Benjamin Admin
e2be51b0aa
P106 — mc_audit_type.py: zentrales Quality-Thema. Klassifiziert pro MC: verifiable / process_internal / doc_internal / ambiguous. Pattern-Match auf check_question + title + fail_criteria (Schulung, AVV abgeschlossen, TOM umgesetzt, DSFA durchgefuehrt, Ausnahmen dokumentieren, kostenfrei zur Verfuegung, opt-out intern ermoeglichen, …). Interne MCs werden in der MC-Auswertung NICHT mehr als FAIL gewertet, sondern als CHECK markiert (audit_status='check'). Sie zaehlen im build_scorecard als skipped (nicht failed) damit der Score realistisch ist. build_internal_checks_block_html() rendert sie als separaten blauen Block 'Pruefungen die wir von aussen NICHT durchfuehren koennen' nach dem MC-Scorecard. Erwartete Wirkung: bei VW 95 FAILs → wahrscheinlich 30-40 echte verifiable_fails + 50-60 internal_checks. GF-Mail wird drastisch realistischer (statt 'Sie haben 95 Verstoesse' → 'Sie haben 35 extern sichtbare Themen + 60 interne Checks, bitte mit DSB klaeren'). P83 — BUILD_SHA in backend/admin/consent-tester Dockerfiles als ARG + ENV. check-rebuild-needed.sh kann jetzt deployed vs local SHA vergleichen + REBUILD REQUIRED melden. P80 v2 — check_replay.py macht jetzt vollstaendigen Replay aller post-fetch Quality-Generatoren: vendor_normalizer (Dedup), audit_quality_checks, cookie_compliance_audit, tcf_vendor_authority, cookie_value_entropy, cookie_network_tracer. Snapshots aus alter Zeit zeigen jetzt im Replay den aktuellen Audit-Stand. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
backend-compliance
Python/FastAPI service implementing the DSGVO compliance API: DSR, DSFA, consent, controls, risks, evidence, audit, vendor management, ISMS, change requests, document generation.
Port: 8002 (container: bp-compliance-backend)
Stack: Python 3.12, FastAPI, SQLAlchemy 2.x, Alembic, Keycloak auth.
Architecture
compliance/
├── api/ # Routers (thin, ≤30 LOC per handler)
├── services/ # Business logic
├── repositories/ # DB access
├── domain/ # Value objects, domain errors
├── schemas/ # Pydantic models, split per domain
└── db/models/ # SQLAlchemy ORM, one module per aggregate
The service follows this layered target structure but not all files are fully refactored yet. Phase 1 backlog is tracked in .claude/rules/loc-exceptions.txt (27 backend-compliance files currently excepted).
See ../AGENTS.python.md for the full convention and ../.claude/rules/architecture.md for the non-negotiable rules.
Run locally
cd backend-compliance
pip install -r requirements.txt
export COMPLIANCE_DATABASE_URL=... # Postgres (Hetzner or local)
uvicorn main:app --reload --port 8002
Tests
pytest compliance/tests/ -v
pytest --cov=compliance --cov-report=term-missing
Layout: tests/unit/, tests/integration/, tests/contracts/. Contract tests diff /openapi.json against tests/contracts/openapi.baseline.json.
Public API surface
404+ endpoints across /api/v1/*. Grouped by domain: ai, audit, consent, dsfa, dsr, gdpr, vendor, evidence, change-requests, generation, projects, company-profile, isms. Every path is a contract — see the "Public endpoints" rule in the root CLAUDE.md.
Environment
| Var | Purpose |
|---|---|
COMPLIANCE_DATABASE_URL |
Postgres DSN, sslmode=require |
KEYCLOAK_* |
Auth verification |
QDRANT_URL, QDRANT_API_KEY |
Vector search |
CORE_VALKEY_URL |
Session cache |
Don't touch
Database schema, __tablename__, column names, existing migrations under migrations/. See root CLAUDE.md rule 3.