feat(report): add dense personal report appendix

Co-Authored-By: Claude Code <noreply@anthropic.com>

tests/test_reader_appendix_language.py

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+"""Copy-only tests: these strings are vocabulary cases, not engine fixtures."""
+
+import pytest
+
+from scripts.reader_appendix_language import clean_reader_appendix_markdown
+
+
+@pytest.mark.parametrize("raw,label", [
+    ("parameter_sensitive", "参数敏感"),
+    ("pyjhora_behavior_only", "仅单一外部参照，未做多引擎核对"),
+    ("not_multiengine_parity", "仅单一外部参照，未做多引擎核对"),
+    ("unresolved_external_tuple_boundary", "外部边界未对齐"),
+    ("partial_verified", "部分核验"),
+    ("raw_appendix_only", "仅原始附录可见"),
+    ("missing_in_local", "本地暂无"),
+])
+def test_status_copy_preserves_rows(raw, label):
+    source = f"| sign_cn | degree_in_sign | nakshatra_lord |\n| 白羊座 | 12.5 | {raw} |\n"
+    result = clean_reader_appendix_markdown(source)
+    assert result == source.replace(raw, label)
+    assert result.count("\n") == source.count("\n")
+
+
+@pytest.mark.parametrize("raw", ["PyJHora", "JHora", "pyjhora"])
+def test_external_engine_names(raw):
+    assert clean_reader_appendix_markdown(raw) == "外部参照引擎"
+
+
+@pytest.mark.parametrize("raw", ["PL9", "PL9 第 83-88 页", "PL9 第 40 / 48 页", "PL9 page 99-100", "PL9.pdf", "PL9 第 43–44 页"])
+def test_external_product_pages(raw):
+    assert clean_reader_appendix_markdown(raw) == "外部参照资料"
+
+
+@pytest.mark.parametrize("raw", ["cmd_full_reading", "jyotish_engine.cmd_full_reading", "render_pl9_markdown", "build_professional_report_reference_packet"])
+def test_internal_functions(raw):
+    assert clean_reader_appendix_markdown(raw) == "本地计算"
+
+
+@pytest.mark.parametrize("raw,label", [("blocked", "暂不可用"), ("executed", "已执行"), ("available", "可用"), ("computed", "已计算")])
+def test_ambiguous_words_only_in_whole_cells(raw, label):
+    prose = f"The {raw} result is not a claim.\n| {raw} result | `{raw}` | {raw} |\n"
+    assert clean_reader_appendix_markdown(prose) == f"The {raw} result is not a claim.\n| {raw} result | `{label}` | {label} |\n"
+    assert clean_reader_appendix_markdown(raw) == raw
+
+
+def test_chart_fence_unchanged_and_copy_idempotent():
+    fence = '```jyotish-chart\n{"title":"parameter_sensitive","id":"D1"}\n```\n'
+    source = "参数敏感\n" + fence + "| parameter_sensitive |\n"
+    result = clean_reader_appendix_markdown(source)
+    assert fence in result
+    assert clean_reader_appendix_markdown(result) == result
+
+
+def test_public_boundary_only_leaves_internal_renderer_and_json_unchanged():
+    from scripts.professional_report_reference import build_professional_report_reference
+    from types import SimpleNamespace
+
+    packet = {"status": "parameter_sensitive"}
+    engine = SimpleNamespace(
+        build_professional_report_reference_packet=lambda *args: packet,
+        render_pl9_markdown=lambda value: "| parameter_sensitive | cmd_full_reading |",
+    )
+    handler = SimpleNamespace(
+        _high_rigor_birth_payload=lambda body: {"year": 2000, "hour": 0, "minute": 0, "today": "2026-01-01"},
+        _compute_full_reading_for_thematic=lambda birth: {},
+    )
+    assert build_professional_report_reference(handler, {"format": "json"}, engine=engine)["report"] is packet
+    assert build_professional_report_reference(handler, {"format": "markdown"}, engine=engine)["markdown"] == "| parameter_sensitive | cmd_full_reading |"
+    assert engine.render_pl9_markdown(packet) == "| parameter_sensitive | cmd_full_reading |"
+    assert packet == {"status": "parameter_sensitive"}

