feat: Implement mobile application and lead processing utilities.

scripts/extract_duesseldorf.py

@@ -0,0 +1,62 @@
+import pypdf
+import re
+import csv
+
+pdf_path = 'cologne_duesseldorf_data/duesseldorf_innungen.pdf'
+output_csv = 'cologne_duesseldorf_data/duesseldorf_leads.csv'
+
+def extract_duesseldorf_leads():
+    try:
+        reader = pypdf.PdfReader(pdf_path)
+        text = ""
+        for page in reader.pages:
+            text += page.extract_text() + "\n"
+        
+        lines = text.split('\n')
+        leads = []
+        current_innung = "Unknown Innung"
+        
+        # Regex for email
+        email_regex = re.compile(r'[\w\.-]+@[\w\.-]+\.\w+')
+        
+        for i, line in enumerate(lines):
+            line = line.strip()
+            if not line:
+                continue
+            
+            # Update current Innung if line looks like a title (pure text, no email, short-ish)
+            # This is still heuristic but let's try to capture lines with "Innung" OR "Verband"
+            if ("Innung" in line or "Verband" in line) and "@" not in line and len(line) < 100:
+                current_innung = line
+            
+            emails = email_regex.findall(line)
+            for email in emails:
+                email = email.rstrip('.')
+                
+                if any(l['Email'] == email for l in leads):
+                    continue
+                    
+                leads.append({
+                    'Firm/Innung': current_innung,
+                    'Contact': "N/A", 
+                    'Email': email,
+                    'Phone': "N/A",
+                    'Region': 'Düsseldorf'
+                })
+        
+        # Write to CSV
+        with open(output_csv, 'w', newline='', encoding='utf-8') as f:
+            writer = csv.DictWriter(f, fieldnames=['Firm/Innung', 'Contact', 'Email', 'Phone', 'Region'])
+            writer.writeheader()
+            writer.writerows(leads)
+            
+        print(f"Extracted {len(leads)} leads from Düsseldorf PDF.")
+        # Print first 5 for verification
+        for l in leads[:5]:
+            print(f"- {l['Firm/Innung']}: {l['Email']}")
+        
+    except Exception as e:
+        print(f"Error extracting Düsseldorf leads: {e}")
+
+if __name__ == "__main__":
+    extract_duesseldorf_leads()