Netlify + FaunaDB    

Example of using FaunaDB with Netlify functions

• About this application
• Setup & Run Locally
• TLDR; Quick Deploy
• Tutorial
  • Background
  • 1. Create React app
  • 2. Create a function
    • Anatomy of a Lambda function
    • Setting up functions for local development
  • 4. Connect the function to the frontend app
  • 5. Finishing the Backend Functions
  • Wrapping Up

About this application

This application is using React for the frontend, Netlify Functions for API calls, and FaunaDB as the backing database.

Setup & Run Locally

1. Clone down the repository

   git clone git@github.com:netlify/netlify-faunadb-example.git

2. Install the dependencies

   npm install

3. Run project locally

   npm start

TLDR; Quick Deploy

1. Click the Deploy to Netlify Button

Tutorial

Background

This application is using React for the frontend, Netlify Functions for API calls, and FaunaDB as the backing database.

We are going to explore how to get up and running with netlify functions and how to deploy your own serverless backend.

So, lets dive right in!

1. Create React app

We are using React for this demo app, but you can use whatever you want to manage the frontend.

Into VueJS? Awesome use that.

Miss the days of jQuery? Righto jQuery away!

Fan of vanillaJS? By all means, have at it!

1. Install create react app

   npm install create-react-app -g

2. Create the react app!

   create-react-app my-app

3. The react app is now setup!

   # change directories into my-app
   cd my-app
   # start the app
   npm start

2. Create a function

Now, lets create a function for our app and wire that up to run locally.

The functions in our project are going to live in a /functions folder. You can set this to whatever you'd like but we like the /functions convention.

Anatomy of a Lambda function

All AWS Lambda functions have the following signature:

exports.handler = (event, context, callback) => {
  // "event" has informatiom about the path, body, headers etc of the request
  console.log('event', event)
  // "context" has information about the lambda environment and user details
  console.log('context', context)
  // The "callback" ends the execution of the function and returns a reponse back to the caller
  return callback(null, {
    statusCode: 200,
    body: JSON.stringify({
      data: '⊂◉‿◉つ'
    })
  })
}

We are going to use the faunadb npm package to connect to our Fauna Database and create an item

Setting up functions for local development

Lets rock and roll.

1. Create a ./functions directory

   # make functions directory
   mdkir functions

2. Install netlify-lambda

   Netlify lambda is a tool for locally emulating the serverless function for development and for bundling our serverless function with third party npm modules (if we are using those)

   npm i netlify-lambda --save-dev
   

   To simulate our function endpoints locally, we need to setup a proxy for webpack to use.

   In package.json add:

   {
     "name": "react-lambda",
     ...
     "proxy": {
       "/.netlify/functions": {
         "target": "http://localhost:9000",
         "pathRewrite": {
           "^/\\.netlify/functions": ""
         }
       }
     }
   }

   This will proxy requests we make to /.netlify/functions to our locally running function server at port 9000.

3. Add our start & build commands

   Lets go ahead and add our start & build command to npm scripts in package.json. These will let us running things locally and give a command for netlify to run to build our app & functions when we are ready to deploy.

   We are going to be using the npm-run-all npm module to run our frontend & backend in parallel in the same terminal window.

   So install it!

   npm install npm-run-all --save-dev
   

   About npm start

   The start:app command will run react-scripts start to run our react app

   The start:server command will run netlify-lambda serve functions -c ./webpack.config.js to run our function code locally. The -c webpack-config flag lets us set a custom webpack config to fix a module issue with faunaDB module.

   Running npm start in our terminal will run npm-run-all --parallel start:app start:server to fire them both up at once.

   About npm build

   The build:app command will run react-scripts build to run our react app

   The build:server command will run netlify-lambda build functions -c ./webpack.config.js to run our function code locally.

   Running npm run build in our terminal will run npm-run-all --parallel build:** to fire them both up at once.

   Your package.json should look like

   {
     "name": "netlify-fauna",
     "scripts": {
       "👇 ABOUT-bootstrap-command": "💡 scaffold and setup FaunaDB #",
       "bootstrap": "node ./scripts/bootstrap-fauna-database.js",
       "👇 ABOUT-start-command": "💡 start the app and server #",
       "start": "npm-run-all --parallel start:app start:server",
       "start:app": "react-scripts start",
       "start:server": "netlify-lambda serve functions -c ./webpack.config.js",
       "👇 ABOUT-prebuild-command": "💡 before 'build' runs, run the 'bootstrap' command #",
       "prebuild": "echo 'setup faunaDB' && npm run bootstrap",
       "👇 ABOUT-build-command": "💡 build the react app and the serverless functions #",
       "build": "npm-run-all --parallel build:**",
       "build:app": "react-scripts build",
       "build:functions": "netlify-lambda build functions -c ./webpack.config.js",
     },
     "dependencies": {
       "faunadb": "^0.2.2",
       "react": "^16.4.0",
       "react-dom": "^16.4.0",
       "react-scripts": "1.1.4"
     },
     "devDependencies": {
       "netlify-lambda": "^0.4.0",
       "npm-run-all": "^4.1.3"
     },
     "proxy": {
       "/.netlify/functions": {
         "target": "http://localhost:9000",
         "pathRewrite": {
           "^/\\.netlify/functions": ""
         }
       }
     }
   }
   

4. Install FaunaDB and write the create function

   We are going to be using the faunadb npm module to call into our todos index in FaunaDB.

