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    4.6.3 • Public • Published
    Minimal MEAN

    CircleCI DeepScan grade Coverage Status

    A very thin TypeScript-based MongoDB helper with optional, rich ODM (Object Document Mapper) convenience features

    Check out the sample full-stack project Lemon Mart Server

    Check out my book Angular 6 for Enterprise-Ready Web Applications. Get it on http://AngularForEnterprise.com.

    Looking to containerize MongoDB? Checkout excellalabs/mongo for a fully featured Mongo container (with Auth & SSL) inherited from the official Mongo Docker image and instructions on how to deploy it on AWS.

    Major Features

    • connect()`

      MongoDB async connection harness

      It can be a challenge to ensure that database connectivity exists, when writing an fully async web application. connect() makes it easy to connect to a MongoDB instance and makes it safe to be called simultanously from multiple threads starting up at the same time.

    • Document and IDocument

      Base Class and Interface to help define your own models

    • CollectionFactory

      Define collections, organize indexes and aggregate queries alongside collection implementation. Below are the convenience features of a DocumentTS collection

      • get collection returns the navtive MongoDB collection, so you can directly operate on it
      get collection(): ICollectionProvider<TDocument>
      • aggregate allows you run a MongoDB aggregation pipeline
      aggregate(pipeline: object[]): AggregationCursor<TDocument>
      • findOne and findOneAndUpdate simplifies the operation of commonly used database functionality, automatically hydrating the models it returns
      async findOne(filter: FilterQuery<TDocument>, options?: FindOneOptions)
      async findOneAndUpdate(
        filter: FilterQuery<TDocument>,
        update: TDocument | UpdateQuery<TDocument>,
        options?: FindOneAndReplaceOption
       ): Promise<TDocument | null>
      • findWithPagination is by far the best feature of DocumentTS, allowing you filter, sort, and paginate large collections of data. This function is geared towards use with data tables, so you specifies searchable properties, turn off hydration, and use a debug feature to fine tune your queries.
      async findWithPagination<TReturnType extends IDbRecord>(
        queryParams: Partial<IQueryParameters> & object,
        aggregationCursorFunc?: Func<AggregationCursor<TReturnType>>,
        query?: string | object,
        searchableProperties?: string[],
        hydrate = true,
        debugQuery = false
      ): Promise<IPaginationResult<TReturnType>>

    Quick Start

    Supports MongoDB v4+, Mongo Driver 3.3+ and TypeScript 3.7+

    • Add DocumentTS to your project with npm install document-ts mongodb
    • Connect to your Mongo database using connect()
    • Connect will retry connecting to the database 10 times every 2 seconds
      • Set connectionRetryWait (in seconds) and connectionRetryMax to modify this behavior
    • Specify isProd and certFileUri to connect using an SSL certificate
    import { connect } from 'document-ts'
    async function start() {
      // If isProd is set to true and a .pem file is provided, SSL will be used to connect: i.e. connect(config.mongoUri, isProd, 'server/compose-ca.pem')
      await connect(process.env.MONGO_URI)
    • If you use connect() then you don't have to worry about having your Database Instance initialized during an asynchoronous start up sequence. getDbInstance gives you access to the native MongoDB driver to perform custom functions like creating indexes.
    import { getDbInstance } from 'document-ts'
    // assuming this is called within an async function
    await dbInstance.collection('users').createIndexes([
        key: {
          displayName: 1,
        key: {
          email: 1,
        unique: true,
    • Define the interface for your first model

      See tests\user.ts for sample Model implementation

    import { IDocument } from 'document-ts'
    export interface IUser extends IDocument {
    • Define the class for your model

