Skip to content

Learn Fauna database fundamentals with Fauna Query Language (FQL) v10 and the JavaScript driver.

Notifications You must be signed in to change notification settings

fauna/js-sample-app

Repository files navigation

Fauna JavaScript sample app

This sample app shows how to use Fauna in a production application.

The app uses Node.js and the Fauna v10 JavaScript driver to create HTTP API endpoints for an e-commerce store. You can use the app's API endpoints to manage products, customers, and orders for the store.

The app uses Fauna schemas and queries to:

  • Read and write data with strong consistency.

  • Define and handle relationships between resources, such as linking orders to products and customers.

  • Validate data changes against business logic.

The app's source code includes comments that highlight Fauna best practices.

Highlights

The sample app uses the following Fauna features:

  • Document type enforcement: Collection schemas enforce a structure for the app's documents. Fauna rejects document writes that don't conform to the schema, ensuring data consistency. Zero-downtime migrations let you safely change the schemas at any time.

  • Relationships: Normalized references link documents across collections. The app's queries use projection to dynamically retrieve linked documents, even when deeply nested. No complex joins, aggregations, or duplication needed.

  • Computed fields: Computed fields dynamically calculate their values at query time. For example, each customer's orders field uses a query to fetch a set of filtered orders. Similarly, each order's total is calculated at query time based on linked product prices and quantity.

  • Constraints: The app uses constraints to ensure field values are valid. For example, the app uses unique constraints to ensure each customer has a unique email address and each product has a unique name. Similarly, check constraints ensure each customer has only one cart at a time and that product prices are not negative.

  • User-defined functions (UDFs): The app uses UDFs to store business logic as reusable queries. For example, the app uses a checkout() UDF to process order updates. checkout() calls another UDF, validateOrderStatusTransition(), to validate status transitions for orders.

Requirements

To run the app, you'll need:

You should also be familiar with basic Fauna CLI commands and usage. For an overview, see the Fauna CLI docs.

Setup

  1. Clone the repo and navigate to the js-sample-app directory:

    git clone [email protected]:fauna/js-sample-app.git
    cd js-sample-app
  2. Log in to Fauna using the Fauna CLI:

    fauna cloud-login

    When prompted, enter:

    • Endpoint name: cloud (Press Enter)
    • Email address: The email address for your Fauna account.
    • Password: The password for your Fauna account.
    • Which endpoint would you like to set as default? The cloud-* endpoint for your preferred region group. For example, to use the US region group, use cloud-us.

    The command requires an email and password login. If you log in to the Fauna using GitHub or Netlify, you can enable email and password login using the Forgot Password workflow.

  3. Use the Fauna CLI to create the ECommerce database:

    fauna create-database ECommerce
  4. Create a .fauna-project config file for the project:

    fauna project init

    When prompted, enter:

    • schema as the schema directory.
    • dev as the environment name.
    • The default endpoint.
    • ECommerce as the database.
  5. Push the .fsl files in the schema directory to the ECommerce database:

    fauna schema push

    When prompted, accept and stage the schema.

  6. Check the status of the staged schema:

    fauna schema status
  7. When the status is ready, commit the staged schema to the database:

    fauna schema commit

    The commit applies the staged schema to the database. The commit creates the collections and user-defined functions (UDFs) defined in the .fsl files of the schema directory.

  8. Create a key with the server role for the ECommerce database:

    fauna create-key --environment='' ECommerce server

    Copy the returned secret. The app can use the key's secret to authenticate requests to the database.

  9. Make a copy of the .env.example file and name the copy .env. For example:

    cp .env.example .env
  10. In .env, set the FAUNA_SECRET environment variable to the secret you copied earlier:

    ...
    FAUNA_SECRET=fn...
    ...
    

Add sample data

The app includes tests that check the app's API endpoints and create related documents in the ECommerce database.

From the root directory, run:

npm install && npm run test

You can view documents created by the tests in the Fauna Dashboard.

Run the app

The app runs an HTTP API server. From the root directory, run:

npm install && npm run dev

Once started, the local server is available at http://localhost:8000.

HTTP API endpoints

The app's HTTP API endpoints are defined in *.controller.ts files in the src/routes directory.

Reference documentation for the endpoints is available at https://fauna.github.io/js-sample-app/.

Make API requests

You can use the endpoints to make API requests that read and write data from the ECommerce database.

For example, with the local server running in a separate terminal tab, run the following curl request to the POST /products endpoint. The request creates a Product collection document in the ECommerce database.

curl -v \
  http://localhost:8000/products \
  -H "Content-Type: application/json" \
  -d '{
    "name": "The Old Man and the Sea",
    "price": 899,
    "description": "A book by Ernest Hemingway",
    "stock": 10,
    "category": "books"
  }'

Expand the app

You can further expand the app by adding fields and endpoints.

As an example, the following steps adds a computed totalPurchaseAmt field to Customer documents and related API responses:

  1. If you haven't already, add the sample data:

    npm install && npm run test
  2. In schema/collections.fsl, add the following totalPurchaseAmt computed field definition to the Customer collection:

    collection Customer {
      ...
      // Use a computed field to get the set of Orders for a customer.
      compute orders: Set<Order> = (customer => Order.byCustomer(customer))
    
    + // Use a computed field to calculate the customer's cumulative purchase total.
    + // The field sums purchase `total` values from the customer's linked Order documents.
    + compute totalPurchaseAmt: Number = (customer => customer.orders.fold(0, (sum, order) => {
    +   let order: Any = order
    +   sum + order.total
    + }))
      ...
    }
    ...

    Save schema/collections.fsl.

  3. Push the updated schema to the ECommerce database:

    fauna schema push

    When prompted, accept and stage the schema.

  4. Check the status of the staged schema:

    fauna schema status
  5. When the status is ready, commit the staged schema changes to the database:

    fauna schema commit
  6. In src/routes/customers/customers.controller.ts, add the totalPurchaseAmt field to the customerResponse FQL template:

    // Project Customer document fields for consistent responses.
    const customerResponse = fql`
      customer {
        id,
        name,
        email,
    +   totalPurchaseAmt,
        address
      }
    `;

    Save src/routes/customers/customers.controller.ts.

    Customer-related endpoints use this template to project Customer document fields in responses.

  7. Start the app server:

    npm install && npm run dev
  8. With the local server running in a separate terminal tab, run the following curl request to the POST /customers endpoint:

    curl -v http://localhost:8000/customers/999

    The response includes the computed totalPurchaseAmt field:

    {
      "id": "999",
      "name": "Valued Customer",
      "email": "[email protected]",
      "totalPurchaseAmt": 27000,
      "address": {
        "street": "123 Main St",
        "city": "San Francisco",
        "state": "CA",
        "postalCode": "12345",
        "country": "United States"
      }
    }