stadtwerke/scripts/parse_cologne_serp.py

56 lines
1.9 KiB
Python

import json
import csv
import re
# Parse the SERP output file (it's JSON content inside a text file, usually)
# The previous view_file showed it's valid JSON.
input_file = r'C:\Users\a931627\.gemini\antigravity\brain\6060ab5d-4406-4d40-803f-c8d1df8bb430\.system_generated\steps\141\output.txt'
output_csv = 'cologne_duesseldorf_data/cologne_leads.csv'
def parse_serp():
with open(input_file, 'r', encoding='utf-8') as f:
data = json.load(f)
leads = []
items = data.get('items', [])
email_regex = re.compile(r'[\w\.-]+@[\w\.-]+\.\w+')
for item in items:
if item.get('type') == 'organic':
desc = item.get('description', '')
title = item.get('title', '')
snippet = item.get('pre_snippet', '')
full_text = f"{title} {desc} {snippet}"
emails = email_regex.findall(full_text)
for email in emails:
email = email.rstrip('.')
# Use title or domain as Innung name
innung_name = item.get('website_name') or item.get('domain') or title
if any(l['Email'] == email for l in leads):
continue
leads.append({
'Firm/Innung': innung_name,
'Contact': "N/A",
'Email': email,
'Phone': "N/A",
'Region': 'Köln'
})
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 Cologne SERP.")
for l in leads:
print(f"{l['Firm/Innung']}: {l['Email']}")
if __name__ == "__main__":
parse_serp()