Get started: write, test, and deploy your first functions

To get started with Cloud Functions, try working through this tutorial, which starts with the required setup tasks and works through creating, testing, and deploying two related functions:

• An "add message" function that exposes a URL that accepts a text value and writes it to Cloud Firestore.
• A "make uppercase" function that triggers on a Cloud Firestore write and transforms the text to uppercase.

Here's the full sample code containing the functions:

// The Cloud Functions for Firebase SDK to create Cloud Functions and triggers.
const {logger} = require("firebase-functions");
const {onRequest} = require("firebase-functions/v2/https");
const {onDocumentCreated} = require("firebase-functions/v2/firestore");

// The Firebase Admin SDK to access Firestore.
const {initializeApp} = require("firebase-admin/app");
const {getFirestore} = require("firebase-admin/firestore");

initializeApp();

// Take the text parameter passed to this HTTP endpoint and insert it into
// Firestore under the path /messages/:documentId/original
exports.addmessage = onRequest(async (req, res) => {
  // Grab the text parameter.
  const original = req.query.text;
  // Push the new message into Firestore using the Firebase Admin SDK.
  const writeResult = await getFirestore()
      .collection("messages")
      .add({original: original});
  // Send back a message that we've successfully written the message
  res.json({result: `Message with ID: ${writeResult.id} added.`});
});

// Listens for new messages added to /messages/:documentId/original
// and saves an uppercased version of the message
// to /messages/:documentId/uppercase
exports.makeuppercase = onDocumentCreated("/messages/{documentId}", (event) => {
  // Grab the current value of what was written to Firestore.
  const original = event.data.data().original;

  // Access the parameter `{documentId}` with `event.params`
  logger.log("Uppercasing", event.params.documentId, original);

  const uppercase = original.toUpperCase();

  // You must return a Promise when performing
  // asynchronous tasks inside a function
  // such as writing to Firestore.
  // Setting an 'uppercase' field in Firestore document returns a Promise.
  return event.data.ref.set({uppercase}, {merge: true});
});
index.js

# The Cloud Functions for Firebase SDK to create Cloud Functions and set up triggers.
from firebase_functions import firestore_fn, https_fn

# The Firebase Admin SDK to access Cloud Firestore.
from firebase_admin import initialize_app, firestore
import google.cloud.firestore

app = initialize_app()


@https_fn.on_request()
def addmessage(req: https_fn.Request) -> https_fn.Response:
    """Take the text parameter passed to this HTTP endpoint and insert it into
    a new document in the messages collection."""
    # Grab the text parameter.
    original = req.args.get("text")
    if original is None:
        return https_fn.Response("No text parameter provided", status=400)

    firestore_client: google.cloud.firestore.Client = firestore.client()

    # Push the new message into Cloud Firestore using the Firebase Admin SDK.
    _, doc_ref = firestore_client.collection("messages").add({"original": original})

    # Send back a message that we've successfully written the message
    return https_fn.Response(f"Message with ID {doc_ref.id} added.")


@firestore_fn.on_document_created(document="messages/{pushId}")
def makeuppercase(event: firestore_fn.Event[firestore_fn.DocumentSnapshot | None]) -> None:
    """Listens for new documents to be added to /messages. If the document has
    an "original" field, creates an "uppercase" field containg the contents of
    "original" in upper case."""

    # Get the value of "original" if it exists.
    if event.data is None:
        return
    try:
        original = event.data.get("original")
    except KeyError:
        # No "original" field, so do nothing.
        return

    # Set the "uppercase" field.
    print(f"Uppercasing {event.params['pushId']}: {original}")
    upper = original.upper()
    event.data.reference.update({"uppercase": upper})
main.py

About this tutorial

We've chosen Cloud Firestore and HTTP-triggered functions for this sample in part because these background triggers can be thoroughly tested through the Firebase Local Emulator Suite. This toolset also supports Realtime Database, Cloud Storage, PubSub, Auth, and HTTP callable triggers. Other types of background triggers such as Remote Config and TestLab triggers can be tested interactively using toolsets not described in this page.

