feat: Add SunnyBand scanner and multi-system menu to main.py

src/main.py

@@ -2,72 +2,99 @@ import datetime
 from screener.data_fetcher import validate_date_range, fetch_financial_data, get_stocks_in_time_range
 from screener.c_canslim import check_quarterly_earnings, check_return_on_equity, check_sales_growth
 from screener.a_canslim import check_annual_eps_growth
-from screener.l_canslim import check_industry_leadership  # ✅ NEW: Import L Score function
+from screener.l_canslim import check_industry_leadership
-from screener.i_canslim import check_institutional_sponsorship  # ✅ NEW: Import I Score function
+from screener.i_canslim import check_institutional_sponsorship
 from screener.csv_appender import append_scores_to_csv
-from screener.screeners import SCREENERS  # Import categories
+from screener.screeners import SCREENERS
-from screener.user_input import get_user_screener_selection  # Import function
+from screener.user_input import get_user_screener_selection
+
+def get_float_input(prompt: str) -> float:
+    while True:
+        try:
+            return float(input(prompt))
+        except ValueError:
+            print("Please enter a valid number")
+
+def get_scanner_parameters():
+    """Get user input for scanner parameters"""
+    min_price = get_float_input("Enter minimum stock price ($): ")
+    max_price = get_float_input("Enter maximum stock price ($): ")
+    min_volume = int(input("Enter minimum volume: "))
+    return min_price, max_price, min_volume
 
 def main():
-    # 1️⃣ Ask user for start and end date
+    print("\nStock Analysis System")
-    user_start_date = input("Enter start date (YYYY-MM-DD): ")
+    print("1. Run CANSLIM Screener")
-    user_end_date = input("Enter end date (YYYY-MM-DD): ")
+    print("2. Run SunnyBand Scanner")
+    print("3. Launch Trading System")
+    print("4. Exit")
     
-    # 2️⃣ Validate and adjust date range if needed
+    choice = input("\nSelect an option (1-4): ")
-    start_date, end_date = validate_date_range(user_start_date, user_end_date, required_quarters=4)
     
-    # 3️⃣ Get selected screeners & customization preferences
+    if choice == "1":
-    selected_screeners = get_user_screener_selection()  
+        # 1️⃣ Ask user for start and end date
-    print(f"\n✅ Selected Screeners: {selected_screeners}\n")  # ✅ DEBUG LOG
+        user_start_date = input("Enter start date (YYYY-MM-DD): ")
+        user_end_date = input("Enter end date (YYYY-MM-DD): ")
     
-    # 4️⃣ Get all stock symbols dynamically
+        # 2️⃣ Validate and adjust date range if needed
-    symbol_list = get_stocks_in_time_range(start_date, end_date)
+        start_date, end_date = validate_date_range(user_start_date, user_end_date, required_quarters=4)
+        selected_screeners = get_user_screener_selection()
+        symbol_list = get_stocks_in_time_range(start_date, end_date)
         
-    if not symbol_list:
+        if not symbol_list:
-        print("No stocks found within the given date range.")
+            print("No stocks found within the given date range.")
+            return
+
+        print(f"Processing {len(symbol_list)} stocks within the given date range...\n")
+
+        for symbol in symbol_list:
+            data = fetch_financial_data(symbol, start_date, end_date)
+
+            if not data:
+                print(f"⚠️ Warning: No data returned for {symbol}. Assigning default score.\n")
+                scores = {screener: 0.25 for category in selected_screeners for screener in selected_screeners[category]}
+            else:
+                scores = {}
+
+                for category, screeners in selected_screeners.items():
+                    for screener, threshold in screeners.items():
+                        if screener == "EPS_Score":
+                            scores[screener] = check_quarterly_earnings(data.get("quarterly_eps", []))
+                        elif screener == "Annual_EPS_Score":
+                            scores[screener] = check_annual_eps_growth(data.get("annual_eps", []))
+                        elif screener == "Sales_Score":
+                            scores[screener] = check_sales_growth(data.get("sales_growth", []))
+                        elif screener == "ROE_Score":
+                            scores[screener] = check_return_on_equity(data.get("roe", []))
+                        elif screener == "L_Score":
+                            scores[screener] = check_industry_leadership(symbol)
+                            print(f"🟢 {symbol} - L_Score: {scores[screener]}")
+                        elif screener == "I_Score":
+                            scores[screener] = check_institutional_sponsorship(symbol)
+                            print(f"🏢 {symbol} - I_Score: {scores[screener]}")
+                        
+                        if isinstance(threshold, (int, float)):
+                            scores[screener] = scores[screener] >= threshold
+
+            scores["Total_Score"] = sum(scores.values())
+            append_scores_to_csv(symbol, scores)
+
+        print("✅ Scores saved in data/metrics/stock_scores.csv\n")
+
+    elif choice == "2":
+        min_price, max_price, min_volume = get_scanner_parameters()
+        from screener.t_sunnyband import run_sunny_scanner
+        run_sunny_scanner(min_price, max_price, min_volume)
+        
+    elif choice == "3":
+        from trading.main import main as trading_main
+        trading_main()
+        
+    elif choice == "4":
+        print("Exiting...")
         return
-
+    else:
-    print(f"Processing {len(symbol_list)} stocks within the given date range...\n")
+        print("Invalid choice. Please try again.")
-
-    # 5️⃣ Process each stock symbol
-    for symbol in symbol_list:
-        data = fetch_financial_data(symbol, start_date, end_date)
-
-        if not data:
-            print(f"⚠️ Warning: No data returned for {symbol}. Assigning default score.\n")
-            scores = {screener: 0.25 for category in selected_screeners for screener in selected_screeners[category]}
-        else:
-            scores = {}
-
-            # 6️⃣ Compute scores dynamically based on user selection
-            for category, screeners in selected_screeners.items():
-                for screener, threshold in screeners.items():
-                    if screener == "EPS_Score":
-                        scores[screener] = check_quarterly_earnings(data.get("quarterly_eps", []))
-                    elif screener == "Annual_EPS_Score":
-                        scores[screener] = check_annual_eps_growth(data.get("annual_eps", []))
-                    elif screener == "Sales_Score":
-                        scores[screener] = check_sales_growth(data.get("sales_growth", []))
-                    elif screener == "ROE_Score":
-                        scores[screener] = check_return_on_equity(data.get("roe", []))
-                    elif screener == "L_Score":
-                        scores[screener] = check_industry_leadership(symbol)  # ✅ NEW: Industry Leadership Calculation
-                        print(f"🟢 {symbol} - L_Score: {scores[screener]}")  # ✅ DEBUG LOG
-                    elif screener == "I_Score":
-                        scores[screener] = check_institutional_sponsorship(symbol)  # ✅ NEW: Institutional Sponsorship Check
-                        print(f"🏢 {symbol} - I_Score: {scores[screener]}")  # ✅ DEBUG LOG
-                    
-                    # Apply user-defined threshold if applicable
-                    if isinstance(threshold, (int, float)):
-                        scores[screener] = scores[screener] >= threshold
-
-        # 7️⃣ Calculate Total Score
-        scores["Total_Score"] = sum(scores.values())  # ✅ NEW: Total Score Calculation
-
-        # 8️⃣ Append results to CSV
-        append_scores_to_csv(symbol, scores)
-
-    print("✅ Scores saved in data/metrics/stock_scores.csv\n")
 
 if __name__ == "__main__":
     main()