diff --git a/brancheneinstufung.py b/brancheneinstufung.py index 904db609..a48be603 100644 --- a/brancheneinstufung.py +++ b/brancheneinstufung.py @@ -1256,21 +1256,20 @@ def _process_single_row(self, row_num, row_data, process_wiki=True, process_chat if website_url.strip() != "" and website_url.strip().lower() != "k.a.": website_raw = get_website_raw(website_url) website_summary = summarize_website_content(website_raw) - try: - self.sheet_handler.sheet.update(values=[[website_raw]], range_name=f"AR{row_num}") - debug_print(f"Zeile {row_num}: Spalte AR Update erfolgreich – Auszug: {website_raw[:100]}...") - except Exception as e: - debug_print(f"Zeile {row_num}: Fehler beim Update von Spalte AR: {e}") - try: - self.sheet_handler.sheet.update(values=[[website_summary]], range_name=f"AS{row_num}") - debug_print(f"Zeile {row_num}: Spalte AS Update erfolgreich – Zusammenfassung: {website_summary}") - except Exception as e: - debug_print(f"Zeile {row_num}: Fehler beim Update von Spalte AS: {e}") - debug_print(f"Zeile {row_num}: Website-Daten gescrapt. Rohtext Länge: {len(website_raw)}, Zusammenfassung: {website_summary}") + debug_print(f"Zeile {row_num}: Website-Daten gescrapt. Rohtext (Länge {len(website_raw)}): {website_raw[:100]}..., Zusammenfassung: {website_summary}") else: debug_print(f"Zeile {row_num}: Kein gültiger Website-URL vorhanden, Website-Scraping wird übersprungen.") - # Wikipedia-Verarbeitung (falls process_wiki True) + # Erstelle einen Dict mit allen Werten, die in dieser Zeile aktualisiert werden sollen. + # Dadurch können wir alle Updates in einem einzigen Aufruf zusammenfassen. + updates = {} + + # Spalte AR: Website Rohtext + updates[f"AR{row_num}"] = website_raw + # Spalte AS: Website Zusammenfassung + updates[f"AS{row_num}"] = website_summary + + # Weiterer Verarbeitungsteil: Wikipedia-Verarbeitung (falls process_wiki True) wiki_update_range = f"L{row_num}:R{row_num}" dt_wiki_range = f"AN{row_num}" company_data = {} @@ -1295,16 +1294,16 @@ def _process_single_row(self, row_num, row_data, process_wiki=True, process_chat 'umsatz': 'k.A.', 'mitarbeiter': 'k.A.', 'categories': 'k.A.', 'full_infobox': 'k.A.' } - self.sheet_handler.sheet.update(values=[[ - row_data[11] if len(row_data) > 11 and row_data[11].strip() not in ["", "k.A."] else "k.A.", - company_data.get('url', 'k.A.'), - company_data.get('first_paragraph', 'k.A.'), - company_data.get('branche', 'k.A.'), - company_data.get('umsatz', 'k.A.'), - company_data.get('mitarbeiter', 'k.A.'), - company_data.get('categories', 'k.A.') - ]], range_name=wiki_update_range) - self.sheet_handler.sheet.update(values=[[datetime.now().strftime("%Y-%m-%d %H:%M:%S")]], range_name=dt_wiki_range) + updates.update({ + f"L{row_num}": row_data[11] if len(row_data) > 11 and row_data[11].strip() not in ["", "k.A."] else "k.A.", + f"M{row_num}": company_data.get('url', 'k.A.'), + f"N{row_num}": company_data.get('first_paragraph', 'k.A.'), + f"O{row_num}": company_data.get('branche', 'k.A.'), + f"P{row_num}": company_data.get('umsatz', 'k.A.'), + f"Q{row_num}": company_data.get('mitarbeiter', 'k.A.'), + f"R{row_num}": company_data.get('categories', 'k.A.') + }) + updates[dt_wiki_range] = datetime.now().strftime("%Y-%m-%d %H:%M:%S") else: debug_print(f"Zeile {row_num}: Wikipedia-Timestamp bereits gesetzt – überspringe Wiki-Auswertung.") @@ -1315,16 +1314,20 @@ def _process_single_row(self, row_num, row_data, process_wiki=True, process_chat if len(row_data) <= 40 or row_data[40].strip() == "": crm_umsatz = row_data[8] if len(row_data) > 8 else "k.A." abgleich_result = compare_umsatz_values(crm_umsatz, company_data.get('umsatz', 'k.A.')) - self.sheet_handler.sheet.update(values=[[abgleich_result]], range_name=f"AG{row_num}") + updates[f"AG{row_num}"] = abgleich_result + crm_data = ";".join(row_data[1:10]) wiki_data_str = ";".join(row_data[11:18]) valid_result = process_wiki_verification(crm_data, wiki_data_str) - self.sheet_handler.sheet.update(values=[[valid_result]], range_name=f"R{row_num}") + updates[f"R{row_num}"] = valid_result + fsm_result = evaluate_fsm_suitability(company_name, company_data) - self.sheet_handler.sheet.update(values=[[fsm_result["suitability"]]], range_name=f"Y{row_num}") - self.sheet_handler.sheet.update(values=[[fsm_result["justification"]]], range_name=f"Z{row_num}") + updates[f"Y{row_num}"] = fsm_result["suitability"] + updates[f"Z{row_num}"] = fsm_result["justification"] + st_estimate = evaluate_servicetechnicians_estimate(company_name, company_data) - self.sheet_handler.sheet.update(values=[[st_estimate]], range_name=f"AD{row_num}") + updates[f"AD{row_num}"] = st_estimate + internal_value = row_data[7] if len(row_data) > 7 else "k.A." internal_category = map_internal_technicians(internal_value) if internal_value != "k.A." else "k.A." if internal_category != "k.A." and st_estimate != internal_category: @@ -1332,25 +1335,43 @@ def _process_single_row(self, row_num, row_data, process_wiki=True, process_chat discrepancy = explanation else: discrepancy = "ok" - self.sheet_handler.sheet.update(values=[[discrepancy]], range_name=f"AF{row_num}") + updates[f"AF{row_num}"] = discrepancy + crm_employee = row_data[10] if len(row_data) > 10 else "k.A." wiki_employee = company_data.get('mitarbeiter', 'k.A.') emp_estimate = process_employee_estimation(company_name, company_data.get('first_paragraph', 'k.A.'), crm_employee) emp_consistency = process_employee_consistency(crm_employee, wiki_employee, emp_estimate) - self.sheet_handler.sheet.update(values=[[emp_estimate]], range_name=f"AB{row_num}") - self.sheet_handler.sheet.update(values=[[emp_consistency]], range_name=f"AC{row_num}") + updates[f"AB{row_num}"] = emp_estimate + updates[f"AC{row_num}"] = emp_consistency + revenue_result = evaluate_umsatz_chatgpt(company_name, company_data.get('umsatz', 'k.A.')) - self.sheet_handler.sheet.update(values=[[revenue_result]], range_name=f"AG{row_num}") + updates[f"AG{row_num}"] = revenue_result + total_tokens = f"Wiki: {token_count(str(company_data.get('first_paragraph', '')))}, Chat: {token_count(crm_data + wiki_data_str)}, Emp: {token_count(str(emp_estimate))}" - self.sheet_handler.sheet.update(values=[[total_tokens]], range_name=f"AQ{row_num}") - self.sheet_handler.sheet.update(values=[[datetime.now().strftime('%Y-%m-%d %H:%M:%S')]], range_name=dt_chat_range) + updates[f"AQ{row_num}"] = total_tokens + updates[dt_chat_range] = datetime.now().strftime("%Y-%m-%d %H:%M:%S") else: debug_print(f"Zeile {row_num}: ChatGPT-Timestamp bereits gesetzt – überspringe ChatGPT-Auswertung.") - # Aktualisiere Timestamp und Version + # Abschließende Updates: Timestamp für letzte Prüfung und Version current_dt = datetime.now().strftime("%Y-%m-%d %H:%M:%S") - self.sheet_handler.sheet.update(values=[[current_dt]], range_name=ver_range) - self.sheet_handler.sheet.update(values=[[Config.VERSION]], range_name=ver_range) + updates[ver_range] = current_dt + updates["AP" + str(row_num)] = Config.VERSION + + # Führe ein Batch-Update aller gesammelten Werte für diese Zeile durch + try: + batch_updates = [] + for cell, value in updates.items(): + batch_updates.append({ + "range": cell, + "values": [[value]] + }) + # Verwende die batch_update-Methode von gspread + self.sheet_handler.sheet.batch_update(batch_updates) + debug_print(f"Zeile {row_num}: Batch-Update erfolgreich durchgeführt. Geschriebene Werte: {updates}") + except Exception as e: + debug_print(f"Zeile {row_num}: Fehler beim Batch-Update: {e}") + debug_print(f"Zeile {row_num} abgeschlossen. URL: {company_data.get('url', 'k.A.')}, " f"Branche: {company_data.get('branche', 'k.A.')}, Umsatz-Abgleich: {abgleich_result}, " f"Validierung: {valid_result}, FSM: {fsm_result['suitability']}, " @@ -1359,7 +1380,6 @@ def _process_single_row(self, row_num, row_data, process_wiki=True, process_chat - # ==================== ALIGNMENT DEMO FÜR HAUPTBLATT UND CONTACTS ==================== def alignment_demo_full():