaction.done', () => {})
db.listeners('compaction.done') // $ExpectType (() => void)[]
db.rawListeners('compaction.done') // $ExpectType (() => void)[]
db.listenerCount('compaction.done') // $ExpectType number

// Test Generics and types
const db2 = new Datastore<Schema>({ filename: 'path/to/datafile' })
db2.loadDatabase();

db2.findOne({ _id: 'id1' }, (err, doc) => {
  doc._id; // added by nedb
  doc.hello; // provided by user
  // @ts-expect-error
  doc.notExistingKey; // should fail
});