'''
    DS2000
    Spring 2023
    Sample code from class - recommendation sytem - driver
    
    Algorithm:
        * Have a bunch of TVShow objects =====> NEXT WEEK
        * Ask the user (Laney) for info about a show they 've watched =====> TODAY
        * Recommend shows with similar episode lengths, season,
          user age, and with high rating


    Possible todo --- ask the user for their rating, and recommend
                opposite of something they don't like, similar
                of something they like
'''


import csv
from tvshow import TVShow  

SHOW_FILE = "sec3_recommendations.csv"

def read_file(filename):
    ''' Function: read_file
        Parameter: filename, a string
        Returns: 2d list of strings
        Does: iterates over csv file, turning each row into
                item in 2d list
    '''
    data = []
    with open(filename, "r") as infile:
        csvfile = csv.reader(infile)
        next(csvfile)
        for row in csvfile:
            data.append(row)
    return data

def make_show_objs(lst):
    ''' Function: make_show_objs
        Parameters: 2d list of strings
        Returns: 1d list of TVShow objects
        Does: iterates over list, turns each row into an object
    '''
    shows = []
    for row in lst:
        title = row[0]
        length = int(row[1])
        seasons = int(row[2])
        rating = float(row[3])
        age = int(row[4])
        show = TVShow(title, length = length, seasons = seasons,
                      rating = rating, age = age)
        shows.append(show)
    return shows

def main():
    # gather data - read from the file
    show_lst = read_file(SHOW_FILE)
    
    # Gather data - ask the user for info about their show
    title = input("What show?\n")
    length = int(input("Length of episodes?\n"))
    seasons = int(input("How many seasons?\n"))
    age = int(input("How old are you?\n"))

    # computation - make a list of TVShow objects 
    show_objs = make_show_objs(show_lst)

    # computation - make an object of the TVShow class
    user_show = TVShow(title, age = age, length = length,
                       seasons = seasons)
    
    # computation - filter the list of show_objs to make recommendations
    recs = []
    for show in show_objs:
        if show.recommend(user_show):
            recs.append(show)
            
    # computation - find the nearest euclidean distance
    min_show = None
    min_dist = float("inf")
    for rec in recs:
        dist = rec.euclidean(user_show)
        print("Got distance:", dist)
        if dist < min_dist:
            min_dist = dist
            min_show = rec
            
    
    # communication - tell the user what we recommend
    print("\n\nDS2000 thinks Laney should watch...")
    for rec in recs:
        print(rec)
        
    # communication - tell the user the smallest distance
    print("\nBut start with...", min_show)
    
    
 
    
  
main()