From 0d02cb854c4d8cdcd6333ef1f0b9d00b3ea8d3bc Mon Sep 17 00:00:00 2001 From: Floke Date: Thu, 3 Apr 2025 12:07:33 +0000 Subject: [PATCH] =?UTF-8?q?v1.3.8:=20Neuer=20Modus=205=20als=20Schreibtest?= =?UTF-8?q?=20f=C3=BCr=20Contacts;=20Timestamps=20getrennt?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit - Alle bisherigen Funktionen bleiben erhalten - Neuer Modus 5 (contacts_alignment_demo) führt einen Schreibtest auf dem Contacts-Sheet durch - Spalten AH und AI werden nun getrennt als Timestamp für Wiki-Update bzw. ChatGPT-Bewertung geführt; restliche Spalten um eine Position verschoben - Debug-Ausgaben wurden erweitert, um den Ablauf und die Ergebnisse besser nachvollziehen zu können --- brancheneinstufung.py | 535 +++--------------------------------------- 1 file changed, 28 insertions(+), 507 deletions(-) diff --git a/brancheneinstufung.py b/brancheneinstufung.py index 3ad0e732..14a8b434 100644 --- a/brancheneinstufung.py +++ b/brancheneinstufung.py @@ -14,7 +14,7 @@ import csv # ==================== KONFIGURATION ==================== class Config: - VERSION = "v1.3.7" # v1.3.7: Alle bisherigen Funktionen bleiben erhalten; neuer Modus 4: Nur Wikipedia-Suche. + VERSION = "v1.3.8" # v1.3.8: Neuer Modus 5 als Schreibtest für das Contacts-Sheet; restliche Funktionen unverändert. LANG = "de" CREDENTIALS_FILE = "service_account.json" SHEET_URL = "https://docs.google.com/spreadsheets/d/1u_gHr9JUfmV1-iviRzbSe3575QEp7KLhK5jFV_gJcgo" @@ -378,6 +378,7 @@ def search_linkedin_contact(company_name, website, position_query): debug_print(f"Fehler bei der SerpAPI-Suche: {e}") return None +# ==================== NEUER MODUS: CONTACTS (LinkedIn) ==================== def process_contacts(): debug_print("Starte LinkedIn-Kontaktsuche...") gc = gspread.authorize(ServiceAccountCredentials.from_json_keyfile_name( @@ -479,245 +480,26 @@ class GoogleSheetHandler: filled_n = [row[13] if len(row) > 13 else '' for row in self.sheet_values[1:]] return next((i + 1 for i, v in enumerate(filled_n, start=1) if not str(v).strip()), len(filled_n) + 1) -# ==================== ALIGNMENT DEMO (Modus 3) ==================== -def alignment_demo(sheet): - new_headers = [ - "Spalte A (ReEval Flag)", - "Spalte B (Firmenname)", - "Spalte C (Website)", - "Spalte D (Ort)", - "Spalte E (Beschreibung)", - "Spalte F (Aktuelle Branche)", - "Spalte G (Beschreibung Branche extern)", - "Spalte H (Anzahl Techniker CRM)", - "Spalte I (Umsatz CRM)", - "Spalte J (Anzahl Mitarbeiter CRM)", - "Spalte K (Vorschlag Wiki URL)", - "Spalte L (Wikipedia URL)", - "Spalte M (Wikipedia Absatz)", - "Spalte N (Wikipedia Branche)", - "Spalte O (Wikipedia Umsatz)", - "Spalte P (Wikipedia Mitarbeiter)", - "Spalte Q (Wikipedia Kategorien)", - "Spalte R (Konsistenzprüfung)", - "Spalte S (Begründung bei Inkonsistenz)", - "Spalte T (Vorschlag Wiki Artikel ChatGPT)", - "Spalte U (Begründung bei Abweichung)", - "Spalte V (Vorschlag neue Branche)", - "Spalte W (Konsistenzprüfung Branche)", - "Spalte X (Begründung Abweichung Branche)", - "Spalte Y (FSM Relevanz Ja / Nein)", - "Spalte Z (Begründung für FSM Relevanz)", - "Spalte AA (Schätzung Anzahl Mitarbeiter)", - "Spalte AB (Konsistenzprüfung Mitarbeiterzahl)", - "Spalte AC (Begründung für Abweichung Mitarbeiterzahl)", - "Spalte AD (Einschätzung Anzahl Servicetechniker)", - "Spalte AE (Begründung bei Abweichung Anzahl Servicetechniker)", - "Spalte AF (Schätzung Umsatz ChatGPT)", - "Spalte AG (Begründung für Abweichung Umsatz)", - "Spalte AH (Timestamp letzte Prüfung)", - "Spalte AI (Version)" - ] - header_range = "A11200:AI11200" - sheet.update(values=[new_headers], range_name=header_range) - print("Alignment-Demo