Engineering

Building a Python web application with Elastic App Search

This post is a brief summary of a presentation I gave recently where I deploy Elastic App Search, show off the ease of setup, data indexing, and relevance tuning, and take look at a few of the many refined APIs. It’s also written up in a codelab with step-by-step instructions for building a movies search engine app using Python Flask. The app will work on desktop or mobile and is a fast, simple, and reliable way to query the information. Here’s a quick summary of what you’ll learn:

  • Creating an App Search instance on Elastic Cloud
  • Navigating to the admin console
  • Ingesting data
  • Creating a search experience with a Python client
  • Containerizing the app and deploying it on a cloud platform

A little insight on App Search

Elastic App Search is a ready-to-use, complete search solution with user-friendly relevance tuning and analytics built in. It lets users — of almost any skill level — easily add a powerful and customizable search experience to any application, website, or mobile app using a refined set of APIs and management tools. You can deploy App Search instances from the Elastic Cloud dashboard, so you get all the tooling needed for a powerfully relevant search experience with the operational flexibility and scale of Elastic Cloud. It powers search for thousands of popular applications around the world and it's backed by the speed and relevance of Elasticsearch, no matter how large your deployment grows.

Elastic App Search UI visualization

Starting the App Search tutorial

The tutorial uses Elastic Cloud to deploy App Search. If you’re not a current Elastic Cloud user, you can spin up a free 14-day trial. Then you can jump to the codelab and/or the video presentation to follow along:

App Search codelab tutorial

Thanks for following along! Looking for something to read next? Check out How to build React search experiences quickly and What your Elastic App Search analytics are telling you.