#!/usr/bin/env python3
"""
CI 可观测性看板 - 从 Gitea Actions API 拉取数据并生成 Markdown/HTML 日报
用法:
  python3 scripts/ci/ci_dashboard.py --days 7
  python3 scripts/ci/ci_dashboard.py --days 30 --output ci_report.md
  python3 scripts/ci/ci_dashboard.py --workflow ci-cd.yml --days 7
  python3 scripts/ci/ci_dashboard.py --days 7 --html --html-output dashboard.html
环境变量:
  GITEA_URL      Gitea 地址 (默认 https://git.xiaoxiajianji.com)
  GITEA_REPO     仓库 (默认 xiaoxia/xiaoxia-saas)
  GITEA_TOKEN    API Token (优先) 或 GITEA_USERNAME + GITEA_PASSWORD
"""

import argparse
import base64
import json
import math
import os
import statistics
import sys
import urllib.error
import urllib.request
from collections import defaultdict
from datetime import UTC, datetime, timedelta, timezone

# ── 配置 ──────────────────────────────────────────────
DEFAULT_GITEA_URL = "https://git.xiaoxiajianji.com"
DEFAULT_REPO = "xiaoxia/xiaoxia-saas"
DEFAULT_DAYS = 7
PAGE_LIMIT = 50  # 每页数量，最大50


# ── API 封装 ─────────────────────────────────────────
class GiteaActions:
    def __init__(self, base_url, repo, token=None, username=None, password=None):
        self.base_url = base_url.rstrip("/")
        self.repo = repo
        self.token = token
        self.username = username
        self.password = password
        self.api_base = f"{self.base_url}/api/v1/repos/{self.repo}/actions"

    def _request(self, path):
        url = f"{self.api_base}/{path}"
        req = urllib.request.Request(url)
        if self.token:
            req.add_header("Authorization", f"token {self.token}")
        elif self.username and self.password:
            auth = base64.b64encode(f"{self.username}:{self.password}".encode()).decode()
            req.add_header("Authorization", f"Basic {auth}")
        try:
            with urllib.request.urlopen(req, timeout=30) as resp:
                return json.loads(resp.read().decode())
        except urllib.error.HTTPError as e:
            print(f"[WARN] HTTP {e.code}: {url}", file=sys.stderr)
            return None
        except Exception as e:
            print(f"[WARN] 请求失败 {url}: {e}", file=sys.stderr)
            return None

    def list_runs(self, status=None, branch=None, event=None, page=1, limit=PAGE_LIMIT):
        """获取 workflow runs 列表"""
        params = []
        if status:
            params.append(f"status={status}")
        if branch:
            params.append(f"branch={branch}")
        if event:
            params.append(f"event={event}")
        params.append(f"page={page}")
        params.append(f"limit={limit}")
        path = f"runs?{'&'.join(params)}"
        data = self._request(path)
        if not data:
            return [], 0
        runs = data.get("workflow_runs", [])
        total = data.get("total_count", 0)
        return runs, total

    def get_run_jobs(self, run_id):
        """获取 run 的所有 job"""
        data = self._request(f"runs/{run_id}/jobs")
        if not data:
            return []
        return data.get("jobs", [])

    def list_workflows(self):
        """获取所有 workflow"""
        data = self._request("workflows")
        if not data:
            return []
        return data.get("workflows", [])


# ── 工具函数 ─────────────────────────────────────────
def parse_datetime(s):
    """解析 ISO 格式时间字符串"""
    if not s or s.startswith("1970") or s.startswith("0001"):
        return None
    try:
        if s.endswith("Z"):
            s = s[:-1] + "+00:00"
        return datetime.fromisoformat(s)
    except Exception:
        return None


def to_shanghai(dt):
    """转换为上海时区"""
    if dt is None:
        return None
    if dt.tzinfo is None:
        dt = dt.replace(tzinfo=UTC)
    return dt.astimezone(timezone(timedelta(hours=8)))


def duration_seconds(start_str, end_str):
    """计算耗时（秒）"""
    start = parse_datetime(start_str)
    end = parse_datetime(end_str)
    if not start or not end:
        return None
    return (end - start).total_seconds()


def fmt_duration(seconds):
    """格式化耗时显示"""
    if seconds is None:
        return "N/A"
    seconds = int(seconds)
    if seconds < 60:
        return f"{seconds}s"
    mins, secs = divmod(seconds, 60)
    if mins < 60:
        return f"{mins}m{secs:02d}s"
    hours, mins = divmod(mins, 60)
    return f"{hours}h{mins:02d}m"


def percentile(sorted_values, p):
    """计算百分位数"""
    if not sorted_values:
        return None
    k = (len(sorted_values) - 1) * (p / 100)
    f = math.floor(k)
    c = math.ceil(k)
    if f == c:
        return sorted_values[int(k)]
    return sorted_values[f] * (c - k) + sorted_values[c] * (k - f)


def classify_failure(job_name, step_name=None):
    """根据失败的 job/step 名称分类失败原因"""
    name = f"{job_name} {step_name or ''}".lower()
    if any(k in name for k in ["lint", "ruff", "flake8", "eslint", "prettier", "black", "mypy"]):
        return "代码质量 / Lint"
    if any(k in name for k in ["unit test", "pytest", "vitest", "jest"]):
        return "单元测试失败"
    if any(k in name for k in ["integration", "e2e"]):
        return "集成测试 / E2E"
    if any(k in name for k in ["build", "compile", "docker", "image"]):
        return "构建失败"
    if any(k in name for k in ["deploy", "preview", "release"]):
        return "部署失败"
    if any(k in name for k in ["setup", "checkout", "cache", "install", "deps"]):
        return "环境 / 依赖"
    if any(k in name for k in ["migrate", "migration", "schema"]):
        return "数据库迁移"
    return "其他"