The following sections of this tutorial detail the steps required to build, test, and deploy the sample.

Create a Firebase Project

1. In the Firebase console, click Add project.

   • To add Firebase resources to an existing Google Cloud project, enter its project name or select it from the dropdown menu.

   • To create a new project, enter the desired project name. You can also optionally edit the project ID displayed below the project name.

2. If prompted, review and accept the Firebase terms.

3. Click Continue.

4. (Optional) Set up Google Analytics for your project, which enables you to have an optimal experience using any of the following Firebase products:

   Firebase Crashlytics Firebase Cloud Messaging

   Firebase In-App Messaging Firebase Remote Config

   Remote Config personalization Firebase A/B Testing

   Either select an existing Google Analytics account or to create a new account.

   If you create a new account, select your Analytics reporting location, then accept the data sharing settings and Google Analytics terms for your project.

5. Click Create project (or Add Firebase, if you're using an existing Google Cloud project).

Firebase automatically provisions resources for your Firebase project. When the process completes, you'll be taken to the overview page for your Firebase project in the Firebase console.

Set up your environment and the Firebase CLI

Initialize your project

When you initialize Firebase SDK for Cloud Functions, you create an empty project containing dependencies and some minimal sample code. If you are using Node.js, you can choose either TypeScript or JavaScript for composing functions. For the purposes of this tutorial, you'll also need to initialize Cloud Firestore.

To initialize your project:

1. Run firebase login to log in via the browser and authenticate the Firebase CLI.
2. Go to your Firebase project directory.
3. Run firebase init firestore. For this tutorial, you can accept the default values when prompted for Firestore rules and index files. If you haven't used Cloud Firestore in this project yet, you'll also need to select a starting mode and location for Firestore as described in Get started with Cloud Firestore.
4. Run firebase init functions. The CLI prompts you to choose an existing codebase or initialize and name a new one. When you're just getting started, a single codebase in the default location is adequate; later, as your implementation expands, you might want to organize functions in codebases.

5. The CLI gives you these options for language support:

   • JavaScript
   • TypeScript
   • Python

   For this tutorial, select JavaScript or Python. For authoring in TypeScript, see Write Functions with TypeScript.

6. The CLI gives you an option to install dependencies. This is safe to decline if you want to manage dependencies in another way.

After these commands complete successfully, your project structure looks like this:

myproject
+- .firebaserc    # Hidden file that helps you quickly switch between
|                 # projects with `firebase use`
|
+- firebase.json  # Describes properties for your project
|
+- functions/     # Directory containing all your functions code
      |
      +- .eslintrc.json  # Optional file containing rules for JavaScript linting.
      |
      +- package.json  # npm package file describing your Cloud Functions code
      |
      +- index.js      # Main source file for your Cloud Functions code
      |
      +- node_modules/ # Directory where your dependencies (declared in
                        # package.json) are installed

myproject
+- .firebaserc    # Hidden file that helps you quickly switch between
|                 # projects with `firebase use`
|
+- firebase.json  # Describes properties for your project
|
+- functions/     # Directory containing all your functions code
      |
      +- main.py      # Main source file for your Cloud Functions code
      |
      +- requirements.txt  #  List of the project's modules and packages 
      |
      +- venv/ # Directory where your dependencies are installed

Import the required modules and initialize an app

After you have completed the setup tasks, you can open the source directory and start adding code as described in the following sections. For this sample, your project must import the Cloud Functions and Admin SDK modules. Add lines like the following to your source file:

// The Cloud Functions for Firebase SDK to create Cloud Functions and triggers.
const {logger} = require("firebase-functions");
const {onRequest} = require("firebase-functions/v2/https");
const {onDocumentCreated} = require("firebase-functions/v2/firestore");

