Added Generate All FUNC and Interactive Graphs

app.py

@@ -86,41 +86,210 @@
 #     st.markdown("<br><hr><center><p style='color: grey;'>© 2024 All Rights Reserved</p></center><br>", unsafe_allow_html=True)
 
 
+# import streamlit as st
+# import requests
+# import pandas as pd
+# import pymongo
+# import datetime
+# from pymongo import MongoClient
+# import matplotlib.pyplot as plt
+# import os
+# import ssl
+# import pytz  # Importing pytz for timezone handling
+
+
+
+# # Fetch the secret key from environment variables
+# Mongo_ip = os.getenv("Mongo_IP")
+
+# # Setting up IST timezone
+# ist_timezone = pytz.timezone("Asia/Kolkata")
+
+# # Connect to MongoDB
+# client = MongoClient(
+#     Mongo_ip,
+#     ssl=True,
+#     ssl_cert_reqs=ssl.CERT_NONE  # Bypass SSL certificate verification
+# )
+# db = client.GoldRates
+# collection = db['GoldRates']
+
+# # Backend functions
+# def jina(url):
+#     base_url = "https://r.jina.ai/"
+#     url = base_url + url
+#     response = requests.get(url)
+#     return response.text
+
+# def price_cities(url):
+#     text = jina(url)
+#     pos1 = text.find('**')
+#     new = text[:pos1]
+
+#     twentytwok = new[int(new.find('22K')):int(new.find('24K'))]
+#     value_22k = twentytwok[int(twentytwok.find('\n\n') + 1): int(twentytwok.find('\n\n+'))][3:]
+#     value_22k = value_22k.split('\n')[0]
+
+#     twentyfourk = new[int(new.find('24K')):int(new.find('18K'))]
+#     value_24k = twentyfourk[int(twentyfourk.find('\n\n') + 1): int(twentyfourk.find('\n\n+'))][3:]
+#     value_24k = value_24k.split('\n')[0]
+
+#     eighteenk = new[int(new.find('18K')):]
+#     value_18k = eighteenk[int(eighteenk.find('\n\n') + 1): int(eighteenk.find('\n\n+'))][3:]
+#     value_18k = value_18k.split('\n')[0]
+
+#     return value_24k, value_22k, value_18k
+
+# # Helper function to insert data only once per day (no time constraint)
+# def insert_data_if_not_exists(city, date, value_24k, value_22k, value_18k):
+#     query = {"Date": date, "Place": city}
+#     if not collection.find_one(query):
+#         document = {
+#             "Date": date,
+#             "Place": city,
+#             "GoldRate_24k": float(value_24k.replace(',', '')),
+#             "GoldRate_22k": float(value_22k.replace(',', '')),
+#             "GoldRate_18k": float(value_18k.replace(',', ''))
+#         }
+#         collection.insert_one(document)
+
+# # Function to fetch weekly data for chart
+# def fetch_weekly_data(city):
+#     today = datetime.datetime.now(ist_timezone)
+#     start_date = today - datetime.timedelta(days=7)
+#     query = {"Place": city, "Date": {"$gte": start_date.strftime("%Y-%m-%d")}}
+#     return list(collection.find(query).sort("Date", -1))
+
+# # Function to check if it's the first run of the day after 12:30 PM IST
+# def is_first_run_after_1230():
+#     today = datetime.datetime.now(ist_timezone)
+#     time_check = today.replace(hour=12, minute=30, second=0, microsecond=0)
+#     date_check = today.strftime("%Y-%m-%d")
+#     return today >= time_check and not collection.find_one({"Date": date_check})
+
+# # Fetch and save rates for all cities
+# def fetch_and_save_all_cities():
+#     date_today = datetime.datetime.now(ist_timezone).strftime("%Y-%m-%d")
+#     for city in cities:
+#         city_url = f"https://www.goodreturns.in/gold-rates/{city}.html"
+#         try:
+#             value_24k, value_22k, value_18k = price_cities(city_url)
+#             insert_data_if_not_exists(city, date_today, value_24k, value_22k, value_18k)
+#         except Exception as e:
+#             st.error(f"Could not fetch the gold rates for {city}. {e}")
+
+# # List of cities
+# cities = ['Hyderabad', 'Ahmedabad', 'Ayodhya', 'Bangalore', 'Bhubaneswar', 'Chandigarh', 'Chennai',
+#           'Coimbatore', 'Delhi',  'Jaipur', 'Kerala', 'Kolkata', 'Lucknow',
+#           'Madurai', 'Mangalore', 'Mumbai', 'Mysore', 'Nagpur', 'Nashik', 'Patna',
+#           'Pune', 'Rajkot', 'Salem', 'Surat', 'Trichy', 'Vadodara', 'Vijayawada', 'Visakhapatnam']
+
+# # Main UI
+# st.title('Gold Rates in Indian Cities')