   So install it in the project

   npm i faunadb --save

   Then create a new function file in /functions called todos-create.js

   /* code from functions/todos-create.js */
   import faunadb from 'faunadb' /* Import faunaDB sdk */
   
   /* configure faunaDB Client with our secret */
   const q = faunadb.query
   const client = new faunadb.Client({
     secret: process.env.FAUNADB_SERVER_SECRET
   })
   
   /* export our lambda function as named "handler" export */
   exports.handler = (event, context, callback) => {
     /* parse the string body into a useable JS object */
     const data = JSON.parse(event.body)
     console.log('Hello webinar. Function `todo-create` invoked', data)
     const todoItem = {
       data: data
     }
     /* construct the fauna query */
     return client.query(q.Create(q.Ref('classes/todos'), todoItem))
       .then((response) => {
         console.log('success', response)
         /* Success! return the response with statusCode 200 */
         return callback(null, {
           statusCode: 200,
           body: JSON.stringify(response)
         })
       }).catch((error) => {
         console.log('error', error)
         /* Error! return the error with statusCode 400 */
         return callback(null, {
           statusCode: 400,
           body: JSON.stringify(error)
         })
       })
   }

4. Connect the function to the frontend app

Inside of the react app, we can now wire up the /.netlify/functions/todos-create endpoint to an AJAX request.

// Function using fetch to POST to our API endpoint
function createTodo(data) {
  return fetch('/.netlify/functions/todos-create', {
    body: JSON.stringify(data),
    method: 'POST'
  }).then(response => {
    return response.json()
  })
}

// Todo data
const myTodo = {
  title: 'My todo title',
  completed: false,
}

// create it!
createTodo(myTodo).then((response) => {
  console.log('API response', response)
  // set app state
}).catch((error) => {
  console.log('API error', error)
})

Requests to /.netlify/function/[Function-File-Name] will work seamlessly on localhost and on the live site because we are using the local proxy with webpack.

We will be skipping over the rest of the frontend parts of the app because you can use whatever framework you'd like to build your application.

All the demo React frontend code is available here

5. Finishing the Backend Functions

So far we have created our todo-create function done and we've seen how we make requests to our live function endpoints. It's now time to add the rest of our CRUD functions to manage our todos.

1. Read Todos by ID

   Then create a new function file in /functions called todos-read.js

   /* code from functions/todos-read.js */
   import faunadb from 'faunadb'
   import getId from './utils/getId'
   
   const q = faunadb.query
   const client = new faunadb.Client({
     secret: process.env.FAUNADB_SERVER_SECRET
   })
   
   exports.handler = (event, context, callback) => {
     const id = getId(event.path)
     console.log(`Function 'todo-read' invoked. Read id: ${id}`)
     return client.query(q.Get(q.Ref(`classes/todos/${id}`)))
       .then((response) => {
         console.log('success', response)
         return callback(null, {
           statusCode: 200,
           body: JSON.stringify(response)
         })
       }).catch((error) => {
         console.log('error', error)
         return callback(null, {
           statusCode: 400,
           body: JSON.stringify(error)
         })
       })
   }

2. Read All Todos

   Then create a new function file in /functions called todos-read-all.js

   /* code from functions/todos-read-all.js */
   import faunadb from 'faunadb'
   
   const q = faunadb.query
   const client = new faunadb.Client({
     secret: process.env.FAUNADB_SERVER_SECRET
   })
   
   exports.handler = (event, context, callback) => {
     console.log('Function `todo-read-all` invoked')
     return client.query(q.Paginate(q.Match(q.Ref('indexes/all_todos'))))
       .then((response) => {
         const todoRefs = response.data
         console.log('Todo refs', todoRefs)
         console.log(`${todoRefs.length} todos found`)
         // create new query out of todo refs. http://bit.ly/2LG3MLg
         const getAllTodoDataQuery = todoRefs.map((ref) => {
           return q.Get(ref)
         })
         // then query the refs
         return client.query(getAllTodoDataQuery).then((ret) => {
           return callback(null, {
             statusCode: 200,
             body: JSON.stringify(ret)
           })
         })
       }).catch((error) => {
         console.log('error', error)
         return callback(null, {
           statusCode: 400,
           body: JSON.stringify(error)
         })
       })
   }

