added poster links

.gitignore

@@ -1,3 +1,4 @@
 .DS_Store
 .env
 .DS_Store
+MovieDatabase.csv

database.py

@@ -1,6 +1,7 @@
 import requests
 import pandas as pd
 import os
+from tqdm import tqdm  # Import tqdm for progress bar
 
 # Load CSV
 try:
@@ -14,7 +15,7 @@ except FileNotFoundError:
 column_names = [
     "id", "Title", "Year", "Rated", "Runtime", "Genre1", "Genre2", "Genre3",
     "Director", "Writer", "Plot", "Awards", "IMDb", "Rotten Tomatoes",
-    "Metascore", "IMDb_votes", "Type", "BoxOffice"  #add musab moiz udisha columns for personal rating. i added that manually in the csv
+    "Metascore", "IMDb_votes", "Type", "BoxOffice", "Poster"  # Add Musab, Moiz, Udisha columns for personal rating if needed
 ]
 database = pd.DataFrame(columns=column_names)
 
@@ -30,8 +31,7 @@ def get_movie(movie_id):
             if data.get("Response") == "True":
                 # Extract genres
                 genres = (data.get("Genre") or "").split(", ")
-                genre1, genre2, genre3 = genres[:3] if len(genres) >= 3 else genres + [None] * (3 - len(genres)
-)
+                genre1, genre2, genre3 = genres[:3] if len(genres) >= 3 else genres + [None] * (3 - len(genres))
                 # Append the movie data to the DataFrame
                 database.loc[len(database)] = [
                     movie_id,
@@ -50,6 +50,7 @@ def get_movie(movie_id):
                     data.get("imdbVotes"),
                     data.get("Type"),
                     data.get("BoxOffice"),
+                    data.get("Poster"),
                 ]
             else:
                 print(f"Error in API response for movie_id {movie_id}: {data.get('Error')}")
@@ -58,12 +59,12 @@ def get_movie(movie_id):
     except Exception as e:
         print(f"Exception occurred for movie_id {movie_id}: {e}")
 
-# Loop through movie IDs in the CSV and fetch details
-for i in range(len(df)):
+# Loop through movie IDs in the CSV and fetch details with a progress bar
+for i in tqdm(range(len(df)), desc="Fetching movie details", unit="movie"):
     movie_id = df.iloc[i, 0]
     get_movie(movie_id)
 
 # Save the DataFrame to a CSV file
-output_file = '/Users/moizpro/Desktop/MoviesRecommender/MovieRecommender'
+output_file = '/Users/moizpro/Desktop/MoviesRecommender/MovieRecommender/MovieDatabase.csv'
 database.to_csv(output_file, index=False)
 print(f"Movie database saved to {output_file}")