app.py

app.py

@@ -1,184 +1,39 @@
 import streamlit as st
 import requests
-import pandas as pd
-import plotly.graph_objs as go
+import time
 from datetime import datetime
-from requests.adapters import HTTPAdapter
-from requests.packages.urllib3.util.retry import Retry
 
-# Function to create a session with retry logic
-def create_session():
-    session = requests.Session()
-    retry = Retry(total=5, backoff_factor=1, status_forcelist=[500, 502, 503, 504])
-    adapter = HTTPAdapter(max_retries=retry)
-    session.mount('http://', adapter)
-    session.mount('https://', adapter)
-    return session
-
-# Function to fetch historical price data from CoinGecko
-def fetch_historical_data(coin_id, from_timestamp, to_timestamp):
-    url = f"https://api.coingecko.com/api/v3/coins/{coin_id}/market_chart/range?vs_currency=usd&from={from_timestamp}&to={to_timestamp}"
-    session = create_session()
-    try:
-        response = session.get(url)
-        response.raise_for_status()
-        data = response.json()
-        prices = data.get('prices', [])
-        if not prices:
-            return "No historical data available for the selected date range."
-        return prices
-    except requests.RequestException as e:
-        return f"Error fetching historical data: {e}"
-
-# Function to fetch current prices from CoinGecko
-def fetch_current_price(coin_id):
+# Function to fetch real-time data from CoinGecko
+def fetch_real_time_data(coin_id):
     url = f"https://api.coingecko.com/api/v3/simple/price?ids={coin_id}&vs_currencies=usd"
-    session = create_session()
     try:
-        response = session.get(url)
+        response = requests.get(url)
         response.raise_for_status()
         data = response.json()
-        price = data.get(coin_id, {}).get('usd', 'N/A')
-        return price
+        return data
     except requests.RequestException as e:
-        return f"Error fetching current price: {e}"
-
-# Function to convert dates to timestamps
-def date_to_timestamp(date_str):
-    try:
-        return int(pd.Timestamp(date_str).timestamp())
-    except Exception as e:
-        st.error(f"Error converting date to timestamp: {e}")
-        return None
-
-# Function to plot historical prices using Plotly
-def plot_historical_prices(coin_name, from_date, to_date):
-    from_timestamp = date_to_timestamp(from_date)
-    to_timestamp = date_to_timestamp(to_date)
-    
-    if from_timestamp is None or to_timestamp is None:
-        return "Invalid date format. Please ensure dates are in YYYY-MM-DD format."
-    
-    prices = fetch_historical_data(coin_name, from_timestamp, to_timestamp)
-    
-    if isinstance(prices, str):  # Error message
-        return prices
-    
-    try:
-        df = pd.DataFrame(prices, columns=['timestamp', 'price'])
-        df['date'] = pd.to_datetime(df['timestamp'], unit='ms')
-        
-        fig = go.Figure()
-        fig.add_trace(go.Scatter(x=df['date'], y=df['price'], mode='lines', name=coin_name))
-        fig.update_layout(title=f'{coin_name.capitalize()} Prices from {from_date} to {to_date}', xaxis_title='Date', yaxis_title='Price (USD)')
-        return fig
-    except Exception as e:
-        return f"Error plotting historical prices: {e}"
-
-# Function to provide TradingView widget HTML
-def tradingview_widget():
-    return """
-    <iframe 
-        src="https://www.tradingview.com/widgetembed/?frameElementId=tradingview_ea33b&symbol=BINANCE:BTCUSDT&interval=60" 
-        width="800" 
-        height="600" 
-        frameborder="0" 
-        allowtransparency="true" 
-        scrolling="no" 
-        allowfullscreen="true">
-    </iframe>
-    """
-
-# Functions for mocked analyses
-def analyze_order_book():
-    return "Order book analysis: Buying pressure above, selling pressure below."
-
-def analyze_technicals():
-    return "Technical analysis: Divergence detected, RSI showing overbought."
-
-def analyze_funding_rate():
-    return "Funding rate: Higher on longs, suggesting bullish sentiment."
-
-def analyze_on_chain():
-    return "On-chain analysis: Ichimoku cloud shows potential reversal."
+        return {"error": str(e)}
 