3. Update todo by ID

   Then create a new function file in /functions called todos-update.js

   /* code from functions/todos-update.js */
   import faunadb from 'faunadb'
   import getId from './utils/getId'
   
   const q = faunadb.query
   const client = new faunadb.Client({
     secret: process.env.FAUNADB_SERVER_SECRET
   })
   
   exports.handler = (event, context, callback) => {
     const data = JSON.parse(event.body)
     const id = getId(event.path)
     console.log(`Function 'todo-update' invoked. update id: ${id}`)
     return client.query(q.Update(q.Ref(`classes/todos/${id}`), {data}))
       .then((response) => {
         console.log('success', response)
         return callback(null, {
           statusCode: 200,
           body: JSON.stringify(response)
         })
       }).catch((error) => {
         console.log('error', error)
         return callback(null, {
           statusCode: 400,
           body: JSON.stringify(error)
         })
       })
   }

4. Delete by ID

   Then create a new function file in /functions called todos-delete.js

   /* code from functions/todos-delete.js */
   import faunadb from 'faunadb'
   import getId from './utils/getId'
   
   const q = faunadb.query
   const client = new faunadb.Client({
     secret: process.env.FAUNADB_SERVER_SECRET
   })
   
   exports.handler = (event, context, callback) => {
     const id = getId(event.path)
     console.log(`Function 'todo-delete' invoked. delete id: ${id}`)
     return client.query(q.Delete(q.Ref(`classes/todos/${id}`)))
       .then((response) => {
         console.log('success', response)
         return callback(null, {
           statusCode: 200,
           body: JSON.stringify(response)
         })
       }).catch((error) => {
         console.log('error', error)
         return callback(null, {
           statusCode: 400,
           body: JSON.stringify(error)
         })
       })
   }

5. Delete batch todos

   Then create a new function file in /functions called todos-delete-batch.js

   /* code from functions/todos-delete-batch.js */
   import faunadb from 'faunadb'
   import getId from './utils/getId'
   
   const q = faunadb.query
   const client = new faunadb.Client({
     secret: process.env.FAUNADB_SERVER_SECRET
   })
   
   exports.handler = (event, context, callback) => {
     const data = JSON.parse(event.body)
     console.log('data', data)
     console.log('Function `todo-delete-batch` invoked', data.ids)
     // construct batch query from IDs
     const deleteAllCompletedTodoQuery = data.ids.map((id) => {
       return q.Delete(q.Ref(`classes/todos/${id}`))
     })
     // Hit fauna with the query to delete the completed items
     return client.query(deleteAllCompletedTodoQuery)
       .then((response) => {
         console.log('success', response)
         return callback(null, {
           statusCode: 200,
           body: JSON.stringify(response)
         })
       }).catch((error) => {
         console.log('error', error)
         return callback(null, {
           statusCode: 400,
           body: JSON.stringify(error)
         })
       })
   }

After we deploy all these functions, we will be able to call them from our frontend code with these fetch calls:

/* Frontend code from src/utils/api.js */
/* Api methods to call /functions */

const create = (data) => {
  return fetch('/.netlify/functions/todos-create', {
    body: JSON.stringify(data),
    method: 'POST'
  }).then(response => {
    return response.json()
  })
}

const readAll = () => {
  return fetch('/.netlify/functions/todos-read-all').then((response) => {
    return response.json()
  })
}

const update = (todoId, data) => {
  return fetch(`/.netlify/functions/todos-update/${todoId}`, {
    body: JSON.stringify(data),
    method: 'POST'
  }).then(response => {
    return response.json()
  })
}

const deleteTodo = (todoId) => {
  return fetch(`/.netlify/functions/todos-delete/${todoId}`, {
    method: 'POST',
  }).then(response => {
    return response.json()
  })
}

const batchDeleteTodo = (todoIds) => {
  return fetch(`/.netlify/functions/todos-delete-batch`, {
    body: JSON.stringify({
      ids: todoIds
    }),
    method: 'POST'
  }).then(response => {
    return response.json()
  })
}

export default {
  create: create,
  readAll: readAll,
  update: update,
  delete: deleteTodo,
  batchDelete: batchDeleteTodo
}

Wrapping Up

I hope you have enjoyed this tutorial on building your own CRUD API using Netlify serverless functions and FaunaDB.

As you can see, functions can be extremely powerful when combined with a cloud database!

The sky is the limit on what you can build with the JAM stack and we'd love to hear about what you make.

Next Steps

This example can be improved with users/authentication. Next steps to build out the app would be:

• Add in the concept of users for everyone to have their own todo list
• Wire up authentication using Netlify Identity JWTs
• Add in due dates to todos and wire up Functions to notify users via email/SMS
• File for IPO?