// The Firebase Admin SDK to access Firestore.
const {initializeApp} = require("firebase-admin/app");
const {getFirestore} = require("firebase-admin/firestore");

initializeApp();
index.js

# The Cloud Functions for Firebase SDK to create Cloud Functions and set up triggers.
from firebase_functions import firestore_fn, https_fn

# The Firebase Admin SDK to access Cloud Firestore.
from firebase_admin import initialize_app, firestore
import google.cloud.firestore

app = initialize_app()
main.py

These lines load the required modules and initialize an admin app instance from which Cloud Firestore changes can be made. Wherever Admin SDK support is available, as it is for FCM, Authentication, and Firebase Realtime Database, it provides a powerful way to integrate Firebase using Cloud Functions.

The Firebase CLI automatically installs the Firebase Admin SDK and Firebase SDK for Cloud Functions modules when you initialize your project. For more information about adding 3rd party libraries to your project, see Handle Dependencies.

Add the "add message" function

For the "add message" function, add these lines to your source file:

// Take the text parameter passed to this HTTP endpoint and insert it into
// Firestore under the path /messages/:documentId/original
exports.addmessage = onRequest(async (req, res) => {
  // Grab the text parameter.
  const original = req.query.text;
  // Push the new message into Firestore using the Firebase Admin SDK.
  const writeResult = await getFirestore()
      .collection("messages")
      .add({original: original});
  // Send back a message that we've successfully written the message
  res.json({result: `Message with ID: ${writeResult.id} added.`});
});
index.js

@https_fn.on_request()
def addmessage(req: https_fn.Request) -> https_fn.Response:
    """Take the text parameter passed to this HTTP endpoint and insert it into
    a new document in the messages collection."""
    # Grab the text parameter.
    original = req.args.get("text")
    if original is None:
        return https_fn.Response("No text parameter provided", status=400)

    firestore_client: google.cloud.firestore.Client = firestore.client()

    # Push the new message into Cloud Firestore using the Firebase Admin SDK.
    _, doc_ref = firestore_client.collection("messages").add({"original": original})

    # Send back a message that we've successfully written the message
    return https_fn.Response(f"Message with ID {doc_ref.id} added.")
main.py

The "add message" function is an HTTP endpoint. Any request to the endpoint results in request and response objects passed to the the request handler for your platform (onRequest() or on_request).

HTTP functions are synchronous (similar to callable functions), so you should send a response as quickly as possible and defer work using Cloud Firestore. The "add message" HTTP function passes a text value to the HTTP endpoint and inserts it into the database under the path /messages/:documentId/original.

Add the "make uppercase" function

For the "make uppercase" function, add these lines to your source file:

// Listens for new messages added to /messages/:documentId/original
// and saves an uppercased version of the message
// to /messages/:documentId/uppercase
exports.makeuppercase = onDocumentCreated("/messages/{documentId}", (event) => {
  // Grab the current value of what was written to Firestore.
  const original = event.data.data().original;

  // Access the parameter `{documentId}` with `event.params`
  logger.log("Uppercasing", event.params.documentId, original);

  const uppercase = original.toUpperCase();

  // You must return a Promise when performing
  // asynchronous tasks inside a function
  // such as writing to Firestore.
  // Setting an 'uppercase' field in Firestore document returns a Promise.
  return event.data.ref.set({uppercase}, {merge: true});
});
index.js

@firestore_fn.on_document_created(document="messages/{pushId}")
def makeuppercase(event: firestore_fn.Event[firestore_fn.DocumentSnapshot | None]) -> None:
    """Listens for new documents to be added to /messages. If the document has
    an "original" field, creates an "uppercase" field containg the contents of
    "original" in upper case."""