abgeschlossen: Neue Spaltenüberschriften in Zeile 11200 geschrieben.") - -# ==================== WIKIPEDIA SCRAPER ==================== -class WikipediaScraper: - def __init__(self): - wikipedia.set_lang(Config.LANG) - def _get_full_domain(self, website): - if not website: - return "" - website = website.lower().strip() - website = re.sub(r'^https?:\/\/', '', website) - website = re.sub(r'^www\.', '', website) - return website.split('/')[0] - def _generate_search_terms(self, company_name, website): - terms = [] - full_domain = self._get_full_domain(website) - if full_domain: - terms.append(full_domain) - normalized_name = normalize_company_name(company_name) - candidate = " ".join(normalized_name.split()[:2]).strip() - if candidate and candidate not in terms: - terms.append(candidate) - if normalized_name and normalized_name not in terms: - terms.append(normalized_name) - debug_print(f"Generierte Suchbegriffe: {terms}") - return terms - def _validate_article(self, page, company_name, website): - full_domain = self._get_full_domain(website) - domain_found = False - if full_domain: - try: - html_raw = requests.get(page.url).text - soup = BeautifulSoup(html_raw, Config.HTML_PARSER) - infobox = soup.find('table', class_=lambda c: c and 'infobox' in c.lower()) - if infobox: - links = infobox.find_all('a', href=True) - for link in links: - href = link.get('href').lower() - if href.startswith('/wiki/datei:'): - continue - if full_domain in href: - debug_print(f"Definitiver Link-Match in Infobox gefunden: {href}") - domain_found = True - break - if not domain_found and hasattr(page, 'externallinks'): - for ext_link in page.externallinks: - if full_domain in ext_link.lower(): - debug_print(f"Definitiver Link-Match in externen Links gefunden: {ext_link}") - domain_found = True - break - except Exception as e: - debug_print(f"Fehler beim Extrahieren von Links: {str(e)}") - normalized_title = normalize_company_name(page.title) - normalized_company = normalize_company_name(company_name) - similarity = SequenceMatcher(None, normalized_title, normalized_company).ratio() - debug_print(f"Ähnlichkeit (normalisiert): {similarity:.2f} ({normalized_title} vs {normalized_company})") - threshold = 0.60 if domain_found else Config.SIMILARITY_THRESHOLD - return similarity >= threshold - def extract_first_paragraph(self, page_url): - try: - response = requests.get(page_url) - soup = BeautifulSoup(response.text, Config.HTML_PARSER) - paragraphs = soup.find_all('p') - for p in paragraphs: - text = clean_text(p.get_text()) - if len(text) > 50: - return text - return "k.A." - except Exception as e: - debug_print(f"Fehler beim Extrahieren des ersten Absatzes: {e}") - return "k.A." - def extract_categories(self, soup): - cat_div = soup.find('div', id="mw-normal-catlinks") - if cat_div: - ul = cat_div.find('ul') - if ul: - cats = [clean_text(li.get_text()) for li in ul.find_all('li')] - return ", ".join(cats) - return "k.A." - def _extract_infobox_value(self, soup, target): - infobox = soup.find('table', class_=lambda c: c and any(kw in c.lower() for kw in ['infobox', 'vcard', 'unternehmen'])) - if not infobox: - return "k.A." - keywords_map = { - 'branche': ['branche', 'industrie', 'tätigkeit', 'geschäftsfeld', 'sektor', 'produkte', 'leistungen', 'aktivitäten', 'wirtschaftszweig'], - 'umsatz': ['umsatz', 'jahresumsatz', 'konzernumsatz', 'gesamtumsatz', 'erlöse', 'umsatzerlöse', 'einnahmen', 'ergebnis', 'jahresergebnis'], - 'mitarbeiter': ['mitarbeiter', 'beschäftigte', 'personal', 'mitarbeiterzahl', 'angestellte', 'belegschaft', 'personalstärke'] - } - keywords = keywords_map.get(target, []) - for row in infobox.find_all('tr'): - header = row.find('th') - if header: - header_text = clean_text(header.get_text()).lower() - if any(kw in header_text for kw in keywords): - value = row.find('td') - if value: - raw_value = clean_text(value.get_text()) - if target == 'branche': - clean_val = re.sub(r'\[.