+# st.subheader('Select a city to view the current gold rates and a weekly trend.')
+# st.sidebar.title("About the Project")
+# st.sidebar.write("This project fetches current gold rates for 24K, 22K, and 18K gold from GoodReturns for 28 Indian states. The rates for 1g, 8g, and 10g are displayed.")
+# st.sidebar.write("**Developed by:**")
+# st.sidebar.write("[Srish Rachamalla](https://www.linkedin.com/in/srishrachamalla/)")
+# st.sidebar.write("[Sai Teja Pallerla](https://www.linkedin.com/in/saiteja-pallerla-668734225/)")
+
+# # Dropdown for city selection
+# selected_city = st.selectbox('Select a City', cities)
+
+# # Generate button
+# if st.button("Generate Gold Rates"):
+#     # If it's the first time after 12:30 PM, fetch and save rates for all cities
+#     if is_first_run_after_1230():
+#         fetch_and_save_all_cities()
+#         st.success("Gold rates for all cities have been fetched and saved.")
+
+#     # Fetch and display gold rates for the selected city
+#     if selected_city:
+#         date_today = datetime.datetime.now(ist_timezone).strftime("%Y-%m-%d")
+#         city_url = f"https://www.goodreturns.in/gold-rates/{selected_city}.html"
+
+#         try:
+#             value_24k, value_22k, value_18k = price_cities(city_url)
+#             insert_data_if_not_exists(selected_city, date_today, value_24k, value_22k, value_18k)
+
+#             # Prepare data for current rates
+#             current_data = {
+#                 'Gold Purity': ['24K', '22K', '18K'],
+#                 '1g Price (₹)': [float(value_24k.replace(',', '')), float(value_22k.replace(',', '')), float(value_18k.replace(',', ''))],
+#                 '8g Price (₹)': [float(value_24k.replace(',', '')) * 8, float(value_22k.replace(',', '')) * 8, float(value_18k.replace(',', '')) * 8],
+#                 '10g Price (₹)': [float(value_24k.replace(',', '')) * 10, float(value_22k.replace(',', '')) * 10, float(value_18k.replace(',', '')) * 10]
+#             }
+
+#             # Display current data
+#             df = pd.DataFrame(current_data)
+#             st.write(f"Gold rates in {selected_city} as of {date_today}:")
+#             st.dataframe(df.style.format(precision=2).set_properties(**{
+#                 'background-color': 'black',
+#                 'color': 'white',
+#                 'border-color': 'gray'
+#             }))
+
+#             # Weekly trend data
+#             weekly_data = fetch_weekly_data(selected_city)
+#             if weekly_data:
+#                 dates = [doc["Date"] for doc in weekly_data]
+#                 rates_24k = [doc["GoldRate_24k"] for doc in weekly_data]
+#                 rates_22k = [doc["GoldRate_22k"] for doc in weekly_data]
+#                 rates_18k = [doc["GoldRate_18k"] for doc in weekly_data]
+
+#                 # Plot weekly trends
+#                 plt.figure(figsize=(10, 5))
+#                 plt.plot(dates, rates_24k, label="24K Gold", color="gold", marker='o')
+#                 plt.plot(dates, rates_22k, label="22K Gold", color="red", marker='o')
+#                 plt.plot(dates, rates_18k, label="18K Gold", color="brown", marker='o')
+#                 plt.title(f"Gold Rates Trend in {selected_city} (Past Week)")
+#                 plt.xlabel("Date")
+#                 plt.ylabel("Price (₹)")
+#                 plt.legend()
+#                 plt.xticks(rotation=45)
+#                 st.pyplot(plt)
+
+#         except Exception as e:
+#             st.error(f"Could not fetch the gold rates. Please try again. {e}")
+
+#     # Footer
+#     st.markdown("<br><hr><center><p style='color: grey;'>© 2024 All Rights Reserved</p></center><br>", unsafe_allow_html=True)
+
 import streamlit as st
 import requests
 import pandas as pd
 import pymongo
 import datetime
+import pytz
 from pymongo import MongoClient
-import matplotlib.pyplot as plt
-import os
+import plotly.graph_objs as go
+from plotly.subplots import make_subplots
 import ssl
-import pytz  # Importing pytz for timezone handling
-
-
-
-# Fetch the secret key from environment variables
-Mongo_ip = os.getenv("Mongo_IP")
 
