Chat GPT Bugfix für Deepseek

brancheneinstufung.py

@@ -89,108 +89,7 @@ class GoogleSheetHandler:
         )
 
 # ==================== WIKIPEDIA SCRAPER ====================
-class WikipediaScraper:
+class_=lambda c: c and any(
-    """Klasse zur Handhabung der Wikipedia-Suche und Datenextraktion"""
-    
-    def __init__(self):
-        wikipedia.set_lang(Config.LANG)
-        
-    def _extract_domain_hint(self, website):
-        """Extrahiert den Domain-Schlüssel aus der Website-URL"""
-        if not website:
-            return ""
-        # Entferne Protokoll und www, zerlege in Teile
-        clean_url = website.lower().replace("https://", "").replace("http://", "").replace("www.", "")
-        domain_parts = clean_url.split(".")
-        return domain_parts[0] if domain_parts else ""
-
-    def _generate_search_terms(self, company_name, website_hint=""):
-        """Generiert Suchbegriffe aus Firmenname und Website"""
-        search_terms = [company_name.strip()]
-        
-        # Bereinigung von Rechtsformen und Sonderzeichen
-        clean_name = re.sub(
-            r'\s+(?:GmbH|AG|KG|OHG|e\.V\.|mbH|& Co\. KG| GmbH & Co\. KG).*$', 
-            '', 
-            company_name
-        ).strip()
-        
-        # Füge bereinigten Namen hinzu, wenn unterschiedlich
-        if clean_name and clean_name != company_name:
-            search_terms.append(clean_name)
-            
-        # Extrahiere erste zwei relevante Wörter
-        name_words = [w for w in re.split(r'\W+', clean_name) if w]
-        if len(name_words) >= 2:
-            search_terms.append(" ".join(name_words[:2]))
-            
-        # Domain-Hint hinzufügen
-        domain_hint = self._extract_domain_hint(website_hint)
-        if domain_hint and domain_hint not in ["de", "com", "org", "net"]:
-            search_terms.append(domain_hint)
-            
-        debug_print(f"Generierte Suchbegriffe: {search_terms}")
-        return list(set(search_terms))  # Duplikate entfernen
-
-    def _validate_article(self, page, company_name, domain_hint=""):
-        """Überprüft ob der Artikel zum Unternehmen passt"""
-        # Normalisiere beide Namen
-        page_title = re.sub(r'\(.*?\)', '', page.title).strip().lower()
-        search_name = re.sub(r'[^a-zA-Z0-9äöüß ]', '', company_name).strip().lower()
-        
-        # Ähnlichkeitsprüfung
-        similarity = SequenceMatcher(None, page_title, search_name).ratio()
-        debug_print(f"Ähnlichkeit '{page_title}' vs '{search_name}': {similarity:.2f}")
-        
-        # Zusätzliche Domain-Prüfung
-        if domain_hint:
-            html_content = requests.get(page.url).text.lower()
-            if domain_hint not in html_content:
-                debug_print(f"Domain-Hint '{domain_hint}' nicht im Artikel gefunden")
-                return False
-                
-        return similarity >= Config.SIMILARITY_THRESHOLD
-    
-    @retry_on_failure
-    def search_company_article(self, company_name, website_hint=""):
-        """Hauptfunktion zur Artikelsuche"""
-        search_terms = self._generate_search_terms(company_name, website_hint)
-        domain_hint = self._extract_domain_hint(website_hint)
-        
-        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, domain_hint):
-                            return page
-                    except wikipedia.exceptions.DisambiguationError:
-                        continue
-            except Exception as e:
-                debug_print(f"Fehler bei Suche nach {term}: {str(e)}")
-                continue
-        return None
-    
-    def extract_company_data(self, page_url):
-        """Extrahiert Branche und Umsatz aus dem Wikipedia-Artikel"""
-        response = requests.get(page_url)
-        soup = BeautifulSoup(response.text, Config.HTML_PARSER)
-        
-        return {
-            'branche': self._extract_infobox_value(soup, 'branche'),
-            'umsatz': self._extract_infobox_value(soup, 'umsatz'),
-            'url': page_url
-        }
-
-# ==================== WIKIPEDIA SCRAPER ====================
-class WikipediaScraper:
-    def _extract_infobox_value(self, soup, target):
-        """Extrahiert spezifischen Wert aus der Infobox mit erweiterten Suchmustern"""
-        # Erweiterte Infobox-Erkennung
-        infobox = soup.find('table', class_=lambda c: c and any(
             kw in c.lower() for kw in ['infobox', 'vcard', 'unternehmen']
         ))
         
@@ -239,6 +138,110 @@ class WikipediaScraper:
 
         return "k.A."
 
