brancheneinstufung2.py aktualisiert
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@@ -12,6 +12,7 @@ Version: v1.8.0
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"""
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import logging
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import os
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import argparse
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import time
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from datetime import datetime
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@@ -23,6 +24,7 @@ from helpers import create_log_filename, initialize_target_schema, alignment_dem
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from google_sheet_handler import GoogleSheetHandler
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from wikipedia_scraper import WikipediaScraper
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from data_processor import DataProcessor
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from sync_manager import SyncManager
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import helpers
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import google_sheet_handler
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@@ -51,12 +53,26 @@ def main():
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Verarbeitet Kommandozeilen-Argumente, richtet Logging ein,
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initialisiert Komponenten und dispatchet zu den passenden Modi.
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"""
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# --- Importe innerhalb der Funktion, um Abhängigkeiten klar zu halten ---
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import argparse
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import time
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import logging
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import os # <<< NEU: für Dateipfad-Prüfung
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from config import Config, log_module_versions, create_log_filename
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from google_sheet_handler import GoogleSheetHandler
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from wikipedia_scraper import WikipediaScraper
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from data_processor import DataProcessor
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from sync_manager import SyncManager # <<< NEU: SyncManager importieren
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import helpers
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import google_sheet_handler # Für Version-Logging
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# --- Argument Parser ---
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parser = argparse.ArgumentParser(
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description=f"Firmen-Datenanreicherungs-Skript {Config.VERSION}.",
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formatter_class=argparse.RawTextHelpFormatter
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)
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mode_categories = {
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"Daten-Synchronisation": ["sync"], # <<< NEU: Eigene Kategorie für den Sync
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"Batch-Verarbeitung": ["wiki_verify", "website_scraping", "summarize_website", "branch_eval", "suggest_parents", "fsm_pitch"],
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"Sequentielle Verarbeitung": ["full_run"],
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"Re-Evaluation": ["reeval"],
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@@ -79,6 +95,9 @@ def main():
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parser.add_argument("--min_umsatz", type=float, help="Mindestumsatz in MIO € für 'find_wiki_serp'.", default=200.0)
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parser.add_argument("--min_employees", type=int, help="Mindest-MA für 'find_wiki_serp'.", default=500)
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# <<< NEU: Argument für den Pfad der Sync-Datei
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parser.add_argument("--sync_file", type=str, help="Pfad zur D365 Excel-Exportdatei für den 'sync'-Modus.", default="d365_export.xlsx")
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args = parser.parse_args()
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# --- Modusauswahl (interaktiv, wenn nicht über CLI) ---
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@@ -111,6 +130,13 @@ def main():
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print("\nAbgebrochen.")
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return
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# --- Logging Konfiguration ---
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# Definiere hier die Logging-Konstanten, falls sie nicht global sind
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LOG_LEVEL = logging.DEBUG if Config.DEBUG else logging.INFO
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LOG_FORMAT = '%(asctime)s - %(levelname)-8s - %(name)-25s - %(message)s'
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logging.basicConfig(level=LOG_LEVEL, format=LOG_FORMAT)
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logger = logging.getLogger(__name__)
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# --- Logdatei-Konfiguration abschließen ---
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log_file_path = create_log_filename(selected_mode)
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if log_file_path:
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@@ -120,7 +146,7 @@ def main():
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logging.getLogger('').addHandler(file_handler)
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logger.info(f"===== Skript gestartet: Modus '{selected_mode}' =====")
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logger.info(f"Projekt-Version (Config): {Config.VERSION}") # Umbenannt zur Klarheit
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logger.info(f"Projekt-Version (Config): {Config.VERSION}")
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logger.info(f"Logdatei: {log_file_path or 'FEHLER - Keine Logdatei'}")
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logger.info(f"CLI Argumente: {args}")
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@@ -130,81 +156,89 @@ def main():
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Config.load_api_keys()
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sheet_handler = GoogleSheetHandler()
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wiki_scraper = WikipediaScraper()
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data_processor = DataProcessor(sheet_handler=sheet_handler, wiki_scraper=wiki_scraper)
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# --- Modul-Versionen loggen (NACH der Initialisierung) ---
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modules_to_log = {
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"DataProcessor": data_processor,
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"GoogleSheetHandler": google_sheet_handler,
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"WikipediaScraper": wikipedia_scraper,
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"Helpers": helpers
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}
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log_module_versions(modules_to_log)
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# --- Ende Version-Logging ---
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# Expliziter Setup-Aufruf, nachdem alle Konfigurationen geladen sind.
