Mongoose

This is the official documentation of the @forestadmin/agent Node.js agent.

The Mongoose data source allows importing collections from a Mongoose instance.

To make everything work as expected, you need to install the package @forestadmin/datasource-mongoose.

agent.js

const { createAgent } = require('@forestadmin/agent');
const { createMongooseDataSource } = require('@forestadmin/datasource-mongoose');
const connection = require('./mongoose-models');

// Create agent and import collections from mongoose.connection
const agent = createAgent(options).addDataSource(
  createMongooseDataSource(connection, { flattenMode: 'none' }),
);

mongoose-models.js

const mongoose = require('mongoose');

const connectionString = 'mongodb://root:password@localhost:27017';
const connection = mongoose.createConnection(connectionString);

connection.model(
  'persons',
  new mongoose.Schema({
    name: String,
    age: Number,

    // Nested object
    address: { streetName: String, city: String, country: String },

    // List of nested objects
    bills: [{ title: String, amount: Number, issueDate: Date, payedBy: [String] }],
  }),
);

module.exports = connection;

Dealing with deeply nested models

One Mongoose collection split into four Forest-Admin collections

When passing flattenMode: 'none' to the Mongoose data source, the connector will map each Mongoose model to a single Forest Admin collection without transformations.

As models in Mongoose can be deeply nested, that may not be what you want:

• Nested references will not be displayed as relations.

• JSON editors will be displayed for nested data.

Understanding flattenMode

	Description
flattenMode: 'auto'	Arrays of objects and arrays of references are converted to independent Forest Admin collections. All other fields are moved to the root of each collection
flattenMode: 'manual'	You are in full control on which virtual collections are created, and which fields are moved
flattenMode: 'none'	No transformation are made: Forest Admin collection use the exact same structure than your Mongoose models
flattenMode: 'legacy'	Retro-compatibility with previous versions
not defined	Equivalent to legacy but a warning is displayed at server startup

The forest admin agent may need to create "virtual" collections to represent relationships, especially in flattenMode: 'auto'. If you use this mode along with the include collection whitelist mode, check that you also include useful relationship collections.

Example

Supposing that persons records have the following format:

{
  "name": "Sherlock Holmes",
  "age": 54,
  "address": {
    "streetName": "Baker Street",
    "city": "London",
    "country": "Great Britain"
  },
  "bills": [
    {
      "title": "Rent",
      "amount": 0,
      "issueDate": "1887-04-17",
      "payedBy": ["Sherlock", "John", "Mrs Hudson"]
    }
  ]
}

The following samples are equivalent, and will import two collections into your Forest Admin panel:

• persons with the following fields: name, age, address->streetName, address->city, address->country.

• persons_bills with the following fields: title, amount, issueDate, payedBy.

// Automatic mode
const dataSource = createMongooseDataSource(mongoose.connection, {
  flattenMode: 'auto',
});

// Manual mode
const dataSource = createMongooseDataSource(mongoose.connection, {
  flattenMode: 'manual',
  flattenOptions: {
    // name of the Mongoose model
    persons: {
      // paths that should be converted to independent collections
      asModels: ['bills'],

      // paths that should be moved to the root of the collection
      asFields: ['address'],
      // or
      // asFields: ['address.streetName', 'address.city', 'address.country'],
      // or
      // asFields: [{ field: 'address', level: 1 }],
    },
  },
});

Data Navigation

When customizing your agent, you will need to navigate through your data efficiently. This section explains how to structure paths based on different field types.

Separator Behavior

There are two different separators depending on the field type:

• Nested Fields (@@@) – Used when accessing a nested field.

• Related Data (:) – Used when accessing related data.

Example

Consider a User collection with an address relation that contains a city field, which itself has a nested name field.

User (collection) → address (relation) → city (field) → name (nested field)

To access the name field inside city, the path would be:

address:city@@@name

This structure ensures a clear distinction between relationships and nested properties.