tests/test_report_density_facts.py

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+"""Golden facts use deliberately fictional input, never a user birth record."""
+import copy
+import json
+from pathlib import Path
+
+from scripts.reader_dasha_applicability import BOUNDARY, render_dasha_applicability
+from scripts.report_fact_table_contract import validate_fact_tables
+
+ROOT = Path(__file__).resolve().parents[1]
+
+
+def test_golden_applicability_never_relaxes_missing_or_inapplicable_families():
+    packet = json.loads((ROOT / "frontend/tests/fixtures/report-density-fictional-reader.json").read_text(encoding="utf8"))
+    original = copy.deepcopy(packet)
+    output = render_dasha_applicability(packet)
+    families = packet["worksheets"]["timing_and_predictive_systems"]["dasha_master_pack"]["families"]
+    assert len(families) == 15
+    assert output.count(BOUNDARY) == len(families) - 1 + 2
+    for key, value in families.items():
+        if key == "vimshottari":
+            assert "| Vimshottari |" not in output
+            continue
+        name = "Kala Chakra" if key == "kala_chakra" else key.replace("_", "-").title()
+        assert f"| {name} |" in output
+        if value.get("reason"):
+            from scripts.reader_dasha_applicability import REASON_LABELS
+            assert REASON_LABELS[value["reason"]] in output
+            assert value["reason"] not in output
+    assert all(name in output for name in ["Narayana", "Tribhagi-40", "Shattrimshatsama", "Satabdika", "Mudda", "Patyayini"])
+    assert "月宿与月相组合未满足该大运的适用条件" in output
+    assert "本地计算尚未提供可用周期" in output
+    assert packet == original
+
+
+def test_golden_narayana_periods_and_readable_known_and_unknown_reasons():
+    packet = json.loads((ROOT / "frontend/tests/fixtures/report-density-fictional-reader.json").read_text(encoding="utf8"))
+    timing = packet["worksheets"]["timing_and_predictive_systems"]
+    assert len(timing["narayana_dasha"]["mahadasha_sequence"]) == 12
+    assert len(timing["narayana_dasha"]["dense_boundaries"]) == 156
+    output = render_dasha_applicability(packet)
+    narayana = next(line for line in output.splitlines() if line.startswith("| Narayana |"))
+    assert "本次已返回周期" in narayana
+    assert "这不代表已完成多引擎验证" in narayana
+    assert "缺少可核对周期" not in narayana
+    assert "本次计算未提供帕特雅伊尼年运周期" in output
+    assert "patyayini_dasha_missing" not in output
+    timing["annual_tajika_pack"]["patyayini_dasha"]["reason"] = "unknown_internal_reason_123 arbitrary English detail"
+    unknown = render_dasha_applicability(packet)
+    assert "暂无可核对的详细说明" in unknown
+    assert "unknown_internal_reason_123" not in unknown
+    assert "arbitrary English detail" not in unknown
+
+
+def test_legacy_applicability_discloses_missing_evidence_without_guessing_families():
+    output = render_dasha_applicability({})
+    assert "缺少本次计算的结构化适用性证据" in output
+    assert BOUNDARY not in output
+
+
+def test_full_golden_shared_markdown_is_byte_identical_and_reader_copy_is_clean():
+    from types import SimpleNamespace
+    from scripts.professional_report_reference import build_professional_report_reference
+    from scripts.reader_appendix_language import clean_reader_appendix_markdown
+
+    packet = json.loads((ROOT / "frontend/tests/fixtures/report-density-fictional-reader.json").read_text(encoding="utf8"))
+    raw = packet["markdown"]
+    engine = SimpleNamespace(build_professional_report_reference_packet=lambda *args: packet, render_pl9_markdown=lambda value: raw)
+    handler = SimpleNamespace(_high_rigor_birth_payload=lambda body: {"year": 2000, "hour": 12, "minute": 0, "today": "2026-09-22"}, _compute_full_reading_for_thematic=lambda birth: {})
+    for include in (False, True):
+        result = build_professional_report_reference(handler, {"format": "markdown", "include_fact_tables": include}, engine=engine)
+        assert result["markdown"].encode("utf8") == raw.encode("utf8")
+        if include:
+            assert result["reader_dasha_applicability"] == packet["reader_dasha_applicability"]
+    clean = clean_reader_appendix_markdown(raw)
+    assert "pl9" in raw.lower()
+    assert "pl9" not in clean.lower()
+    assert len(clean.splitlines()) == len(raw.splitlines())
+    assert sum(line.startswith("|") for line in clean.splitlines()) == sum(line.startswith("|") for line in raw.splitlines())
+    for field in ("degree_in_sign", "sign_cn", "nakshatra_lord"):
+        assert clean.count(field) == raw.count(field)
+
+
+def test_optional_table_validator_fails_closed_on_bad_shape():
+    errors = []
+    validate_fact_tables([{"id": "annual"}], lambda *error: errors.append(error))
+    assert errors
+    errors.clear()
+    validate_fact_tables([], lambda *error: errors.append(error))
+    assert not errors