This is my third and final article looking at new features in Google Cloud functions as Google starts to narrow the gap to Amazon’s AWS Lambda.
This is my third and final article looking at new features in Google Cloud functions as Google starts to narrow the gap to Amazon’s AWS Lambda product. Until recently Node.js 6 was the only option for writing Google Cloud functions. That’s changed now with the addition of Node.js 8 (read my article) and Python 3 runtimes available in public beta.
Let’s take a look at how to use the Python environment by deploying a HTTP function that performs the same task as my Node.js 8 Cloud Functions demo does. We’ll use the
requests library and randomuser.me API to output a JSON object representing data about a single user, then add one extra key
Items of note here include:
requestargument will be a Flask request object
make_response— in this case, we pass a JSON string
requirements.txtwhich looks like this for our example (version numbers can also be specified e.g.
(Flask is provided as part of the environment, so isn’t listed here).
When deploying this function we have to tell Google to use the Python 3 runtime. To do this we’ll need to make sure we have the latest
gcloud beta commands:
$ gcloud components update
$ gcloud components install beta
Deployment is simple (we have to use the
beta commands and explicitly say we want the Python runtime):
$ gcloud beta functions deploy getUserDetails --runtime python37 --trigger-http --project <projectId>
<projectId> is the ID of your Google Cloud project. The function can be invoked simply bu visiting its URL which will look something like:
<projectId> will depend on your Google Cloud project setup, and the
gcloud command will display the full invocation URL for your function at the end of a successful deployment.
The output looks like this:
The Cloud Functions console also shows that the function is using the Python runtime:
And that’s all there is to it!
This article originally appeared on Simon's Medium.