Update app.py
Browse files
app.py
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import streamlit as st
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import requests
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import pandas as pd
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def jina(url):
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base_url = "https://r.jina.ai/"
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url = base_url + url
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value_18k = value_18k.split('\n')[0]
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return value_24k, value_22k, value_18k
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# List of cities
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cities = ['Ahmedabad', 'Ayodhya', 'Bangalore', 'Bhubaneswar', 'Chandigarh', 'Chennai',
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'Coimbatore', 'Delhi',
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'Madurai', 'Mangalore', 'Mumbai', 'Mysore', 'Nagpur', 'Nashik', 'Patna',
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'Pune', 'Rajkot', 'Salem', 'Surat', 'Trichy', 'Vadodara', 'Vijayawada', 'Visakhapatnam']
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#
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st.sidebar.title("About the Project")
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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.")
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st.sidebar.write("**Developed by:**")
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st.sidebar.write("[Srish Rachamalla](https://www.linkedin.com/in/srishrachamalla/)")
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st.sidebar.write("[Sai Teja Pallerla](https://www.linkedin.com/in/saiteja-pallerla-668734225/)")
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# Main UI
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st.title('Gold Rates in Indian Cities')
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st.subheader('Select a city to view the current gold rates')
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# Dropdown for city selection
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selected_city = st.selectbox('Select a City', cities)
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#
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if
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st.markdown("<br><hr><center><p style='color: grey;'>© 2024 All Rights Reserved</p></center><br>", unsafe_allow_html=True)
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+
# import streamlit as st
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# import requests
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# import pandas as pd
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# # Your backend functions
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# def jina(url):
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# base_url = "https://r.jina.ai/"
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# url = base_url + url
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# response = requests.get(url)
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# return response.text
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# def price_cities(url):
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# text = jina(url)
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# pos1 = text.find('**')
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# new = text[:pos1]
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# twentytwok = new[int(new.find('22K')):int(new.find('24K'))]
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# value_22k = twentytwok[int(twentytwok.find('\n\n') + 1): int(twentytwok.find('\n\n+'))][3:]
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# value_22k = value_22k.split('\n')[0]
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# twentyfourk = new[int(new.find('24K')):int(new.find('18K'))]
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# value_24k = twentyfourk[int(twentyfourk.find('\n\n') + 1): int(twentyfourk.find('\n\n+'))][3:]
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# value_24k = value_24k.split('\n')[0]
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# eighteenk = new[int(new.find('18K')):]
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# value_18k = eighteenk[int(eighteenk.find('\n\n') + 1): int(eighteenk.find('\n\n+'))][3:]
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# value_18k = value_18k.split('\n')[0]
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# return value_24k, value_22k, value_18k
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# # List of cities
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# cities = ['Ahmedabad', 'Ayodhya', 'Bangalore', 'Bhubaneswar', 'Chandigarh', 'Chennai',
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# 'Coimbatore', 'Delhi', 'Hyderabad', 'Jaipur', 'Kerala', 'Kolkata', 'Lucknow',
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# 'Madurai', 'Mangalore', 'Mumbai', 'Mysore', 'Nagpur', 'Nashik', 'Patna',
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# 'Pune', 'Rajkot', 'Salem', 'Surat', 'Trichy', 'Vadodara', 'Vijayawada', 'Visakhapatnam']
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# # Sidebar content
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# st.sidebar.title("About the Project")
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# 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.")
