"""端到端冒烟：生成数据（若缺失）→ 跑 pipeline → 打印图谱规模、演化事件数、一个匹配示例。

不需要启动服务，用于快速验证全链路可用。
"""
from __future__ import annotations

import json
import sys
from pathlib import Path

ROOT = Path(__file__).resolve().parents[1]
sys.path.insert(0, str(ROOT))

from app.config import load_config, resolve  # noqa: E402
from app.graph.tkg import TemporalKG  # noqa: E402
from app.match.engine import MatchEngine  # noqa: E402
from app.match.resume import parse_resume  # noqa: E402
from app.models import ResumeProfile  # noqa: E402
from app.services.pipeline import run_pipeline  # noqa: E402
from app.extract.base import load_lexicon  # noqa: E402


def main() -> None:
    if not (ROOT / "data" / "jd_raw").exists():
        print("数据不存在，先生成数据集……")
        import subprocess
        subprocess.run([sys.executable, str(ROOT / "scripts" / "generate_dataset.py")],
                       check=True)

    print("=" * 56)
    print("步骤 1/3：端到端 pipeline（导入→清洗→抽取→图谱→演化→发现）")
    print("=" * 56)
    stats = run_pipeline(load_config())
    print(json.dumps(stats["stages"], ensure_ascii=False, indent=2))

    print("\n步骤 2/3：图谱规模与演化事件")
    kg = TemporalKG.load(resolve(load_config(), "graph_path"))
    print("图谱统计：", kg.stats())
    java_id = "job_Java开发工程师"
    java_events = kg.events_of(java_id)
    print(f"Java开发工程师 演化事件 {len(java_events)} 条，示例：")
    for ev in java_events[:4]:
        print("  -", ev.description)
    snap_2020 = kg.snapshot(java_id, "2020-06-01")
    snap_2025 = kg.snapshot(java_id, "2025-06-01")
    print("2020 时点技能：", sorted(s["skill"] for s in snap_2020["skills"])[:8])
    print("2025 时点技能：", sorted(s["skill"] for s in snap_2025["skills"])[:8])

    print("\n步骤 3/3：人岗匹配示例（resume_full.txt vs Java开发工程师）")
    text = (ROOT / "data" / "resumes" / "resume_full.txt").read_text(encoding="utf-8")
    profile = parse_resume(text)
    job = kg.jobs[java_id]
    result = MatchEngine(load_lexicon()).match(profile, job)
    print(f"脱敏后姓名: {profile.name}  手机: {profile.phone}  邮箱: {profile.email}")
    print(f"总分 {result.total_score}，维度 {result.dimension_scores}，是否匹配 {result.is_match}")
    print("缺失必备技能：", result.missing_required)
    for stage in result.learning_path:
        print(" ", stage["goal"])

    # 断言冒烟通过的关键指标
    assert kg.stats()["jobs"] >= 15, "岗位节点数量异常"
    assert kg.stats()["events"] > 0, "未产生演化事件"
    assert result.total_score >= 60, "完整简历应匹配 Java 岗位"
    print("\n冒烟测试通过 [OK]")


if __name__ == "__main__":
    main()