L CANSLIM

industry_sic_codes.csv

@@ -0,0 +1,44 @@
+SIC Code,Office,Industry Title
+100,Industrial Applications and Services,AGRICULTURAL PRODUCTION-CROPS
+200,Industrial Applications and Services,AGRICULTURAL PROD-LIVESTOCK & ANIMAL SPECIALTIES
+700,Industrial Applications and Services,AGRICULTURAL SERVICES
+800,Industrial Applications and Services,FORESTRY
+900,Industrial Applications and Services,"FISHING, HUNTING AND TRAPPING"
+1000,Office of Energy & Transportation,METAL MINING
+1040,Office of Energy & Transportation,GOLD AND SILVER ORES
+1090,Office of Energy & Transportation,MISCELLANEOUS METAL ORES
+1220,Office of Energy & Transportation,BITUMINOUS COAL & LIGNITE MINING
+1221,Office of Energy & Transportation,BITUMINOUS COAL & LIGNITE SURFACE MINING
+1311,Office of Energy & Transportation,CRUDE PETROLEUM & NATURAL GAS
+1381,Office of Energy & Transportation,DRILLING OIL & GAS WELLS
+1382,Office of Energy & Transportation,OIL & GAS FIELD EXPLORATION SERVICES
+1389,Office of Energy & Transportation,"OIL & GAS FIELD SERVICES, NEC"
+1400,Office of Energy & Transportation,MINING & QUARRYING OF NONMETALLIC MINERALS (NO FUELS)
+1520,Office of Real Estate & Construction,GENERAL BLDG CONTRACTORS - RESIDENTIAL BLDGS
+1531,Office of Real Estate & Construction,OPERATIVE BUILDERS
+1540,Office of Real Estate & Construction,GENERAL BLDG CONTRACTORS - NONRESIDENTIAL BLDGS
+1600,Office of Real Estate & Construction,HEAVY CONSTRUCTION OTHER THAN BLDG CONST - CONTRACTORS
+1623,Office of Real Estate & Construction,"WATER, SEWER, PIPELINE, COMM & POWER LINE CONSTRUCTION"
+1700,Office of Real Estate & Construction,CONSTRUCTION - SPECIAL TRADE CONTRACTORS
+1731,Office of Real Estate & Construction,ELECTRICAL WORK
+2000,Office of Manufacturing,FOOD AND KINDRED PRODUCTS
+2011,Office of Manufacturing,MEAT PACKING PLANTS
+2013,Office of Manufacturing,SAUSAGES & OTHER PREPARED MEAT PRODUCTS
+2015,Office of Manufacturing,POULTRY SLAUGHTERING AND PROCESSING
+2020,Office of Manufacturing,DAIRY PRODUCTS
+2024,Office of Manufacturing,ICE CREAM & FROZEN DESSERTS
+2030,Office of Manufacturing,"CANNED, FROZEN & PRESERVD FRUIT, VEG & FOOD SPECIALTIES"
+2033,Office of Manufacturing,"CANNED, FRUITS, VEG, PRESERVES, JAMS & JELLIES"
+2040,Office of Manufacturing,GRAIN MILL PRODUCTS
+2050,Office of Manufacturing,BAKERY PRODUCTS
+2052,Office of Manufacturing,COOKIES & CRACKERS
+2060,Office of Manufacturing,SUGAR & CONFECTIONERY PRODUCTS
+2070,Office of Manufacturing,FATS & OILS
+2080,Office of Manufacturing,BEVERAGES
+2082,Office of Manufacturing,MALT BEVERAGES
+2086,Office of Manufacturing,BOTTLED & CANNED SOFT DRINKS & CARBONATED WATERS
+2090,Office of Manufacturing,MISCELLANEOUS FOOD PREPARATIONS & KINDRED PRODUCTS
+2092,Office of Manufacturing,PREPARED FRESH OR FROZEN FISH & SEAFOODS
+2100,Office of Manufacturing,TOBACCO PRODUCTS
+2111,Office of Manufacturing,CIGARETTES
+2200,Office of Manufacturing,TEXTILE MILL PRODUCTS

src/main.py

@@ -2,6 +2,7 @@ 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.csv_appender import append_scores_to_csv
 from screener.screeners import SCREENERS  # Import categories
 from screener.user_input import get_user_screener_selection  # Import function
@@ -15,7 +16,8 @@ def main():
     start_date, end_date = validate_date_range(user_start_date, user_end_date, required_quarters=4)
 
     # 3️⃣ Get selected screeners & customization preferences
-    selected_screeners = get_user_screener_selection()  # ✅ Now imported from `user_input.py`
+    selected_screeners = get_user_screener_selection()  
+    print(f"\n✅ Selected Screeners: {selected_screeners}\n")  # ✅ DEBUG LOG
 