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if not data_processor.setup():
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logger.critical("Setup des DataProcessors fehlgeschlagen. Das Skript wird beendet.")
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return
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# --- Modus-Dispatching ---
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start_time = time.time()
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# Sequentiell & Re-Eval Schritte parsen
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steps_to_run_set = set(step.strip().lower() for step in args.steps.split(',') if step.strip() in valid_steps) if args.steps else set(valid_steps)
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if selected_mode == "full_run":
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start_row = args.start_sheet_row or sheet_handler.get_start_row_index("Timestamp letzte Pruefung") + sheet_handler._header_rows + 1
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num_to_process = args.limit or (len(sheet_handler.get_all_data_with_headers()) - start_row + 1)
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data_processor.process_rows_sequentially(
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start_sheet_row=start_row, num_to_process=num_to_process,
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process_wiki_steps='wiki' in steps_to_run_set,
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process_chatgpt_steps='chat' in steps_to_run_set,
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process_website_steps='web' in steps_to_run_set,
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process_ml_steps='ml_predict' in steps_to_run_set
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)
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elif selected_mode == "reeval":
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data_processor.process_reevaluation_rows(
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row_limit=args.limit, clear_flag=True,
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process_wiki_steps='wiki' in steps_to_run_set,
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process_chatgpt_steps='chat' in steps_to_run_set,
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process_website_steps='web' in steps_to_run_set,
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process_ml_steps='ml_predict' in steps_to_run_set
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)
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elif selected_mode == "reclassify_branches":
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data_processor.reclassify_all_branches(
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start_sheet_row=args.start_sheet_row,
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limit=args.limit
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)
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elif selected_mode == "alignment":
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alignment_demo(sheet_handler)
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elif selected_mode == "train_technician_model":
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data_processor.train_technician_model()
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# KORRIGIERTE EINRÜCKUNG
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elif selected_mode == "predict_technicians":
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data_processor.process_predict_technicians(
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start_sheet_row=args.start_sheet_row,
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limit=args.limit
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)
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elif hasattr(data_processor, f"process_{selected_mode}"):
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# Dynamischer Aufruf für die meisten Batch-Modi
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method_to_call = getattr(data_processor, f"process_{selected_mode}")
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method_args = {}
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if "limit" in method_to_call.__code__.co_varnames: method_args["limit"] = args.limit
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if "start_sheet_row" in method_to_call.__code__.co_varnames: method_args["start_sheet_row"] = args.start_sheet_row
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if "end_sheet_row" in method_to_call.__code__.co_varnames: method_args["end_sheet_row"] = args.end_sheet_row
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if "min_umsatz" in method_to_call.__code__.co_varnames: method_args["min_umsatz"] = args.min_umsatz
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if "min_employees" in method_to_call.__code__.co_varnames: method_args["min_employees"] = args.min_employees
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method_to_call(**method_args)
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elif hasattr(data_processor, f"run_{selected_mode}"): # Für 'run_plausibility_checks_batch'
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method_to_call = getattr(data_processor, f"run_{selected_mode}")
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method_to_call(start_sheet_row=args.start_sheet_row, end_sheet_row=args.end_sheet_row, limit=args.limit)
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# <<< NEU: Früher Ausstieg für den Sync-Modus, da er keine Scraper/Prozessoren braucht
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if selected_mode == "sync":
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d365_file_path = args.sync_file
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if not os.path.exists(d365_file_path):
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logger.critical(f"Export-Datei nicht gefunden: {d365_file_path}")
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print(f"\n! FEHLER: Die angegebene Sync-Datei wurde nicht gefunden: {d365_file_path}")
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else:
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sync_manager = SyncManager(sheet_handler, d365_file_path)
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sync_manager.run_sync()
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else:
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logger.error(f"Unbekannter Modus '{selected_mode}' im Dispatcher.")
