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Full Stack Web Engineer Exercise

Overview

This exercise requires the engineer to perform a range of tasks that are typical in developing, deploying, and operating a live site.

The project is a blank slate, the only artifact being the products.json file, which will form the basis for the application's data model.

The exit criteria of this exercise is to observe:

  • What method and technology was used to deploy core infrastructure like databases, web servers, etc.
  • What technologies were selected and why?
  • What architecture patterns were selected and why?

The over arching goal of this exercise is to gain insight into how the engineer approaches building and deploying a full stack project. Given the limited time box of most of our explorations, a strong grasp of current tools and frameworks crucial to rapidly building prototypes capable of semi-production deployment is key.

Scenario

This exercise is based on a simple end to end scenario; building a basic product viewer web application.

We have a raw product file, products.json, and the following requirements:

  1. That a user can view the product images and titles through a web application
  2. That an application developer can access the data through an API
  3. That a user can search for a product by entering a keyword on the web application
  4. That an operations person can view basic graphs on the load/use of the application

Requirements

Your code should meet the following requirements:

  • Be PEP8 compliant
  • Implement a unit test for each material function, capable of being tested using pytest or nosetest
  • Contain sufficient docstrings and comments to make it easy to reason about

Things to keep in mind

  • Full stack encompasses everything from design, development, deployment and operations
  • This is a mile wide, inch deep exercise, focus on clearing all tasks at the same level, and avoid going deeper than need be into any one task

Submission Process

To avoid dependencies on services like AWS, we suggest you complete your work inside a Docker container, using Ubuntu 13.04 (64 bit) or 13.10 (64 bit) as the base OS, and simply check-in your application's docker file as part of your overall Github fork.