diff --git a/duplicate_checker.py b/duplicate_checker.py
index 6b275e98..d86874e6 100644
--- a/duplicate_checker.py
+++ b/duplicate_checker.py
@@ -1,3 +1,4 @@
+import os
 import re
 import logging
 import pandas as pd
@@ -14,11 +15,37 @@ WEIGHTS = {
     'name':   0.4,
     'city':   0.1,
 }
+LOG_DIR = '/log'
+LOG_FILENAME = 'duplicate_check.log'
 
 # --- Logging Setup ---
-LOG_FORMAT = '%(asctime)s - %(levelname)-8s - %(name)s - %(message)s'
-logging.basicConfig(level=logging.DEBUG, format=LOG_FORMAT)
+if not os.path.exists(LOG_DIR):
+    try:
+        os.makedirs(LOG_DIR)
+    except Exception as e:
+        print(f"Warnung: Konnte Log-Ordner nicht anlegen: {e}")
+log_path = os.path.join(LOG_DIR, LOG_FILENAME)
+
 logger = logging.getLogger(__name__)
+logger.setLevel(logging.DEBUG)
+
+formatter = logging.Formatter('%(asctime)s - %(levelname)-8s - %(name)s - %(message)s')
+
+# Console Handler
+console_handler = logging.StreamHandler()
+console_handler.setLevel(logging.INFO)
+console_handler.setFormatter(formatter)
+logger.addHandler(console_handler)
+
+# File Handler
+try:
+    file_handler = logging.FileHandler(log_path, mode='a', encoding='utf-8')
+    file_handler.setLevel(logging.DEBUG)
+    file_handler.setFormatter(formatter)
+    logger.addHandler(file_handler)
+    logger.info(f"Logging auch in Datei: {log_path}")
+except Exception as e:
+    logger.warning(f"Konnte keine Log-Datei schreiben: {e}")
 
 # --- Hilfsfunktionen ---
 def normalize_company_name(name: str) -> str:
@@ -41,7 +68,7 @@ def normalize_domain(url: str) -> str:
 
 
 def main():
-    logger.info("Starte den Duplikats-Check (v2.0 mit Blocking und Maximum Logging)...")
+    logger.info("Starte den Duplikats-Check (v2.0 mit Logging in /log)...")
     # GoogleSheetHandler initialisieren
     try:
         sheet_handler = GoogleSheetHandler()
@@ -71,7 +98,7 @@ def main():
         df['norm_name'] = df['CRM Name'].fillna('').apply(normalize_company_name)
         df['norm_domain'] = df['CRM Website'].fillna('').apply(normalize_domain)
         df['city'] = df['CRM Ort'].fillna('').apply(lambda x: str(x).casefold().strip())
-        logger.debug(f"{label}-Daten nach Normalisierung. Erste Zeile: {df.iloc[0].to_dict()}")
+        logger.debug(f"{label}-Daten normalisiert. Erste Zeile: {df.iloc[0].to_dict()}")
 
     # Blocking per Domain
     indexer = recordlinkage.Index()
@@ -100,7 +127,7 @@ def main():
     for match_idx, group in features.reset_index().groupby('level_1'):
         logger.info(f"--- Prüfe: Zeile {match_idx} ---")
         df_block = group.sort_values('score', ascending=False)
-        logger.debug(f"  Kandidaten für Zeile {match_idx}:\n{df_block[['level_0','score','domain','name_sim','city']].to_string(index=False)}")
+        logger.debug(f"Kandidaten für Zeile {match_idx}:\n{df_block[['level_0','score','domain','name_sim','city']].to_string(index=False)}")
         top = df_block.iloc[0]
         crm_idx = top['level_0'] if top['score'] >= SCORE_THRESHOLD else None
         if crm_idx is not None: