Update app.py

app.py

@@ -1,14 +1,15 @@
 import yfinance as yf
 import pandas as pd
 import numpy as np
-import matplotlib.pyplot as plt
-import seaborn as sns
+import plotly.graph_objects as go
 import streamlit as st
+from datetime import datetime
 
-# Step 1: Define a function to fetch real-time market data
+# Step 1: Define a function to fetch real-time market data up to the current date
 def fetch_data(ticker_symbol):
     ticker = yf.Ticker(ticker_symbol)
-    data = ticker.history(period="1y")  # Fetches 1 year of historical data
+    end_date = datetime.now().strftime('%Y-%m-%d')  # Get the current date
+    data = ticker.history(start="2023-01-01", end=end_date)  # Fetches data from the start of this year to the current date
     return data
 
 # Step 2: Define a function to calculate indicators
@@ -63,49 +64,70 @@ nifty_data = calculate_indicators(nifty_data)
 st.subheader(f"Data Overview for {ticker_symbol}")
 st.write(nifty_data.head())
 
-# Step 6: Visualizations
-st.subheader(f"Close Price for {ticker_symbol}")
-fig, ax = plt.subplots(figsize=(12, 6))
-sns.lineplot(x=nifty_data.index, y=nifty_data['Close'])
-st.pyplot(fig)
-
-st.subheader(f"Moving Averages, EMA, and RSI for {ticker_symbol}")
-fig, ax = plt.subplots(figsize=(12, 6))
-sns.lineplot(x=nifty_data.index, y=nifty_data['MA20'], label='MA20')
-sns.lineplot(x=nifty_data.index, y=nifty_data['MA50'], label='MA50')
-sns.lineplot(x=nifty_data.index, y=nifty_data['RSI'], label='RSI')
-plt.axhline(y=70, color='red', linestyle='--', label='Overbought (70)')
-plt.axhline(y=30, color='green', linestyle='--', label='Oversold (30)')
-plt.legend()
-plt.title("Moving Averages and RSI")
-st.pyplot(fig)
-
-# Step 7: Buy and Sell Signals Visualization
+# Step 6: Visualizations using Plotly for Interactivity
 st.subheader(f"Buy and Sell Signals for {ticker_symbol}")
-fig, ax = plt.subplots(figsize=(12, 6))
-sns.lineplot(x=nifty_data.index, y=nifty_data['Close'], label='Close Price', color='blue')
-sns.lineplot(x=nifty_data.index, y=nifty_data['TrendSMA'], label='Trend SMA', color='gray')
+
+# Create a Plotly figure
+fig = go.Figure()
+
+# Add Close Price line
+fig.add_trace(go.Scatter(
+    x=nifty_data.index,
+    y=nifty_data['Close'],
+    mode='lines',
+    name='Close Price',
+    line=dict(color='blue')
+))
+
+# Add Trend SMA line
+fig.add_trace(go.Scatter(
+    x=nifty_data.index,
+    y=nifty_data['TrendSMA'],
+    mode='lines',
+    name='Trend SMA',
+    line=dict(color='gray')
+))
 
 # Plot Buy Signals
 buy_signals = nifty_data[nifty_data['BuySignal']]
-plt.scatter(buy_signals.index, buy_signals['Close'], marker='^', color='green', label='Buy Signal', s=100)
+fig.add_trace(go.Scatter(
+    x=buy_signals.index,
+    y=buy_signals['Close'],
+    mode='markers',
+    name='Buy Signal',
+    marker=dict(symbol='triangle-up', color='green', size=10)
+))
 
 # Plot Sell Signals
 sell_signals = nifty_data[nifty_data['SellSignal']]
-plt.scatter(sell_signals.index, sell_signals['Close'], marker='v', color='red', label='Sell Signal', s=100)
-
-plt.legend()
-plt.title("Buy and Sell Signals with Trend Filter")
-st.pyplot(fig)
-
-# Step 8: Interactive Timeframe Selection and Alerts
+fig.add_trace(go.Scatter(
+    x=sell_signals.index,
+    y=sell_signals['Close'],
+    mode='markers',
+    name='Sell Signal',
+    marker=dict(symbol='triangle-down', color='red', size=10)
+))
+
+# Update layout for better readability
+fig.update_layout(
+    title=f"Buy and Sell Signals with Trend Filter for {ticker_symbol}",
+    xaxis_title="Date",
+    yaxis_title="Close Price",
+    legend_title="Legend",
+    template="plotly_dark"
+)
+
+# Show Plotly figure in Streamlit
+st.plotly_chart(fig)
+
+# Step 7: Interactive Timeframe Selection and Alerts
 st.sidebar.subheader("Select Timeframe:")
-timeframes = ['15m', '60m', '1d', '5d', '1mo', '3mo', '6mo', '1y', '2y', '5y', '10y', 'ytd', 'max']
+timeframes = ['1d', '5d', '1mo', '3mo', '6mo', '1y', '2y', '5y', '10y', 'ytd', 'max']
 selected_timeframe = st.sidebar.selectbox('Timeframe', timeframes)
 
 st.sidebar.subheader("Set Alerts:")
 alert_type = st.sidebar.selectbox('Alert Type', ['Price', 'RSI'])
 alert_value = st.sidebar.number_input('Enter Alert Value')
 
-# Step 9: Run the Streamlit App (Note: Do not use st.run())
+# Step 8: Run the Streamlit App (Note: Do not use st.run())
 # Save as `app.py` and run it using `streamlit run app.py`