feat: Implement mobile application and lead processing utilities.

scripts/extract_leads_unterfranken_v2.py

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+
+import re
+import csv
+from pypdf import PdfReader
+
+def extract_leads_v2(pdf_path, output_csv):
+    print(f"Extracting from {pdf_path}...")
+    reader = PdfReader(pdf_path)
+    text_lines = []
+    
+    # Extract text and split into lines
+    for page in reader.pages:
+        page_text = page.extract_text()
+        if page_text:
+            text_lines.extend(page_text.split('\n'))
+
+    leads = []
+    current_innung = "Unbekannte Innung"
+    
+    # regex patterns
+    email_pattern = re.compile(r"E-Mail:\s*([a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,})", re.IGNORECASE)
+    obermeister_pattern = re.compile(r"Obermeister(?:in)?:\s*(.*)", re.IGNORECASE)
+    ansprechpartner_pattern = re.compile(r"Ansprechpartner(?:in)?:\s*(.*)", re.IGNORECASE)
+    kreishandwerksmeister_pattern = re.compile(r"Kreishandwerksmeister(?:in)?:\s*(.*)", re.IGNORECASE)
+    landkreis_pattern = re.compile(r"^Landkreis(e?):", re.IGNORECASE)
+
+    # Temporary storage for the current Innung's data
+    # We need to be careful: a single Innung block might have multiple contacts?
+    # Based on the PDF, usually contacts follow the Innung header.
+    
+    # Strategy: 
+    # Iterate through lines.
+    # If we detect "Landkreis:", look back for Innung Name. Update current_innung.
+    # Process lines for contacts/emails. Assign to current_innung.
+
+    extracted_entries = [] # List of dicts
+    
+    # Clean lines first
+    lines = [l.strip() for l in text_lines]
+    
+    seen_combinations = set()
+
+    for i, line in enumerate(lines):
+        if not line:
+            continue
+            
+        # Detect Innung Name via Lookahead/Lookbehind context
+        # Check if this line is "Landkreis: ..."
+        if landkreis_pattern.match(line):
+            # The Innung Name is likely the previous non-empty line
+            # Look backwards from i-1
+            k = i - 1
+            while k >= 0 and not lines[k]:
+                k -= 1
+            
+            if k >= 0:
+                potential_name = lines[k]
+                # Sanity check: Name shouldn't be too long or look like a page number "5.12.2025 8"
+                if len(potential_name) < 100 and not re.match(r'^\d{2}\.\d{2}\.\d{4}', potential_name):
+                     current_innung = potential_name
+                     # print(f"Found Innung: {current_innung}")
+
+        # Capture People
+        contact_person = None
+        match_om = obermeister_pattern.match(line)
+        if match_om:
+            contact_person = match_om.group(1).strip()
+        
+        match_ap = ansprechpartner_pattern.match(line)
+        if match_ap: # We take Ansprechpartner too
+             contact_person = match_ap.group(1).strip()
+             
+        match_khm = kreishandwerksmeister_pattern.match(line)
+        if match_khm:
+             contact_person = match_khm.group(1).strip()
+
+        # Capture Email
+        match_email = email_pattern.search(line)
+        if match_email:
+            email = match_email.group(1).strip()
+            
+            # If we found an email, we verify if valid
+            if len(email) < 5 or "@" not in email:
+                continue
+
+            # Check if we have a contact person on this line or previous line?
+            # The loop structure is linear. If we found a contact person 3 lines ago, should we link it?
+            # A simple heuristic: Keep the last seen contact person for this Innung block.
+            # But the block might define "Obermeister" then "Email", then "Ansprechpartner" then "Email".
+            # So we need `current_contact` state that resets somewhat?
+            # Actually, usually getting the email is the trigger to save a lead.
+            # We use the most recently seen contact person *since the last email or Innung change*.
+            
+            entry = {
+                "Firm/Innung": current_innung,
+                "Contact Person": contact_person if contact_person else "N/A", # Use local var if found on same line, else need state
+                "Email": email,
+                "Region": "Unterfranken"
+            }
+            
+            # Improvement: If contact_person is None on this line, try to use a "running" contact person
+            # But we must be careful not to apply Obermeister to Ansprechpartner's email.
+            # Let's verify the text dump. 
+            # 117: Obermeister: Ullrich Amthor
+            # ...
+            # 123: E-Mail: ... 
+            
+            # So the contact person appears BEFORE the email.
+            pass
+
+    # Refined loop with state
+    current_contact = "N/A"
+    
+    # Reset loop
+    current_innung = "Unbekannte Innung"
+    
+    for i, line in enumerate(lines):
+        if not line:
+            continue
+
+        # 1. Check for Innung Header (Landkreis pattern)
+        if landkreis_pattern.match(line):
+             # Backtrack to find name
+            k = i - 1
+            while k >= 0 and not lines[k]:
+                k -= 1
+            if k >= 0:
+                potential_name = lines[k]
+                if len(potential_name) < 100 and not re.match(r'^\d{2}\.\d{2}\.\d{4}', potential_name):
+                     current_innung = potential_name
+                     current_contact = "N/A" # Reset contact for new Innung
+
+
+        # 2. Check for Contact Person
+        # If line starts with Obermeister/Ansprechpartner, store it.
+        match_om = obermeister_pattern.match(line)
+        if match_om:
+            current_contact = match_om.group(1).strip()
+            continue # Move to next line (don't expect email on same line usually, but check pdf)
+        
+        match_ap = ansprechpartner_pattern.match(line)
+        if match_ap:
+             current_contact = match_ap.group(1).strip()
+             continue
+
+        match_khm = kreishandwerksmeister_pattern.match(line)
+        if match_khm:
+             current_contact = match_khm.group(1).strip()
+             continue
+
+
+        # 3. Check for Email description on same line (rare but possible) or email line
+        match_email = email_pattern.search(line)
+        if match_email:
+            email = match_email.group(1).strip()
+            
+            # Dedup
+            combo = (current_innung, email)
+            if combo in seen_combinations:
+                continue
+            seen_combinations.add(combo)
+            
+            leads.append({
+                "Firm/Innung": current_innung,
+                "Contact Person": current_contact,
+                "Email": email,
+                "Region": "Unterfranken"
+            })
+
+
+    # Write to CSV
+    with open(output_csv, 'w', newline='', encoding='utf-8') as f:
+        writer = csv.DictWriter(f, fieldnames=["Firm/Innung", "Contact Person", "Email", "Region"])
+        writer.writeheader()
+        writer.writerows(leads)
+    
+    print(f"Extracted {len(leads)} leads to {output_csv}")
+
+if __name__ == "__main__":
+    extract_leads_v2("leads/raw/unterfranken.pdf", "leads/raw/leads_unterfranken_v2.csv")