import os import re import logging import pandas as pd import numpy as np import recordlinkage from rapidfuzz import fuzz from google_sheet_handler import GoogleSheetHandler # --- Konfiguration --- CRM_SHEET_NAME = "CRM_Accounts" MATCHING_SHEET_NAME = "Matching_Accounts" # Threshold gesenkt und konfigurierbar im Code SCORE_THRESHOLD = 0.75 WEIGHTS = { 'domain': 0.5, 'name': 0.4, 'city': 0.1, } # Relativer Log-Ordner LOG_DIR = 'log' LOG_FILENAME = 'duplicate_check.log' # --- Logging Setup --- 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: s = str(name).casefold() for src, dst in [('ä','ae'), ('ö','oe'), ('ü','ue'), ('ß','ss')]: s = s.replace(src, dst) s = re.sub(r'[^a-z0-9\s]', ' ', s) stops = ['gmbh','ag','kg','ug','ohg','holding','group','international'] tokens = [t for t in s.split() if t and t not in stops] return ' '.join(tokens) def normalize_domain(url: str) -> str: s = str(url).casefold().strip() s = re.sub(r'^https?://', '', s) s = s.split('/')[0] if s.startswith('www.'): s = s[4:] return s def main(): logger.info("Starte den Duplikats-Check mit Fallback-Blocking...") # GoogleSheetHandler initialisieren try: sheet_handler = GoogleSheetHandler() logger.info("GoogleSheetHandler initialisiert") except Exception as e: logger.critical(f"FEHLER bei Initialisierung des GoogleSheetHandler: {e}") return # Daten laden crm_df = sheet_handler.get_sheet_as_dataframe(CRM_SHEET_NAME) match_df = sheet_handler.get_sheet_as_dataframe(MATCHING_SHEET_NAME) if crm_df is None or crm_df.empty or match_df is None or match_df.empty: logger.critical("CRM- oder Matching-Daten leer. Abbruch.") return logger.info(f"{len(crm_df)} CRM-Zeilen, {len(match_df)} Matching-Zeilen geladen") # Normalisierung for df, label in [(crm_df, 'CRM'), (match_df, 'Matching')]: 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()) df['name_token'] = df['norm_name'].apply(lambda x: x.split()[0] if x else np.nan) # Leere Werte als NaN markieren df['norm_domain'].replace('', np.nan, inplace=True) df['city'].replace('', np.nan, inplace=True) logger.debug(f"{label}-Normalisierung: norm_domain={df.iloc[0]['norm_domain']}, name_token={df.iloc[0]['name_token']}") # Blocking: Domain und Name-Token index_dom = recordlinkage.Index() index_dom.block('norm_domain') pairs_dom = index_dom.index(crm_df, match_df) index_name = recordlinkage.Index() index_name.block('name_token') pairs_name = index_name.index(crm_df, match_df) # Union der Kandidatenpaare candidate_pairs = pairs_dom.append(pairs_name).drop_duplicates() logger.info(f"Blocking abgeschlossen: Dom-Paare={len(pairs_dom)}, Name-Paare={len(pairs_name)}, Gesamt={len(candidate_pairs)}") # Vergleichsregeln definieren compare = recordlinkage.Compare() compare.exact('norm_domain', 'norm_domain', label='domain', missing_value=0) compare.string('norm_name', 'norm_name', method='jarowinkler', label='name_sim') compare.exact('city', 'city', label='city', missing_value=0) features = compare.compute(candidate_pairs, crm_df, match_df) logger.debug(f"Features berechnet: {features.head()}...") # Score berechnen features['score'] = ( WEIGHTS['domain'] * features['domain'] + WEIGHTS['name'] * features['name_sim'] + WEIGHTS['city'] * features['city'] ) logger.info("Scores berechnet") # Per-Match Logging und Auswahl results = [] crm_map = crm_df.reset_index() for match_idx, group in features.reset_index().groupby('level_1'): logger.info(f"--- Prüfe Matching-Zeile {match_idx} ---") df_block = group.sort_values('score', ascending=False).copy() # CRM-Daten für Log df_block['CRM Name'] = df_block['level_0'].map(crm_map.set_index('index')['CRM Name']) # Log der Top-Kandidaten for _, row in df_block.head(5).iterrows(): logger.debug(f"Candidate [{int(row['level_0'])}]: score={row['score']:.3f}, name_sim={row['name_sim']:.3f}, dom={row['domain']}, city={row['city']} => {row['CRM Name']}") top = df_block.iloc[0] crm_idx = top['level_0'] if top['score'] >= SCORE_THRESHOLD else None if crm_idx is not None: logger.info(f" --> Match: {int(crm_idx)} ({top['CRM Name']}) mit Score {top['score']:.2f}") else: logger.info(f" --> Kein Match (höchster Score {top['score']:.2f})") results.append((crm_idx, match_idx, top['score'])) # Ausgabe zusammenstellen match_map = match_df.reset_index() output = match_map[['CRM Name','CRM Website','CRM Ort','CRM Land']].copy() output[['Matched CRM Name','Matched CRM Website','Matched CRM Ort','Matched CRM Land','Score']] = '' for crm_idx, match_idx, score in results: if crm_idx is not None: crm_row = crm_map[crm_map['index']==crm_idx].iloc[0] output.at[match_idx, 'Matched CRM Name'] = crm_row['CRM Name'] output.at[match_idx, 'Matched CRM Website'] = crm_row['CRM Website'] output.at[match_idx, 'Matched CRM Ort'] = crm_row['CRM Ort'] output.at[match_idx, 'Matched CRM Land'] = crm_row['CRM Land'] output.at[match_idx, 'Score'] = round(score,3) # Zurückschreiben ins Google Sheet data = [output.columns.tolist()] + output.values.tolist() success = sheet_handler.clear_and_write_data(MATCHING_SHEET_NAME, data) if success: logger.info(f"Erfolgreich geschrieben: {len([r for r in results if r[0] is not None])} Matches") else: logger.error("Fehler beim Schreiben ins Google Sheet.") if __name__ == '__main__': main()