 # Setting up IST timezone
 ist_timezone = pytz.timezone("Asia/Kolkata")
+Mongo_ip = os.getenv("Mongo_IP")
 
 # Connect to MongoDB
+MONGO_URI = Mongo_ip
+# client = MongoClient(MONGO_URI, ssl=True, ssl_cert_reqs=ssl.CERT_NONE)
 client = MongoClient(
-    Mongo_ip,
+    MONGO_URI,
     ssl=True,
     ssl_cert_reqs=ssl.CERT_NONE  # Bypass SSL certificate verification
 )
 db = client.GoldRates
 collection = db['GoldRates']
-
+# List of cities
+cities = ['Hyderabad', 'Ahmedabad', 'Ayodhya', 'Bangalore', 'Bhubaneswar', 'Chandigarh', 'Chennai',
+          'Coimbatore', 'Delhi',  'Jaipur', 'Kerala', 'Kolkata', 'Lucknow',
+          'Madurai', 'Mangalore', 'Mumbai', 'Mysore', 'Nagpur', 'Nashik', 'Patna',
+          'Pune', 'Rajkot', 'Salem', 'Surat', 'Trichy', 'Vadodara', 'Vijayawada', 'Visakhapatnam']
 # Backend functions
 def jina(url):
     base_url = "https://r.jina.ai/"
-    url = base_url + url
-    response = requests.get(url)
+    response = requests.get(base_url + url)
     return response.text
-
 def price_cities(url):
     text = jina(url)
     pos1 = text.find('**')
@@ -140,10 +309,8 @@ def price_cities(url):
 
     return value_24k, value_22k, value_18k
 
-# Helper function to insert data only once per day (no time constraint)
 def insert_data_if_not_exists(city, date, value_24k, value_22k, value_18k):
-    query = {"Date": date, "Place": city}
-    if not collection.find_one(query):
+    if not collection.find_one({"Date": date, "Place": city}):
         document = {
             "Date": date,
             "Place": city,
@@ -153,21 +320,17 @@ def insert_data_if_not_exists(city, date, value_24k, value_22k, value_18k):
         }
         collection.insert_one(document)
 
-# Function to fetch weekly data for chart
 def fetch_weekly_data(city):
     today = datetime.datetime.now(ist_timezone)
     start_date = today - datetime.timedelta(days=7)
-    query = {"Place": city, "Date": {"$gte": start_date.strftime("%Y-%m-%d")}}
-    return list(collection.find(query).sort("Date", -1))
+    return list(collection.find({"Place": city, "Date": {"$gte": start_date.strftime("%Y-%m-%d")}}).sort("Date", -1))
 
-# Function to check if it's the first run of the day after 12:30 PM IST
 def is_first_run_after_1230():
     today = datetime.datetime.now(ist_timezone)
     time_check = today.replace(hour=12, minute=30, second=0, microsecond=0)
     date_check = today.strftime("%Y-%m-%d")
     return today >= time_check and not collection.find_one({"Date": date_check})
 
-# Fetch and save rates for all cities
 def fetch_and_save_all_cities():
     date_today = datetime.datetime.now(ist_timezone).strftime("%Y-%m-%d")
     for city in cities:
@@ -178,41 +341,34 @@ def fetch_and_save_all_cities():
         except Exception as e:
             st.error(f"Could not fetch the gold rates for {city}. {e}")
 