      See tests\user.ts for sample Model implementation

    import { Document } from 'document-ts'
    export class User extends Document<IUser> implements IUser {
      static collectionName = 'users'
      private password: string
      public email: string
      public firstName: string
      public lastName: string
      public role: string
      constructor(user?: IUser) {
        super(User.collectionName, user)
    • Implement getCalculatedPropertiesToInclude() which will ensure that your get properties that are "calculate" on the fly will be serialized when sending the model down to the client, but it will not be saved in the database.
      getCalculatedPropertiesToInclude(): string[]{
          return ['fullName']
    • Implement getPropertiesToExclude() which will ensure that certain properties like passwords will not be serialized when sending the model down to the client, but it will still be saved in the database.
      getPropertiesToExclude(): string[]{
          return ['password']
    • Implement the CollectionFactory class, so that you can run Mongo queries without having to call getDbInstance or specify the collection and TypeScript type name every time you run a query. CollectionFactory provides convenience functions like find, findOne, findOneAndUpdate, findWithPagination and similar, while also handling hydration tasks, such as serializing getters and child documents.
    import { CollectionFactory } from 'document-ts'
    class UserCollectionFactory extends CollectionFactory<User> {
      constructor(docType: typeof User) {
        super(User.collectionName, docType, ['firstName', 'lastName', 'email'])
    export let UserCollection = new UserCollectionFactory(User)
    • CollectionFactory is powerful and flexible. In your custom class, you can implement MongoDB aggregate queries to run advance join-like queries, geo queries and whatever MongoDB supports. findWithPagination itself is very powerful and will enable you to implement paginated dashboards with easse.

    • findWithPagination leverage query parameters for pagination and configuration

    export interface IQueryParameters {
      filter?: string
      skip?: number
      limit?: number
      sortKeyOrList?: string | Object[] | Object
      projectionKeyOrList?: string | Object[] | Object
    • Optionally implement toJSON() to customize serialization/hydration behavior or extend ISerializable
      toJSON() {
        let keys = Object.keys(this).concat(['fullAddress', 'localAddress'])
        return Serialize(SerializationStrategy.JSON, this, keys)
    • Optionally implement toBSON() to customize database serialization behavior or extend ISerializable
      toBSON() {
        let keys = Object.keys(this).concat(['fullAddress', 'localAddress'])
        return Serialize(SerializationStrategy.BSON, this, keys)
    • To debug the default serialization behavior, implement
      toJSON() {
        // drop a breakpoint here or console.log(this)
        return super.toJSON()
      toBSON() {
        return super.toBSON()

    See the Lemon Mart Server sample project for usage - https://github.com/duluca/lemon-mart-server


    • Reliable
      • Rely on the rock-solid Native Node.js MongoDB drivers
      • Don't inject custom code into DB calls without explicit intent by the developer
      • Don't hide new MongoDB features, so you don't have to wait DocumentTS to be updated before you can use them
    • Optional
      • Stays out of the way, so developers can slowly transition
      • If performance becomes a concern easily switch to native MongoDB calls for the best performance
    • Async
      • Ensure developers can write simpler and more reliable code by surfaceing promises and async/await features
    • Convienient
      • Developers define their own models through simple Interfaces
      • Choose fields that you want to automatically hydrate, such as child or related objects
      • Serialize calculated fields with every request
      • Protect certain fields (like passwords) from serialization, so they aren't accidently sent across the wire
    • Promote Good Patterns
      • Suggest/enable easy to understand and implement patters for developers, so their code can scale and remain organized
    • Prevent Bloat
      • Leverage TypeScript types, interfaces, generics and inheritance to achieve development-time certainty of proper database access
      • Keep the code smart, readable and lean
      • Be very selective about any new features

    What It Isn't

    Not a full-fledged ODM or ORM replacement and doesn't aspire to be one like Mongoose or Camo. Databases are HARD. MongoDB took many years to mature, Microsoft has been trying for a really long time to build a reliable ORM with Entity Framework, Mongoose and many other ODMs are ridden with bugs (no offense) when you push them beyond the basics. It takes great resources to deliver a solid data access experience, so with DocumentTS you can developer directly against MongoDB while enjoying some conveniences as you choose.


    Although DocumentTS doesn't aspire to replace Mongoose or Camo, it most definitely is inspired by them in the way they've solved certain problems such as hydration. Check out the source code for those projects here:

    Building This Project

    • Run npm install
    • Run npm test



    npm i document-ts

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