feat: Implement mobile application and lead processing utilities.

scripts/prepare_batch6_v2.py

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+import json
+
+processed_proximates = [
+    "Baugewerbe", "Dachdecker", "Elektro", "Sanitär", "Stahl", "Tischler", "Maler", "Kraftfahrzeug", "Friseur", "Fleischer",
+    "Zimmerer", "Glaser", "Rollladen", "Gebäudereiniger", "Augenoptiker", "Bäcker", "Konditoren", "Schornsteinfeger", "Steinmetz", "Straßenbauer",
+    "Stukkateur", "Boots", "Gold", "Informationstechnik", "Kachel", "Karosserie", "Schneider", "Instrumenten", "Orthopädie", "Parkett", "Sattler", "Werbe", "Zahn"
+]
+
+def is_processed(name):
+    for p in processed_proximates:
+        # Check for word boundary or similar to avoid false positives if possible, but simple substring is mostly fine
+        # "Sanitär" matches "Innung Sanitär-Heizung..."
+        if p in name:
+            return True
+    return False
+
+def prepare_batch6():
+    with open('cologne_duesseldorf_data/duesseldorf_targets.json', 'r', encoding='utf-8') as f:
+        targets = json.load(f)
+        
+    new_targets = []
+    skipped_count = 0
+    for t in targets:
+        if not is_processed(t['innung']):
+            new_targets.append(t)
+        else:
+            skipped_count += 1
+            
+    print(f"Skipped {skipped_count} processed targets.")
+    print(f"Found {len(new_targets)} unprocessed targets.")
+    
+    batch6 = new_targets[:30]
+    with open('cologne_duesseldorf_data/batch6_targets.json', 'w', encoding='utf-8') as f:
+        json.dump(batch6, f, indent=2)
+        
+    for i, t in enumerate(batch6):
+        print(f"Target {i+1}: {t['innung']}")
+
+if __name__ == "__main__":
+    prepare_batch6()