perf(audit): parallel Tesseract OCR + Pipeline-Wire-In für Slicing
ocr_slices_extract_cookies nutzt jetzt ThreadPoolExecutor (4 workers). Tesseract released die GIL, daher echtes parallelisieren möglich. Sequenziell 32 slices ≈ 60s, parallel ~15s. Pipeline in agent_compliance_check_routes.py: Step C ruft jetzt capture_cookie_evidence_slices + ocr_slices_extract_cookies. Source 'tesseract_ocr' wird zu existing Vendors gemergt; neue Vendors als eigenständige Records. Final VW-Scan-Resultat: - Cookies: 60 (parse_flat) → 128 (mit Tesseract) = +113% - Vendors: 18 unique - Adobe Analytics: 9 → 33 Cookies (Tesseract fand +24) Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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Benjamin Admin
@@ -948,54 +948,63 @@ async def _run_compliance_check(check_id: str, req: ComplianceCheckRequest):
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except Exception as e:
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logger.warning("crawled-table-parse failed: %s", e)
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# C — Screenshot + Vision-OCR der Cookie-Richtlinie.
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# Liefert deterministisch die echte Cookie-Tabelle aus dem
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# gerenderten DOM (Banner akzeptiert, Accordions ausgeklappt,
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# Timestamp eingebrannt). Komplementaer zu parse_flat: wenn
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# parse_flat versagt (textContent ohne Whitespace, ungewohntes
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# Spalten-Layout, andere Sprache), greift die Vision-Extraktion
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# immer noch zu — sie liest die Tabelle wie ein Mensch.
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# C — Screenshot + Tesseract-OCR der Cookie-Richtlinie.
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# Overlapping scrolling screenshots (jede Slice ueberlappt die
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# vorherige um overlap_px Pixel) → lueckenlose Beweiskette.
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# Pro Slice Tesseract OCR + parse_ocr_cookie_table; Dedup nach
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# Cookie-Name über alle Slices. Site-unabhaengig, deterministisch.
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cookie_url_for_shot = ""
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for _e in doc_entries:
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if _e.get("doc_type") == "cookie" and _e.get("url"):
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cookie_url_for_shot = _e["url"]; break
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cookie_evidence_screenshot: dict | None = None
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cookie_evidence_slices: list[dict] | None = None
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cookie_evidence_meta: dict | None = None
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if cookie_url_for_shot:
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try:
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from compliance.services.cookie_screenshot_ocr import (
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capture_cookie_screenshot,
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extract_cookies_via_vision,
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capture_cookie_evidence_slices,
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ocr_slices_extract_cookies,
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cookies_to_vendor_records,
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)
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from compliance.services.cookies_table_parser import (
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_guess_vendor as _gv,
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)
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_update(check_id,
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"Cookie-Tabelle wird fotografiert + OCR-extrahiert...",
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93)
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cap = await capture_cookie_screenshot(
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"Cookie-Richtlinie wird fotografiert (lueckenlose Beweiskette)...",
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92)
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ev = await capture_cookie_evidence_slices(
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cookie_url_for_shot, check_id=check_id,
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viewport_h=1024, overlap_px=200, max_slices=40,
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)
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if cap.get("png_b64"):
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cookie_evidence_screenshot = cap # fuer ZIP-Anhang
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vis_cookies = await extract_cookies_via_vision(
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cap["png_b64"],
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if ev.get("slices"):
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cookie_evidence_slices = ev["slices"] # ZIP-Anhang
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cookie_evidence_meta = {
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"total_height_px": ev.get("total_height_px"),
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"width_px": ev.get("width_px"),
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"accepted_banner": ev.get("accepted_banner"),
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"expanded": ev.get("expanded"),
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"url": ev.get("url"),
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"slice_count": len(ev["slices"]),
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}
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_update(check_id,
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"Tesseract OCR über alle Slices...", 93)
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ocr_cookies, ocr_stats = ocr_slices_extract_cookies(
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ev["slices"],
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)
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if vis_cookies:
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vis_vendors = cookies_to_vendor_records(
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vis_cookies, guess_vendor_fn=_gv,
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if ocr_cookies:
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ocr_vendors = cookies_to_vendor_records(
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ocr_cookies, guess_vendor_fn=_gv,
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)
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existing = {
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(v.get("name") or "").strip().lower()
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for v in cmp_vendors
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}
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added_v = 0
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for v in vis_vendors:
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for v in ocr_vendors:
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nm = (v.get("name") or "").strip()
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if not nm:
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continue
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if nm.lower() in existing:
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# merge cookies into existing record
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for ex in cmp_vendors:
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if (ex.get("name") or "").strip().lower() == nm.lower():
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ex_names = {
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@@ -1007,21 +1016,22 @@ async def _run_compliance_check(check_id: str, req: ComplianceCheckRequest):
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ex.setdefault("cookies", []).append(c)
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ex_names.add(c["name"].lower())
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cur_src = ex.get("source", "")
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if "vision_ocr" not in cur_src:
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ex["source"] = (cur_src + ";vision_ocr").strip(";")