# ── 数据收集 ─────────────────────────────────────────
def fetch_runs_in_range(ga, start_date, end_date, workflow_filter=None):
    """拉取指定日期范围内的所有 completed runs"""
    all_runs = []
    page = 1
    print(f"[INFO] 拉取 {start_date} ~ {end_date} 的 CI runs...", file=sys.stderr)
    while True:
        runs, total = ga.list_runs(status="completed", page=page, limit=PAGE_LIMIT)
        if not runs:
            break
        if workflow_filter:
            runs = [r for r in runs if workflow_filter in r.get("path", "")]
        in_range = []
        out_range_old = False
        for run in runs:
            started = to_shanghai(parse_datetime(run.get("started_at")))
            if not started:
                continue
            run_date = started.date()
            if start_date <= run_date <= end_date:
                in_range.append(run)
            elif run_date < start_date:
                out_range_old = True
        all_runs.extend(in_range)
        print(
            f"[INFO] 第 {page} 页: {len(runs)} 条, 范围内 {len(in_range)} 条, 累计 {len(all_runs)} 条", file=sys.stderr
        )
        if out_range_old or len(runs) < PAGE_LIMIT:
            break
        page += 1
        if page > 100:
            print("[WARN] 超过100页，停止拉取", file=sys.stderr)
            break
    print(f"[INFO] 共获取 {len(all_runs)} 条 run 数据", file=sys.stderr)
    return all_runs


def enrich_with_jobs(ga, runs, max_failures=50):
    """为 runs 补充 job 详情（失败原因分析 + runner 统计）
    失败 run 按时间倒序取最近 N 个（避免 API 调用过多），
    成功 run 采样用于 runner 分布统计。
    """
    # 失败 run 取最近 N 个
    failure_runs = [r for r in runs if r.get("conclusion") != "success"]
    failure_runs = failure_runs[:max_failures]  # 已经是时间倒序
    print(f"[INFO] 为最近 {len(failure_runs)} 个失败 run 拉取 job 详情...", file=sys.stderr)
    for i, run in enumerate(failure_runs):
        jobs = ga.get_run_jobs(run["id"])
        run["_jobs"] = jobs
        if (i + 1) % 10 == 0:
            print(f"[INFO] 已处理 {i+1}/{len(failure_runs)}", file=sys.stderr)
    # 成功 run 采样用于 runner 分布
    success_runs = [r for r in runs if r.get("conclusion") == "success"]
    sample_size = min(50, len(success_runs))
    if sample_size > 0:
        sampled = success_runs[:: max(1, len(success_runs) // sample_size)]
        print(f"[INFO] 采样 {len(sampled)} 个成功 run 用于 runner 统计...", file=sys.stderr)
        for run in sampled:
            if "_jobs" not in run:
                jobs = ga.get_run_jobs(run["id"])
                run["_jobs"] = jobs
    return runs


# ── 统计分析 ─────────────────────────────────────────
def analyze_runs(runs):
    """对 runs 做全面统计分析"""
    if not runs:
        return {}

    # 基础统计
    total = len(runs)
    success = sum(1 for r in runs if r.get("conclusion") == "success")
    failure = sum(1 for r in runs if r.get("conclusion") == "failure")
    cancelled = sum(1 for r in runs if r.get("conclusion") == "cancelled")
    other = total - success - failure - cancelled
    success_rate = (success / total * 100) if total > 0 else 0

    # 耗时统计
    durations = []
    for r in runs:
        d = duration_seconds(r.get("started_at"), r.get("completed_at"))
        if d and d > 0:
            durations.append(d)
    durations.sort()
    avg_dur = statistics.mean(durations) if durations else None
    median_dur = percentile(durations, 50)
    p95_dur = percentile(durations, 95)

    # 按日期统计
    daily_stats = defaultdict(lambda: {"total": 0, "success": 0, "failure": 0, "durations": []})
    for r in runs:
        started = to_shanghai(parse_datetime(r.get("started_at")))
        if not started:
            continue
        day = started.date().isoformat()
        daily_stats[day]["total"] += 1
        if r.get("conclusion") == "success":
            daily_stats[day]["success"] += 1
        elif r.get("conclusion") == "failure":
            daily_stats[day]["failure"] += 1
        d = duration_seconds(r.get("started_at"), r.get("completed_at"))
        if d and d > 0:
            daily_stats[day]["durations"].append(d)

    # 按 workflow 统计
    wf_stats = defaultdict(lambda: {"total": 0, "success": 0, "failure": 0, "durations": []})
    for r in runs:
        path = r.get("path", "")
        wf_name = path.split("@")[0] if "@" in path else path
        wf_stats[wf_name]["total"] += 1
        if r.get("conclusion") == "success":
            wf_stats[wf_name]["success"] += 1
        elif r.get("conclusion") == "failure":
            wf_stats[wf_name]["failure"] += 1
        d = duration_seconds(r.get("started_at"), r.get("completed_at"))
        if d and d > 0:
            wf_stats[wf_name]["durations"].append(d)

    # 按触发事件统计
    event_stats = defaultdict(lambda: {"total": 0, "success": 0, "failure": 0})
    for r in runs:
        evt = r.get("event", "unknown")
        event_stats[evt]["total"] += 1
        if r.get("conclusion") == "success":
            event_stats[evt]["success"] += 1
        elif r.get("conclusion") == "failure":
            event_stats[evt]["failure"] += 1

