Experimental validation helper based on JSON Schema definitions using DJV. Currently only a very basic implementation which allows to convert the Schema to Mongo's $jsonSchema.

This is one way to get a common validation system starting at the client (browser app) through the middleware (web server) down to the persistence layer (database). Since there are many different approaches, this implementation may eventually disappear as a whole. But for now here is what it does.

Let's assume we got some very simple entity which will be stored in our (mongodb) database.

interface ITestObject {
    _id: string
    name: string
}

We would like to always have the _id field set to some unique identifier and the name to have no more than 10 characters. For this we declare the following JSON schema (actually the whole example here can be found in the mongodb.ts test script).

const testSchema: ISchema<ITestObject> = {
    $schema: 'http://json-schema.org/schema#',
    $id: 'http://isxs-validation.test/schemas/mongodbjson',
    additionalProperties: false,
    type: 'object',
    message: { de: 'Objekt unvollständig' },
    properties: {
        _id: {
            message: { de: 'Kennung ungültig' },
            pattern: uniqueId,
            type: 'string',
        },
        name: {
            maxLength: 10,
            message: { de: 'Name nicht angegeben oder zu lang' },
            minLength: 1,
            type: 'string',
        },
    },
    required: ['_id', 'name'],
}

There are methods to manually register the schema and validate against it. If we want to use MongoDb as the database system, then the module includes a simple but neat helper class. The way the initialisation code is used in the test environment is a bit weird but appropriate for educational purposes.

class TestCollection extends CollectionBase<ITestObject> {
    readonly name = 'isxs-validation-test-mongodb'

    readonly schema = testSchema

    constructor(protected readonly _database: Db) {
        super()
    }

    protected getCollection(): Promise<Collection<ITestObject>> {
        return Promise.resolve(this._database.collection(this.name))
    }

    async initializeForTest(): Promise<void> {
        const collection = await this._database.createCollection(this.name)

        return this.initialize(collection, this._database)
    }
}

Beside some playing around with the database connection (for a near production approach see my Movie Database Playground) the important point is calling the initialize method of the base class. This will not only register the schema for later validation but additionaly convert it to the MongoDb representation and install it inside the database.

async initialize(collection: Collection<TType>, database: Db): Promise<void> {
    await this.onInitialize(collection)

    addSchema(this.schema)

    await database.command({ collMod: this.name, validator: { $jsonSchema: convertToMongo(this.schema) } })
}

Since the MongoDb validation (which by the way requires 3.6 or later) is a bit bare bones, all modifying operations using base class methods will do an additional validation to get enhanced error messages.

private processValidatableError(item: TType, type: string, error: any): IValidationError[] {
    if (error.code !== 121) {
        databaseError('error during %s: %s', type, getMessage(error))

        throw error
    }

    try {
        return (
            validate(item, this.schema) || [
                { constraint: 'database', message: { en: getMessage(error) }, property: '*' },
            ]
        )
    } catch (e) {
        databaseError('error during %s validation: %s', type, getMessage(e))

        throw error
    }
}

If we want to add some new entity the result will be the list of potential schema violations.

const errors = await collection.insertOne({ _id: uuid(), name: 'Das geht aber so leider nicht' })

strict(errors, 'MongoDb: Fehler erwartet')
strict.strictEqual(errors.length, 1, `MongoDb: ungültige Anzahl ${errors.length} von Fehlermeldungen`)

In addition the validate method may be called explicitly at any time, even in the client. To do so the middleware just has to transfer the JSON schema to the client app and register it there globally using the addSchema method.

In the current evaluation state this leads to a seamless validation infrastructure throughout all software layers for more or less simple applications. This will not cover any issues, which can only be validated inside the database (for example key violations), but for some applications it may be a big step forward.