159 lines
6.4 KiB
Python
159 lines
6.4 KiB
Python
import os
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import re
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import logging
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import pandas as pd
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import recordlinkage
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from rapidfuzz import fuzz
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from google_sheet_handler import GoogleSheetHandler
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# --- Konfiguration ---
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CRM_SHEET_NAME = "CRM_Accounts"
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MATCHING_SHEET_NAME = "Matching_Accounts"
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SCORE_THRESHOLD = 0.8
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WEIGHTS = {
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'domain': 0.5,
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'name': 0.4,
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'city': 0.1,
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}
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LOG_DIR = '/log'
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LOG_FILENAME = 'duplicate_check.log'
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# --- Logging Setup ---
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if not os.path.exists(LOG_DIR):
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try:
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os.makedirs(LOG_DIR)
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except Exception as e:
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print(f"Warnung: Konnte Log-Ordner nicht anlegen: {e}")
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log_path = os.path.join(LOG_DIR, LOG_FILENAME)
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logger = logging.getLogger(__name__)
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logger.setLevel(logging.DEBUG)
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formatter = logging.Formatter('%(asctime)s - %(levelname)-8s - %(name)s - %(message)s')
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# Console handler
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console_handler = logging.StreamHandler()
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console_handler.setLevel(logging.INFO)
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console_handler.setFormatter(formatter)
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logger.addHandler(console_handler)
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# File handler
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try:
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file_handler = logging.FileHandler(log_path, mode='a', encoding='utf-8')
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file_handler.setLevel(logging.DEBUG)
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file_handler.setFormatter(formatter)
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logger.addHandler(file_handler)
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logger.info(f"Logging auch in Datei: {log_path}")
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except Exception as e:
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logger.warning(f"Konnte keine Log-Datei schreiben: {e}")
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# --- Hilfsfunktionen ---
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def normalize_company_name(name: str) -> str:
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s = str(name).casefold()
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for src, dst in [('ä','ae'), ('ö','oe'), ('ü','ue'), ('ß','ss')]:
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s = s.replace(src, dst)
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s = re.sub(r'[^a-z0-9\s]', ' ', s)
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stops = ['gmbh','ag','kg','ug','ohg','holding','group','international']
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tokens = [t for t in s.split() if t and t not in stops]
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return ' '.join(tokens)
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def normalize_domain(url: str) -> str:
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s = str(url).casefold().strip()
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s = re.sub(r'^https?://', '', s)
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s = s.split('/')[0]
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if s.startswith('www.'):
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s = s[4:]
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return s
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def main():
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logger.info("Starte den Duplikats-Check (v2.0 mit Kandidaten-Logging)...")
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try:
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sheet_handler = GoogleSheetHandler()
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logger.info("GoogleSheetHandler initialisiert")
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except Exception as e:
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logger.critical(f"FEHLER bei Initialisierung des GoogleSheetHandler: {e}")
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return
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# Daten laden
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crm_df = sheet_handler.get_sheet_as_dataframe(CRM_SHEET_NAME)
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match_df = sheet_handler.get_sheet_as_dataframe(MATCHING_SHEET_NAME)
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if crm_df is None or crm_df.empty or match_df is None or match_df.empty:
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logger.critical("CRM- oder Matching-Daten leer. Abbruch.")
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return
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logger.info(f"{len(crm_df)} CRM-Zeilen, {len(match_df)} Matching-Zeilen geladen")
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# Normalisierung
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for df, label in [(crm_df, 'CRM'), (match_df, 'Matching')]:
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df['norm_name'] = df['CRM Name'].fillna('').apply(normalize_company_name)
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df['norm_domain'] = df['CRM Website'].fillna('').apply(normalize_domain)
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df['city'] = df['CRM Ort'].fillna('').apply(lambda x: str(x).casefold().strip())
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logger.debug(f"{label}-Daten normalisiert: Beispiel: {df.iloc[0][['norm_name','norm_domain','city']].to_dict()}")
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# Blocking
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indexer = recordlinkage.Index()
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indexer.block('norm_domain')
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candidate_pairs = indexer.index(crm_df, match_df)
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logger.info(f"Blocking abgeschlossen: {len(candidate_pairs)} Kandidatenpaare")
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# Compare
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compare = recordlinkage.Compare()
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compare.exact('norm_domain', 'norm_domain', label='domain')
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compare.string('norm_name', 'norm_name', method='jarowinkler', label='name_sim')
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compare.exact('city', 'city', label='city')
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features = compare.compute(candidate_pairs, crm_df, match_df)
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logger.debug(f"Features berechnet: {features.head()}\n...")
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# Score
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features['score'] = (WEIGHTS['domain']*features['domain'] +
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WEIGHTS['name']*features['name_sim'] +
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WEIGHTS['city']*features['city'])
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logger.info("Scores berechnet")
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# Per Match Logging
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results = []
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crm_df_idx = crm_df.reset_index()
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for match_idx, group in features.reset_index().groupby('level_1'):
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logger.info(f"--- Prüfe Matching-Zeile {match_idx} ---")
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df_block = group.sort_values('score', ascending=False).copy()
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# Enrich with CRM fields
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df_block['CRM Name'] = df_block['level_0'].map(crm_df_idx.set_index('index')['CRM Name'])
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df_block['CRM Website'] = df_block['level_0'].map(crm_df_idx.set_index('index')['CRM Website'])
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df_block['CRM Ort'] = df_block['level_0'].map(crm_df_idx.set_index('index')['CRM Ort'])
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# Log top candidates
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logger.debug("Kandidaten (CRM_Index, Score, Domain, Name_sim, City, CRM Name):")
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for _, row in df_block.iterrows():
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logger.debug(f" [{int(row['level_0'])}] score={row['score']:.3f} dom={row['domain']} name_sim={row['name_sim']:.3f} city={row['city']} => {row['CRM Name']}")
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top = df_block.iloc[0]
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crm_idx = top['level_0'] if top['score'] >= SCORE_THRESHOLD else None
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if crm_idx is not None:
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logger.info(f" --> Match: CRM-Index {int(crm_idx)} ({top['CRM Name']}) mit Score {top['score']:.2f}")
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else:
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logger.info(f" --> Kein Match (höchster Score {top['score']:.2f})")
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results.append((crm_idx, match_idx, top['score']))
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# Prepare output
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match_df_idx = match_df.reset_index()
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output = match_df_idx[['CRM Name','CRM Website','CRM Ort','CRM Land']].copy()
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output['Matched CRM Name'] = ''
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output['Matched CRM Website'] = ''
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output['Matched CRM Ort'] = ''
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output['Matched CRM Land'] = ''
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output['Score'] = 0.0
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for crm_idx, match_idx, score in results:
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if crm_idx is not None:
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crm_row = crm_df_idx[crm_df_idx['index']==crm_idx].iloc[0]
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output.at[match_idx, 'Matched CRM Name'] = crm_row['CRM Name']
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output.at[match_idx, 'Matched CRM Website'] = crm_row['CRM Website']
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output.at[match_idx, 'Matched CRM Ort'] = crm_row['CRM Ort']
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output.at[match_idx, 'Matched CRM Land'] = crm_row['CRM Land']
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output.at[match_idx, 'Score'] = round(score,3)
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# Write back
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data = [output.columns.tolist()] + output.values.tolist()
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success = sheet_handler.clear_and_write_data(MATCHING_SHEET_NAME, data)
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if success:
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logger.info(f"Erfolgreich geschrieben: {len([r for r in results if r[0] is not None])} Matches")
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else:
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logger.error("Fehler beim Schreiben ins Google Sheet.")
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if __name__ == '__main__':
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main()
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