    # 失败原因 + runner + job 耗时（需要 _jobs 数据）
    failure_categories = defaultdict(int)
    failed_jobs_by_name = defaultdict(int)
    job_success_stats = defaultdict(lambda: {"total": 0, "success": 0, "failure": 0})
    runner_stats = defaultdict(lambda: {"jobs": 0, "success": 0, "failure": 0, "durations": []})
    job_time_stats = defaultdict(list)
    infra_failures = 0
    business_failures = 0
    other_failures_count = 0

    # 基础设施关键词（与 ci_health_check.py 保持一致的分类逻辑）
    infra_job_keywords = ["checkout", "build", "deploy", "cleanup", "setup", "cache", "install", "docker"]
    business_job_keywords = [
        "unit test",
        "pytest",
        "vitest",
        "jest",
        "lint",
        "eslint",
        "prettier",
        "integration",
        "e2e",
        "validate",
        "code quality",
        "mypy",
        "ruff",
        "flake8",
    ]

    for r in runs:
        jobs = r.get("_jobs", [])
        if not jobs:
            continue
        for job in jobs:
            runner = job.get("runner_name", "unknown")
            conclusion = job.get("conclusion", "unknown")
            job_name = job.get("name", "unknown")
            job_name_lower = job_name.lower()

            runner_stats[runner]["jobs"] += 1
            job_success_stats[job_name]["total"] += 1
            if conclusion == "success":
                runner_stats[runner]["success"] += 1
                job_success_stats[job_name]["success"] += 1
            elif conclusion == "failure":
                runner_stats[runner]["failure"] += 1
                job_success_stats[job_name]["failure"] += 1

            jd = duration_seconds(job.get("started_at"), job.get("completed_at"))
            if jd and jd > 0:
                runner_stats[runner]["durations"].append(jd)
                job_time_stats[job_name].append(jd)

            if conclusion == "failure":
                failed_jobs_by_name[job_name] += 1
                failed_step = None
                for step in job.get("steps", []):
                    if step.get("conclusion") == "failure":
                        failed_step = step.get("name")
                        break
                category = classify_failure(job_name, failed_step)
                failure_categories[category] += 1

                # 基础设施 vs 业务代码分类
                is_infra = any(k in job_name_lower for k in infra_job_keywords) and not any(
                    k in job_name_lower for k in business_job_keywords
                )
                is_business = any(k in job_name_lower for k in business_job_keywords)
                if is_infra:
                    infra_failures += 1
                elif is_business:
                    business_failures += 1
                else:
                    other_failures_count += 1

    return {
        "total": total,
        "success": success,
        "failure": failure,
        "cancelled": cancelled,
        "other": other,
        "success_rate": success_rate,
        "avg_duration": avg_dur,
        "median_duration": median_dur,
        "p95_duration": p95_dur,
        "durations": durations,
        "daily_stats": dict(sorted(daily_stats.items())),
        "workflow_stats": dict(wf_stats),
        "event_stats": dict(event_stats),
        "failure_categories": dict(failure_categories),
        "failed_jobs_top": dict(sorted(failed_jobs_by_name.items(), key=lambda x: -x[1])[:15]),
        "runner_stats": dict(runner_stats),
        "job_time_stats": dict(job_time_stats),
        "job_success_stats": dict(job_success_stats),
        "infra_failures": infra_failures,
        "business_failures": business_failures,
        "other_failures_combined": other_failures_count,
    }


# ── Markdown 报表生成 ────────────────────────────────
def generate_markdown(stats, start_date, end_date, repo):
    """生成 Markdown 格式的日报"""
    lines = []
    lines.append("# CI 运行状态看板")
    lines.append("")
    lines.append(f"> 统计周期: **{start_date} ~ {end_date}**")
    lines.append(f"> 仓库: `{repo}`")
    lines.append(f"> 生成时间: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}")
    lines.append("")

    # 概览
    lines.append("## 📊 整体概览")
    lines.append("")
    lines.append("| 指标 | 数值 |")
    lines.append("|------|------|")
    lines.append(f"| 总构建次数 | **{stats['total']}** |")
    lines.append(f"| ✅ 成功 | {stats['success']} |")
    lines.append(f"| ❌ 失败 | {stats['failure']} |")
    lines.append(f"| ⏹️ 取消 | {stats['cancelled']} |")
    lines.append(f"| 📈 成功率 | **{stats['success_rate']:.1f}%** |")
    lines.append(f"| ⏱️ 平均耗时 | {fmt_duration(stats['avg_duration'])} |")
    lines.append(f"| ⏱️ P50 耗时 | {fmt_duration(stats['median_duration'])} |")
    lines.append(f"| ⏱️ P95 耗时 | {fmt_duration(stats['p95_duration'])} |")
    lines.append("")

    # 每日趋势
    lines.append("## 📈 每日趋势")
    lines.append("")
    lines.append("| 日期 | 总次数 | 成功 | 失败 | 成功率 | 平均耗时 | P95 耗时 |")
    lines.append("|------|--------|------|------|--------|----------|----------|")
    for day, s in stats["daily_stats"].items():
        rate = (s["success"] / s["total"] * 100) if s["total"] > 0 else 0
        durations = sorted(s["durations"])
        avg = statistics.mean(durations) if durations else None
        p95 = percentile(durations, 95) if durations else None
        lines.append(
            f"| {day} | {s['total']} | {s['success']} | {s['failure']} | {rate:.1f}% | {fmt_duration(avg)} | {fmt_duration(p95)} |"
        )
    lines.append("")

