732642856
295 lines
10 KiB
Python
295 lines
10 KiB
Python
#!/usr/bin/env python3
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"""Regression tests for reusable historical event backtest reporting."""
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from __future__ import annotations
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from scripts import historical_event_backtest as backtest
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def _payload(events: list[dict]) -> dict:
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return {
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"subject": {
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"year": 1955,
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"month": 2,
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"day": 24,
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"hour": 19,
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"minute": 15,
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"lat": 37.7749,
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"lon": -122.4194,
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"tz": 8.0,
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"node_mode": "mean",
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},
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"events": events,
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}
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def _strict_packet(
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route: str,
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*,
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verdict: str,
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dominant_label: str | None,
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score: int,
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blocked: bool = False,
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confidence_cap: str = "medium-high",
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missing_evidence: list[str] | None = None,
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official_level: str = "primary",
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source_priority_mode: str = "vedastro_official_primary",
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) -> dict:
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return {
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"routing": {"question_type": route},
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"strict_workflow": {
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"question_type": route,
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"blocked": blocked,
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"confidence_cap": confidence_cap,
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"missing_evidence": missing_evidence or [],
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"present_evidence": {
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"vedastro_official_snapshot": {
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"level": official_level,
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"source": "vedastro_official",
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"status": "partial" if official_level == "primary" else "fallback",
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},
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"source_priority": {
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"mode": source_priority_mode,
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"priority": [
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"vedastro_official_snapshot",
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"local_supplemental_modules",
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"local_engine_fallback_when_official_blocked",
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],
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},
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},
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"event_judgement": {
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"event_family": route,
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"verdict": verdict,
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"dominant_label": dominant_label,
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"score": score,
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"primary_drivers": ["vimshottari_current", "narayana_current"],
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"secondary_context": ["functional_benefic_malefic_used"],
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},
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"technique_audit": [
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{
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"technique": "VedAstro Official Full Snapshot",
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"status": "used" if official_level == "primary" else "blocked",
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"role": "primary_raw_evidence",
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}
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],
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"life_event_graph": {
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"version": "life_event_graph_v1",
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"route": route,
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"dominant_label": dominant_label,
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"verdict": verdict,
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"event_nodes": [],
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},
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},
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}
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def test_backtest_reports_strong_hit_with_official_snapshot_priority(monkeypatch) -> None:
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def fake_strict_workflow(**kwargs):
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assert kwargs["transit_date"] == "2019-12-15"
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return _strict_packet(
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"career",
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verdict="high_probability_window",
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dominant_label="career_status",
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score=84,
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)
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monkeypatch.setattr(backtest.mcp_server, "strict_workflow", fake_strict_workflow)
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report = backtest.build_report(
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_payload(
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[
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{
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"id": "career_turn_2019",
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"date": "2019-12-15",
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"domain": "career",
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"expected_label": "career_status",
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"summary": "事业逐渐好转",
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}
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]
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)
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)
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assert report["scope"] == "historical_event_backtest"
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assert report["summary"]["total_events"] == 1
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assert report["summary"]["strong_hits"] == 1
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assert report["summary"]["official_primary_events"] == 1
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event = report["events"][0]
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assert event["route"] == "career"
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assert event["result_class"] == "strong_hit"
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assert event["official_snapshot"]["level"] == "primary"
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assert event["evidence"]["source_priority_mode"] == "vedastro_official_primary"
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assert event["matched_expected_label"] is True
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def test_backtest_marks_blocked_and_unsupported_domains(monkeypatch) -> None:
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def fake_strict_workflow(**kwargs):
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return _strict_packet(
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"relationship",
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verdict="insufficient_evidence",
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dominant_label=None,
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score=28,
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blocked=True,
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confidence_cap="low",
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missing_evidence=["d9_navamsa", "upapada_lagna"],
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official_level="fallback",
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source_priority_mode="local_fallback_only",
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)
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monkeypatch.setattr(backtest.mcp_server, "strict_workflow", fake_strict_workflow)
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report = backtest.build_report(
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_payload(
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[
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{
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"id": "marriage_probe",
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"date": "2026-06-09",
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"domain": "marriage",
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"expected_label": "legal_marriage",
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},
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{
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"id": "move_1999",
