Jesse_Chen
bab0718700
Web export now calls the same full pack as the long skill report and caches an owner-only Markdown download. Appendix failure stays unavailable and does not change the main report status. Co-authored-by: Cursor <cursoragent@cursor.com>
254 lines
9.8 KiB
Python
254 lines
9.8 KiB
Python
"""Call-surface and assembly locks for full-mode longform export."""
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from __future__ import annotations
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from types import SimpleNamespace
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from ayanamsa_utils import ACTIVE_AYANAMSA_NAME, apply_ayanamsa
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from scripts.jyotish_engine import (
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_attach_report_governance_contracts,
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_build_natal_foundation_modules,
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_compute_chart_from_args,
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_native_dasha_master_families,
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_render_finished_reading_navigation,
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cmd_kp,
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render_pl9_markdown,
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)
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from scripts.professional_report_reference import _export_args
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BEIJING = {
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"year": 1990,
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"month": 1,
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"day": 1,
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"hour": 12,
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"minute": 0,
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"second": 0,
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"lat": 39.9042,
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"lon": 116.4074,
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"tz": 8,
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"ayanamsa": "raman",
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}
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def test_export_args_default_today_target_year_and_age() -> None:
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args = _export_args({**BEIJING, "today": "2026-09-05"})
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assert args.today == "2026-09-05"
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assert args.target_year == 2026
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assert args.age == 36
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assert args.hour == 12
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assert args.minute == 0
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def test_export_args_keeps_explicit_age_and_does_not_duplicate_kwargs() -> None:
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args = _export_args({**BEIJING, "today": "2026-09-05", "target_year": 2027, "age": 40})
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assert args.target_year == 2027
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assert args.age == 40
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def test_reading_navigation_emits_required_headings() -> None:
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markdown = "\n".join(_render_finished_reading_navigation({
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"report_quality_gate": {"status": "review_required", "checks": []},
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"worksheets": {
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"timing_and_predictive_systems": {
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"annual_tajika_pack": {"status": "partial_verified"},
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"annual_tajika_series": {"years": {"2026": {}, "2027": {}, "2028": {}}},
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},
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"advanced_systems": {"kp_monthly_report": {"status": "parameter_sensitive", "months": [{}] * 36}},
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"strengths_and_scores": {"functional_benefic_malefic": {"status": "partial_verified"}},
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"divisional_and_special_charts": {"upagrahas": {"Gulika": {}}},
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},
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"birth_time_sensitivity": {"status": "not_rectified"},
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}))
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for heading in (
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"## 成品阅读导航",
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"### 先读什么",
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"### 结论等级规则",
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"### 专题判读协议",
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"### 质量验收矩阵",
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"### 对照覆盖表",
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):
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assert heading in markdown
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assert "| 三年年度展开 | present |" in markdown
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assert "| KP 三年流月支持 | present |" in markdown
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def test_markdown_without_candidate_window_says_not_rectified() -> None:
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packet = {
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"schema": "pl9_style_professional_export_v1",
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"birth_info": BEIJING,
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"worksheets": {},
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"raw_full_reading": {"modules": {}},
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"personal_report_producer": {"main_body": {"status": "partial_verified"}},
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"reader_engine_boundary_notice": {
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"primary_text_zh": "多引擎口径说明",
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"display_rule": "keep_blocked_labels",
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},
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}
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packet = _attach_report_governance_contracts(packet, SimpleNamespace(
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**BEIJING,
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birth_time_accuracy="confirmed",
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))
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markdown = render_pl9_markdown(packet)
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assert "## 成品阅读导航" in markdown
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assert "### 出生时间敏感度" in markdown
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assert "未做校时" in markdown
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assert packet["birth_time_sensitivity"]["status"] == "not_rectified"
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def test_candidate_range_keeps_minute_matrix_status() -> None:
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args = SimpleNamespace(
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**BEIJING,
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birth_time_accuracy="provisional",
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candidate_range={"start_time": "11:50", "end_time": "12:10", "representative_time": "12:00"},
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)
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packet = _attach_report_governance_contracts(
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{"worksheets": {}, "raw_full_reading": {"modules": {}}},
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args,
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)
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assert packet["birth_time_sensitivity"]["status"] == "candidate_window_only"
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assert packet["birth_time_sensitivity"]["window"]["candidate_count"] >= 2
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def _producer_packet(worksheets: dict) -> dict:
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return {
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"schema": "pl9_style_professional_export_v1",
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"birth_info": BEIJING,
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"worksheets": worksheets,
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"full_report_pack": {"sections": {}},
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"personal_report_producer": {"main_body": {"status": "partial_verified"}},
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"reader_engine_boundary_notice": {
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"primary_text_zh": "多引擎口径说明",
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"display_rule": "keep_blocked_labels",
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},
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}
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def test_native_dasha_families_mark_present_modules_executed() -> None:
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families = _native_dasha_master_families({
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"dasha": {"current_dasha": {"lord": "Saturn"}},
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"narayana_dasha": {"status": "computed"},
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"yogini_dasha": {"error": "missing"},