    # 成功率趋势图
    lines.append("### 成功率趋势图")
    lines.append("")
    lines.append("```")
    max_bar = 40
    days = list(stats["daily_stats"].keys())
    if len(days) > 14:
        days = days[-14:]
    for day in days:
        s = stats["daily_stats"][day]
        rate = (s["success"] / s["total"] * 100) if s["total"] > 0 else 0
        bar_len = int(rate / 100 * max_bar)
        bar = "█" * bar_len + "░" * (max_bar - bar_len)
        lines.append(f"{day} {bar} {rate:5.1f}% ({s['total']}次)")
    lines.append("```")
    lines.append("")

    # 按 Workflow 统计
    lines.append("## 🧩 各 Workflow 统计")
    lines.append("")
    wf_sorted = sorted(stats["workflow_stats"].items(), key=lambda x: -x[1]["total"])
    lines.append("| Workflow | 次数 | 成功 | 失败 | 成功率 | 平均耗时 | P95 耗时 |")
    lines.append("|----------|------|------|------|--------|----------|----------|")
    for wf, s in wf_sorted:
        rate = (s["success"] / s["total"] * 100) if s["total"] > 0 else 0
        durations = sorted(s["durations"])
        avg = statistics.mean(durations) if durations else None
        p95 = percentile(durations, 95) if durations else None
        wf_short = wf.split("/")[-1] if "/" in wf else wf
        lines.append(
            f"| `{wf_short}` | {s['total']} | {s['success']} | {s['failure']} | {rate:.1f}% | {fmt_duration(avg)} | {fmt_duration(p95)} |"
        )
    lines.append("")

    # 失败原因分析
    if stats["failure_categories"]:
        lines.append("## ❌ 失败原因分析")
        lines.append("")
        lines.append("> ⚠️ 基于最近 N 个失败 run 采样分析，用于趋势参考")
        lines.append("")
        lines.append("### 按分类统计")
        lines.append("")
        total_failures = sum(stats["failure_categories"].values())
        fc_sorted = sorted(stats["failure_categories"].items(), key=lambda x: -x[1])
        lines.append("| 分类 | 次数 | 占比 |")
        lines.append("|------|------|------|")
        for cat, cnt in fc_sorted:
            pct = (cnt / total_failures * 100) if total_failures > 0 else 0
            lines.append(f"| {cat} | {cnt} | {pct:.1f}% |")
        lines.append("")

        lines.append("### Top 失败 Job")
        lines.append("")
        lines.append("| Job 名称 | 失败次数 |")
        lines.append("|----------|----------|")
        for job, cnt in stats["failed_jobs_top"].items():
            lines.append(f"| `{job}` | {cnt} |")
        lines.append("")

    # Runner 利用率
    if stats["runner_stats"]:
        lines.append("## 🏃 Runner 利用率")
        lines.append("")
        runner_sorted = sorted(stats["runner_stats"].items(), key=lambda x: -x[1]["jobs"])
        lines.append("| Runner | Job 数 | 成功 | 失败 | 成功率 | 平均耗时 |")
        lines.append("|--------|--------|------|------|--------|----------|")
        for runner, s in runner_sorted:
            rate = (s["success"] / s["jobs"] * 100) if s["jobs"] > 0 else 0
            avg = statistics.mean(s["durations"]) if s["durations"] else None
            lines.append(
                f"| `{runner}` | {s['jobs']} | {s['success']} | {s['failure']} | {rate:.1f}% | {fmt_duration(avg)} |"
            )
        lines.append("")

    # Job 耗时排行
    if stats["job_time_stats"]:
        lines.append("## ⏱️ Job 耗时排行 (Top 20 by P95)")
        lines.append("")
        job_stats = []
        for name, durs in stats["job_time_stats"].items():
            if not durs:
                continue
            durs_sorted = sorted(durs)
            job_stats.append(
                {
                    "name": name,
                    "count": len(durs_sorted),
                    "avg": statistics.mean(durs_sorted),
                    "p50": percentile(durs_sorted, 50),
                    "p95": percentile(durs_sorted, 95),
                }
            )
        job_stats.sort(key=lambda x: -x["p95"])
        top_n = min(20, len(job_stats))
        lines.append("| Job 名称 | 次数 | 平均 | P50 | P95 |")
        lines.append("|----------|------|------|-----|-----|")
        for j in job_stats[:top_n]:
            lines.append(
                f"| `{j['name']}` | {j['count']} | {fmt_duration(j['avg'])} | {fmt_duration(j['p50'])} | {fmt_duration(j['p95'])} |"
            )
        lines.append("")

    # 触发事件分布
    lines.append("## 📋 触发事件分布")
    lines.append("")
    evt_sorted = sorted(stats["event_stats"].items(), key=lambda x: -x[1]["total"])
    lines.append("| 事件类型 | 次数 | 成功 | 失败 | 成功率 |")
    lines.append("|----------|------|------|------|--------|")
    for evt, s in evt_sorted:
        rate = (s["success"] / s["total"] * 100) if s["total"] > 0 else 0
        lines.append(f"| `{evt}` | {s['total']} | {s['success']} | {s['failure']} | {rate:.1f}% |")
    lines.append("")

    return "\n".join(lines)


# ── HTML 看板生成 ────────────────────────────────────
def generate_html(stats, start_date, end_date, repo):
    """生成 HTML 格式的可视化看板（内嵌 ECharts）"""
    # 准备图表数据

    # 1. 每日成功率趋势
    daily_dates = list(stats["daily_stats"].keys())
    daily_success_rates = []
    daily_run_counts = []
    for day in daily_dates:
        s = stats["daily_stats"][day]
        rate = (s["success"] / s["total"] * 100) if s["total"] > 0 else 0
        daily_success_rates.append(round(rate, 1))
        daily_run_counts.append(s["total"])