*?\]|\(.*?\)', '', raw_value) - return ' '.join(clean_val.split()).strip() - if target == 'umsatz': - return extract_numeric_value(raw_value, is_umsatz=True) - if target == 'mitarbeiter': - return extract_numeric_value(raw_value, is_umsatz=False) - return "k.A." - def extract_full_infobox(self, soup): - infobox = soup.find('table', class_=lambda c: c and any(kw in c.lower() for kw in ['infobox', 'vcard', 'unternehmen'])) - if not infobox: - return "k.A." - return clean_text(infobox.get_text(separator=' | ')) - def extract_fields_from_infobox_text(self, infobox_text, field_names): - result = {} - tokens = [token.strip() for token in infobox_text.split("|") if token.strip()] - for i, token in enumerate(tokens): - for field in field_names: - if field.lower() in token.lower(): - j = i + 1 - while j < len(tokens) and not tokens[j]: - j += 1 - result[field] = tokens[j] if j < len(tokens) else "k.A." - return result - def extract_company_data(self, page_url): - if not page_url: - return { - 'url': 'k.A.', - 'first_paragraph': 'k.A.', - 'branche': 'k.A.', - 'umsatz': 'k.A.', - 'mitarbeiter': 'k.A.', - 'categories': 'k.A.', - 'full_infobox': 'k.A.' - } - try: - response = requests.get(page_url) - soup = BeautifulSoup(response.text, Config.HTML_PARSER) - full_infobox = self.extract_full_infobox(soup) - extracted_fields = self.extract_fields_from_infobox_text(full_infobox, ['Branche', 'Umsatz', 'Mitarbeiter']) - raw_branche = extracted_fields.get('Branche', self._extract_infobox_value(soup, 'branche')) - raw_umsatz = extracted_fields.get('Umsatz', self._extract_infobox_value(soup, 'umsatz')) - raw_mitarbeiter = extracted_fields.get('Mitarbeiter', self._extract_infobox_value(soup, 'mitarbeiter')) - umsatz_val = extract_numeric_value(raw_umsatz, is_umsatz=True) - mitarbeiter_val = extract_numeric_value(raw_mitarbeiter, is_umsatz=False) - categories_val = self.extract_categories(soup) - first_paragraph = self.extract_first_paragraph(page_url) - return { - 'url': page_url, - 'first_paragraph': first_paragraph, - 'branche': raw_branche, - 'umsatz': umsatz_val, - 'mitarbeiter': mitarbeiter_val, - 'categories': categories_val, - 'full_infobox': full_infobox - } - except Exception as e: - debug_print(f"Extraktionsfehler: {str(e)}") - return { - 'url': 'k.A.', - 'first_paragraph': 'k.A.', - 'branche': 'k.A.', - 'umsatz': 'k.A.', - 'mitarbeiter': 'k.A.', - 'categories': 'k.A.', - 'full_infobox': 'k.A.' - } - @retry_on_failure - def search_company_article(self, company_name, website): - search_terms = self._generate_search_terms(company_name, website) - for term in search_terms: - try: - results = wikipedia.search(term, results=Config.WIKIPEDIA_SEARCH_RESULTS) - debug_print(f"Suchergebnisse für '{term}': {results}") - for title in results: - try: - page = wikipedia.page(title, auto_suggest=False) - if self._validate_article(page, company_name, website): - return page - except (wikipedia.exceptions.DisambiguationError, wikipedia.exceptions.PageError) as e: - debug_print(f"Seitenfehler: {str(e)}") - continue - except Exception as e: - debug_print(f"Suchfehler: {str(e)}") - continue - return None - -# ==================== GOOGLE SHEET HANDLER (für Hauptdaten) ==================== -class GoogleSheetHandler: - def __init__(self): - self.sheet = None - self.sheet_values = [] - self._connect() - def _connect(self): - scope = ["https://www.googleapis.com/auth/spreadsheets"] - creds = ServiceAccountCredentials.from_json_keyfile_name(Config.CREDENTIALS_FILE, scope) - self.sheet = gspread.authorize(creds).open_by_url(Config.SHEET_URL).sheet1 - self.sheet_values = self.sheet.get_all_values() - def get_start_index(self): - filled_n = [row[13] if len(row) > 13 else '' for row in self.sheet_values[1:]] - return next((i + 1 for i, v in enumerate(filled_n, start=1) if not str(v).strip()), len(filled_n) + 1) +# ==================== NEUER MODUS 5: CONTACTS-ALIGNMENT DEMO (Schreibtest Contacts) ==================== +def contacts_alignment_demo(): + debug_print("Starte Contacts-Alignment-Demo (Schreibtest)...") + gc = gspread.authorize(ServiceAccountCredentials.from_json_keyfile_name( + Config.CREDENTIALS_FILE, ["https://www.googleapis.com/auth/spreadsheets"])) + sh = gc.open_by_url(Config.SHEET_URL) + try: + contacts_sheet = sh.worksheet("Contacts") + except gspread.exceptions.WorksheetNotFound: + contacts_sheet = sh.add_worksheet(title="Contacts", rows="1000", cols="10") + debug_print("Neues Blatt 'Contacts' erstellt.") + # Schreibe Header falls noch nicht vorhanden + if not contacts_sheet.get_all_values(): + header = ["Firmenname", "Website", "Vorname", "Nachname", "Position", "Anrede", "E-Mail"] + contacts_sheet.update("A1:G1", [header]) + debug_print("Header in 'Contacts' geschrieben.") + # Schreibe eine Testzeile + test_row = ["TestFirma", "www.test.de", "Max", "Mustermann", "Testposition", "Herr", "max.mustermann@test.de"] + contacts_sheet.update("A2:G2", [test_row]) + debug_print("Testzeile in 'Contacts' geschrieben.") # ==================== ALIGNMENT DEMO (Modus 3) ==================== def alignment_demo(sheet): @@ -755,278 +537,17 @@ def alignment_demo(sheet): "Spalte AE (Begründung bei Abweichung Anzahl Servicetechniker)", "Spalte AF (Schätzung Umsatz ChatGPT)", "Spalte AG (Begründung für Abweichung Umsatz)", - "Spalte AH (Timestamp letzte Prüfung)", - "Spalte AI (Version)" + "Spalte AH (Timestamp Wiki Update)", + "Spalte AI (Timestamp ChatGPT Bewertung)", + "Spalte AJ (Version)" ] - header_range = "A11200:AI11200" + header_range = "A11200:AJ11200" sheet.update(values=[new_headers], range_name=header_range) print("Alignment-Demo abgeschlossen: Neue Spaltenüberschriften in Zeile 11200 geschrieben.") -# ==================== NEUER MODUS 4: NUR WIKIPEDIA-SUCHE ==================== -def process_wikipedia_only(): - debug_print("Starte ausschließlich Wikipedia-Suche (Modus 4)...") - gc = gspread.authorize(ServiceAccountCredentials.from_json_keyfile_name( - Config.CREDENTIALS_FILE, ["https://www.googleapis.com/auth/spreadsheets"])) - sh = gc.open_by_url(Config.SHEET_URL) - main_sheet = sh.sheet1 - data = main_sheet.get_all_values() - start_index = GoogleSheetHandler().get_start_index() - debug_print(f"Starte bei Zeile {start_index+1}") - for i, row in enumerate(data[1:], start=2): - if i < start_index: - continue - company_name = row[1] if len(row) > 1 else "" - website = row[2] if len(row) > 2 else "" - debug_print(f"Verarbeite Zeile {i}: {company_name}") - article = WikipediaScraper().search_company_article(company_name, website) - if article: - company_data = WikipediaScraper().extract_company_data(article.url) - else: - company_data = { - 'url': 'k.A.', - 'first_paragraph': 'k.A.', - 'branche': 'k.A.', - 'umsatz': 'k.A.', - 'mitarbeiter': 'k.A.', - 'categories': 'k.A.', - 'full_infobox': 'k.A.' - } - wiki_values = [ - row[10] if len(row) > 10 and row[10].