6f0df5a774
Stop tracking personal workflow artifacts at repo root, add CI and MIT license, align README and agent skills with artifacts/ defaults, and enable Ruff in dev/CI so releases are verifiable without local-only runs. Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com> Co-authored-by: Cursor <cursoragent@cursor.com>
215 lines
7.1 KiB
Python
215 lines
7.1 KiB
Python
"""Tests for plan review helpers."""
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from vlm.models import ExecutionPlan, FileOperation
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from vlm.plan_render import render_review_verdict
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from vlm.plan_review import (
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build_duplicate_path_maps,
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build_identity_lookup,
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check_review_requirements,
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enrich_review_rows,
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normalized_path_key,
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prepare_review_rows,
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review_plan,
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save_review_csv,
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)
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from vlm.plan_structure_preview import build_structure_preview_lines
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from vlm.planner import apply_review_to_plan, load_plan, save_plan
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from vlm.utils import utc_now
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def _minimal_plan(operations: list[FileOperation]) -> ExecutionPlan:
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return ExecutionPlan(
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plan_id="t",
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created_at=utc_now(),
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operations=operations,
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summary={"total": len(operations), "move": 1, "rename": 0, "quarantine": 0, "no-op": 0},
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)
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def test_render_review_verdict_blocked_and_ok():
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assert "BLOCKED" in render_review_verdict({"high_risk_operations": 2})
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assert "OK TO DRY-RUN" in render_review_verdict({"high_risk_operations": 0})
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def test_build_identity_lookup_and_enrich(tmp_path):
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identities = {
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"vlm_schema_version": "1.0",
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"movies": [],
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"series": [
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{
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"path": str(tmp_path / "dl/Show.S01E01.mkv"),
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"filename": "Show.S01E01.mkv",
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"category": "series",
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"title": "Show",
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"season": 1,
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"episodes": [1],
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"confidence": 1.0,
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"needs_review": False,
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"video_metadata": {"resolution": "1080p", "size_bytes": 1000},
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}
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],
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}
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lookup = build_identity_lookup(identities)
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op = FileOperation(
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operation_type="move",
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source_path=tmp_path / "dl/Show.S01E01.mkv",
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destination_path=tmp_path / "lib/series/Show/Season 01/S01E01.mkv",
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reason="organize",
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has_conflict=False,
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review_context={"title": "Show", "category": "series", "season": 1, "episode": 1},
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)
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plan = _minimal_plan([op])
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rows = [
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{
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"index": "1",
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"operation_type": "move",
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"risk_flags": "",
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"source_path": str(op.source_path),
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"destination_path": str(op.destination_path),
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"reason": op.reason,
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}
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]
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enriched = enrich_review_rows(rows, plan, identity_lookup=lookup, library_root=tmp_path / "lib")
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assert enriched[0]["title"] == "Show"
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assert enriched[0]["quality_hint"]
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assert enriched[0]["source_name"] == "Show.S01E01.mkv"
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def test_check_review_requirements_missing_csv(tmp_path):
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plan_path = tmp_path / "plan.json"
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op = FileOperation(
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operation_type="quarantine",
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source_path=tmp_path / "Series.S20E01.mkv",
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destination_path=None,
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reason="Series needs manual review (season exceeds configured threshold)",
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has_conflict=False,
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)
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plan = _minimal_plan([op])
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save_plan(plan, plan_path)
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loaded = load_plan(plan_path)
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errors = check_review_requirements(loaded, plan_path, tmp_path / "missing.csv")
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assert len(errors) == 1
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assert "not found" in errors[0]
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def test_check_review_requirements_requires_apply_review(tmp_path):
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plan_path = tmp_path / "plan.json"
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csv_path = tmp_path / "plan_manual_review.csv"
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op = FileOperation(
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operation_type="move",
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source_path=tmp_path / "a.mkv",
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destination_path=tmp_path / "lib/a.mkv",
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reason="Series needs manual review (season exceeds configured threshold)",
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has_conflict=True,
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)