-# List of cities
-cities = ['Hyderabad', 'Ahmedabad', 'Ayodhya', 'Bangalore', 'Bhubaneswar', 'Chandigarh', 'Chennai',
-          'Coimbatore', 'Delhi',  'Jaipur', 'Kerala', 'Kolkata', 'Lucknow',
-          'Madurai', 'Mangalore', 'Mumbai', 'Mysore', 'Nagpur', 'Nashik', 'Patna',
-          'Pune', 'Rajkot', 'Salem', 'Surat', 'Trichy', 'Vadodara', 'Vijayawada', 'Visakhapatnam']
-
-# Main UI
-st.title('Gold Rates in Indian Cities')
-st.subheader('Select a city to view the current gold rates and a weekly trend.')
-st.sidebar.title("About the Project")
-st.sidebar.write("This project fetches current gold rates for 24K, 22K, and 18K gold from GoodReturns for 28 Indian states. The rates for 1g, 8g, and 10g are displayed.")
-st.sidebar.write("**Developed by:**")
-st.sidebar.write("[Srish Rachamalla](https://www.linkedin.com/in/srishrachamalla/)")
-st.sidebar.write("[Sai Teja Pallerla](https://www.linkedin.com/in/saiteja-pallerla-668734225/)")
-
-# Dropdown for city selection
-selected_city = st.selectbox('Select a City', cities)
+# Get last Friday's date
+def get_last_friday():
+    today = datetime.datetime.now(ist_timezone)
+    last_friday = today - datetime.timedelta(days=(today.weekday() - 4) % 7)
+    return last_friday.strftime("%Y-%m-%d")
+def fetch_historical_data(city, days=365):  # Default to the past year
+    end_date = datetime.datetime.now(ist_timezone)
+    start_date = end_date - datetime.timedelta(days=days)
+    return list(collection.find({"Place": city, "Date": {"$gte": start_date.strftime("%Y-%m-%d"), "$lte": end_date.strftime("%Y-%m-%d")}}).sort("Date", 1))
+def display_city_gold_rates(city):
+    today = datetime.datetime.now(ist_timezone)
+    date_to_fetch = today.strftime("%Y-%m-%d")
 
-# Generate button
-if st.button("Generate Gold Rates"):
-    # If it's the first time after 12:30 PM, fetch and save rates for all cities
-    if is_first_run_after_1230():
-        fetch_and_save_all_cities()
-        st.success("Gold rates for all cities have been fetched and saved.")
+    if today.weekday() >= 5:  # Weekend
+        st.info("Today is a weekend. Showing last available data.")
 
-    # Fetch and display gold rates for the selected city
-    if selected_city:
-        date_today = datetime.datetime.now(ist_timezone).strftime("%Y-%m-%d")
-        city_url = f"https://www.goodreturns.in/gold-rates/{selected_city}.html"
+    # Attempt to retrieve document for today's date
+    doc = collection.find_one({"Date": date_to_fetch, "Place": city})
 
+    if not doc:
+        st.warning(f"No data found for {city} on {date_to_fetch}. Scraping for latest data...")
+        city_url = f"https://www.goodreturns.in/gold-rates/{city}.html"
         try:
             value_24k, value_22k, value_18k = price_cities(city_url)
-            insert_data_if_not_exists(selected_city, date_today, value_24k, value_22k, value_18k)
+            insert_data_if_not_exists(city, date_to_fetch, value_24k, value_22k, value_18k)
+            st.success(f"Fetched latest gold rates for {city}.")
 
-            # Prepare data for current rates
+            # Prepare current rates table with newly scraped data
             current_data = {
                 'Gold Purity': ['24K', '22K', '18K'],
                 '1g Price (₹)': [float(value_24k.replace(',', '')), float(value_22k.replace(',', '')), float(value_18k.replace(',', ''))],
@@ -222,36 +378,178 @@ if st.button("Generate Gold Rates"):
 
