from __future__ import annotations import hashlib import json from pathlib import Path from typing import Any import pandas as pd from src.domain import CODE_VERSION, PRODUCT, RULESET_ID, SCHEMA_ID def input_hash(payload: dict[str, Any]) -> str: raw = json.dumps(payload, sort_keys=True, ensure_ascii=False, default=str) return hashlib.sha256(raw.encode("utf-8")).hexdigest()[:16] def build_report(result: dict[str, Any]) -> dict[str, Any]: return { "product": PRODUCT, "code_version": CODE_VERSION, "schema_id": SCHEMA_ID, "ruleset_id": RULESET_ID, "run_id": result["run_id"], "input_hash": result["input_hash"], "verdict": result["verdict"].value if hasattr(result["verdict"], "value") else result["verdict"], "status_label": result["status_label"], "kpis": result["kpis"], "findings": [item.model_dump() if hasattr(item, "model_dump") else item for item in result.get("findings") or []], "unknowns": [item.model_dump() if hasattr(item, "model_dump") else item for item in result.get("unknowns") or []], "reasons": result.get("reasons") or [], "validation": result["validation"].model_dump() if hasattr(result.get("validation"), "model_dump") else result.get("validation"), "note": "Uploaded code is not executed. Suggested patches are not merged.", } def write_downloads(result: dict[str, Any], folder: Path) -> dict[str, str]: folder.mkdir(parents=True, exist_ok=True) run_id = result["run_id"] files = { "findings": folder / f"{run_id}_findings.csv", "unknowns": folder / f"{run_id}_unknowns.csv", "comparison": folder / f"{run_id}_comparison.csv", "report": folder / f"{run_id}_report.json", } pd.DataFrame(result.get("finding_rows") or []).to_csv(files["findings"], index=False) pd.DataFrame(result.get("unknown_rows") or []).to_csv(files["unknowns"], index=False) pd.DataFrame(result.get("comparison") or []).to_csv(files["comparison"], index=False) files["report"].write_text(json.dumps(result["report"], indent=2, ensure_ascii=False, default=str), encoding="utf-8") return {key: str(path) for key, path in files.items()}