Create app.py

app.py

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+import gradio as gr
+import yfinance as yf
+import pandas as pd
+import plotly.graph_objects as go
+from transformers import pipeline
+from datetime import datetime, timedelta
+import requests
+from bs4 import BeautifulSoup
+import feedparser
+
+# ------------------- Constants -------------------
+KSE_100 = [
+    "HBL", "UBL", "MCB", "BAHL", "ABL", 
+    "LUCK", "EFERT", "FCCL", "DGKC", "MLCF",
+    "OGDC", "PPL", "POL", "PSO", "SNGP",
+    "ENGRO", "HUBC", "KAPCO", "NESTLE", "EFOODS",
+    "PSX", "TRG", "SYS", "NML", "ILP",
+    "ATRL", "NRL", "HASCOL", "SHEL", "BAFL"
+]  # Add all KSE-100 tickers
+
+# ------------------- Hugging Face Models -------------------
+sentiment_analyzer = pipeline("text-classification", model="ProsusAI/finbert")
+news_summarizer = pipeline("summarization", model="facebook/bart-large-cnn")
+
+# ------------------- Technical Analysis -------------------
+def calculate_rsi(data, window=14):
+    delta = data['Close'].diff()
+    gain = (delta.where(delta > 0, 0)).rolling(window=window).mean()
+    loss = (-delta.where(delta < 0, 0)).rolling(window=window).mean()
+    rs = gain / loss
+    return 100 - (100 / (1 + rs))
+
+# ------------------- Data Fetching -------------------
+def get_stock_data(ticker):
+    try:
+        stock = yf.Ticker(f"{ticker}.KA")
+        data = stock.history(period="1y")
+        if data.empty:
+            return None
+        data['RSI'] = calculate_rsi(data)
+        return data
+    except:
+        return None
+
+# ------------------- Analysis Engine -------------------
+def analyze_ticker(ticker):
+    data = get_stock_data(ticker)
+    if data is None:
+        return None
+    
+    current_price = data['Close'].iloc[-1]
+    rsi = data['RSI'].iloc[-1]
+    
+    # Simple Recommendation Logic
+    if rsi < 30:
+        status = "STRONG BUY"
+        color = "green"
+    elif rsi > 70:
+        status = "STRONG SELL"
+        color = "red"
+    else:
+        status = "HOLD"
+        color = "orange"
+    
+    return {
+        "ticker": ticker,
+        "price": round(current_price, 2),
+        "rsi": round(rsi, 2),
+        "status": status,
+        "color": color
+    }
+
+# ------------------- Generate Recommendations -------------------
+def get_recommendations():
+    recommendations = []
+    for ticker in KSE_100:
+        analysis = analyze_ticker(ticker)
+        if analysis:
+            recommendations.append(analysis)
+    
+    df = pd.DataFrame(recommendations)
+    df = df.sort_values(by='rsi')
+    return df
+
+# ------------------- Interface Components -------------------
+def create_stock_analysis(ticker):
+    data = get_stock_data(ticker)
+    if data is None:
+        return "Data not available", None, None
+    
+    # Create Plot
+    fig = go.Figure(data=[go.Candlestick(
+        x=data.index,
+        open=data['Open'],
+        high=data['High'],
+        low=data['Low'],
+        close=data['Close']
+    )])
+    fig.update_layout(title=f"{ticker} Price Chart")
+    
+    # Analysis
+    analysis = analyze_ticker(ticker)
+    status_md = f"## {analysis['status']} \n" \
+                f"**Price**: {analysis['price']} \n" \
+                f"**RSI**: {analysis['rsi']}"
+    
+    return status_md, fig.to_html(), get_news(ticker)
+
+def get_news(ticker):
+    try:
+        url = f"https://www.google.com/search?q={ticker}+stock+pakistan&tbm=nws"
+        response = requests.get(url)
+        soup = BeautifulSoup(response.text, 'html.parser')
+        articles = soup.find_all('div', class_='BNeawe vvjwJb AP7Wnd')[:3]
+        return "\n\n".join([a.text for a in articles])
+    except:
+        return "News unavailable"
+
+# ------------------- Gradio Interface -------------------
+with gr.Blocks(title="PSX Trading Dashboard", theme=gr.themes.Soft()) as app:
+    with gr.Row():
+        # Left Sidebar - KSE-100 List
+        with gr.Column(scale=1, min_width=200):
+            gr.Markdown("## KSE-100 Constituents")
+            kse_list = gr.DataFrame(
+                value=pd.DataFrame(KSE_100, columns=["Ticker"]),
+                interactive=False,
+                height=600
+            )
+        
+        # Main Content
+        with gr.Column(scale=3):
+            gr.Markdown("# PSX Trading Dashboard")
+            with gr.Row():
+                ticker_input = gr.Textbox(label="Enter Ticker", placeholder="HBL")
+                analyze_btn = gr.Button("Analyze")
+            
+            status_output = gr.Markdown()
+            chart_output = gr.HTML()
+            news_output = gr.Textbox(label="Latest News", interactive=False)
+        
+        # Right Sidebar - Recommendations
+        with gr.Column(scale=1, min_width=200):
+            gr.Markdown("## Live Recommendations")
+            recommendations = gr.DataFrame(
+                headers=["Ticker", "Price", "RSI", "Status"],
+                datatype=["str", "number", "number", "str"],
+                interactive=False,
+                height=600
+            )
+    
+    # Event Handlers
+    analyze_btn.click(
+        fn=create_stock_analysis,
+        inputs=ticker_input,
+        outputs=[status_output, chart_output, news_output]
+    )
+    
+    app.load(
+        fn=get_recommendations,
+        outputs=recommendations,
+        every=300  # Refresh every 5 minutes
+    )
+
+# ------------------- Run App -------------------
+if __name__ == "__main__":
+    app.launch(server_port=7860, share=True)