+class WikipediaScraper:
+    def __init__(self):
+        wikipedia.set_lang(Config.LANG)
+
+    def _extract_domain_hint(self, website):
+            """Extrahiert den Domain-Schlüssel aus der Website-URL"""
+            if not website:
+                return ""
+            # Entferne Protokoll und www, zerlege in Teile
+            clean_url = website.lower().replace("https://", "").replace("http://", "").replace("www.", "")
+            domain_parts = clean_url.split(".")
+            return domain_parts[0] if domain_parts else ""
+
+    def _generate_search_terms(self, company_name, website_hint=""):
+            """Generiert Suchbegriffe aus Firmenname und Website"""
+            search_terms = [company_name.strip()]
+            
+            # Bereinigung von Rechtsformen und Sonderzeichen
+            clean_name = re.sub(
+                r'\s+(?:GmbH|AG|KG|OHG|e\.V\.|mbH|& Co\. KG| GmbH & Co\. KG).*$', 
+                '', 
+                company_name
+            ).strip()
+            
+            # Füge bereinigten Namen hinzu, wenn unterschiedlich
+            if clean_name and clean_name != company_name:
+                search_terms.append(clean_name)
+                
+            # Extrahiere erste zwei relevante Wörter
+            name_words = [w for w in re.split(r'\W+', clean_name) if w]
+            if len(name_words) >= 2:
+                search_terms.append(" ".join(name_words[:2]))
+                
+            # Domain-Hint hinzufügen
+            domain_hint = self._extract_domain_hint(website_hint)
+            if domain_hint and domain_hint not in ["de", "com", "org", "net"]:
+                search_terms.append(domain_hint)
+                
+            debug_print(f"Generierte Suchbegriffe: {search_terms}")
+            return list(set(search_terms))  # Duplikate entfernen
+
+    def _validate_article(self, page, company_name, domain_hint=""):
+            """Überprüft ob der Artikel zum Unternehmen passt"""
+            # Normalisiere beide Namen
+            page_title = re.sub(r'\(.*?\)', '', page.title).strip().lower()
+            search_name = re.sub(r'[^a-zA-Z0-9äöüß ]', '', company_name).strip().lower()
+            
+            # Ähnlichkeitsprüfung
+            similarity = SequenceMatcher(None, page_title, search_name).ratio()
+            debug_print(f"Ähnlichkeit '{page_title}' vs '{search_name}': {similarity:.2f}")
+            
+            # Zusätzliche Domain-Prüfung
+            if domain_hint:
+                html_content = requests.get(page.url).text.lower()
+                if domain_hint not in html_content:
+                    debug_print(f"Domain-Hint '{domain_hint}' nicht im Artikel gefunden")
+                    return False
+                    
+            return similarity >= Config.SIMILARITY_THRESHOLD
+        
+        @retry_on_failure
+
+    def search_company_article(self, company_name, website_hint=""):
+            """Hauptfunktion zur Artikelsuche"""
+            search_terms = self._generate_search_terms(company_name, website_hint)
+            domain_hint = self._extract_domain_hint(website_hint)
+            
+            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, domain_hint):
+                                return page
+                        except wikipedia.exceptions.DisambiguationError:
+                            continue
+                except Exception as e:
+                    debug_print(f"Fehler bei Suche nach {term}: {str(e)}")
+                    continue
+            return None
+
+    def extract_company_data(self, page_url):
+            """Extrahiert Branche und Umsatz aus dem Wikipedia-Artikel"""
+            response = requests.get(page_url)
+            soup = BeautifulSoup(response.text, Config.HTML_PARSER)
+            
+            return {
+                'branche': self._extract_infobox_value(soup, 'branche'),
+                'umsatz': self._extract_infobox_value(soup, 'umsatz'),
+                'url': page_url
+            }
+        
+    
+    # ==================== WIKIPEDIA SCRAPER ====================
+    class WikipediaScraper:
+
+    def _extract_infobox_value(self, soup, target):
+            """Extrahiert spezifischen Wert aus der Infobox mit erweiterten Suchmustern"""
+            # Erweiterte Infobox-Erkennung
+            infobox = soup.find('table',
+
 # ==================== DATA PROCESSOR ====================
 class DataProcessor:
     """Klasse zur Steuerung des Gesamtprozesses"""