Google Cloud Function (getting started)
To create a Google Cloud Function we need a Google Cloud Project and gcloud SDK.
If we have already some projects we can check them by typing:
gcloud projects list
PROJECT_ID NAME PROJECT_NUMBER
gef-ld-toolbox gef-ld-toolbox 1080184168142
gfw-apis Global Forest Watch API 872868960419
resource-watch Resource Watch 312603932249
skydipper-196010 skydipper 230510979472
soc-platform SOC Platform 345072612231
and select one by:
gcloud config set project gef-ld-toolbox
On the example folder we have set the 2 ways we work with cloud functions. Javascript and Python.
You will need to add a main.py file with your function
import ee
import json
with open("privatekey.json") as keyfile:
extracted_key_data = keyfile.read()
credentials = ee.ServiceAccountCredentials(key_data=extracted_key_data)
ee.Initialize(credentials, use_cloud_api=True)
#service_account = '[email protected]'
#credentials = ee.ServiceAccountCredentials(service_account, 'privatekey.json')
#ee.Initialize(credentials)
def serialize_response(url):
return {
'download_url': url
}
def download_image(request):
# For more information about CORS and CORS preflight requests, see
# https://developer.mozilla.org/en-US/docs/Glossary/Preflight_request
# for more information.
# Set CORS headers for the main request
headers = {
'Access-Control-Allow-Origin': '*',
'Content-Type': 'application/json'
}
# Set CORS headers for the preflight request
if request.method == 'OPTIONS':
# Allows GET requests from any origin with the Content-Type
# header and caches preflight response for an 3600s
headers.update({
'Access-Control-Allow-Origin': '*',
'Access-Control-Allow-Methods': 'GET, POST, OPTIONS',
'Access-Control-Allow-Headers': 'Content-Type',
'Access-Control-Max-Age': '3600'
})
return ('', 204, headers)
request = request.get_json()
if 'geometry' in request:
polygon = ee.Geometry.Polygon(request['geometry'].get('features')[0].get('geometry').get('coordinates'))
image = ee.Image(request['assetId']).clip(ee.Geometry(polygon))
else:
image = ee.Image(request['assetId'])
url = image.getDownloadUrl()
return (json.dumps(serialize_response(url)), 200, headers)In the same directory include the privatekey.json with the service account keys and the requirements.txt file.
You can test it with the next lib pip install gcp-functions-emulator
and then run:
gcpfemu -m <path to module/file/main.py> -f <function_name>
Finally cd to that directory and deploy the cloud Function with the following command:
gcloud beta functions deploy <function Name> --runtime python37 --trigger-http
Note that the cloud function name (<function Name>) must match the name of the function we defined.
You will need to add a index.js file with your function
const ee = require('@google/earthengine');
const PRIVATE_KEY = require('./privatekey.json');
const serialize = (originalData) => {
return JSON.stringify({
rows: [originalData]
});
};
const interact_raster = (input) => {
const reducer = {
"reducer":ee.Reducer.first(),
"geometry":ee.Geometry.Point(input.point, 'EPSG:4326'),
"bestEffort":true,
"maxPixels":10e8,
"tileScale":10
}
return ee.Image(input.asset_id).reduceRegion(reducer);
};
exports.rasterInteraction = (req, res) => {
const body = req.body
res.set('Access-Control-Allow-Origin', '*');
res.set('Content-Type', 'application/json');
if (req.method === 'OPTIONS') {
// Send response to OPTIONS requests
res.set('Access-Control-Allow-Methods', 'POST, GET, OPTIONS');
res.set('Access-Control-Allow-Headers', 'Content-Type');
res.set('Access-Control-Max-Age', '3600');
res.status(204).send('');
}
ee.data.authenticateViaPrivateKey(
PRIVATE_KEY,
() => {
ee.initialize(null, null, () => {
const result = interact_raster(body);
result.evaluate((json) => res.status(200).send(serialize(json)));
});
},
e => console.error(`Authentication error: ${e}`)
);
};In the same directory include the privatekey.json with the service account keys and the package.json file.
You can test it adding to your package.json file the next line
"devDependencies": {
"@google-cloud/functions-framework": "^1.2.1"
},
"scripts": {
"start": "functions-framework --target=rasterInteraction"
},Doing a npm install and running the server with npm start and check http://localhost:8080/
To deploy it cd to that directory and deploy the cloud Function with the following command:
gcloud beta functions deploy <function Name> --runtime nodejs10 --trigger-http
Note that the cloud function name (<function Name>) must match the name of the function we defined.
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