def check_na(column, movies):
if column == "RT" or column == "Rotten Tomatoes":
movies = column_checker('take_movie_while', movies, 'rating_rt')
elif column == "IMDb" or column == "Internet Movie Database":
movies = column_checker('take_movie_while', movies, 'rating_imdb')
elif column == "Metacritic" or column == "MC":
movies = column_checker('take_movie_while', movies,
'rating_metacritic')
elif column == "date":
movies = column_checker('take_movie_while', movies, 'date')
elif column == "box_office":
movies = column_checker('take_movie_while', movies, 'box_office')
return movies
def rating_filter(movies, r_min, r_max, r_type):
if r_type == "Internet Movie Database" or r_type == "IMBd":
movies = column_checker('popular_movies', movies, 'rating_imdb')
movies = filter(lambda movie: _imdb(movie['rating_imdb']) > r_min
and _imdb(movie['rating_imbd']) < r_max, movies)
elif r_type == "Rotten Tomatoes" or r_type == "RT":
movies = column_checker('popular_movies', movies, 'rating_rt')
movies = filter(lambda movie: _rt(movie['rating_rt']) > r_min
and _rt(movie['rating_rt']) < r_max, movies)
elif r_type == "Metacritic" or r_type == "MC":
movies = column_checker('popular_movies', movies, 'rating_metacritic')
movies = filter(lambda movie: _mc(movie['rating_metacritic']) > r_min
and _mc(movie['rating_metacritic']) < r_max, movies)
for movie in movies:
yield movie
def filter_by_date(movies: Generator,
date: int, lower: bool = True) -> Generator:
movies = column_checker('filter_by_date', movies, 'date')
if lower:
movies = filter(lambda movie: int(movie['date']) < date, movies)
else:
movies = filter(lambda movie: int(movie['date']) > date, movies)
for movie in movies:
yield movie
def _movies_rating(movies: Generator, r_type: str) -> Generator:
if r_type == "All":
movies = rating_columns_checker('popular_actors', movies)
movies = map(lambda movie: [movie['id'], _rating(movie['rating_imdb'],
movie['rating_rt'], movie['rating_metacritic'])], movies)
if r_type == "Rotten Tomatoes" or r_type == "RT":
movies = column_checker('popular_actors', movies, 'rating_rt')
movies = map(lambda movie: [movie['id'], _rt(movie['rating_rt'])],
movies)
if r_type == "Internet Movie Database" or r_type == "IMDb":
movies = column_checker('popular_actors', movies, 'rating_imdb')
movies = map(lambda movie: [movie['id'], _imdb(movie['rating_imdb'])],
movies)
if r_type == "Metacritic" or r_type == "MC":
movies = column_checker('popular_actors', movies, 'rating_metacritic')
movies = map(lambda movie: [movie['id'],
_mc(movie['rating_metacritic'])], movies)
for movie in movies:
yield movie
def highest_paid_actors(movies: Generator, k_actors: int = 1) -> List[str]:
movies = column_checker('highest_paid_actors', movies, 'box_office')
movies = list(movies)
actors = map(lambda actor: actor['actor'], load_actors())
actors = list(set(actors))
actors_earnings = list(
map(lambda actor: actor_earnings(actor, movies), actors))
actors_earnings.sort(key=lambda x: x[1], reverse=True)
actors = actors_earnings[:k_actors]
actors = [
str([actor[1], actor[0],
top_movies(actor[1], movies)]) for actor in actors
]
return actors