    # 2. 各 Workflow 耗时对比
    wf_sorted = sorted(stats["workflow_stats"].items(), key=lambda x: -x[1]["total"])
    wf_names = []
    wf_avg_durations = []
    for wf, s in wf_sorted:
        wf_short = wf.split("/")[-1] if "/" in wf else wf
        wf_names.append(wf_short)
        avg = statistics.mean(s["durations"]) if s["durations"] else 0
        wf_avg_durations.append(round(avg / 60, 1))  # 转为分钟

    # 3. 失败原因分布（饼图数据 - 基础设施 vs 业务 vs 其他）
    total_infra_biz = stats["infra_failures"] + stats["business_failures"] + stats["other_failures_combined"]
    infra_rate = (stats["infra_failures"] / total_infra_biz * 100) if total_infra_biz > 0 else 0
    failure_pie_data = [
        {"value": stats["infra_failures"], "name": "基础设施问题"},
        {"value": stats["business_failures"], "name": "业务代码问题"},
        {"value": stats["other_failures_combined"], "name": "其他"},
    ]

    # 4. 各 Job 成功率排行（横向柱状图，取成功率最低的 Top 15）
    job_stats_list = []
    for name, s in stats["job_success_stats"].items():
        if s["total"] >= 3:  # 至少有3次才统计
            rate = (s["success"] / s["total"] * 100) if s["total"] > 0 else 0
            job_stats_list.append(
                {
                    "name": name,
                    "rate": round(rate, 1),
                    "total": s["total"],
                    "success": s["success"],
                }
            )
    job_stats_list.sort(key=lambda x: x["rate"])
    job_stats_list = job_stats_list[:15]  # 取成功率最低的15个
    job_names = [j["name"] for j in job_stats_list]
    job_rates = [j["rate"] for j in job_stats_list]

    # 核心指标
    total_runs = stats["total"]
    success_rate = round(stats["success_rate"], 1)
    avg_dur_min = round(stats["avg_duration"] / 60, 1) if stats["avg_duration"] else 0
    infra_fail_rate = round(infra_rate, 1)

    now_str = datetime.now().strftime("%Y-%m-%d %H:%M:%S")

    # 序列化数据为 JSON（供 JS 使用）
    data_json = json.dumps(
        {
            "daily_dates": daily_dates,
            "daily_success_rates": daily_success_rates,
            "daily_run_counts": daily_run_counts,
            "wf_names": wf_names,
            "wf_avg_durations": wf_avg_durations,
            "failure_pie_data": failure_pie_data,
            "job_names": job_names,
            "job_rates": job_rates,
        },
        ensure_ascii=False,
    )

