Python 3 on Google App Engine flexible environment now in beta

Developers running Python on Google App Engine have long asked for support for Python 3 and third-party Python packages. Today we're excited to announce the beta release of the Python runtime on App Engine Flexible Environment with support for Python 3.4 and 2.7. You can now develop applications in the Python version you prefer and create performant mobile and web backends using the frameworks and libraries of your choice. Meanwhile, developers benefit from App Engine's built-in services, such as autoscaling, load balancing, microservices support and traffic splitting and hence can focus on their code and not worry about infrastructure maintenance.

Here at Google, we're committed to the open-source model and strive for product designs that promote choice for developers. App Engine Flexible Environment runtimes are simple and lean, distributed on github, and can access services from any cloud platform provider, including Google Cloud Platform using the Python Client Libraries. Because of containerization, you can run your application on App Engine Flexible, Google Container Engine, Google Compute Engine, locally (for example by using minikube), and on any cloud provider that supports containers.

Getting started with Python on App Engine is easy. The best place to start is the Python developer hub, where we've gathered everything Python in one place. If you’re new to App Engine, we recommend trying out this Quickstart to get a sense of how App Engine Flexible works. Here's a quick video of the quickstart experience for you to watch.

For more experienced users and those who wish to learn more about Python on Google Cloud Platform, we recommend completing the bookshelf tutorial.

When running a Python application on App Engine, you can use the tools and databases you already know and love. Use Flask, Django, Pyramid, Falcon, Tornado or any other framework to build your app. You can also check out samples on how to use MongoDB, MySQL or Google Cloud Datastore.

Using the Google cloud client library, you can take advantage of Google’s advanced APIs and services, including Google BigQuery, Google Cloud Pub/Sub, and Google Cloud Storage using simple and easy-to-understand API formatting:

from gcloud import storage
client = storage.Client(‘<your-project-id>’)
bucket = client.get_bucket('<your-bucket-name>')
blob = bucket.blob('my-test-file.txt')
blob.upload_from_string('this is test content!')

We're thrilled to welcome Python 3 developers to Google Cloud Platform and are committed to making further investments in App Engine Standard and Flexible to help make you as productive as possible.

Feel free to reach out to us on Twitter using the handle @googlecloud. We're also on the Google Cloud Slack community. To get in touch, request an invite to join the Slack Python channel.