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.') - ] - wiki_range = f"K{i}:Q{i}" - main_sheet.update(values=[wiki_values], range_name=wiki_range) - debug_print(f"Zeile {i} mit Wikipedia-Daten aktualisiert.") - current_dt = datetime.now().strftime("%Y-%m-%d %H:%M:%S") - main_sheet.update(values=[[current_dt]], range_name=f"AH{i}") - main_sheet.update(values=[[Config.VERSION]], range_name=f"AI{i}") - time.sleep(Config.RETRY_DELAY) - debug_print("Wikipedia-Suche abgeschlossen.") - -# ==================== GOOGLE SHEET HANDLER (für Hauptdaten) ==================== -class GoogleSheetHandler: - def __init__(self): - self.sheet = None - self.sheet_values = [] - self._connect() - def _connect(self): - scope = ["https://www.googleapis.com/auth/spreadsheets"] - creds = ServiceAccountCredentials.from_json_keyfile_name(Config.CREDENTIALS_FILE, scope) - self.sheet = gspread.authorize(creds).open_by_url(Config.SHEET_URL).sheet1 - self.sheet_values = self.sheet.get_all_values() - def get_start_index(self): - filled_n = [row[13] if len(row) > 13 else '' for row in self.sheet_values[1:]] - return next((i + 1 for i, v in enumerate(filled_n, start=1) if not str(v).strip()), len(filled_n) + 1) - -# ==================== NEUER MODUS: CONTACTS (LinkedIn) ==================== -def process_contacts(): - debug_print("Starte LinkedIn-Kontaktsuche...") - gc = gspread.authorize(ServiceAccountCredentials.from_json_keyfile_name( - Config.CREDENTIALS_FILE, ["https://www.googleapis.com/auth/spreadsheets"])) - sh = gc.open_by_url(Config.SHEET_URL) - try: - contacts_sheet = sh.worksheet("Contacts") - except gspread.exceptions.WorksheetNotFound: - contacts_sheet = sh.add_worksheet(title="Contacts", rows="1000", cols="10") - header = ["Firmenname", "Website", "Vorname", "Nachname", "Position", "Anrede", "E-Mail"] - contacts_sheet.update("A1:G1", [header]) - debug_print("Neues Blatt 'Contacts' erstellt und Header eingetragen.") - main_sheet = sh.sheet1 - data = main_sheet.get_all_values() - positions = ["Serviceleiter", "IT-Leiter", "Leiter After Sales", "Leiter Einsatzplanung"] - new_rows = [] - for idx, row in enumerate(data[1:], start=2): - company_name = row[1] if len(row) > 1 else "" - website = row[2] if len(row) > 2 else "" - debug_print(f"Verarbeite Firma: '{company_name}' (Zeile {idx}), Website: '{website}'") - if not company_name or not website: - debug_print("Überspringe, da Firmenname oder Website fehlt.") - continue - for pos in positions: - debug_print(f"Suche nach Position: '{pos}' bei '{company_name}'") - contact = search_linkedin_contact(company_name, website, pos) - if contact: - debug_print(f"Kontakt gefunden: {contact}") - new_rows.append([contact["Firmenname"], contact["Website"], contact["Vorname"], contact["Nachname"], contact["Position"], "", ""]) - else: - debug_print(f"Kein Kontakt für Position '{pos}' bei '{company_name}' gefunden.") - if new_rows: - last_row = len(contacts_sheet.get_all_values()) + 1 - range_str = f"A{last_row}:G{last_row + len(new_rows) - 1}" - contacts_sheet.update(range_str, new_rows) - debug_print(f"{len(new_rows)} Kontakte in 'Contacts' hinzugefügt.") - else: - debug_print("Keine Kontakte gefunden in der Haupttabelle.") - -# ==================== DATA PROCESSOR ==================== -class DataProcessor: - def __init__(self): - self.sheet_handler = GoogleSheetHandler() - self.wiki_scraper = WikipediaScraper() - def process_rows(self, num_rows=None): - if MODE == "2": - print("Re-Evaluierungsmodus: Verarbeitung aller Zeilen mit 'x' in Spalte A.") - for i, row in enumerate(self.sheet_handler.sheet_values[1:], start=2): - if row[0].strip().lower() == "x": - self._process_single_row(i, row) - elif MODE == "3": - print("Alignment-Demo-Modus: Schreibe neue Spaltenüberschriften in Zeile 11200.") - alignment_demo(self.sheet_handler.sheet) - else: - start_index = self.sheet_handler.get_start_index() - print(f"Starte bei Zeile {start_index+1}") - rows_processed = 0 - for i, row in enumerate(self.sheet_handler.sheet_values[1:], start=2): - if i < start_index: - continue - if num_rows is not None and rows_processed >= num_rows: - break - self._process_single_row(i, row) - rows_processed += 1 - def _process_single_row(self, row_num, row_data): - company_name = row_data[1] if len(row_data) > 1 else "" - website = row_data[2] if len(row_data) > 2 else "" - wiki_update_range = f"K{row_num}:Q{row_num}" - chatgpt_range = f"AF{row_num}" - abgleich_range = f"AG{row_num}" - valid_range = f"R{row_num}" - dt_range = f"AH{row_num}" - ver_range = f"AI{row_num}" - print(f"\n[{datetime.now().strftime('%H:%M:%S')}] Verarbeite Zeile {row_num}: {company_name}") - - if len(row_data) > 10 and row_data[10].strip() not in ["", "k.A."]: - wiki_url = row_data[10].strip() - try: - company_data = self.wiki_scraper.extract_company_data(wiki_url) - except Exception as e: - debug_print(f"Fehler beim Laden des vorgeschlagenen Wikipedia-Artikels: {e}") - article = self.wiki_scraper.search_company_article(company_name, website) - company_data = self.wiki_scraper.extract_company_data(article.url) if article else { - 'url': 'k.A.', 'first_paragraph': 'k.A.', 'branche': 'k.A.', - 'umsatz': 'k.A.', 'mitarbeiter': 'k.A.', 'categories': 'k.A.', - 'full_infobox': 'k.A.' - } - else: - article = self.wiki_scraper.search_company_article(company_name, website) - company_data = self.wiki_scraper.extract_company_data(article.url) if article else { - 'url': 'k.A.', 'first_paragraph': 'k.A.', 'branche': 'k.A.', - 'umsatz': 'k.A.', 'mitarbeiter': 'k.A.', 'categories': 'k.A.', - 'full_infobox': 'k.A.' - } - - wiki_values = [ - row_data[10] if len(row_data) > 10 and row_data[10].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.') - ] - self.sheet_handler.sheet.update(values=[wiki_values], range_name=wiki_update_range) - wait_for_sheet_update(self.sheet_handler.sheet, f"K{row_num}", wiki_values[0]) - time.sleep(3) - - self.sheet_handler.sheet.update(values=[["XX"]], range_name=chatgpt_range) - - 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=abgleich_range) - - crm_data = ";".join(row_data[1:10]) - wiki_data = ";".join(row_data[11:17]) - valid_result = validate_article_with_chatgpt(crm_data, wiki_data) - self.sheet_handler.sheet.update(values=[[valid_result]], range_name=valid_range) - - crm_branche = row_data[5] if len(row_data) > 5 else "k.A." - beschreibung_branche = row_data[6] if len(row_data) > 6 else "k.A." - wiki_branche = company_data.get('branche', 'k.A.') - wiki_kategorien = company_data.get('categories', 'k.A.') - branche_result = evaluate_branche_chatgpt(crm_branche, beschreibung_branche, wiki_branche, wiki_kategorien) - branche_v_range = f"V{row_num}" - branche_w_range = f"W{row_num}" - branche_x_range = f"X{row_num}" - self.sheet_handler.sheet.update(values=[[branche_result["branch"]]], range_name=branche_v_range) - self.sheet_handler.sheet.update(values=[[branche_result["consistency"]]], range_name=branche_w_range) - self.sheet_handler.sheet.update(values=[[branche_result["justification"]]], range_name=branche_x_range) - - 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}") - - st_estimate = evaluate_servicetechnicians_estimate(company_name, company_data) - self.sheet_handler.sheet.update(values=[[st_estimate]], range_name=f"AD{row_num}") - 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: - explanation = evaluate_servicetechnicians_explanation(company_name, st_estimate, company_data) - discrepancy = explanation - else: - discrepancy = "ok" - self.sheet_handler.sheet.update(values=[[discrepancy]], range_name=f"AE{row_num}") - - self.sheet_handler.sheet.update(values=[["XX"]], range_name="AF" + str(row_num)) - self.sheet_handler.sheet.update(values=[["XX"]], range_name="AG" + str(row_num)) - - current_dt = datetime.now().strftime("%Y-%m-%d %H:%M:%S") - self.sheet_handler.sheet.update(values=[[current_dt]], range_name=dt_range) - self.sheet_handler.sheet.update(values=[[Config.VERSION]], range_name=ver_range) - - debug_print(f"✅ Aktualisiert: URL: {company_data.get('url', 'k.A.')}, " - f"Branche: {company_data.get('branche', 'k.A.')}, Umsatz-Abgleich: {abgleich_result}, " - f"Validierung: {valid_result}, Branchenvorschlag: {branche_result['branch']}, " - f"FSM: {fsm_result['suitability']}, Servicetechniker-Schätzung: {st_estimate}") - time.sleep(Config.RETRY_DELAY) - -# ==================== NEUER MODUS: CONTACTS (LinkedIn) ==================== -def process_contacts(): - debug_print("Starte LinkedIn-Kontaktsuche...") - gc = gspread.authorize(ServiceAccountCredentials.from_json_keyfile_name( - Config.CREDENTIALS_FILE, ["https://www.googleapis.com/auth/spreadsheets"])) - sh = gc.open_by_url(Config.SHEET_URL) - try: - contacts_sheet = sh.worksheet("Contacts") - except gspread.exceptions.WorksheetNotFound: - contacts_sheet = sh.add_worksheet(title="Contacts", rows="1000", cols="10") - header = ["Firmenname", "Website", "Vorname", "Nachname", "Position", "Anrede", "E-Mail"] - contacts_sheet.update("A1:G1", [header]) - debug_print("Neues Blatt 'Contacts' erstellt und Header eingetragen.") - main_sheet = sh.sheet1 - data = main_sheet.get_all_values() - positions = ["Serviceleiter", "IT-Leiter", "Leiter After Sales", "Leiter Einsatzplanung"] - new_rows = [] - for idx, row in enumerate(data[1:], start=2): - company_name = row[1] if len(row) > 1 else "" - website = row[2] if len(row) > 2 else "" - debug_print(f"Verarbeite Firma: '{company_name}' (Zeile {idx}), Website: '{website}'") - if not company_name or not website: - debug_print("Überspringe, da Firmenname oder Website fehlt.") - continue - for pos in positions: - debug_print(f"Suche nach Position: '{pos}' bei '{company_name}'") - contact = search_linkedin_contact(company_name, website, pos) - if contact: - debug_print(f"Kontakt gefunden: {contact}") - new_rows.append([contact["Firmenname"], contact["Website"], contact["Vorname"], contact["Nachname"], contact["Position"], "", ""]) - else: - debug_print(f"Kein Kontakt für Position '{pos}' bei '{company_name}' gefunden.") - if new_rows: - last_row = len(contacts_sheet.get_all_values()) + 1 - range_str = f"A{last_row}:G{last_row + len(new_rows) - 1}" - contacts_sheet.update(range_str, new_rows) - debug_print(f"{len(new_rows)} Kontakte in 'Contacts' hinzugefügt.") - else: - debug_print("Keine Kontakte gefunden in der Haupttabelle.") - # ==================== MAIN PROGRAMM ==================== if __name__ == "__main__": - print("Modi: 1 = regulärer Modus, 2 = Re-Evaluierungsmodus, 3 = Alignment-Demo, 4 = Nur Wikipedia-Suche, 5 = LinkedIn Contacts") + print("Modi: 1 = regulärer Modus, 2 = Re-Evaluierungsmodus, 3 = Alignment-Demo, 4 = Nur Wikipedia-Suche, 5 = Contacts-Alignment Demo (Schreibtest)") mode_input = input("Wählen Sie den Modus: ").strip() if mode_input == "2": MODE = "2" @@ -1052,5 +573,5 @@ if __name__ == "__main__": elif MODE == "4": process_wikipedia_only() elif MODE == "5": - process_contacts() + contacts_alignment_demo() print(f"\n✅ Auswertung abgeschlossen ({Config.VERSION})")