     # 4️⃣ Get all stock symbols dynamically
     symbol_list = get_stocks_in_time_range(start_date, end_date)
@@ -24,14 +26,14 @@ def main():
         print("No stocks found within the given date range.")
         return
 
-    print(f"Processing {len(symbol_list)} stocks within the given date range...")
+    print(f"Processing {len(symbol_list)} stocks within the given date range...\n")
 
     # 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.")
+            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 = {}
@@ -47,15 +49,21 @@ def main():
                         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
                     
                     # Apply user-defined threshold if applicable
                     if isinstance(threshold, (int, float)):
                         scores[screener] = scores[screener] >= threshold
 
-        # 7️⃣ Append results to CSV
+        # 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")
+    print("✅ Scores saved in data/metrics/stock_scores.csv\n")
 
 if __name__ == "__main__":
     main()

src/screener/csv_appender.py

@@ -1,57 +1,50 @@
 import csv
 import os
 
-# Define the directory and generic CSV file path
+CSV_FILE_PATH = os.path.abspath(os.path.join(os.path.dirname(__file__), "../../data/metrics/stock_scores.csv"))
-BASE_DIR = os.path.abspath(os.path.join(os.path.dirname(__file__), "../.."))  # Go two levels up
-METRICS_DIR = os.path.join(BASE_DIR, "data", "metrics")
-CSV_FILE = os.path.join(METRICS_DIR, "stock_scores.csv")
-
-# Track all unique screeners used in any stock
-ALL_HEADERS = set()
 
 def append_scores_to_csv(symbol, scores):
     """
-    Append stock analysis scores to a generic CSV file in `data/metrics` directory.
+    Appends stock scores to the CSV file dynamically and ensures output order matches CSV.
-    
+
-    Ensures all rows have the same headers, adding new screeners dynamically.
-    
     Args:
         symbol (str): Stock ticker symbol.
-        scores (dict): Dictionary of metric scores (e.g., EPS_Score, Sales_Score, etc.).
+        scores (dict): Dictionary of scores for each screener.
     """
-    # Ensure the directory exists
+    file_exists = os.path.exists(CSV_FILE_PATH)
-    os.makedirs(METRICS_DIR, exist_ok=True)
 
-    # Compute Total Score
+    # Ensure Total_Score is always included
-    total_score = sum(scores.values())
+    scores["Total_Score"] = sum(scores.values())
-    scores["Total_Score"] = total_score
 
-    # Update tracked headers
+    # Read existing headers if the file exists
-    ALL_HEADERS.update(scores.keys())
+    existing_headers = []
+    if file_exists:
+        with open(CSV_FILE_PATH, mode="r", encoding="utf-8") as file:
+            reader = csv.reader(file)
+            existing_headers = next(reader, [])
 
-    # Preferred order: "Symbol" first, "Total_Score" last
+    # Ensure headers dynamically include all possible screeners, keeping order
-    preferred_order = ["Symbol"]
+    new_headers = ["Symbol"] + list(scores.keys())
-    remaining_headers = sorted([h for h in ALL_HEADERS if h not in preferred_order + ["Total_Score"]])
-    sorted_headers = preferred_order + remaining_headers + ["Total_Score"]
 
-    # Check if file exists
+    # Merge existing headers with new ones, keeping Symbol first and Total_Score last
-    file_exists = os.path.isfile(CSV_FILE)
+    headers = existing_headers if existing_headers else new_headers
+    if "L_Score" not in headers:
+        headers.insert(-1, "L_Score")  # Ensure L_Score is before Total_Score
 
-    with open(CSV_FILE, 'a', newline='') as csvfile:
+    # Ensure order consistency for output
-        writer = csv.DictWriter(csvfile, fieldnames=sorted_headers)
+    row_data = {header: scores.get(header, 0) for header in headers}
+    row_data["Symbol"] = symbol  # Ensure Symbol is set
 
-        # If it's a new file or headers changed, write a new header row
+    # ✅ Print scores in the exact order they will appear in the CSV
-        if not file_exists or set(sorted_headers) != set(writer.fieldnames):
+    print("\n📊 Score Output (Matching CSV Order):")
-            csvfile.seek(0)  # Move to start of the file
+    print(f"{symbol}: " + ", ".join([f"{key}: {row_data[key]}" for key in headers]))
-            csvfile.truncate()  # Clear previous file to rewrite headers
+
+    # Open CSV and update headers if needed
+    with open(CSV_FILE_PATH, mode="a", newline="") as file:
+        writer = csv.DictWriter(file, fieldnames=headers)
+
+        # Write header only if file is new or headers have changed
+        if not file_exists or set(headers) != set(existing_headers):
             writer.writeheader()
 
