{"action":"opened","issue":{"url":"https://api.github.com/repos/tiyd-python-2015-08/assigments/issues/288","labels_url":"https://api.github.com/repos/tiyd-python-2015-08/assigments/issues/288/labels{/name}","comments_url":"https://api.github.com/repos/tiyd-python-2015-08/assigments/issues/288/comments","events_url":"https://api.github.com/repos/tiyd-python-2015-08/assigments/issues/288/events","html_url":"https://github.com/tiyd-python-2015-08/assigments/issues/288","id":109353916,"number":288,"title":"20 -- Polyglot -- Jonathan Frederick","user":{"login":"JonathanFrederick","id":11638659,"avatar_url":"https://avatars.githubusercontent.com/u/11638659?v=3","gravatar_id":"","url":"https://api.github.com/users/JonathanFrederick","html_url":"https://github.com/JonathanFrederick","followers_url":"https://api.github.com/users/JonathanFrederick/followers","following_url":"https://api.github.com/users/JonathanFrederick/following{/other_user}","gists_url":"https://api.github.com/users/JonathanFrederick/gists{/gist_id}","starred_url":"https://api.github.com/users/JonathanFrederick/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/JonathanFrederick/subscriptions","organizations_url":"https://api.github.com/users/JonathanFrederick/orgs","repos_url":"https://api.github.com/users/JonathanFrederick/repos","events_url":"https://api.github.com/users/JonathanFrederick/events{/privacy}","received_events_url":"https://api.github.com/users/JonathanFrederick/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"milestone":null,"comments":0,"created_at":"2015-10-01T18:15:52Z","updated_at":"2015-10-01T18:15:52Z","closed_at":null,"body":"* [ ] Blank slate\r\n  * [ ] Create a GitHub repo called `programming-language-classifier`\r\n  * [ ] Set up your requirements/virtual environment\r\n  * [ ] Copy all the files from this folder into your repo\r\n* [ ] Normal mode\r\n  * [ ] Collect a corpus of programming language snippets to use for training data\r\n  * [ ] Extract features from your corpus for your classifier, either using an existing Transformer or one you've written\r\n    * [ ] **Be sure you can explain at a high-level how your Transfomer works**\r\n  * [ ] Write a classifier function that takes a string of code and returns a guess for the language the code was written in\r\n  * [ ] Test your classifier using the provided test files\r\n    * [ ] **Be sure you do not use the test files as your training data**\r\n  * [ ] Demonstrate the use/results of your classifier in an IPython notebook\r\n* [ ] Hard mode\r\n  * [ ] Create a runnable Python file that takes a command-line argument of a source code file and prints out the guessed programming language\r\n  * [ ] Calculate the probability of various programming languages, and return the top percentages probable\r\n  * [ ] Add command-line flags to make your program more versatile"}}