In this project, you will build a webapp where users can vote for their favorite pieces of media.

In contrast to previous projects, instead of implementing a pre-defined spec you will be imitating an existing site: http://media-ranker-2-0.herokuapp.com. Your job is to match the functionality and styling of this site as closely as possible.

This is an individual, stage 2 project.

The purpose of this assignment is to reinforce the following concepts:

• Previous Rails learning, including MVC, RESTful routing, and the request cycle
• Testing Rails applications
• Building complex model logic
• Using session and flash to track data between requests
• DRYing up Rails code
• Working with a CSS framework
• Styling a page based on an existing design

• db/media_seeds.csv: Some starter media to work with
• app/assets/images/owl.jpg: The owl picture from the site

The Rails inflector considers "media" to be the plural of "medium", which is not really what we mean here. You may want to choose a different word to represent "a book, movie or album" internally. The instructor-proved example site uses the word "work".

Regardless of how you choose to implement this project or how much of it gets done, you should exhibit

• Squeaky-clean git hygiene, including
  • A fresh branch for each new feature
  • Regular commits
  • Descriptive commit messages
• Fanatical devotion to test-driven development
  • Pseudocode first, then write the tests, then write code to make them pass
• Steadfast adherence to agile development practices
  • User stories should be listed and prioritized using a Trello board
  • The finished application should be deployed to Heroku (deploy early, deploy often)
• Unrelenting use of semantic HTML

We will begin with some in-class work, exploring the site and pondering implementation details. Before you start writing any code, you should:

• Explore the existing Media Ranker site to become familiar with the necessary functionality
• Create a Trello board to manage user stories
• Create an ERD for the models

Then, once you have a solid plan for how to structure your project:

• Fork and clone the repo
• Use rails new . to generate a new Rails project in the cloned directory
  • Verify that the changes we've made to Rails' defaults (postgres as the DB, spec-style testing) have been applied
• git init, git add . and git commit -m "Initial Rails setup"

Mimic the site's basic functionality around Media, without worrying (yet) about Users or Votes:

• Build a main page, with a list of the top 10 media of each category, as well as a spotlight section for the top media overall
• Build an index page for each media category
• Build a details page for each piece of media
• Make sure any models and controllers you've built so far are well-tested

Mimic the site's functionality around Users and Voting:

• Allow users to "log in" to the site, and use the session to keep track of which user is currently logged in for a given browser
• Allow users to vote for media, and sort media by vote count whenever a list of media is displayed
• Add a list of voting users to the details page for each media
• Don't allow a user to vote for the same media more than once
• Add a page for each user, as well as a page showing a summary of all users
• Make sure any models and controllers you've built so far are well-tested

Passwords and security are tricky! We'll talk about that sort of thing a little in the coming weeks, but for now you don't need to provide any sort of security. The user gives you a username, and your site should just trust them.

Use Foundation to style the site to match the example. The layout as well as the look and feel should match as close as possible.

Once your test coverage is comprehensive, your HTML is semantic, your user stories have all been moved to the Done column and your application has been deployed to Heroku, you may consider the following enhancements.

1. DRY up your code as much as you can! Techniques worth investigating:
   • Helper methods
   • Controller filters
   • Polymorphic routes
2. Add a recommendation system that suggests media to a user based on what they have previously voted for.