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"date": "1999-08-01",
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"domain": "move",
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"summary": "搬家",
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},
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]
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)
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)
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assert report["summary"]["blocked_events"] == 1
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assert report["summary"]["unsupported_domain_events"] == 1
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blocked, unsupported = report["events"]
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assert blocked["result_class"] == "blocked"
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assert blocked["boundary"]["reason"] == "strict_workflow_blocked"
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assert unsupported["result_class"] == "unsupported_domain"
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assert unsupported["boundary"]["reason"] == "route_not_yet_implemented_for_event_backtest"
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def test_backtest_distinguishes_weak_hit_and_miss(monkeypatch) -> None:
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def fake_strict_workflow(**kwargs):
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if kwargs["transit_date"] == "2025-02-28":
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return _strict_packet(
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"finance",
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verdict="moderate_probability_window",
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dominant_label="income_growth",
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score=66,
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)
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return _strict_packet(
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"career",
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verdict="insufficient_evidence",
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dominant_label=None,
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score=22,
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confidence_cap="low",
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)
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monkeypatch.setattr(backtest.mcp_server, "strict_workflow", fake_strict_workflow)
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report = backtest.build_report(
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_payload(
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[
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{
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"id": "project_end_cashflow",
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"date": "2025-02-28",
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"domain": "wealth",
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"expected_label": "public_wealth_status",
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"summary": "项目结束但收到小额定金",
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},
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{
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"id": "career_false_start",
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"date": "2026-01-10",
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"domain": "career",
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"expected_label": "project_manifestation",
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"summary": "短期项目未成",
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},
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]
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)
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)
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assert report["summary"]["weak_hits"] == 1
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assert report["summary"]["misses"] == 1
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first, second = report["events"]
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assert first["result_class"] == "weak_hit"
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assert first["matched_expected_label"] is False
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assert first["boundary"]["reason"] == "label_mismatch_under_supported_route"
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assert second["result_class"] == "miss"
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assert second["boundary"]["reason"] == "insufficient_evidence"
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def test_backtest_carries_conflicts_and_blocked_items_from_strict_contract(monkeypatch) -> None:
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def fake_strict_workflow(**kwargs):
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packet = _strict_packet(
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"career",
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verdict="high_probability_window",
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dominant_label="career_status",
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score=84,
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)
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packet["strict_workflow"]["blocked_items"] = ["official_event_radar_partial"]
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packet["strict_workflow"]["conflicts"] = [{"type": "official_local_dasha_conflict"}]
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return packet
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monkeypatch.setattr(backtest.mcp_server, "strict_workflow", fake_strict_workflow)
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report = backtest.build_report(
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_payload(
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[
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{
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"id": "career_turn_2019",
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"date": "2019-12-15",
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"domain": "career",
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"expected_label": "career_status",
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"summary": "事业逐渐好转",
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}
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]
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)
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)
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assert report["events"][0]["evidence"]["blocked_items"] == ["official_event_radar_partial"]
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assert report["events"][0]["evidence"]["conflicts"] == [{"type": "official_local_dasha_conflict"}]
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def test_backtest_carries_top_reader_contract_summary_from_strict_contract(monkeypatch) -> None:
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def fake_strict_workflow(**kwargs):
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packet = _strict_packet(
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"career",
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verdict="high_probability_window",
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dominant_label="career_status",
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score=84,
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)
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packet["strict_workflow"]["adjudication_stages"] = {
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"promise": {"status": "present"},
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"activation": {
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"status": "present",
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"required_timing_systems": ["Vimshottari", "Narayana"],
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},
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}
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packet["strict_workflow"]["multi_reference_reading_summary"] = {
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"root_frame": {"signal": "career_promise"},
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"modifier_frame": {"functional_benefic_malefic": {"used": True}},
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}
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packet["strict_workflow"]["main_conflicts"] = [{"type": "official_local_dasha_conflict"}]
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return packet
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monkeypatch.setattr(backtest.mcp_server, "strict_workflow", fake_strict_workflow)
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report = backtest.build_report(
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_payload(
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[
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{
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"id": "career_turn_2019",
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"date": "2019-12-15",
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"domain": "career",
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"expected_label": "career_status",
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"summary": "事业逐渐好转",
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}
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]
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)
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)
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event = report["events"][0]
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assert event["evidence"]["adjudication_stages"]["activation"]["required_timing_systems"] == [
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"Vimshottari",
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"Narayana",
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]
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assert event["evidence"]["multi_reference_reading_summary"]["root_frame"]["signal"] == "career_promise"
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assert event["evidence"]["main_conflicts"] == [{"type": "official_local_dasha_conflict"}]
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