236 lines
8.3 KiB
Python
236 lines
8.3 KiB
Python
#!/usr/bin/env python3
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"""
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Batch Ground Truth Test — run compliance check on all 10 GT websites.
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Usage:
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python3 batch_gt_test.py [--backend-url URL]
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Calls the compliance-check API for each website's DSI + Impressum URLs,
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polls for results, and prints a comparison table.
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"""
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import argparse
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import json
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import sys
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import time
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import httpx
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# 10 GT websites with their known document URLs
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GT_WEBSITES = [
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{
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"name": "SafetyKon",
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"documents": [
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{"doc_type": "dse", "url": "https://safetykon.de/datenschutz"},
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{"doc_type": "impressum", "url": "https://safetykon.de/impressum"},
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],
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},
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{
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"name": "IHK Konstanz",
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"documents": [
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{"doc_type": "dse", "url": "https://www.ihk.de/konstanz/servicemarken/ueber-uns/downloads/datenschutzinformationen-zum-internetangebot-4163288"},
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{"doc_type": "impressum", "url": "https://www.ihk.de/konstanz/impressum"},
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],
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},
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{
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"name": "Stadt Koeln",
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"documents": [
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{"doc_type": "dse", "url": "https://www.stadt-koeln.de/datenschutz"},
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{"doc_type": "impressum", "url": "https://www.stadt-koeln.de/impressum"},
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],
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},
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{
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"name": "BMW",
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"documents": [
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{"doc_type": "dse", "url": "https://www.bmw.de/de/footer/metanavigation/datenschutz.html"},
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{"doc_type": "impressum", "url": "https://www.bmw.de/de/footer/metanavigation/impressum.html"},
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],
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},
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{
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"name": "Sparkasse Bodensee",
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"documents": [
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{"doc_type": "dse", "url": "https://www.sparkasse-bodensee.de/de/home/toolbar/datenschutz.html"},
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{"doc_type": "impressum", "url": "https://www.sparkasse-bodensee.de/de/home/toolbar/impressum.html"},
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],
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},
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{
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"name": "Spiegel",
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"documents": [
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{"doc_type": "dse", "url": "https://www.spiegel.de/datenschutz-spiegel"},
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{"doc_type": "impressum", "url": "https://www.spiegel.de/impressum"},
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{"doc_type": "nutzungsbedingungen", "url": "https://www.spiegel.de/nutzungsbedingungen"},
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],
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},
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{
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"name": "TUEV Sued",
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"documents": [
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{"doc_type": "dse", "url": "https://www.tuvsud.com/de-de/datenschutzerklaerung"},
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{"doc_type": "impressum", "url": "https://www.tuvsud.com/de-de/impressum"},
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],
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},
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{
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"name": "ETO Gruppe",
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"documents": [
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{"doc_type": "dse", "url": "https://www.etogruppe.com/datenschutz.html"},
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{"doc_type": "impressum", "url": "https://www.etogruppe.com/impressum.html"},
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],
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},
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{
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"name": "Caritas",
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"documents": [
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{"doc_type": "dse", "url": "https://www.caritas.de/datenschutz"},
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{"doc_type": "impressum", "url": "https://www.caritas.de/impressum"},
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],
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},
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{
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"name": "BfDI",
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"documents": [
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{"doc_type": "dse", "url": "https://www.bfdi.bund.de/DE/Meta/Datenschutz/datenschutz_node.html"},
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{"doc_type": "impressum", "url": "https://www.bfdi.bund.de/DE/Meta/Impressum/impressum_node.html"},
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],
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},
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]
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def run_check(backend_url: str, website: dict) -> dict:
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"""Submit compliance check and poll for results."""
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with httpx.Client(timeout=30.0, verify=False) as client:
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# Start check
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resp = client.post(
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f"{backend_url}/api/compliance/agent/compliance-check",
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json={
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"documents": website["documents"],
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"use_agent": False,
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},
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)
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if resp.status_code != 200:
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return {"error": f"Start failed: {resp.status_code}"}
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check_id = resp.json().get("check_id")
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if not check_id:
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return {"error": "No check_id"}
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# Poll (max 15 min)
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for _ in range(300):
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time.sleep(3)
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poll = client.get(
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f"{backend_url}/api/compliance/agent/compliance-check/{check_id}"
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)
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if poll.status_code != 200:
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continue
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data = poll.json()
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if data.get("status") == "completed":
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return data.get("result", {})
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if data.get("status") == "failed":
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return {"error": data.get("error", "Check failed")}
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return {"error": "Timeout (15 min)"}
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def print_results(all_results: list[tuple[str, dict]]):
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"""Print comparison table."""
