duplicate_checker.py aktualisiert

duplicate_checker.py

@@ -6,64 +6,60 @@ from thefuzz import fuzz
 from helpers import normalize_company_name, simple_normalize_url
 from google_sheet_handler import GoogleSheetHandler
 
-# duplicate_checker.py v2.7 (Logging-Setup Fix)
+# duplicate_checker.py v2.8 (Match-Komponenten im Log)
-# Version: 2025-08-06_17-30
+# Version: 2025-08-06_17-50
 
 # --- Konfiguration ---
 CRM_SHEET_NAME      = "CRM_Accounts"
 MATCHING_SHEET_NAME = "Matching_Accounts"
 SCORE_THRESHOLD     = 80
 LOG_DIR             = "Log"
-LOG_FILE            = "duplicate_check_v2.7.log"
+LOG_FILE            = "duplicate_check_v2.8.log"
 
 # --- Logging Setup ---
 if not os.path.exists(LOG_DIR):
     os.makedirs(LOG_DIR, exist_ok=True)
 log_path = os.path.join(LOG_DIR, LOG_FILE)
-
+root = logging.getLogger()
-# Clear existing handlers
+root.setLevel(logging.DEBUG)
-root_logger = logging.getLogger()
+# Remove old handlers
-root_logger.setLevel(logging.DEBUG)
+for h in list(root.handlers):
-for h in list(root_logger.handlers):
+    root.removeHandler(h)
-    root_logger.removeHandler(h)
-
-# Formatter
 formatter = logging.Formatter("%(asctime)s - %(levelname)-8s - %(message)s")
-
+# Console
-# Console Handler - INFO+
 ch = logging.StreamHandler(sys.stdout)
 ch.setLevel(logging.INFO)
 ch.setFormatter(formatter)
-root_logger.addHandler(ch)
+root.addHandler(ch)
-
+# File
-# File Handler - DEBUG+
 fh = logging.FileHandler(log_path, mode='a', encoding='utf-8')
 fh.setLevel(logging.DEBUG)
 fh.setFormatter(formatter)
-root_logger.addHandler(fh)
+root.addHandler(fh)
-
 logger = logging.getLogger(__name__)
 logger.info(f"Logging to console and file: {log_path}")
-logger.info("Starting duplicate_checker.py v2.7 | Version: 2025-08-06_17-30")
+logger.info("Starting duplicate_checker.py v2.8 | Version: 2025-08-06_17-50")
 
 
-def calculate_similarity(record1, record2):
+def calculate_similarity_components(r1, r2):
-    total_score = 0
+    """Gibt einzelne Komponenten und Gesamt-Score zurück."""
-    dom1 = record1.get('normalized_domain', '')
+    # Domain
-    dom2 = record2.get('normalized_domain', '')
+    dom1 = r1.get('normalized_domain', '')
-    if dom1 and dom1 == dom2:
+    dom2 = r2.get('normalized_domain', '')
-        total_score += 100
+    domain_match = 1 if dom1 and dom1 == dom2 else 0
-    name1 = record1.get('normalized_name', '')
+    # Name
-    name2 = record2.get('normalized_name', '')
+    name1 = r1.get('normalized_name', '')
-    if name1 and name2:
+    name2 = r2.get('normalized_name', '')
-        total_score += fuzz.token_set_ratio(name1, name2) * 0.7
+    name_score = fuzz.token_set_ratio(name1, name2) if name1 and name2 else 0
-    if record1.get('CRM Ort') == record2.get('CRM Ort') and record1.get('CRM Land') == record2.get('CRM Land'):
+    # Ort+Land
-        total_score += 20
+    loc_match = 1 if (r1.get('CRM Ort') == r2.get('CRM Ort') and r1.get('CRM Land') == r2.get('CRM Land')) else 0
-    return round(total_score)
+    # Gewichte
+    total = domain_match * 100 + name_score * 0.7 + loc_match * 20
+    return round(total), domain_match, round(name_score,1), loc_match
 
 
 def main():
-    logger.info("Starte Duplikats-Check v2.7")
+    logger.info("Starte Duplikats-Check v2.8 (Match-Komponenten im Log)")
     try:
         sheet_handler = GoogleSheetHandler()
         logger.info("GoogleSheetHandler initialisiert")
@@ -71,7 +67,7 @@ def main():
         logger.critical(f"Init GoogleSheetHandler fehlgeschlagen: {e}")
         sys.exit(1)
 
-    # Load data
+    # Daten laden
     logger.info(f"Lade CRM-Daten aus '{CRM_SHEET_NAME}'...")
     crm_df = sheet_handler.get_sheet_as_dataframe(CRM_SHEET_NAME)
     if crm_df is None or crm_df.empty:
@@ -86,7 +82,7 @@ def main():
         return
     logger.info(f"{len(match_df)} Matching-Datensätze geladen")
 
-    # Normalize & blocking key
+    # Normalisierung & Blocking-Key
     for df, label in [(crm_df, 'CRM'), (match_df, 'Matching')]:
         df['normalized_name']   = df['CRM Name'].astype(str).apply(normalize_company_name)
         df['normalized_domain'] = df['CRM Website'].astype(str).apply(simple_normalize_url)
@@ -115,16 +111,21 @@ def main():
         if not candidates:
             results.append({'Potenzieller Treffer im CRM':'', 'Ähnlichkeits-Score':0})
             continue
-        scored = [(crow['CRM Name'], calculate_similarity(mrow, crow)) for crow in candidates]
+        scored = []
+        for crow in candidates:
+            score, dm, ns, lm = calculate_similarity_components(mrow, crow)
+            scored.append((crow['CRM Name'], score, dm, ns, lm))
         top3 = sorted(scored, key=lambda x: x[1], reverse=True)[:3]
-        logger.debug(f" Top3 Kandidaten: {top3}")
+        # Log Top3 mit Komponenten
-        best_name, best_score = max(scored, key=lambda x: x[1])
+        for name, sc, dm, ns, lm in top3:
+            logger.debug(f"  Kandidat: {name}, Score={sc}, Domain={dm}, Name={ns}, Ort={lm}")
+        best_name, best_score, best_dm, best_ns, best_lm = max(scored, key=lambda x: x[1])
         if best_score >= SCORE_THRESHOLD:
             results.append({'Potenzieller Treffer im CRM':best_name, 'Ähnlichkeits-Score':best_score})
-            logger.info(f" --> Match: '{best_name}' Score={best_score}")
+            logger.info(f" --> Match: '{best_name}' Score={best_score} (Dom={best_dm}, Name={best_ns}, Ort={best_lm})")
         else:
-            results.append({'Potenzieller Treffer im CRM': best_name or '', 'Ähnlichkeits-Score': best_score})
+            results.append({'Potenzieller Treffer im CRM':'', 'Ähnlichkeits-Score':best_score})
-            logger.info(f" --> Kein Match (Score {best_score})")
+            logger.info(f" --> Kein Match (Score={best_score}, Dom={best_dm}, Name={best_ns}, Ort={best_lm})")
 
     # Write back
     logger.info("Schreibe Ergebnisse zurück ins Sheet...")