Modeling the App Store and iTunes with Ember Data
summary
Six months of reverse engineering yields a concrete claim: a production search engine called find (find no vowels) that models the App Store and iTunes entirely in the browser using Ember and Ember Data, hosted via GitHub Pages and served from Digital Ocean. It uses Ember Data adapters and serializers with a classifier for polymorphic results, mixins for apps and reviews, and an identity-mapped fetcher for pagination and preloading. It pulls YouTube, Rotten Tomatoes and review data, integrates with Launch Center Pro, and runs faster than the native App Store.
AI-written summary · about
chapters (9)
- 0:00Ember introduction
- 3:36App Store search frustrations
- 7:48Client-side search engine
- 13:01Modeling iTunes data
- 17:31Pagination and API links
- 19:14Dynamic templates
- 20:37Find app features
- 22:44Live demo of Find
- 24:22Q&A
