how to test Cloud Functions for Firebase locally on pc

Question

Today Firebase released its brand new product Cloud Functions for Firebase and I just created a hello world function and deploy it on my existing firebase project.

It looks like it bundles all dependencies and upload it to firebase just like aws lambda function does. But it takes too much time to be done even on minor changes in code and also need a good connectivity of internet . If you are offline for some reason, you are just in dark what code you are writing until you have a way to execute and test that functions offline on your local machine.

Is there any way to test Cloud Functions for Firebase locally?

Answer 1

firebaser here

Deployment of your Functions indeed takes more time than what I'm normally willing to wait for. We're working hard to improve that and (as Brendan said) are working on a local emulator.

But for the moment, I mostly write my actual business logic into a separate Node script first. That way I can test it from a local command prompt with node speech.js. Once I'm satisfied that the function works, I either copy/paste it into my actual Functions file or (better) import the speech module into my functions file and invoke it from there.

One abbreviated example that I quickly dug up is when I was wiring up text extraction using the Cloud Vision API. I have a file called ocr.js that contains:

var fetch = require('node-fetch');

function extract_text(url, gcloud_authorization) {
  console.log('extract_text from image '+url+' with authorization '+gcloud_authorization);

  return fetch(url).then(function(res) {
    return res.buffer();
  }).then(function(buffer) {
    return fetch('https://vision.googleapis.com/v1/images:annotate?key='+gcloud_authorization, {
      method: "POST",
      headers: {
        "Content-Type": "application/json"
      },
      body: JSON.stringify({
        "requests":[
          {
            "image":{
              "content": buffer.toString('base64')
            },
            "features":[
              {
                "type":"TEXT_DETECTION",
                "maxResults":1
              }
            ]
          }
        ]
      })
    });
  }).then(function(res) {
    var json = res.json();
    if (res.status >= 200 && res.status < 300) {
      return json;
    } else {
      return json.then(Promise.reject.bind(Promise));
    }
  }).then(function(json) {
    if (json.responses && json.responses.length && json.responses[0].error) {
      return Promise.reject(json.responses[0].error);
    }
    return json.responses[0].textAnnotations[0].description;
  });
}

if (process.argv.length > 2) {
  // by passing the image URL and gcloud access token, you can test this module
  process.argv.forEach(a => console.log(a));
  extract_text(
    process.argv[2], // image URL
    process.argv[3]  // gcloud access token or API key
  ).then(function(description) {
    console.log(description);
  }).catch(function(error) {
    console.error(error);
  });
}

exports.extract_text = extract_text;

And then in my Functions index.js, I have:

var functions = require('firebase-functions');
var fetch = require('node-fetch');
var ocr = require('./ocr.js');

exports.ocr = functions.database().path('/messages/{room}/{id}').onWrite(function(event) {
  console.log('OCR triggered for /messages/'+event.params.room+'/'+event.params.id);

  if (!event.data || !event.data.exists()) return;
  if (event.data.ocr) return;
  if (event.data.val().text.indexOf("https://firebasestorage.googleapis.com/") !== 0) return; // only OCR images

  console.log(JSON.stringify(functions.env));

  return ocr.extract_text(event.data.val().text, functions.env.googlecloud.apikey).then(function(text) {
    return event.data.adminRef.update({ ocr: text });
  });
});

So as you can see this last file is really just about wiring up the "worker method" ocr.extract_text to the database location.

Note this is a project from a while ago, so some of the syntax (mostly the functions.env part) might have changed a bit.