Posted by Wesley Chun (@wescpy), Developer Advocate, Google Cloud
Since its original launch in 2008, many of the core Google App Engine services such as Datastore, Memcache, and Blobstore, have matured to become their own standalone products: for example, Cloud Datastore, Cloud Memorystore, and Cloud Storage, respectively. The same is true for App Engine Task Queues with Cloud Tasks. Today's Module 7 episode of Serverless Migration Station reviews how App Engine push tasks work, by adding this feature to an existing App Engine ndb Flask app.
App Engine push queues in Flask apps video
That app is where we left off at the end of Module 1, migrating its web framework from App
Engine webapp2 to Flask. The app registers web page visits, creating
a Datastore Entity for each. After a new record is created, the ten most recent visits are
displayed to the end-user. If the app only shows the latest visits, there is no reason to keep
older visits, so the Module 7 exercise adds a push task that deletes all visits older than the
oldest one shown. Tasks execute asynchronously outside the normal application flow.
The following are the changes being made to the application:
taskqueue) API
Except for #4 which occurs in the HTML template file, these updates are reflected in the "diff"s for the main application file:
Adding App Engine push tasks application source code differences
With these changes implemented, the web app now shows the end-user which visits will be deleted by the new push task:
Sample application output
To do this exercise yourself, check out our corresponding codelab which leads you step-by-step through the process. You can use this in addition to the video, which can provide guidance. You can also review the push queue documentation for more information. Arriving at a fully-functioning Module 7 app featuring App Engine push tasks sets the stage for migrating it to Cloud Tasks (and Cloud NDB) ahead in Module 8.
All migration modules, their videos (when available), codelab tutorials, and source code, can be found in the migration repo. While the content focuses initially on Python users, we will cover other legacy runtimes soon so stay tuned.