             # Display current data
             df = pd.DataFrame(current_data)
-            st.write(f"Gold rates in {selected_city} as of {date_today}:")
-            st.dataframe(df.style.format(precision=2).set_properties(**{
+            # st.dataframe(df)
+
+            # Create a styled dataframe for Streamlit
+            styled_df = df.style.format(precision=2).set_properties(**{
                 'background-color': 'black',
                 'color': 'white',
-                'border-color': 'gray'
-            }))
-
-            # Weekly trend data
-            weekly_data = fetch_weekly_data(selected_city)
-            if weekly_data:
-                dates = [doc["Date"] for doc in weekly_data]
-                rates_24k = [doc["GoldRate_24k"] for doc in weekly_data]
-                rates_22k = [doc["GoldRate_22k"] for doc in weekly_data]
-                rates_18k = [doc["GoldRate_18k"] for doc in weekly_data]
-
-                # Plot weekly trends
-                plt.figure(figsize=(10, 5))
-                plt.plot(dates, rates_24k, label="24K Gold", color="gold", marker='o')
-                plt.plot(dates, rates_22k, label="22K Gold", color="red", marker='o')
-                plt.plot(dates, rates_18k, label="18K Gold", color="brown", marker='o')
-                plt.title(f"Gold Rates Trend in {selected_city} (Past Week)")
-                plt.xlabel("Date")
-                plt.ylabel("Price (₹)")
-                plt.legend()
-                plt.xticks(rotation=45)
-                st.pyplot(plt)
+                'border-color': 'gray',
+                'font-size': '16px',
+                'text-align': 'center'
+            }).set_table_attributes('style="width: 80%; margin: auto;"')  # Center the table
+
+            st.dataframe(styled_df)
+
+            # Fetch historical data
+            historical_data = fetch_historical_data(city)
+            
+            if historical_data:
+                dates = [doc["Date"] for doc in historical_data]
+                rates_24k = [doc["GoldRate_24k"] for doc in historical_data]
+                rates_22k = [doc["GoldRate_22k"] for doc in historical_data]
+                rates_18k = [doc["GoldRate_18k"] for doc in historical_data]
+
+                # Create an interactive Plotly line chart for the historical data
+                fig = make_subplots(specs=[[{"secondary_y": False}]])
+
+                # Add 24K data trace
+                fig.add_trace(
+                    go.Scatter(x=dates, y=rates_24k, mode='lines+markers', name="24K Gold",
+                            line=dict(color="gold"), marker=dict(size=8)),
+                    secondary_y=False,
+                )
+
+                # Add 22K data trace
+                fig.add_trace(
+                    go.Scatter(x=dates, y=rates_22k, mode='lines+markers', name="22K Gold",
+                            line=dict(color="red"), marker=dict(size=8)),
+                    secondary_y=False,
+                )
+
+                # Add 18K data trace
+                fig.add_trace(
+                    go.Scatter(x=dates, y=rates_18k, mode='lines+markers', name="18K Gold",
+                            line=dict(color="brown"), marker=dict(size=8)),
+                    secondary_y=False,
+                )
+
+                # Set chart titles and layout
+                fig.update_layout(
+                    title_text=f"Gold Rates Trend in {city} (Historical Data)",
+                    xaxis_title="Date",
+                    yaxis_title="Price (₹)",
+                    hovermode="x unified",
+                    template="plotly_dark"
+                )
+
+                # Display the interactive chart in Streamlit
+                st.plotly_chart(fig, use_container_width=True)
+            else:
+                st.warning(f"No historical data found for {city}.")
 
