app.py

# import streamlit as st
# import requests
# import pandas as pd

# # Your 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
# # List of cities
# cities = ['Ahmedabad', 'Ayodhya', 'Bangalore', 'Bhubaneswar', 'Chandigarh', 'Chennai',
#           'Coimbatore', 'Delhi', 'Hyderabad', 'Jaipur', 'Kerala', 'Kolkata', 'Lucknow',
#           'Madurai', 'Mangalore', 'Mumbai', 'Mysore', 'Nagpur', 'Nashik', 'Patna',
#           'Pune', 'Rajkot', 'Salem', 'Surat', 'Trichy', 'Vadodara', 'Vijayawada', 'Visakhapatnam']

# # Sidebar content
# 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/)")

# # Main UI
# st.title('Gold Rates in Indian Cities')
# st.subheader('Select a city to view the current gold rates')

# # Dropdown for city selection
# selected_city = st.selectbox('Select a City', cities)

# # Fetch and display gold rates
# if selected_city:
#     city_url = f"https://www.goodreturns.in/gold-rates/{selected_city}.html"
    
#     # Fetch the prices using your backend function
#     try:
#         value_24k, value_22k, value_18k = price_cities(city_url)

#         # Convert string values to float for calculation
#         value_22k = round(float(value_22k.replace(',', '')),2)
#         value_24k = round(float(value_24k.replace(',', '')),2)
#         value_18k = round(float(value_18k.replace(',', '')),2)
#         # Prepare data for table
#         data = {
#             # 'SNO': [1, 2, 3],
#             'Gold Purity': ['24K', '22K', '18K'],
#             '1g Price (₹)': [value_24k, value_22k, value_18k],
#             '8g Price (₹)': [value_24k * 8, value_22k * 8, value_18k * 8],
#             '10g Price (₹)': [value_24k * 10, value_22k * 10, value_18k * 10]
#         }

#         # Create a DataFrame for display
#         df = pd.DataFrame(data,index=[1, 2, 3])

#         # Display the DataFrame as a table
#         st.write(f"Gold rates in {selected_city}:")
#         st.dataframe(df.style.format(precision=2).set_properties(**{
#             'background-color': 'black',
#             'color': 'white',
#             'border-color': 'ash'
#         }))

    
#     except Exception as e:
#         st.error(f"Could not fetch the gold rates. Please try again.{e}")
    
#     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



# Fetch the secret key from environment variables
Mongo_ip = os.getenv("Mongo_IP")


# Connect to MongoDB
client = MongoClient(Mongo_ip)
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)
        # st.success(f"Gold rates for {city} on {date} have been saved to MongoDB.")

# Function to fetch weekly data for chart
def fetch_weekly_data(city):
    today = datetime.datetime.today()
    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
def is_first_run_after_1230():
    today = datetime.datetime.today()
    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.today().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.today().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)