Develop testing code snippets and testing cases to test the code developed across the tasks below. You should also develop a readme file to describe the source code and how to use it. Develop at least one good testing case for tasks below.

Import: Write code to import the dataset files into pandas dataframes, drop duplicates, filter rows containing blanks (NAs), and filter out rows from ratings.csv and tags.csv which pertain to movies that are *not* present in movies.csv.

(b) Similar Movies Retrieval: Write python code using pandas that will solicit user input in terms of a movie id (let the input movie id be X), and will output all movies from the database which have at least one genre common with X and have at least one rating identical to that of one of Xs ratings. For example, if X has genres [Crime|Thriller] and has fetched ratings [3.0, 4.0, 4.0], all Crime or Thriller movie that have fetched at least one rating of 3.0 or 4.0 would be output.

(c) Enhancing Similar Movies Retrieval: Your solution in (b) is observed to produce a large number of movies in response to a user input. Think of a way to use the information from tags.csv to produce a list of tag-based similar subset of the results in (b) to highlight to the user. You should describe your proposed approach and also provide python code to identify the tag-based similar subset of similar movies.

movies.csv - movieId,title,genres

ratings.csv- userId, movieId, rating,timestamp

tags.csv - userId, movieId, tags, timestamp