    # HTML 模板（注意：不使用 f-string，避免与 CSS/JS 的大括号冲突）
    html_parts = []
    html_parts.append("<!DOCTYPE html>")
    html_parts.append('<html lang="zh-CN">')
    html_parts.append("<head>")
    html_parts.append('    <meta charset="UTF-8">')
    html_parts.append('    <meta name="viewport" content="width=device-width, initial-scale=1.0">')
    html_parts.append(f"    <title>CI 健康度看板 - {repo}</title>")
    html_parts.append('    <script src="https://cdn.jsdelivr.net/npm/echarts/dist/echarts.min.js"></script>')
    html_parts.append("    <style>")
    html_parts.append("        * { margin: 0; padding: 0; box-sizing: border-box; }")
    html_parts.append("        body {")
    html_parts.append(
        '            font-family: -apple-system, BlinkMacSystemFont, "Segoe UI", "PingFang SC", "Hiragino Sans GB",'
    )
    html_parts.append('                         "Microsoft YaHei", sans-serif;')
    html_parts.append("            background: #f0f2f5;")
    html_parts.append("            color: #333;")
    html_parts.append("            padding: 20px;")
    html_parts.append("        }")
    html_parts.append("        .container { max-width: 1400px; margin: 0 auto; }")
    html_parts.append("        .header {")
    html_parts.append("            background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);")
    html_parts.append("            color: white;")
    html_parts.append("            padding: 24px 32px;")
    html_parts.append("            border-radius: 12px;")
    html_parts.append("            margin-bottom: 20px;")
    html_parts.append("        }")
    html_parts.append("        .header h1 { font-size: 24px; margin-bottom: 8px; }")
    html_parts.append("        .header .subtitle { font-size: 14px; opacity: 0.9; }")
    html_parts.append("        .header .meta { font-size: 12px; opacity: 0.8; margin-top: 8px; }")
    html_parts.append("        .metrics-row {")
    html_parts.append("            display: grid;")
    html_parts.append("            grid-template-columns: repeat(4, 1fr);")
    html_parts.append("            gap: 16px;")
    html_parts.append("            margin-bottom: 20px;")
    html_parts.append("        }")
    html_parts.append("        .metric-card {")
    html_parts.append("            background: white;")
    html_parts.append("            border-radius: 12px;")
    html_parts.append("            padding: 20px;")
    html_parts.append("            box-shadow: 0 2px 8px rgba(0,0,0,0.06);")
    html_parts.append("            transition: transform 0.2s;")
    html_parts.append("        }")
    html_parts.append(
        "        .metric-card:hover { transform: translateY(-2px); box-shadow: 0 4px 12px rgba(0,0,0,0.1); }"
    )
    html_parts.append("        .metric-card .label { font-size: 13px; color: #8c8c8c; margin-bottom: 8px; }")
    html_parts.append("        .metric-card .value { font-size: 28px; font-weight: 600; }")
    html_parts.append("        .metric-card .unit { font-size: 14px; color: #8c8c8c; margin-left: 4px; }")
    html_parts.append("        .metric-card.success .value { color: #52c41a; }")
    html_parts.append("        .metric-card.warning .value { color: #faad14; }")
    html_parts.append("        .metric-card.danger .value { color: #ff4d4f; }")
    html_parts.append("        .metric-card.info .value { color: #1890ff; }")
    html_parts.append("        .charts-grid {")
    html_parts.append("            display: grid;")
    html_parts.append("            grid-template-columns: 1fr 1fr;")
    html_parts.append("            gap: 16px;")
    html_parts.append("            margin-bottom: 20px;")
    html_parts.append("        }")
    html_parts.append("        .chart-card {")
    html_parts.append("            background: white;")
    html_parts.append("            border-radius: 12px;")
    html_parts.append("            padding: 20px;")
    html_parts.append("            box-shadow: 0 2px 8px rgba(0,0,0,0.06);")
    html_parts.append("        }")
    html_parts.append("        .chart-card.full-width { grid-column: 1 / -1; }")
    html_parts.append("        .chart-card h3 {")
    html_parts.append("            font-size: 16px;")
    html_parts.append("            margin-bottom: 12px;")
    html_parts.append("            color: #262626;")
    html_parts.append("            font-weight: 600;")
    html_parts.append("        }")
    html_parts.append("        .chart-container { width: 100%; height: 320px; }")
    html_parts.append("        .chart-container.tall { height: 400px; }")
    html_parts.append("        .footer {")
    html_parts.append("            text-align: center;")
    html_parts.append("            color: #8c8c8c;")
    html_parts.append("            font-size: 12px;")
    html_parts.append("            padding: 16px 0;")
    html_parts.append("        }")
    html_parts.append("        @media (max-width: 900px) {")
    html_parts.append("            .metrics-row { grid-template-columns: repeat(2, 1fr); }")
    html_parts.append("            .charts-grid { grid-template-columns: 1fr; }")
    html_parts.append("        }")
    html_parts.append("        @media (max-width: 600px) {")
    html_parts.append("            .metrics-row { grid-template-columns: 1fr; }")
    html_parts.append("            body { padding: 12px; }")
    html_parts.append("        }")
    html_parts.append("    </style>")
    html_parts.append("</head>")
    html_parts.append("<body>")
    html_parts.append('    <div class="container">')
    html_parts.append('        <div class="header">')
    html_parts.append("            <h1>📊 CI 健康度看板</h1>")
    html_parts.append(f'            <div class="subtitle">仓库: {repo}</div>')
    html_parts.append(f'            <div class="meta">统计周期: {start_date} ~ {end_date} | 生成时间: {now_str}</div>')
    html_parts.append("        </div>")
    html_parts.append('        <div class="metrics-row">')
    html_parts.append('            <div class="metric-card success">')
    html_parts.append('                <div class="label">总成功率</div>')
    html_parts.append(f'                <div class="value">{success_rate}<span class="unit">%</span></div>')
    html_parts.append("            </div>")
    html_parts.append('            <div class="metric-card info">')
    html_parts.append('                <div class="label">总 Run 数</div>')
    html_parts.append(f'                <div class="value">{total_runs}<span class="unit">次</span></div>')
    html_parts.append("            </div>")
    html_parts.append('            <div class="metric-card warning">')
    html_parts.append('                <div class="label">平均耗时</div>')
    html_parts.append(f'                <div class="value">{avg_dur_min}<span class="unit">分钟</span></div>')
    html_parts.append("            </div>")
    html_parts.append('            <div class="metric-card danger">')
    html_parts.append('                <div class="label">基础设施故障率</div>')
    html_parts.append(f'                <div class="value">{infra_fail_rate}<span class="unit">%</span></div>')
    html_parts.append("            </div>")
    html_parts.append("        </div>")
    html_parts.append('        <div class="charts-grid">')
    html_parts.append('            <div class="chart-card full-width">')
    html_parts.append("                <h3>📈 CI 成功率趋势</h3>")
    html_parts.append('                <div id="chart-success-rate" class="chart-container"></div>')
    html_parts.append("            </div>")
    html_parts.append("        </div>")
    html_parts.append('        <div class="charts-grid">')
    html_parts.append('            <div class="chart-card">')
    html_parts.append("                <h3>⏱️ 各 Workflow 平均耗时</h3>")
    html_parts.append('                <div id="chart-wf-duration" class="chart-container"></div>')
    html_parts.append("            </div>")
    html_parts.append('            <div class="chart-card">')
    html_parts.append("                <h3>❌ 失败原因分布</h3>")
    html_parts.append('                <div id="chart-failure-pie" class="chart-container"></div>')
    html_parts.append("            </div>")
    html_parts.append("        </div>")
    html_parts.append('        <div class="charts-grid">')
    html_parts.append('            <div class="chart-card full-width">')
    html_parts.append("                <h3>📋 各 Job 成功率排行（最低 15 名）</h3>")
    html_parts.append('                <div id="chart-job-success" class="chart-container tall"></div>')
    html_parts.append("            </div>")
    html_parts.append("        </div>")
    html_parts.append('        <div class="charts-grid">')
    html_parts.append('            <div class="chart-card full-width">')
    html_parts.append("                <h3>📊 每日 Run 数量趋势</h3>")
    html_parts.append('                <div id="chart-run-count" class="chart-container"></div>')
