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97309be a8f863d 97309be a8f863d 97309be a8f863d 97309be a8f863d 97309be a8f863d 97309be a8f863d 97309be a8f863d | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 | import streamlit as st
import pandas as pd
import plotly.graph_objects as go
from stockbot import StockAnalyzer
import time
st.set_page_config(page_title="Stock Analysis Dashboard", layout="wide")
# Initialize session state
if 'analyzer' not in st.session_state:
st.session_state.analyzer = StockAnalyzer()
st.session_state.last_update = None
def create_candlestick_chart(symbol, price_data):
"""Create a candlestick chart using plotly"""
fig = go.Figure(data=[go.Candlestick(x=price_data.index,
open=price_data['Open'],
high=price_data['High'],
low=price_data['Low'],
close=price_data['Close'])])
fig.update_layout(title=f'{symbol} Price History',
xaxis_title='Date',
yaxis_title='Price ($)',
template='plotly_dark')
return fig
def main():
st.title("Stock Analysis Dashboard")
# Add refresh button
col1, col2 = st.columns([1, 5])
with col1:
if st.button("🔄 Refresh Data"):
st.session_state.analyzer.update_data()
st.session_state.analyzer.analyze_stocks()
st.session_state.last_update = time.strftime("%Y-%m-%d %H:%M:%S")
st.success("Data refreshed!")
with col2:
if st.session_state.last_update:
st.text(f"Last Update: {st.session_state.last_update}")
# Display stock analysis results
results = st.session_state.analyzer.analysis_results
if results:
# Convert results to DataFrame for easier display
data = []
for symbol, info in results.items():
data.append({
'Symbol': symbol,
'Price': f"${info['current_price']}",
'7d Change': f"{info['change_7d']}%",
'30d Change': f"{info['change_30d']}%",
'90d Change': f"{info['change_90d']}%",
'YTD Change': f"{info['change_365d']}%",
'RSI': round(info['rsi'], 2),
'Trend': info['trend'],
'Support': f"${info['support']}",
'Resistance': f"${info['resistance']}",
'Recommendation': info['recommendation'],
'LLM Sentiment': info['llm_analysis']['sentiment'],
'LLM Confidence': f"{info['llm_analysis']['confidence']:.1%}",
'7d Prediction': f"{info['predictions']['prediction_7d']}%",
'21d Prediction': f"{info['predictions']['prediction_21d']}%"
})
df = pd.DataFrame(data)
# Style the dataframe
def color_negative_red(val):
try:
value = float(val.replace('%', '').replace('$', ''))
color = 'red' if value < 0 else 'green' if value > 0 else 'white'
return f'color: {color}'
except:
return ''
styled_df = df.style.applymap(color_negative_red, subset=['7d Change', '30d Change', '90d Change', 'YTD Change'])
# Display the main table
st.dataframe(styled_df, height=400)
# Add detailed view for selected stock
st.subheader("Detailed Stock Analysis")
selected_symbol = st.selectbox("Select a stock for detailed analysis", list(results.keys()))
if selected_symbol:
col1, col2 = st.columns(2)
with col1:
# Display candlestick chart
if selected_symbol in st.session_state.analyzer.price_data:
price_data = st.session_state.analyzer.price_data[selected_symbol]
fig = create_candlestick_chart(selected_symbol, price_data)
st.plotly_chart(fig, use_container_width=True)
with col2:
# Display detailed analysis
stock_info = results[selected_symbol]
st.write("### Technical Analysis")
st.write(f"**Current Price:** ${stock_info['current_price']}")
st.write(f"**RSI:** {stock_info['rsi']:.2f}")
st.write(f"**Trend:** {stock_info['trend']}")
st.write(f"**Support Levels:** ${stock_info['support']}")
st.write(f"**Resistance Levels:** ${stock_info['resistance']}")
st.write("### LLM Analysis")
st.write(f"**Sentiment:** {stock_info['llm_analysis']['sentiment']}")
st.write(f"**Confidence:** {stock_info['llm_analysis']['confidence']:.1%}")
st.write("### Predictions")
st.write(f"**7-Day Forecast:** {stock_info['predictions']['prediction_7d']}%")
st.write(f"**21-Day Forecast:** {stock_info['predictions']['prediction_21d']}%")
st.write(f"**Confidence:** {stock_info['predictions']['confidence']}%")
# Display support/resistance analysis from LLM
if 'support_resistance' in stock_info['llm_analysis']:
st.write("### Support & Resistance Analysis")
sr_analysis = stock_info['llm_analysis']['support_resistance']
st.write(sr_analysis['analysis'])
if __name__ == "__main__":
main() |