Update app.py

app.py

@@ -9,11 +9,13 @@ from collections import Counter
 import numpy as np
 
 # Function to load data from SQLite database
+@st.cache_data
 def load_data(db_file):
     conn = sqlite3.connect(db_file)
     return conn
 
 # Function to fetch genre movie releases by year
+@st.cache_data
 def fetch_genre_movie_releases(conn):
     query = r'''
     SELECT startYear, genres
@@ -35,6 +37,7 @@ def fetch_genre_movie_releases(conn):
     return genre_counts
 
 # Function to fetch data for filled line chart of movie release years
+@st.cache_data
 def fetch_movie_release_years(conn):
     query_release_years = r'''
     SELECT startYear, COUNT(*) as count
@@ -47,6 +50,7 @@ def fetch_movie_release_years(conn):
     return df_release_years
 
 # Function to fetch data and create box plot of average rating by first_genre
+@st.cache_data
 def fetch_and_plot_average_rating_by_genre(conn):
     query = r'''
     SELECT tb.tconst, tb.primaryTitle, tr.averageRating, tb.genres
@@ -57,7 +61,7 @@ def fetch_and_plot_average_rating_by_genre(conn):
     df = pd.read_sql_query(query, conn)
 
     # Function to extract the first genre from the genres list
-    def extract_first_genre(genres):
+def extract_first_genre(genres):
         if genres:
             return genres.split(',')[0].strip()
         else:
@@ -103,6 +107,7 @@ def create_genre_wordcloud(conn):
     st.pyplot(plt.gcf())  # Pass the current figure explicitly to st.pyplot()
 
 # Function to find best movie of each genre by numVotes * averageRating
+@st.cache_data
 def find_best_movies_by_genre(conn):
     query = r'''
     SELECT tb.tconst, tb.primaryTitle, tb.startYear, tb.genres, tr.averageRating, tr.numVotes
@@ -126,6 +131,7 @@ def find_best_movies_by_genre(conn):
     return best_movies_by_genre
 
 # Function to plot stacked area chart of genre movie releases by year using Plotly Express
+@st.cache_data
 def plot_stacked_genre_movie_releases(genre_counts):
     fig = px.area(genre_counts, x='startYear', y='count', color='genres',
                   title='Stacked Genre Movie Releases by Year',
@@ -146,6 +152,7 @@ def plot_stacked_genre_movie_releases(genre_counts):
     return fig
 
 # Function to plot global map of total films per region using Plotly Express
+@st.cache_data
 def plot_global_map():
     df = pd.read_csv('movie_region.csv')
     # Country code to name mapping
@@ -241,6 +248,7 @@ def plot_global_map():
 
 
 # Function to fetch summary info
+@st.cache_data
 def fetch_summary_info(conn):
     # Fetch total count of movies
     query_total_movies = r'''