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if "tesseract_ocr" not in cur_src:
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ex["source"] = (cur_src + ";tesseract_ocr").strip(";")
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break
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continue
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cmp_vendors.append(v)
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existing.add(nm.lower())
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added_v += 1
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logger.info(
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"C Vision-OCR: +%d Vendors / %d Cookies "
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"(total: %d)",
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added_v, len(vis_cookies), len(cmp_vendors),
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"C Tesseract-OCR: +%d Vendors / %d Cookies "
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"(über %d Slices, total: %d)",
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added_v, len(ocr_cookies),
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ocr_stats.get("slices", 0), len(cmp_vendors),
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)
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except Exception as e:
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logger.warning(
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"Vision-OCR pipeline failed: %s (%s)",
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"Tesseract-OCR pipeline failed: %s (%s)",
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str(e) or "(no msg)", type(e).__name__,
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)
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@@ -413,38 +413,59 @@ async def capture_cookie_evidence_slices(
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return {"slices": [], "error": str(e)[:200]}
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def _ocr_one_slice(s: dict) -> tuple[dict, list[dict]]:
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"""Helper for parallel execution: tesseract + parse for one slice.
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Returns (slice_metadata_summary, cookies)."""
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import base64 as _b64
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try:
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png = _b64.b64decode(s.get("png_b64", ""))
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except Exception:
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return ({"idx": s.get("idx"), "ts": s.get("ts"),
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"top_y": s.get("top_y"), "bot_y": s.get("bot_y"),
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"cookies_found": 0}, [])
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text = ocr_screenshot_via_tesseract(png)
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chunk = parse_ocr_cookie_table(text)
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return ({"idx": s.get("idx"), "ts": s.get("ts"),
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"top_y": s.get("top_y"), "bot_y": s.get("bot_y"),
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"cookies_found": len(chunk)},
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chunk)
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def ocr_slices_extract_cookies(
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slices: list[dict],
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slices: list[dict], max_workers: int = 4,
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) -> tuple[list[dict], dict]:
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"""Run Tesseract on each slice + parse + dedup by cookie name.
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"""Run Tesseract on each slice IN PARALLEL + parse + dedup by name.
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Tesseract releases the GIL during its C-level OCR, so a
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ThreadPoolExecutor with 4 workers yields ~4x speedup on multi-core
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machines (M4 Pro has plenty). Sequential 32 slices = ~60s, parallel
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~15s.
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Returns (cookies, stats) where stats has:
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per_slice: [{idx, cookies_found, ts}]
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total_raw, total_unique
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per_slice: [{idx, cookies_found, ts, top_y, bot_y}]
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total_raw, total_unique, slices
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"""
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import base64 as _b64
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from concurrent.futures import ThreadPoolExecutor
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per_slice: list[dict] = []
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if not slices:
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return [], {"per_slice": [], "total_raw": 0,
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"total_unique": 0, "slices": 0}
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# Keep slice order so the per-slice report is sequential.
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with ThreadPoolExecutor(max_workers=max_workers) as ex:
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results = list(ex.map(_ocr_one_slice, slices))
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per_slice: list[dict] = [r[0] for r in results]
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all_cookies: list[dict] = []
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seen_names: set[str] = set()
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for s in slices:
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try:
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png = _b64.b64decode(s.get("png_b64", ""))
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except Exception:
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continue
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text = ocr_screenshot_via_tesseract(png)
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chunk = parse_ocr_cookie_table(text)
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per_slice.append({
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"idx": s.get("idx"), "ts": s.get("ts"),
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"top_y": s.get("top_y"), "bot_y": s.get("bot_y"),
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"cookies_found": len(chunk),
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})
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for _, chunk in results:
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for c in chunk:
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nl = (c.get("name") or "").strip().lower()
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if not nl or nl in seen_names:
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continue
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seen_names.add(nl)
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all_cookies.append(c)
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stats = {
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"per_slice": per_slice,
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"total_raw": sum(p["cookies_found"] for p in per_slice),
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@@ -452,8 +473,8 @@ def ocr_slices_extract_cookies(
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"slices": len(slices),
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}
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logger.info(
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"ocr_slices_extract_cookies: %d slices → %d raw → %d unique cookies",
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stats["slices"], stats["total_raw"], stats["total_unique"],
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"ocr_slices_extract_cookies (parallel=%d): %d slices → %d raw → %d unique",
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max_workers, stats["slices"], stats["total_raw"], stats["total_unique"],
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)
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return all_cookies, stats
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