Jesse_ChenandClaude Opus 5.5
f6fa367f2b
`cmd_double_transit_pac` placed the `D9_{N}宫` target on the D9 lagna sign
and the `D9_{lord}(宫主)` target on that planet's D1 longitude. Both now sit
on D9 signs (D9 house-N sign; the lord's navamsa sign), built in one
testable helper. Target names, D1 and Chandra Lagna layers are unchanged
(pre-fix golden, byte-identical). Evidence-card golden regenerated with the
capture script (one public chart: double-transit conclusions 9 -> 10).
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_017eEAG8HD3mm8gsKXgk8uU8
120 lines
4.8 KiB
Python
120 lines
4.8 KiB
Python
"""Capture real engine consultation responses for the evidence-card tests.
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Three public AA charts (Steve Jobs, Barack Obama, Elizabeth Taylor), the
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research reference date, raman ayanamsa, mean nodes. Each chart carries the
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family route (`workflow`) and, for evidence card v2, the annual
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(`annual_workflow`) and timing (`timing_workflow`) routes with the frontend's
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default twelve-month horizon. External VedAstro is not called (same stand-in
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as the research runner). Each response is trimmed by key only: every kept
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value is the engine's own value, unchanged.
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JYOTISH_API_CHART_CACHE_TTL_SECONDS=0 PYTHONHASHSEED=0 \
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python scripts/research/capture_consult_evidence_card_golden.py
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The chart cache (`scratch/local/api_chart_cache`, 15-minute TTL) stores
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responses with sorted keys, so a warm cache changes dict and list order (not
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values) between runs; TTL 0 keeps every request cold and the output
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byte-reproducible (BUG-1060).
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"""
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from __future__ import annotations
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import json
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import os
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import sys
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from pathlib import Path
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from typing import Any
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ROOT = Path(__file__).resolve().parents[2]
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sys.path[:0] = [str(ROOT), str(ROOT / "scripts"), str(ROOT / "scripts" / "research")]
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from consult_evidence_card_lib import ( # noqa: E402
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AYANAMSA,
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NODE_MODE,
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QUESTIONS,
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REFERENCE_DATE,
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load_public_charts,
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)
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import consult_evidence_card_run as runner # noqa: E402
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OUT = ROOT / "frontend" / "tests" / "fixtures" / "consult-evidence-card-golden.json"
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TOP_KEEP = (
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"success", "question", "routing", "consumer_context", "thematic_report",
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"birth_time_sensitivity", "reference_transparency", "candidate_range",
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"range_boundary_contexts",
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)
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RECTIFICATION_KEEP = ("effective_accuracy", "lagna_boundary", "summary", "enabled_vargas")
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CHART_KEEP = (
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"success", "birth", "ascendant", "planets", "houses", "shadbala", "dasha", "yogas",
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# Evidence card v2: native technique layers (scripts/consultation_native_layers.py).
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"consultation_native_layers",
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)
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EXTRA_ROUTES = (
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("annual_workflow", {"id": "annual", "domain": "annual", "question": "未来一年重点是什么？"}),
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("timing_workflow", {"id": "timing", "domain": "timing", "question": "接下来一年哪些时间点重要？"}),
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)
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MODULE_KEEP = (
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"varga_spectrum", "shadbala", "arudha_padas", "jaimini", "narayana_dasha",
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"ashtakavarga", "dasha_sub_periods", "kp_cusps", "gulika",
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"functional_benefic_malefic", "kakshya", "yogas", "chara_dasha", "transits",
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)
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NARAYANA_KEEP = ("lagna_sign", "current_dasha", "current_year", "current_age", "mahadasha_sequence")
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def _pick(value: dict[str, Any], keys: tuple[str, ...]) -> dict[str, Any]:
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return {key: value[key] for key in keys if key in value}
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def trim(workflow: dict[str, Any]) -> dict[str, Any]:
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out = _pick(workflow, TOP_KEEP)
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out["rectification"] = _pick(workflow.get("rectification") or {}, RECTIFICATION_KEEP)
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chart = workflow.get("chart") or {}
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kept_chart = _pick(chart, CHART_KEEP)
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modules = _pick(chart.get("modules") or {}, MODULE_KEEP)
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if isinstance(modules.get("narayana_dasha"), dict):
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modules["narayana_dasha"] = _pick(modules["narayana_dasha"], NARAYANA_KEEP)
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kept_chart["modules"] = modules
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out["chart"] = kept_chart
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return out
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def main() -> int:
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if os.environ.get("PYTHONHASHSEED") != "0":
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raise SystemExit("Set PYTHONHASHSEED=0 before starting this process (ERR-111).")
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runner._block_external_vedastro()
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question = next(item for item in QUESTIONS if item["id"] == "family")
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charts = []
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for chart in load_public_charts(ROOT):
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workflow = runner._run_workflow(runner._workflow_body(chart, question))
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entry = {
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"id": chart["id"],
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"label": chart["label"],
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"source": chart["source"],
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"case_id": chart["case_id"],
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"rodden_rating": chart["rodden_rating"],
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"workflow": trim(workflow),
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}
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for key, extra in EXTRA_ROUTES:
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entry[key] = trim(runner._run_workflow(runner._workflow_body(chart, extra)))
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charts.append(entry)
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payload = {
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"source": "scripts/research/capture_consult_evidence_card_golden.py",
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"note": "Real engine consultation_workflow responses for three public AA charts, trimmed by key only.",
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"reference_date": REFERENCE_DATE,
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"ayanamsa": AYANAMSA,
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"node_mode": NODE_MODE,
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"route": question["domain"],
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"question": question["question"],
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"extra_routes": {key: extra for key, extra in EXTRA_ROUTES},
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"external_vedastro": "not_called",
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"charts": charts,
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}
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OUT.write_text(json.dumps(payload, ensure_ascii=False, separators=(",", ":")) + "\n", encoding="utf-8")
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print(f"wrote {OUT} ({OUT.stat().st_size} bytes)")
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return 0
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if __name__ == "__main__":
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raise SystemExit(main())
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