83 lines
4.1 KiB
Python
83 lines
4.1 KiB
Python
import json
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import csv
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import re
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import os
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# Files from step 255-268
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files = [
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r'C:\Users\a931627\.gemini\antigravity\brain\6060ab5d-4406-4d40-803f-c8d1df8bb430\.system_generated\steps\255\output.txt',
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r'C:\Users\a931627\.gemini\antigravity\brain\6060ab5d-4406-4d40-803f-c8d1df8bb430\.system_generated\steps\256\output.txt',
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r'C:\Users\a931627\.gemini\antigravity\brain\6060ab5d-4406-4d40-803f-c8d1df8bb430\.system_generated\steps\257\output.txt',
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r'C:\Users\a931627\.gemini\antigravity\brain\6060ab5d-4406-4d40-803f-c8d1df8bb430\.system_generated\steps\258\output.txt',
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r'C:\Users\a931627\.gemini\antigravity\brain\6060ab5d-4406-4d40-803f-c8d1df8bb430\.system_generated\steps\259\output.txt',
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r'C:\Users\a931627\.gemini\antigravity\brain\6060ab5d-4406-4d40-803f-c8d1df8bb430\.system_generated\steps\260\output.txt',
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r'C:\Users\a931627\.gemini\antigravity\brain\6060ab5d-4406-4d40-803f-c8d1df8bb430\.system_generated\steps\261\output.txt',
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r'C:\Users\a931627\.gemini\antigravity\brain\6060ab5d-4406-4d40-803f-c8d1df8bb430\.system_generated\steps\262\output.txt',
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r'C:\Users\a931627\.gemini\antigravity\brain\6060ab5d-4406-4d40-803f-c8d1df8bb430\.system_generated\steps\263\output.txt',
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r'C:\Users\a931627\.gemini\antigravity\brain\6060ab5d-4406-4d40-803f-c8d1df8bb430\.system_generated\steps\264\output.txt',
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r'C:\Users\a931627\.gemini\antigravity\brain\6060ab5d-4406-4d40-803f-c8d1df8bb430\.system_generated\steps\265\output.txt',
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r'C:\Users\a931627\.gemini\antigravity\brain\6060ab5d-4406-4d40-803f-c8d1df8bb430\.system_generated\steps\266\output.txt',
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r'C:\Users\a931627\.gemini\antigravity\brain\6060ab5d-4406-4d40-803f-c8d1df8bb430\.system_generated\steps\267\output.txt',
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r'C:\Users\a931627\.gemini\antigravity\brain\6060ab5d-4406-4d40-803f-c8d1df8bb430\.system_generated\steps\268\output.txt'
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]
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output_csv = 'cologne_duesseldorf_data/duesseldorf_batch5.csv'
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names = [
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"Stukkateur", "Bootsbauer", "Goldschmiede", "IT", "Kachel",
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"Karosserie", "Schneider", "Instrumenten", "Ortho-Technik", "Ortho-Schuh",
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"Parkett", "Sattler", "Werbe", "Zahn"
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]
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def parse_batch5():
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leads = []
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email_regex = re.compile(r'[\w\.-]+@[\w\.-]+\.\w+')
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for i, file_path in enumerate(files):
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try:
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with open(file_path, 'r', encoding='utf-8') as f:
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data = json.load(f)
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items = data.get('items', [])
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innung_name = names[i]
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found_email = False
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for item in items:
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if item.get('type') == 'organic':
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desc = item.get('description', '')
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title = item.get('title', '')
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snippet = item.get('pre_snippet', '')
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full_text = f"{title} {desc} {snippet}"
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emails = email_regex.findall(full_text)
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for email in emails:
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email = email.rstrip('.')
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# Filter out trash
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if email.endswith('png') or email.endswith('jpg') or 'datenschutz' in email:
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continue
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leads.append({
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'Firm/Innung': f"{innung_name} Düsseldorf",
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'Contact': "N/A",
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'Email': email,
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'Phone': "N/A",
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'Region': 'Düsseldorf'
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})
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found_email = True
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break
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if found_email:
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break
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except Exception as e:
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print(f"Error parsing {file_path}: {e}")
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with open(output_csv, 'w', newline='', encoding='utf-8') as f:
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writer = csv.DictWriter(f, fieldnames=['Firm/Innung', 'Contact', 'Email', 'Phone', 'Region'])
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writer.writeheader()
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writer.writerows(leads)
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print(f"Extracted {len(leads)} leads from Batch 5.")
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for l in leads:
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print(f"{l['Firm/Innung']}: {l['Email']}")
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if __name__ == "__main__":
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parse_batch5()
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