    html_parts.append("            </div>")
    html_parts.append("        </div>")
    html_parts.append('        <div class="footer">')
    html_parts.append("            由 ci_dashboard.py 自动生成 | ECharts 可视化")
    html_parts.append("        </div>")
    html_parts.append("    </div>")
    html_parts.append("    <script>")
    html_parts.append(f"    const DATA = {data_json};")
    html_parts.append("")
    # 图表 1: 成功率趋势
    html_parts.append("    (function() {")
    html_parts.append('        const chart = echarts.init(document.getElementById("chart-success-rate"));')
    html_parts.append("        chart.setOption({")
    html_parts.append('            tooltip: { trigger: "axis", formatter: function(params) {')
    html_parts.append('                const p = params[0]; return p.name + "<br/>成功率: <b>" + p.value + "%</b>";')
    html_parts.append("            }},")
    html_parts.append('            grid: { left: "3%", right: "4%", bottom: "3%", containLabel: true },')
    html_parts.append('            xAxis: { type: "category", boundaryGap: false, data: DATA.daily_dates,')
    html_parts.append("                axisLabel: { rotate: 30, fontSize: 11 } },")
    html_parts.append('            yAxis: { type: "value", min: 0, max: 100, axisLabel: { formatter: "{value}%" } },')
    html_parts.append(
        '            series: [{ name: "成功率", type: "line", smooth: true, data: DATA.daily_success_rates,'
    )
    html_parts.append('                itemStyle: { color: "#52c41a" },')
    html_parts.append("                areaStyle: { color: new echarts.graphic.LinearGradient(0, 0, 0, 1, [")
    html_parts.append('                    { offset: 0, color: "rgba(82, 196, 26, 0.3)" },')
    html_parts.append('                    { offset: 1, color: "rgba(82, 196, 26, 0.05)" }')
    html_parts.append("                ])},")
    html_parts.append('                markLine: { silent: true, data: [{ type: "average", name: "平均值",')
    html_parts.append('                    label: { formatter: "均值 {c}%" } }] }')
    html_parts.append("            }]")
    html_parts.append("        });")
    html_parts.append('        window.addEventListener("resize", () => chart.resize());')
    html_parts.append("    })();")
    html_parts.append("")
    # 图表 2: Workflow 耗时对比
    html_parts.append("    (function() {")
    html_parts.append('        const chart = echarts.init(document.getElementById("chart-wf-duration"));')
    html_parts.append("        chart.setOption({")
    html_parts.append('            tooltip: { trigger: "axis", formatter: function(params) {')
    html_parts.append(
        '                const p = params[0]; return p.name + "<br/>平均耗时: <b>" + p.value + " 分钟</b>";'
    )
    html_parts.append("            }},")
    html_parts.append('            grid: { left: "3%", right: "4%", bottom: "15%", containLabel: true },')
    html_parts.append('            xAxis: { type: "category", data: DATA.wf_names,')
    html_parts.append("                axisLabel: { rotate: 30, fontSize: 10, interval: 0 } },")
    html_parts.append('            yAxis: { type: "value", name: "分钟", axisLabel: { formatter: "{value} min" } },')
    html_parts.append('            series: [{ name: "平均耗时", type: "bar", data: DATA.wf_avg_durations,')
    html_parts.append("                itemStyle: { color: new echarts.graphic.LinearGradient(0, 0, 0, 1, [")
    html_parts.append('                    { offset: 0, color: "#1890ff" },')
    html_parts.append('                    { offset: 1, color: "#096dd9" }')
    html_parts.append("                ]), borderRadius: [4, 4, 0, 0] },")
    html_parts.append("                barMaxWidth: 40")
    html_parts.append("            }]")
    html_parts.append("        });")
    html_parts.append('        window.addEventListener("resize", () => chart.resize());')
    html_parts.append("    })();")
    html_parts.append("")
    # 图表 3: 失败原因饼图
    html_parts.append("    (function() {")
    html_parts.append('        const chart = echarts.init(document.getElementById("chart-failure-pie"));')
    html_parts.append("        chart.setOption({")
    html_parts.append('            tooltip: { trigger: "item", formatter: "{b}: {c} 次 ({d}%)" },')
    html_parts.append('            legend: { orient: "vertical", right: "5%", top: "center" },')
    html_parts.append(
        '            series: [{ name: "失败原因", type: "pie", radius: ["40%", "70%"], center: ["35%", "50%"],'
    )
    html_parts.append("                avoidLabelOverlap: false,")
    html_parts.append('                itemStyle: { borderRadius: 6, borderColor: "#fff", borderWidth: 2 },')
    html_parts.append('                label: { show: false, position: "center" },')
    html_parts.append('                emphasis: { label: { show: true, fontSize: 16, fontWeight: "bold" } },')
    html_parts.append("                labelLine: { show: false },")
    html_parts.append("                data: DATA.failure_pie_data,")
    html_parts.append('                color: ["#ff4d4f", "#faad14", "#8c8c8c"]')
    html_parts.append("            }]")
    html_parts.append("        });")
    html_parts.append('        window.addEventListener("resize", () => chart.resize());')
    html_parts.append("    })();")
    html_parts.append("")
    # 图表 4: Job 成功率排行（横向柱状图）
    html_parts.append("    (function() {")
    html_parts.append('        const chart = echarts.init(document.getElementById("chart-job-success"));')
    html_parts.append("        const barData = DATA.job_rates.map(function(rate, i) {")
    html_parts.append("            return { value: rate, itemStyle: {")
    html_parts.append('                color: rate >= 90 ? "#52c41a" : (rate >= 70 ? "#faad14" : "#ff4d4f")')
    html_parts.append("            }};")
    html_parts.append("        });")
    html_parts.append("        chart.setOption({")
    html_parts.append('            tooltip: { trigger: "axis", formatter: function(params) {')
    html_parts.append('                const p = params[0]; return p.name + "<br/>成功率: <b>" + p.value + "%</b>";')
    html_parts.append("            }},")
    html_parts.append('            grid: { left: "3%", right: "8%", bottom: "3%", top: "3%", containLabel: true },')
    html_parts.append('            xAxis: { type: "value", min: 0, max: 100, axisLabel: { formatter: "{value}%" } },')
    html_parts.append('            yAxis: { type: "category", data: DATA.job_names, axisLabel: { fontSize: 11 } },')
    html_parts.append('            series: [{ name: "成功率", type: "bar", data: barData, barWidth: "60%",')
    html_parts.append('                label: { show: true, position: "right", formatter: "{c}%", fontSize: 11 }')
    html_parts.append("            }]")
    html_parts.append("        });")
    html_parts.append('        window.addEventListener("resize", () => chart.resize());')
    html_parts.append("    })();")
    html_parts.append("")
    # 图表 5: 每日 Run 数量趋势（面积图）
    html_parts.append("    (function() {")
    html_parts.append('        const chart = echarts.init(document.getElementById("chart-run-count"));')
    html_parts.append("        chart.setOption({")
    html_parts.append('            tooltip: { trigger: "axis", formatter: function(params) {')
    html_parts.append(
        '                const p = params[0]; return p.name + "<br/>Run 数量: <b>" + p.value + " 次</b>";'
    )
    html_parts.append("            }},")
    html_parts.append('            grid: { left: "3%", right: "4%", bottom: "3%", containLabel: true },')
    html_parts.append('            xAxis: { type: "category", boundaryGap: false, data: DATA.daily_dates,')
    html_parts.append("                axisLabel: { rotate: 30, fontSize: 11 } },")
    html_parts.append('            yAxis: { type: "value", name: "次数" },')
    html_parts.append(
        '            series: [{ name: "Run 数量", type: "line", smooth: true, data: DATA.daily_run_counts,'
    )
    html_parts.append('                itemStyle: { color: "#722ed1" },')
    html_parts.append("                areaStyle: { color: new echarts.graphic.LinearGradient(0, 0, 0, 1, [")
    html_parts.append('                    { offset: 0, color: "rgba(114, 46, 209, 0.3)" },')
    html_parts.append('                    { offset: 1, color: "rgba(114, 46, 209, 0.05)" }')
    html_parts.append("                ])},")
    html_parts.append('                markLine: { silent: true, data: [{ type: "average", name: "平均值",')
    html_parts.append('                    label: { formatter: "均值 {c} 次" } }] }')
    html_parts.append("            }]")
    html_parts.append("        });")
    html_parts.append('        window.addEventListener("resize", () => chart.resize());')
    html_parts.append("    })();")
    html_parts.append("    </script>")
    html_parts.append("</body>")
    html_parts.append("</html>")