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# Bisherige Initialisierung für alle anderen Modi
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wiki_scraper = WikipediaScraper()
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data_processor = DataProcessor(sheet_handler=sheet_handler, wiki_scraper=wiki_scraper)
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# --- Modul-Versionen loggen ---
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modules_to_log = {
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"DataProcessor": data_processor,
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"GoogleSheetHandler": google_sheet_handler,
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"WikipediaScraper": wikipedia_scraper,
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"Helpers": helpers
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}
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log_module_versions(modules_to_log)
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if not data_processor.setup():
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logger.critical("Setup des DataProcessors fehlgeschlagen. Das Skript wird beendet.")
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return
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duration = time.time() - start_time
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logger.info(f"Verarbeitung im Modus '{selected_mode}' abgeschlossen. Dauer: {duration:.2f} Sekunden.")
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# --- Modus-Dispatching ---
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start_time = time.time()
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steps_to_run_set = set(step.strip().lower() for step in args.steps.split(',') if step.strip() in valid_steps) if args.steps else set(valid_steps)
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if selected_mode == "full_run":
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start_row = args.start_sheet_row or sheet_handler.get_start_row_index("Timestamp letzte Pruefung") + sheet_handler._header_rows + 1
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num_to_process = args.limit or (len(sheet_handler.get_all_data_with_headers()) - start_row + 1)
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data_processor.process_rows_sequentially(
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start_sheet_row=start_row, num_to_process=num_to_process,
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process_wiki_steps='wiki' in steps_to_run_set,
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process_chatgpt_steps='chat' in steps_to_run_set,
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process_website_steps='web' in steps_to_run_set,
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process_ml_steps='ml_predict' in steps_to_run_set
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)
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elif selected_mode == "reeval":
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data_processor.process_reevaluation_rows(
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row_limit=args.limit, clear_flag=True,
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process_wiki_steps='wiki' in steps_to_run_set,
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process_chatgpt_steps='chat' in steps_to_run_set,
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process_website_steps='web' in steps_to_run_set,
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process_ml_steps='ml_predict' in steps_to_run_set
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)
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# ... (alle anderen elif-Blöcke bleiben wie sie sind) ...
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elif selected_mode == "reclassify_branches":
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data_processor.reclassify_all_branches(
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start_sheet_row=args.start_sheet_row,
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limit=args.limit
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)
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elif selected_mode == "alignment":
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alignment_demo(sheet_handler)
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elif selected_mode == "train_technician_model":
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data_processor.train_technician_model()
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elif selected_mode == "predict_technicians":
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data_processor.process_predict_technicians(
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start_sheet_row=args.start_sheet_row,
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limit=args.limit
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)
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elif hasattr(data_processor, f"process_{selected_mode}"):
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method_to_call = getattr(data_processor, f"process_{selected_mode}")
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method_args = {}
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if "limit" in method_to_call.__code__.co_varnames: method_args["limit"] = args.limit
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if "start_sheet_row" in method_to_call.__code__.co_varnames: method_args["start_sheet_row"] = args.start_sheet_row
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if "end_sheet_row" in method_to_call.__code__.co_varnames: method_args["end_sheet_row"] = args.end_sheet_row
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if "min_umsatz" in method_to_call.__code__.co_varnames: method_args["min_umsatz"] = args.min_umsatz
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if "min_employees" in method_to_call.__code__.co_varnames: method_args["min_employees"] = args.min_employees
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method_to_call(**method_args)
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elif hasattr(data_processor, f"run_{selected_mode}"):
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method_to_call = getattr(data_processor, f"run_{selected_mode}")
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method_to_call(start_sheet_row=args.start_sheet_row, end_sheet_row=args.end_sheet_row, limit=args.limit)
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else:
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logger.error(f"Unbekannter Modus '{selected_mode}' im Dispatcher.")
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duration = time.time() - start_time
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logger.info(f"Verarbeitung im Modus '{selected_mode}' abgeschlossen. Dauer: {duration:.2f} Sekunden.")
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except (KeyboardInterrupt, EOFError):
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logger.warning("Skript durch Benutzer unterbrochen.")
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@@ -218,7 +252,4 @@ def main():
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logger.info(f"===== Skript beendet =====")
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logging.shutdown()
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if 'selected_mode' in locals() and selected_mode != 'exit' and 'log_file_path' in locals() and log_file_path:
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print(f"\nVerarbeitung abgeschlossen. Logfile: {log_file_path}")
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if __name__ == '__main__':
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main()
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print(f"\nVerarbeitung abgeschlossen. Logfile: {log_file_path}")
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