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"ashtottari_dasha": {},
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"kalachakra_dasha": {"status": "blocked", "reason": "not_applicable"},
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})
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assert families["vimshottari"]["execution_status"] == "executed"
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assert families["narayana"]["execution_status"] == "executed"
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assert families["yogini"]["execution_status"] == "blocked"
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assert families["ashtottari"]["execution_status"] == "blocked"
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assert families["kala_chakra"]["execution_status"] == "blocked"
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def test_timing_mainline_renders_from_native_dasha_when_master_pack_has_no_families() -> None:
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markdown = render_pl9_markdown(_producer_packet({
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"timing_and_predictive_systems": {
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"dasha": {"current_dasha": {"lord": "Saturn"}},
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"narayana_dasha": {"status": "computed"},
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"dasha_master_pack": {"schema": "dasha_master_report_pack_v1", "status": "blocked"},
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"annual_tajika_pack": {"year_lord": {"status": "partial_verified"}},
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},
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}))
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assert "### 大运与时间主线" in markdown
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assert "#### 时间系统证据状态" in markdown
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assert "| Vimshottari |" in markdown
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assert "| Narayana |" in markdown
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assert "| Year Lord |" in markdown
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def test_kp_upagraha_and_yogakaraka_headings_render_when_worksheets_present() -> None:
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markdown = render_pl9_markdown(_producer_packet({
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"divisional_and_special_charts": {
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"upagrahas": {
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"raw": {
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"Gulika": {"sign_idx": 0, "degree_in_sign": 12.5, "source": "local_formula"},
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"Maandi": {"sign_idx": 1, "degree_in_sign": 3.0, "source": "local_formula"},
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},
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},
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},
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"advanced_systems": {
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"kp": {
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"house_basis": "explicit_cusps",
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"planets": {
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"Sun": {
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"kp_lords": {
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"sign": "Capricorn",
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"nakshatra": "Uttara Ashadha",
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"nakshatra_lord": "Sun",
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"sub_lord": "Sun",
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"sub_sub_lord": "Venus",
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},
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"significators": {"A": ["10"], "B": ["10"], "C": [], "D": ["10"]},
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},
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},
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"houses": {
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10: {
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"sign": "Capricorn",
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"cusp_longitude": 280.1,
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"kp_lords": {
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"sign": "Capricorn",
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"nakshatra": "Uttara Ashadha",
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"nakshatra_lord": "Sun",
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"sub_lord": "Moon",
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"sub_sub_lord": "Mars",
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},
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"significators": {"A": ["Sun"], "B": ["Mercury"], "C": [], "D": []},
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},
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2: {"significators": {"A": ["Venus"], "B": ["Jupiter"], "C": [], "D": []}},
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6: {"significators": {"A": ["Saturn"], "B": ["Mars"], "C": [], "D": []}},
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11: {"significators": {"A": ["Moon"], "B": ["Venus"], "C": [], "D": []}},
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},
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"ruling_planets": {
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"day_lord": "Monday",
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"moon_star_lord": "Saturn",
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"ascendant_star_lord": "Sun",
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},
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},
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},
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"strengths_and_scores": {
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"functional_benefic_malefic": {
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"status": "used",
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"ascendant": "Aries",
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"functional_benefics": ["Jupiter", "Sun", "Mars"],
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"functional_malefics": ["Mercury", "Saturn"],
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"yogakarakas": ["Mars"],
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},
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"ashtakavarga": {"method": "local", "version": "test"},
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},
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}))
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assert "### Upagraha / Sub-Planets" in markdown
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assert "### KP Lord / Sub 原始表" in markdown
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assert "#### KP Ruling Planets" in markdown or "#### 行星 KP Lord / Sub" in markdown
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assert "#### KP 显著星 ABCD" in markdown
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assert "#### KP 事业宫位核对" in markdown
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assert "#### 功能性吉凶与 Yogakaraka" in markdown
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assert "Mars" in markdown or "火星" in markdown
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def test_cmd_kp_restores_report_ayanamsa() -> None:
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apply_ayanamsa("raman")
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args = SimpleNamespace(**BEIJING)
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result = cmd_kp(args)
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assert isinstance(result, dict)
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assert isinstance(result.get("planets"), dict)
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assert isinstance(result.get("ruling_planets"), dict)
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assert ACTIVE_AYANAMSA_NAME == "raman"
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def test_natal_foundation_returns_upagrahas_and_functional_layer() -> None:
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apply_ayanamsa("raman")
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args = SimpleNamespace(**BEIJING)
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chart, _asc_idx, jd, _ayanamsa = _compute_chart_from_args(args)
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planets = chart["planets"]
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planet_lons = {
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name: data.get("degree_raw", data["degree"])
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for name, data in planets.items()
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if isinstance(data, dict) and "degree" in data
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}
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asc_lon = chart["ascendant"].get("lon", chart["ascendant"].get("degree"))
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foundation = _build_natal_foundation_modules(args, planet_lons, asc_lon=asc_lon, jd=jd)
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assert foundation["upagrahas"].get("raw")
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assert foundation["functional_benefic_malefic"].get("functional_benefics") or foundation["functional_benefic_malefic"].get("status")
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assert foundation["functional_benefic_malefic"].get("yogakarakas") is not None
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assert ACTIVE_AYANAMSA_NAME == "raman"
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