    return "\n".join(html_parts)


# ── 主函数 ───────────────────────────────────────────
def main():
    parser = argparse.ArgumentParser(description="CI 可观测性看板 - 生成 Gitea Actions 运行状态报表")
    parser.add_argument("--days", type=int, default=DEFAULT_DAYS, help=f"统计最近 N 天 (默认 {DEFAULT_DAYS})")
    parser.add_argument("--output", "-o", type=str, help="输出文件路径 (默认输出到 stdout)")
    parser.add_argument("--workflow", type=str, help="只统计指定 workflow (如 ci-cd.yml)")
    parser.add_argument("--gitea-url", type=str, default=os.environ.get("GITEA_URL", DEFAULT_GITEA_URL))
    parser.add_argument("--repo", type=str, default=os.environ.get("GITEA_REPO", DEFAULT_REPO))
    parser.add_argument("--token", type=str, default=os.environ.get("GITEA_TOKEN"))
    parser.add_argument("--username", type=str, default=os.environ.get("GITEA_USERNAME"))
    parser.add_argument("--password", type=str, default=os.environ.get("GITEA_PASSWORD"))
    parser.add_argument("--no-job-detail", action="store_true", help="不拉取 job 详情")
    parser.add_argument("--max-failures", type=int, default=50, help="最多分析多少个失败 run 的 job 详情 (默认 50)")

    # HTML 输出相关参数
    parser.add_argument("--html", action="store_true", help="生成 HTML 可视化看板")
    parser.add_argument("--html-output", type=str, help="HTML 输出文件路径 (默认 ci_dashboard.html)")

    args = parser.parse_args()

    ga = GiteaActions(
        base_url=args.gitea_url,
        repo=args.repo,
        token=args.token,
        username=args.username,
        password=args.password,
    )

    end_date = datetime.now().date()
    start_date = end_date - timedelta(days=args.days - 1)

    runs = fetch_runs_in_range(ga, start_date, end_date, args.workflow)
    if not runs:
        print("[ERROR] 未获取到任何数据", file=sys.stderr)
        sys.exit(1)

    if not args.no_job_detail:
        runs = enrich_with_jobs(ga, runs, max_failures=args.max_failures)

    stats = analyze_runs(runs)

    # HTML 模式
    if args.html:
        html = generate_html(stats, start_date, end_date, args.repo)
        html_output = args.html_output or args.output or "ci_dashboard.html"
        with open(html_output, "w", encoding="utf-8") as f:
            f.write(html)
        print(f"[INFO] HTML 看板已保存到 {html_output}", file=sys.stderr)
        return

    # 默认 Markdown 模式（向后兼容）
    md = generate_markdown(stats, start_date, end_date, args.repo)
    if args.output:
        with open(args.output, "w", encoding="utf-8") as f:
            f.write(md)
        print(f"[INFO] 报表已保存到 {args.output}", file=sys.stderr)
    else:
        print(md)


if __name__ == "__main__":
    main()