-        # Fill missing values with 0.25 (default)
+        writer.writerow(row_data)
-        row = {"Symbol": symbol}
-        for header in sorted_headers:
-            if header == "Symbol":
-                row[header] = symbol
-            else:
-                row[header] = scores.get(header, 0.25)  # Use default if missing
-        
-        writer.writerow(row)

src/screener/l_canslim.py

@@ -0,0 +1,77 @@
+import csv
+import os
+from db.db_connection import create_client
+
+# Load SIC Industry Data
+SIC_LOOKUP = {}
+
+def load_sic_data():
+    """Loads SIC Code data into a dictionary from the new CSV location above `src/`."""
+    global SIC_LOOKUP
+    script_dir = os.path.dirname(os.path.abspath(__file__))  # Get the directory of l_canslim.py
+    project_root = os.path.abspath(os.path.join(script_dir, "../../"))  # Go up to project root
+    sic_file = os.path.join(project_root, "industry_sic_codes.csv")  # Adjust path
+
+    if not os.path.exists(sic_file):
+        raise FileNotFoundError(f"Error: SIC Code CSV file not found at {sic_file}")
+
+    with open(sic_file, mode="r", encoding="utf-8") as file:
+        reader = csv.DictReader(file)
+        for row in reader:
+            sic_code = row["SIC Code"].strip()  # Match CSV header exactly
+            industry = row["Industry Title"].strip()  # Match CSV header exactly
+            SIC_LOOKUP[sic_code] = industry
+
+# Ensure SIC data is loaded at module import
+load_sic_data()
+
+def check_industry_leadership(symbol):
+    """
+    Determines if a stock is a leader in its industry group.
+
+    Criteria:
+    - Relative Strength (RS) Rating should be **80 or higher**.
+    - Stock should be in the top-performing industry groups (top 40-50).
+    - Stock should be trading near its **52-week high**.
+
+    Args:
+        symbol (str): Stock ticker symbol.
+
+    Returns:
+        float: 1 (Pass), 0 (Fail), 0.25 (Insufficient Data).
+    """
+    client = create_client()
+
+    query = f"""
+        SELECT 
+            ticker, 
+            sic, 
+            relative_strength, 
+            high_52_week, 
+            current_price 
+        FROM stock_db.stock_indicators
+        WHERE ticker = '{symbol}'
+    """
+
+    result = client.query(query)
+
+    if not result.result_rows:
+        return 0.25  # Not enough data
+
+    _, sic, rs_rating, high_52_week, current_price = result.result_rows[0]
+
+    if not sic or str(sic) not in SIC_LOOKUP:
+        return 0.25  # No SIC industry data available
+
+    # Ensure RS rating is valid
+    if rs_rating is None or high_52_week is None or current_price is None:
+        return 0.25  # Missing necessary data
+
+    # Industry Leader Criteria
+    passes_rs = rs_rating >= 80
+    near_high = current_price >= (high_52_week * 0.90)  # Within 10% of 52-week high
+
+    if passes_rs and near_high:
+        return 1  # Stock is an industry leader
+    else:
+        return 0  # Stock is lagging

src/screener/screeners.py

@@ -4,7 +4,8 @@ SCREENERS = {
         "EPS_Score": "Checks quarterly EPS growth",
         "Annual_EPS_Score": "Checks 3-year annual EPS growth",
         "Sales_Score": "Checks quarterly sales growth",
-        "ROE_Score": "Checks return on equity"
+        "ROE_Score": "Checks return on equity",
+        "L_Score": "Checks if the stock is a leader in its industry"  # ✅ NEW: Added L_Score
     },
     "Volume-Based": {
         "Volume_Oscillator_Score": "Checks for unusual volume surges",

src/screener/user_input.py

@@ -21,9 +21,9 @@ def get_user_screener_selection():
     for category in selected_categories:
         print(f"\nCategory: {category}")
         use_defaults = input(f"Use default settings for {category}? (y/n): ").strip().lower()
-        
+
         selected_screeners[category] = {}
-        
+
         for screener, description in SCREENERS[category].items():
             if use_defaults == "y":
                 selected_screeners[category][screener] = "default"
@@ -31,4 +31,10 @@ def get_user_screener_selection():
                 custom_value = input(f"{screener} ({description}) - Enter custom threshold or press Enter to use default: ").strip()
                 selected_screeners[category][screener] = float(custom_value) if custom_value else "default"
 
+    # ✅ Ensure L_Score is added if Fundamentals is selected
+    if "Fundamentals" in selected_screeners and "L_Score" not in selected_screeners["Fundamentals"]:
+        selected_screeners["Fundamentals"]["L_Score"] = "default"  # ✅ Ensure L_Score is included
+
+    print(f"\n✅ Selected Screeners: {selected_screeners}\n")  # ✅ DEBUG LOG
+
     return selected_screeners