    # Get the value of "original" if it exists.
    if event.data is None:
        return
    try:
        original = event.data.get("original")
    except KeyError:
        # No "original" field, so do nothing.
        return

    # Set the "uppercase" field.
    print(f"Uppercasing {event.params['pushId']}: {original}")
    upper = original.upper()
    event.data.reference.update({"uppercase": upper})
main.py

The "make uppercase" function executes when Cloud Firestore is written to, defining the document to listen on. For performance reasons, you should be as specific as possible.

Braces—for example, {documentId}—surround "parameters," wildcards that expose their matched data in the callback. Cloud Firestore triggers the callback whenever new messages are added.

In Node.js, event-driven functions such as Cloud Firestore events are asynchronous. The callback function should return either a null, an Object, or a Promise. If you do not return anything, the function times out, signaling an error, and is retried. See Sync, Async, and Promises.

Emulate execution of your functions

The Firebase Local Emulator Suite allows you to build and test apps on your local machine instead of deploying to a Firebase project. Local testing during development is strongly recommended, in part because it lowers the risk from coding errors that could potentially incur cost in a production environment (for example, an infinite loop).

To emulate your functions:

1. Run firebase emulators:start and check the output for the URL of the Emulator Suite UI. It defaults to localhost:4000, but may be hosted on a different port on your machine. Enter that URL in your browser to open the Emulator Suite UI.

2. Check the output of the firebase emulators:start command for the URL of the HTTP function. It will look similar to http://localhost:5001/MY_PROJECT/us-central1/addMessage, except that:

   1. MY_PROJECT will be replaced with your project ID.
   2. The port may be different on your local machine.

3. Add the query string ?text=uppercaseme to the end of the function's URL. This should look something like: http://localhost:5001/MY_PROJECT/us-central1/addMessage?text=uppercaseme. Optionally, you can change the message "uppercaseme" to a custom message.

4. Create a new message by opening the URL in a new tab in your browser.

5. View the effects of the functions in the Emulator Suite UI:

   1. In the Logs tab, you should see new logs indicating that your HTTP functions ran successfully:

      i functions: Beginning execution of "addMessage"

      i functions: Beginning execution of "makeUppercase"

   2. In the Firestore tab, you should see a document containing your original message as well as the uppercased version of your message (if it was originally "uppercaseme", you'll see "UPPERCASEME").

Deploy functions to a production environment

Once your functions are working as desired in the emulator, you can proceed to deploying, testing, and running them in the production environment. Keep in mind that to deploy in production, your project must be on the Blaze pricing plan. See Cloud Functions pricing.

To complete the tutorial, deploy your functions and then execute them.

1. Run this command to deploy your functions:

    firebase deploy --only functions
    

   After you run this command, the Firebase CLI outputs the URL for any HTTP function endpoints. In your terminal, you should see a line like the following:

   Function URL (addMessage): https://us-central1-MY_PROJECT.cloudfunctions.net/addMessage
   

   The URL contains your project ID as well as a region for the HTTP function. Though you don't need to worry about it now, some production HTTP functions should specify a location to minimize network latency.

   If you encounter access errors such as "Unable to authorize access to project," try checking your project aliasing.

2. Using the URL output by the CLI, add a text query parameter, and open it in a browser:

   https://us-central1-MY_PROJECT.cloudfunctions.net/addMessage?text=uppercasemetoo
   

   The function executes and redirects the browser to the Firebase console at the database location where the text string is stored. This write event triggers the "make uppercase" function, which writes an uppercase version of the string.

After deploying and executing functions, you can view logs in the Google Cloud console. If you need to delete functions in development or production, use the Firebase CLI.

In production, you may want to optimize function performance and control costs by setting minimum and maximum numbers of instances to run. See Control scaling behavior for more information on these runtime options.

Next steps

In this documentation, you can learn more about how to manage functions for Cloud Functions as well as how to to handle all event types supported by Cloud Functions.

To learn more about Cloud Functions, you could also do the following:

• Read about use cases for Cloud Functions.
• Try the Cloud Functions codelab.
• Review and run code samples on GitHub