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# st.sidebar.write("**Developed by:**")
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# st.sidebar.write("[Srish Rachamalla](https://www.linkedin.com/in/srishrachamalla/)")
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# st.sidebar.write("[Sai Teja Pallerla](https://www.linkedin.com/in/saiteja-pallerla-668734225/)")
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# # Main UI
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# st.title('Gold Rates in Indian Cities')
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# st.subheader('Select a city to view the current gold rates')
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# # Dropdown for city selection
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# selected_city = st.selectbox('Select a City', cities)
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# # Fetch and display gold rates
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# if selected_city:
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# city_url = f"https://www.goodreturns.in/gold-rates/{selected_city}.html"
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# # Fetch the prices using your backend function
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# try:
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# value_24k, value_22k, value_18k = price_cities(city_url)
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# # Convert string values to float for calculation
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# value_22k = round(float(value_22k.replace(',', '')),2)
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# value_24k = round(float(value_24k.replace(',', '')),2)
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# value_18k = round(float(value_18k.replace(',', '')),2)
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# # Prepare data for table
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# data = {
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# # 'SNO': [1, 2, 3],
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# 'Gold Purity': ['24K', '22K', '18K'],
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# '1g Price (₹)': [value_24k, value_22k, value_18k],
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# '8g Price (₹)': [value_24k * 8, value_22k * 8, value_18k * 8],
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# '10g Price (₹)': [value_24k * 10, value_22k * 10, value_18k * 10]
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# }
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# # Create a DataFrame for display
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# df = pd.DataFrame(data,index=[1, 2, 3])
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# # Display the DataFrame as a table
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# st.write(f"Gold rates in {selected_city}:")
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# st.dataframe(df.style.format(precision=2).set_properties(**{
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# 'background-color': 'black',
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# 'color': 'white',
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# 'border-color': 'ash'
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# }))
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# except Exception as e:
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# st.error(f"Could not fetch the gold rates. Please try again.{e}")
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# st.markdown("<br><hr><center><p style='color: grey;'>© 2024 All Rights Reserved</p></center><br>", unsafe_allow_html=True)
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import streamlit as st
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import requests
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import pandas as pd
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import pymongo
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import datetime
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from pymongo import MongoClient
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import matplotlib.pyplot as plt
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import os
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# Fetch the secret key from environment variables
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Mongo_ip = os.getenv("Mongo_IP")
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# Connect to MongoDB
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client = MongoClient('mongodb+srv://srishnotebooks:JbpvGNb7FWNLVRFJ@goldrates.vx9zl.mongodb.net/?retryWrites=true&w=majority&appName=Goldrates')
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db = client.GoldRates
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collection = db['GoldRates']
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# Backend functions
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def jina(url):
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base_url = "https://r.jina.ai/"
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url = base_url + url
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value_18k = value_18k.split('\n')[0]
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return value_24k, value_22k, value_18k
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# Helper function to insert data only once per day (no time constraint)
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def insert_data_if_not_exists(city, date, value_24k, value_22k, value_18k):
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query = {"Date": date, "Place": city}
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if not collection.find_one(query):
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document = {
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"Date": date,
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"Place": city,
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"GoldRate_24k": float(value_24k.replace(',', '')),
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"GoldRate_22k": float(value_22k.replace(',', '')),
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"GoldRate_18k": float(value_18k.replace(',', ''))
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}
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collection.insert_one(document)
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# st.success(f"Gold rates for {city} on {date} have been saved to MongoDB.")
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# Function to fetch weekly data for chart
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def fetch_weekly_data(city):
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today = datetime.datetime.today()
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start_date = today - datetime.timedelta(days=7)
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query = {"Place": city, "Date": {"$gte": start_date.strftime("%Y-%m-%d")}}
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return list(collection.find(query).sort("Date", -1))
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# Function to check if it's the first run of the day after 12:30 PM
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def is_first_run_after_1230():
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today = datetime.datetime.today()
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time_check = today.replace(hour=12, minute=30, second=0, microsecond=0)
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date_check = today.strftime("%Y-%m-%d")
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return today >= time_check and not collection.find_one({"Date": date_check})
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# Fetch and save rates for all cities
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def fetch_and_save_all_cities():
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date_today = datetime.datetime.today().strftime("%Y-%m-%d")
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for city in cities:
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city_url = f"https://www.goodreturns.in/gold-rates/{city}.html"
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try:
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value_24k, value_22k, value_18k = price_cities(city_url)
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insert_data_if_not_exists(city, date_today, value_24k, value_22k, value_18k)
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except Exception as e:
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st.error(f"Could not fetch the gold rates for {city}. {e}")
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# List of cities
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cities = ['Hyderabad', 'Ahmedabad', 'Ayodhya', 'Bangalore', 'Bhubaneswar', 'Chandigarh', 'Chennai',
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'Coimbatore', 'Delhi', 'Jaipur', 'Kerala', 'Kolkata', 'Lucknow',
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'Madurai', 'Mangalore', 'Mumbai', 'Mysore', 'Nagpur', 'Nashik', 'Patna',
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'Pune', 'Rajkot', 'Salem', 'Surat', 'Trichy', 'Vadodara', 'Vijayawada', 'Visakhapatnam']
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# Main UI
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st.title('Gold Rates in Indian Cities')
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st.subheader('Select a city to view the current gold rates and a weekly trend.')
