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Project 2: Netflix Recommendation Engine
Create 1000 lines of acceptance tests in RunNetflix.in and RunNetflix.out that test corner cases and failure cases, and add, commit, and push to the private code repo.
Implement and debug the simplest possible solution in Netflix.py with assertions that check pre-conditions, post-conditions, argument validity, and return-value validity, until all tests pass, and add, commit, and push to the private code repo.
Estimated time: 20 hours
Thurs: 3 hours - Initial framework working, passing unit tests for basic functions
Fri: 3 hours - worked on loading caches
Sat: 3 hours - generate answer cache, pass some RMSE tests
Omar: 3 hours
Sun: 5 hours - think. tried different algorithms.
Angela: 2.5 hours
Wed: 3 hours
calvin24, isabella, jesus92, kimyu92, majisto
Test the Cache loading and retrieval functions.
Write a python tool that parses the movie files to create a two caches. The customer cache and the movie cache.
Copy your unit tests and your acceptance tests to your clone of the public test repo, rename the files, do a git pull to synchronize your clone, and then add, commit and push to the public test repo.
The files MUST be named -RunNetflix.in, -RunNetflix.out, -TestNetflix.py, and -TestNetflix.out in the public test repo.
avg(movie avg + customer avg)
Add Skeleton Code modified from collatz
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