         except Exception as e:
-            st.error(f"Could not fetch the gold rates. Please try again. {e}")
+            st.error(f"Could not fetch the gold rates for {city}. {e}")
+            return
+    # else:
+        # st.success(f"Gold Rates for {city} on {date_to_fetch}")
+    # Prepare current rates table
+    if doc:
+        st.success(f"Gold Rates for {city} on {date_to_fetch}")
+
+        # Prepare data for current rates
+        current_data = {
+            'Gold Purity': ['24K', '22K', '18K'],
+            '1g Price (₹)': [doc["GoldRate_24k"], doc["GoldRate_22k"], doc["GoldRate_18k"]],
+            '8g Price (₹)': [doc["GoldRate_24k"] * 8, doc["GoldRate_22k"] * 8, doc["GoldRate_18k"] * 8],
+            '10g Price (₹)': [doc["GoldRate_24k"] * 10, doc["GoldRate_22k"] * 10, doc["GoldRate_18k"] * 10]
+        }
+
+        # Display current data as a stylish table
+        df = pd.DataFrame(current_data)
+
+        # Create a styled dataframe for Streamlit
+        styled_df = df.style.format(precision=2).set_properties(**{
+            'background-color': 'black',
+            'color': 'white',
+            'border-color': 'gray',
+            'font-size': '16px',
+            'text-align': 'center'
+        }).set_table_attributes('style="width: 80%; margin: auto;"')  # Center the table
+
+        st.dataframe(styled_df)
+
+        # Fetch historical data
+        historical_data = fetch_historical_data(city)
+        
+        if historical_data:
+            dates = [doc["Date"] for doc in historical_data]
+            rates_24k = [doc["GoldRate_24k"] for doc in historical_data]
+            rates_22k = [doc["GoldRate_22k"] for doc in historical_data]
+            rates_18k = [doc["GoldRate_18k"] for doc in historical_data]
+
+            # Create an interactive Plotly line chart for the historical data
+            fig = make_subplots(specs=[[{"secondary_y": False}]])
+
+            # Add 24K data trace
+            fig.add_trace(
+                go.Scatter(x=dates, y=rates_24k, mode='lines+markers', name="24K Gold",
+                           line=dict(color="gold"), marker=dict(size=8)),
+                secondary_y=False,
+            )
+
+            # Add 22K data trace
+            fig.add_trace(
+                go.Scatter(x=dates, y=rates_22k, mode='lines+markers', name="22K Gold",
+                           line=dict(color="red"), marker=dict(size=8)),
+                secondary_y=False,
+            )
+
+            # Add 18K data trace
+            fig.add_trace(
+                go.Scatter(x=dates, y=rates_18k, mode='lines+markers', name="18K Gold",
+                           line=dict(color="brown"), marker=dict(size=8)),
+                secondary_y=False,
+            )
+
+            # Set chart titles and layout
+            fig.update_layout(
+                title_text=f"Gold Rates Trend in {city} (Historical Data)",
+                xaxis_title="Date",
+                yaxis_title="Price (₹)",
+                hovermode="x unified",
+                template="plotly_dark"
+            )
+
+            # Display the interactive chart in Streamlit
+            st.plotly_chart(fig, use_container_width=True)
+        else:
+            st.warning(f"No historical data found for {city}.")
+    # else:
+        # st.warning(f"No data found for {city} on {date_to_fetch}.")
+# Main UI
+st.title('Gold Rates in Indian Cities')
+st.subheader('Select a city to view the current gold rates and a weekly trend.')
+st.sidebar.title("About the Project")
+st.sidebar.write("This project fetches current gold rates for 24K, 22K, and 18K gold from GoodReturns for 28 Indian states. The rates for 1g, 8g, and 10g are displayed.")
+st.sidebar.write("**Developed by:**")
+st.sidebar.write("[Srish Rachamalla](https://www.linkedin.com/in/srishrachamalla/)")
+st.sidebar.write("[Sai Teja Pallerla](https://www.linkedin.com/in/saiteja-pallerla-668734225/)")
 
-    # Footer
-    st.markdown("<br><hr><center><p style='color: grey;'>© 2024 All Rights Reserved</p></center><br>", unsafe_allow_html=True)
+selected_city = st.selectbox('Select a City', cities)
 
+if st.button("Generate Gold Rates for Selected City"):
+    if is_first_run_after_1230() and datetime.datetime.now(ist_timezone).weekday() not in [5, 6]: 
+        fetch_and_save_all_cities()
+        st.success("Gold rates for all cities have been fetched and saved.")
+    if selected_city:
+        display_city_gold_rates(selected_city)
+
+if st.button("Generate All Gold Rates"):
+    current_time = datetime.datetime.now(ist_timezone).time()
+    if current_time >= datetime.time(13, 0) and datetime.datetime.now(ist_timezone).weekday() not in [5, 6]:
+        for city in cities:
+            if not collection.find_one({"Date": datetime.datetime.now(ist_timezone).strftime("%Y-%m-%d"), "Place": city}):
+                city_url = f"https://www.goodreturns.in/gold-rates/{city}.html"
+                try:
+                    value_24k, value_22k, value_18k = price_cities(city_url)
+                    insert_data_if_not_exists(city, datetime.datetime.now(ist_timezone).strftime("%Y-%m-%d"), value_24k, value_22k, value_18k)
+                    st.success(f"Gold rates for {city} saved successfully.")
+                except Exception as e:
+                    st.error(f"Could not fetch the gold rates for {city}. {e}")
+        st.success("Gold rates for all cities have been fetched and saved.")
+    else:
+        st.warning("Gold rates can only be saved to the database after 1 PM on weekdays.")
+    for city in cities:
+        st.subheader(f"Gold Rates in {city} as of {datetime.datetime.now(ist_timezone).strftime('%Y-%m-%d')}")
+        display_city_gold_rates(city)