The right way to use App Engine Memcache in Flask apps (Module 12)

Posted by Wesley Chun

Background

In our geared toward serving to builders modernize their serverless purposes, one of many key goals for Google App Engine builders is to improve to the most recent language runtimes, similar to from Python 2 to three or Java 8 to 17. One other goal is to assist builders learn to transfer away from App Engine legacy APIs (now known as “bundled companies”) to Cloud standalone equal companies. As soon as this has been achieved, apps are rather more moveable, making them versatile sufficient to:

In right this moment’s Module 12 video, we will begin our journey by implementing App Engine’s Memcache bundled service, setting us up for our subsequent transfer to a extra full in-cloud caching service, Cloud Memorystore. Most apps sometimes depend on some database, and in lots of conditions, they’ll profit from a caching layer to scale back the variety of queries and enhance response latency. Within the video, we add use of Memcache to a Python 2 app that has already migrated internet frameworks from webapp2 to Flask, offering higher portability and execution choices. Extra importantly, it paves the best way for an eventual 3.x improve as a result of the Python 3 App Engine runtime doesn’t help webapp2. We’ll cowl each the three.x and Cloud Memorystore ports subsequent in Module 13.

Including use of Memcache

The pattern utility registers particular person internet web page “visits,” storing customer info such because the IP deal with and person agent. Within the unique app, these values are saved instantly, after which the latest visits are queried to show within the browser. If the identical person constantly refreshes their browser, every refresh constitutes a brand new go to. To discourage such a abuse, we cache the identical person’s go to for an hour, returning the identical cached listing of most up-to-date visits until a brand new customer arrives or an hour has elapsed since their preliminary go to.

Beneath is pseudocode representing the core a part of the app that saves new visits and queries for the latest visits. Earlier than, you’ll be able to see how every go to is registered. After the replace, the app makes an attempt to fetch these visits from the cache. If cached outcomes can be found and “contemporary” (throughout the hour), they’re used instantly, but when cache is empty, or a brand new customer arrives, the present go to is saved as earlier than, and this newest assortment of visits is cached for an hour. The bolded strains signify the brand new code that manages the cached knowledge.

Wrap-up

Right this moment’s “migration” started with the Module 1 pattern app. We added a Memcache-based caching layer and arrived on the end line with the Module 12 pattern app. To follow this by yourself, observe the codelab doing it by-hand whereas following the video. The Module 12 app will then be able to improve to Cloud Memorystore do you have to select to take action.

In Fall 2021, the App Engine staff prolonged help of most of the bundled companies to next-generation runtimes, that means you might be now not required emigrate to Cloud Memorystore when porting your app to Python 3. You may proceed utilizing Memcache in your Python 3 app as long as you retrofit the code to entry bundled companies from next-generation runtimes.

In the event you do need to transfer to Cloud Memorystore, keep tuned for the Module 13 video or attempt its codelab to get a sneak peek. All Serverless Migration Station content material (codelabs, movies, supply code [when available]) will be accessed at its open supply repo. Whereas our content material initially focuses on Python customers, we hope to in the future cowl different language runtimes, so keep tuned. For added video content material, try our broader Serverless Expeditions collection.