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plan = _minimal_plan([op])
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save_plan(plan, plan_path)
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rows, _ = review_plan(plan)
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save_review_csv(rows, csv_path)
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errors = check_review_requirements(load_plan(plan_path), plan_path, csv_path)
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assert len(errors) == 1
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assert "apply-review" in errors[0]
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def test_check_review_requirements_passes_after_apply_review(tmp_path):
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plan_path = tmp_path / "plan.json"
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csv_path = tmp_path / "plan_manual_review.csv"
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op = FileOperation(
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operation_type="move",
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source_path=tmp_path / "a.mkv",
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destination_path=tmp_path / "lib/a.mkv",
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reason="Series needs manual review (season exceeds configured threshold)",
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has_conflict=True,
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)
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plan = _minimal_plan([op])
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save_plan(plan, plan_path)
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rows, _ = review_plan(plan)
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for row in rows:
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row["operation_type"] = "no-op"
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save_review_csv(rows, csv_path)
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updated = apply_review_to_plan(load_plan(plan_path), csv_path)
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save_plan(updated, plan_path)
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errors = check_review_requirements(load_plan(plan_path), plan_path, csv_path)
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assert errors == []
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def test_planner_noop_manual_review_does_not_block_execute_gate(tmp_path):
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plan_path = tmp_path / "plan.json"
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op = FileOperation(
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operation_type="no-op",
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source_path=tmp_path / "Series.S20E01.mkv",
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destination_path=None,
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reason="Series needs manual review (season exceeds configured threshold)",
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has_conflict=False,
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)
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plan = _minimal_plan([op])
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save_plan(plan, plan_path)
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errors = check_review_requirements(load_plan(plan_path), plan_path, tmp_path / "missing.csv")
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assert errors == []
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def test_review_plan_skips_applied_noop_reason(tmp_path):
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op = FileOperation(
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operation_type="no-op",
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source_path=tmp_path / "a.mkv",
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destination_path=None,
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reason="Modified via manual review: Series needs manual review (season exceeds configured threshold)",
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has_conflict=False,
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)
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rows, counters = review_plan(_minimal_plan([op]))
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assert rows == []
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assert counters["high_risk_operations"] == 0
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def test_build_duplicate_path_maps_uses_canonical_keys(tmp_path):
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raw = str(tmp_path / "movie.mkv")
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analysis = {
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"duplicates": [
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{
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"identity": {"type": "movie", "title": "X", "year": 2020},
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"files": [raw],
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"quality_comparison": [{"path": raw, "resolution": "1080p"}],
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}
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]
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}
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path_to_group, path_to_quality = build_duplicate_path_maps(analysis)
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key = normalized_path_key(raw)
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assert path_to_group[key] == "movie:X:2020"
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assert path_to_quality[key]["resolution"] == "1080p"
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def test_structure_preview_lines(tmp_path):
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lib = tmp_path / "library"
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op = FileOperation(
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operation_type="move",
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source_path=tmp_path / "a.mkv",
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destination_path=lib / "series/Show/Season 01/S01E01.mkv",
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reason="x",
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has_conflict=False,
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review_context={"title": "Show"},
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)
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lines = build_structure_preview_lines(_minimal_plan([op]), lib)
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assert any("Show" in line for line in lines)
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def test_prepare_review_rows_sample_safe(tmp_path):
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ops = [
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FileOperation(
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operation_type="move",
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source_path=tmp_path / f"f{i}.mkv",
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destination_path=tmp_path / f"lib/f{i}.mkv",
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reason="organize",
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has_conflict=False,
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)
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for i in range(5)
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]
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plan = _minimal_plan(ops)
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rows, counters = prepare_review_rows(plan, sample_safe=2)
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assert counters["high_risk_operations"] == 0
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assert len(rows) == 2
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assert all(r["risk_flags"] == "spot_check" for r in rows)
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