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st.sidebar.title("About the Project")
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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.")
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st.sidebar.write("**Developed by:**")
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st.sidebar.write("[Srish Rachamalla](https://www.linkedin.com/in/srishrachamalla/)")
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st.sidebar.write("[Sai Teja Pallerla](https://www.linkedin.com/in/saiteja-pallerla-668734225/)")
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# Dropdown for city selection
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selected_city = st.selectbox('Select a City', cities)
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# Generate button
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if st.button("Generate Gold Rates"):
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# If it's the first time after 12:30 PM, fetch and save rates for all cities
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if is_first_run_after_1230():
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fetch_and_save_all_cities()
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st.success("Gold rates for all cities have been fetched and saved.")
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# Fetch and display gold rates for the selected city
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if selected_city:
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date_today = datetime.datetime.today().strftime("%Y-%m-%d")
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city_url = f"https://www.goodreturns.in/gold-rates/{selected_city}.html"
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try:
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value_24k, value_22k, value_18k = price_cities(city_url)
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insert_data_if_not_exists(selected_city, date_today, value_24k, value_22k, value_18k)
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# Prepare data for current rates
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current_data = {
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'Gold Purity': ['24K', '22K', '18K'],
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'1g Price (₹)': [float(value_24k.replace(',', '')), float(value_22k.replace(',', '')), float(value_18k.replace(',', ''))],
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'8g Price (₹)': [float(value_24k.replace(',', '')) * 8, float(value_22k.replace(',', '')) * 8, float(value_18k.replace(',', '')) * 8],
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'10g Price (₹)': [float(value_24k.replace(',', '')) * 10, float(value_22k.replace(',', '')) * 10, float(value_18k.replace(',', '')) * 10]
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}
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# Display current data
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df = pd.DataFrame(current_data)
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st.write(f"Gold rates in {selected_city} as of {date_today}:")
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st.dataframe(df.style.format(precision=2).set_properties(**{
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'background-color': 'black',
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'color': 'white',
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'border-color': 'gray'
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}))
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# Weekly trend data
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weekly_data = fetch_weekly_data(selected_city)
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if weekly_data:
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dates = [doc["Date"] for doc in weekly_data]
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rates_24k = [doc["GoldRate_24k"] for doc in weekly_data]
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rates_22k = [doc["GoldRate_22k"] for doc in weekly_data]
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| 229 |
+
rates_18k = [doc["GoldRate_18k"] for doc in weekly_data]
|
| 230 |
+
|
| 231 |
+
# Plot weekly trends
|
| 232 |
+
plt.figure(figsize=(10, 5))
|
| 233 |
+
plt.plot(dates, rates_24k, label="24K Gold", color="gold", marker='o')
|
| 234 |
+
plt.plot(dates, rates_22k, label="22K Gold", color="red", marker='o')
|
| 235 |
+
plt.plot(dates, rates_18k, label="18K Gold", color="brown", marker='o')
|
| 236 |
+
plt.title(f"Gold Rates Trend in {selected_city} (Past Week)")
|
| 237 |
+
plt.xlabel("Date")
|
| 238 |
+
plt.ylabel("Price (₹)")
|
| 239 |
+
plt.legend()
|
| 240 |
+
plt.xticks(rotation=45)
|
| 241 |
+
st.pyplot(plt)
|
| 242 |
+
|
| 243 |
+
except Exception as e:
|
| 244 |
+
st.error(f"Could not fetch the gold rates. Please try again. {e}")
|
| 245 |
+
|
| 246 |
+
# Footer
|
| 247 |
st.markdown("<br><hr><center><p style='color: grey;'>© 2024 All Rights Reserved</p></center><br>", unsafe_allow_html=True)
|
| 248 |
|
|
|