-def analyze_news():
-    return "News analysis: Positive sentiment with increasing institutional interest."
+# Streamlit app
+st.title("Real-Time Cryptocurrency Data")
 
-def btc_analysis():
-    order_book = analyze_order_book()
-    technicals = analyze_technicals()
-    funding_rate = analyze_funding_rate()
-    on_chain = analyze_on_chain()
-    news = analyze_news()
-    
-    return f"""
-    {order_book}
-    {technicals}
-    {funding_rate}
-    {on_chain}
-    {news}
-    """
+# Input for selecting cryptocurrency
+coin = st.selectbox("Select Cryptocurrency", ["bitcoin", "ethereum", "binancecoin"])
 
-# Function to fetch real-time trade data from CoinGecko
-def fetch_real_time_trade_data(coin_id):
-    url = f"https://api.coingecko.com/api/v3/coins/{coin_id}/market_chart?vs_currency=usd&days=1"
-    session = create_session()
-    try:
-        response = session.get(url)
-        response.raise_for_status()
-        data = response.json()
-        prices = data.get('prices', [])
-        if prices:
-            return prices[-1]  # Latest price data
-        return "No real-time data available"
-    except requests.RequestException as e:
-        return f"Error fetching real-time trade data: {e}"
-
-# Streamlit App Layout
-st.title("Cryptocurrency Dashboard")
-
-# Dropdown for selecting cryptocurrency
-top_100_cryptos = [
-    'bitcoin', 'ethereum', 'binancecoin', 'ripple', 'solana', 'cardano', 'dogecoin', 'polygon', 'polkadot', 'tron',
-    # Add more top coins as necessary
-]
-
-selected_crypto = st.sidebar.selectbox("Select Cryptocurrency", top_100_cryptos)
-
-# Tabs for different functionalities
-tab = st.sidebar.radio("Choose a Tab", ["Price Chart", "Current Price", "Real-Time Trade Data", "AI BTC Analysis", "TradingView Chart"])
-
-if tab == "Price Chart":
-    st.header("Cryptocurrency Price Chart")
-    from_date = st.date_input("From Date", value=pd.Timestamp("2024-01-01"))
-    to_date = st.date_input("To Date", value=pd.Timestamp("2025-12-31"))
-    
-    if st.button("Plot Chart"):
-        fig = plot_historical_prices(selected_crypto, from_date, to_date)
-        if isinstance(fig, str):  # Error message
-            st.error(fig)
-        else:
-            st.plotly_chart(fig)
-
-elif tab == "Current Price":
-    st.header("Current Cryptocurrency Price")
-    price = fetch_current_price(selected_crypto)
-    st.write(f"The current price of {selected_crypto.capitalize()} is: ${price}")
-
-elif tab == "Real-Time Trade Data":
-    st.header("Real-Time Cryptocurrency Trade Data")
-    data = fetch_real_time_trade_data(selected_crypto)
-    if isinstance(data, str):  # Error message
-        st.error(data)
+# Button to fetch data
+if st.button("Fetch Data"):
+    data = fetch_real_time_data(coin)
+    if "error" in data:
+        st.error(f"Error: {data['error']}")
     else:
-        st.write(f"The latest trading data for {selected_crypto.capitalize()} is: ${data[1]}")
-
-elif tab == "AI BTC Analysis":
-    st.header("AI-Powered BTC Analysis")
-    analysis = btc_analysis()
-    st.write(analysis)
-
-elif tab == "TradingView Chart":
-    st.header("Live TradingView Chart")
-    st.markdown(tradingview_widget(), unsafe_allow_html=True)
+        st.write(f"The current price of {coin.capitalize()} is: ${data[coin]['usd']}")
+
+# Periodic updates
+st.write("Updating data every 5 minutes...")
+while True:
+    data = fetch_real_time_data(coin)
+    if "error" in data:
+        st.error(f"Error: {data['error']}")
+    else:
+        st.write(f"Last updated at {datetime.now()}: The current price of {coin.capitalize()} is: ${data[coin]['usd']}")
+    time.sleep(300)  # Update every 5 minutes