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print()
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print("=" * 100)
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print(f"{'Website':20s} {'Profil':12s} {'DSI L1':10s} {'DSI W':7s} "
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f"{'Imp L1':10s} {'Dienste':8s} {'Docs':5s} {'Status':12s}")
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print("-" * 100)
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for name, result in all_results:
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if "error" in result:
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print(f"{name:20s} {'ERROR':12s} {result['error'][:60]}")
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continue
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profile = result.get("business_profile", {})
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btype = profile.get("business_type", "?").upper()
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industry = profile.get("industry", "?")
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services = len(profile.get("detected_services", []))
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docs = result.get("results", [])
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dsi = next((d for d in docs if d.get("doc_type") == "dse"), {})
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imp = next((d for d in docs if d.get("doc_type") == "impressum"), {})
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dsi_l1 = f"{dsi.get('completeness_pct', 0)}%"
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dsi_w = str(dsi.get("word_count", 0))
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imp_l1 = f"{imp.get('completeness_pct', 0)}%"
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ok_count = sum(1 for d in docs if d.get("completeness_pct", 0) == 100)
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total = len(docs)
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print(f"{name:20s} {btype+'/'+industry:12s} {dsi_l1:10s} {dsi_w:7s} "
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f"{imp_l1:10s} {services:8d} {ok_count}/{total:<3d} "
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f"{'OK' if dsi.get('completeness_pct', 0) == 100 else 'LUECKEN'}")
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print("=" * 100)
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# Detail: all doc results
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print()
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for name, result in all_results:
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if "error" in result:
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continue
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docs = result.get("results", [])
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print(f"--- {name} ---")
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for d in docs:
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pct = d.get("completeness_pct", 0)
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cpct = d.get("correctness_pct", 0)
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dtype = d.get("doc_type", "?")
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label = d.get("label", dtype)
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wc = d.get("word_count", 0)
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scenario = d.get("scenario", "")
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checks = d.get("checks", [])
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l1_total = len([c for c in checks if c.get("level", 1) == 1])
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l1_pass = len([c for c in checks if c.get("level", 1) == 1 and c.get("passed")])
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failed = [c["label"] for c in checks if c.get("level", 1) == 1 and not c.get("passed") and not c.get("skipped") and c.get("severity") != "INFO"]
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print(f" {label:30s} {l1_pass}/{l1_total} L1 ({pct}%) {wc}w {scenario}")
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if failed:
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for f in failed[:5]:
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print(f" ✗ {f[:70]}")
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print()
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def main():
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parser = argparse.ArgumentParser()
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parser.add_argument("--backend-url", default="https://localhost:8002",
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help="Backend compliance URL")
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parser.add_argument("--sites", default="all",
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help="Comma-separated site indices (1-10) or 'all'")
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args = parser.parse_args()
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sites = GT_WEBSITES
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if args.sites != "all":
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indices = [int(i) - 1 for i in args.sites.split(",")]
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sites = [GT_WEBSITES[i] for i in indices if 0 <= i < len(GT_WEBSITES)]
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print(f"Running compliance check on {len(sites)} websites...")
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print(f"Backend: {args.backend_url}")
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print()
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all_results = []
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for i, website in enumerate(sites):
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name = website["name"]
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print(f"[{i+1}/{len(sites)}] {name}...", end=" ", flush=True)
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t0 = time.time()
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result = run_check(args.backend_url, website)
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elapsed = time.time() - t0
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if "error" in result:
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print(f"ERROR ({elapsed:.0f}s): {result['error'][:60]}")
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else:
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docs = result.get("results", [])
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ok = sum(1 for d in docs if d.get("completeness_pct", 0) == 100)
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print(f"OK ({elapsed:.0f}s) — {len(docs)} docs, {ok} vollstaendig")
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all_results.append((name, result))
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print_results(all_results)
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# Save raw results
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out_file = f"batch_results_{time.strftime('%Y%m%d_%H%M%S')}.json"
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with open(out_file, "w") as f:
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json.dump(
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{name: result for name, result in all_results},
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f, indent=2, default=str,
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)
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print(f"\nRaw results saved to {out_file}")
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if __name__ == "__main__":
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main()
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