⛔ [NOT SUPPORTED ANYMORE] ⛔

Rotten Tomatoes Scraper

You can extract information about movies and actors that are listed on the Rotten Tomatoes website using this module. Each movie has different metadata such as Rating, Genre, Box Office, Studio, and Scores. The Genre has 20+ subcategories that also gives you more granular information on a movie. These metadata can be helpful for many data science projects. For actors you can extract movies listed in highest-rated or filmography sections depending on your need. This module uses the BeautifulSoup package to parse HTML documents.

Install

The module requires the following libraries:

• bs4
• requests
• lxml

Then, it can be installed using pip:

pip3 install rotten_tomatoes_scraper

Usage

This module contains three classes: CelebrityScraper, MovieScrape and DirectorScraper.

• CelebrityScraper: You can use this class to extract the complete list of movies that a celebrity participated by calling extract_metadata method and using section='filmography'. Plus, you can also extract the list of top ranked movies by using the same method and section='highest'.

from rotten_tomatoes_scraper.rt_scraper import CelebrityScraper

celebrity_scraper = CelebrityScraper(celebrity_name='jack nicholson')
celebrity_scraper.extract_metadata(section='highest')
movie_titles = celebrity_scraper.metadata['movie_titles']

print(movie_titles)
['On a Clear Day You Can See Forever', 'The Shooting', 'Chinatown', 'Broadcast News']

• MovieScraper: You can use this class to extract metadata of movies. You can feed movie_url or movie_title to extract the movie metadata. If you want to find out what movie genres an actor has participated, you can, first, extract the list of movies that he or she participated using CelebrityScraper. Then, you must instantiate the MovieScraper and feed the movie_title to the extract_metada method. You can see the code below.

from rotten_tomatoes_scraper.rt_scraper import MovieScraper

movie_scraper = MovieScraper(movie_title='Vicky Cristina Barcelona')
movie_scraper.extract_metadata()

print(movie_scraper.metadata)
{'Score_Rotten': '81', 'Score_Audience': '74', 'Genre': ['comedy', 'drama', 'romance']}

from rotten_tomatoes_scraper.rt_scraper import MovieScraper

movie_url = 'https://www.rottentomatoes.com/m/marriage_story_2019'
movie_scraper = MovieScraper(movie_url=movie_url)
movie_scraper.extract_metadata()

print(movie_scraper.metadata)
{'Score_Rotten': '94', 'Score_Audience': '85', 'Genre': ['comedy', 'drama']}

• DirectorScraper: You can use this class to extract metadata of directors. You can feed director_url or director_name to extract the director metadata.

from rotten_tomatoes_scraper.rt_scraper import DirectorScraper

director_url = 'https://www.rottentomatoes.com/celebrity/steven_spielberg'
director_scraper = DirectorScraper(director_url=director_url)
director_scraper.extract_metadata()

print(director_scraper.metadata['Jaws'])
{'Year': '1975', 'Score_Rotten': '98', 'Box_Office': '260870000'}

from rotten_tomatoes_scraper.rt_scraper import DirectorScraper

director_scraper = DirectorScraper(director_name='stanley kubrick')
director_scraper.extract_metadata()
movie_titles = list(director_scraper.metadata.keys())

print(movie_titles)
['Eyes Wide Shut', 'Full Metal Jacket', 'The Shining', 'Barry Lyndon', 'A Clockwork Orange', '2001: A Space Odyssey', 
 'Dr. Strangelove Or: How I Learned to Stop Worrying and Love the Bomb', 'Lolita', 'Spartacus', 'Paths of Glory', 
 'The Killing', "Killer's Kiss", 'The Seafarers', 'Fear and Desire', 'Day of the Fight', 'Flying Padre']

This module doesn't give you a full access to all the metadata that you may find in Rotten Tomatoes website. However, you can easily use it to extract the most important ones.

And, that's pretty much it!