Top 100 movies of particular genre - Rotten Tomatoes

Author: Anshul Pandey

Scripts/Web_Scrappers/Movies_by_Genre_scrapper/README.md

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+<h1 align=center> Top 100 Movies by Genre - Rotten Tomatoes Scraper</h1>
+
+Takes A Movie Genre As A Command-Line Argument, scrapes the top 100 movies of a particular genre and stores rank,rating, title of the movie and total no of reviews in the desired csv file.
+
+## *Author Name*
+[Anshul Pandey](https://github.com/Anshul275)
+
+## Pre-Requisites
+
+Run The Command  `pip install -r requirements.txt`
+
+## To Run the File
+
+For Windows -  `python top100_scrapy.py 'movie-genre name'`
+
+For Ubuntu/Linux - ` ./top100_scrapy.py 'movie-genre name'`
+
+## Screenshots - 
+
+### Generated CSV File
+
+![Screenshot](generated_csv_file.png)
+
+### If movie related to the entered genre is not found
+
+![Screenshot](error.png)

Scripts/Web_Scrappers/Movies_by_Genre_scrapper/error.png

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+import csv
+import requests
+from bs4 import BeautifulSoup
+
+# Method for Scrapping the RottenTomatoes site and storing the list of top 100 movies of a particular genre in csv file
+
+def search_with_genre(genre):
+
+    # Creating the file name (for CSV file) same as input provided 
+    filename = genre
+
+    # Formatting the genre variable for use
+    genre = genre.replace("&","")
+    genre = (genre.lower()).replace(" ","_")
+
+    url = "https://www.rottentomatoes.com/top/bestofrt/top_100_" + genre + "_movies"
+
+    # Requesting and storing the contents of desired webpage in "soup" variable
+    result = requests.get(url)
+    soup = BeautifulSoup(result.text, "html.parser")
+
+    # Finding all the contents stored in the table format
+    find_contents = soup.find(attrs={"class": "table"})
+
+    if find_contents is None:
+        print("\nError - Can't find the movies of genre you are looking for!")
+
+        # If input genre is not found then providing the user with a list of valid genres from which user can choose
+
+        print("Try using these GENRES:")
+        genre_list =    [   "Action & Adventure", "Animation", "Art House & International", "Classics", 
+                            "Comedy", "Documentary", "Drama", "Horror", "Kids & Family", 
+                            "Musical & Performing Arts", "Mystery & Suspense", "Romance", "Science Fiction & Fantasy",
+                            "Special Interest", "Sports & Fitness", "Television", "Western"
+                        ]
+        for i in genre_list:
+            print(i)
+
+    else:
+        rows = find_contents.find_all("tr")
+
+        # Creating a csv file and storing the movie information in it
+        # If a file already exists the program overwrites its contents
+
+        with open(filename+".csv", "w") as csv_file:
+            writer = csv.writer(csv_file)
+
+            # Initializing the first row with the column title
+
+            writer.writerow(["Rank" , "Rating" , "Title" , "No of Reviews"])
+
+            # Iterating all the rows of the scrapped contents and storing them in desired csv file
+
+            for row in range(1,101):
+                dataset = rows[row].find_all("td")
+                rank = dataset[0].text.replace(".","")
+                rating = dataset[1].find(attrs={"class": "tMeterScore"}).text[1:]
+                title = dataset[2].find("a",attrs={"class": "unstyled articleLink"}).text.replace(" ","")
+                reviews = dataset[3].text
+                writer.writerow([rank, rating, title, reviews])
+
+
+
+# Taking the input from the user and searching for movies of particular genre
+print("Enter the genre of the movies you are looking for: ")
+genre = input()
+search_with_genre(genre)