"""Deterministic Markdown reports with escaped untrusted text and explicit data boundaries."""

import html
from datetime import date

from app.schemas.integration_risk import IntegrationRiskRequest
from app.schemas.risk_prediction import RiskAssessmentResult
from app.services.database_risk_scoring import normalize_category, normalize_material
from app.services.purchase_orders import calendar_year_window
from app.services.reports import LEVEL_LABELS


def md_text(value: object) -> str:
    if value is None or value == "":
        return "未提供"
    value = html.escape(str(value), quote=False).replace("\r", " ").replace("\n", " ")
    for char in ("\\", "`", "*", "_", "[", "]", "|", "#", "!"):
        value = value.replace(char, "\\" + char)
    return value


def render_markdown_report(
    payload: IntegrationRiskRequest,
    result: RiskAssessmentResult,
    as_of: date,
    operator_name: str,
) -> str:
    product = payload.assessment
    start, _ = calendar_year_window(as_of, 3)
    info = (
        ("评估对象", product.product_name or product.subject_id),
        ("对象编号", product.subject_id),
        ("请求编号", payload.request_id),
        ("提交品类", product.product_category),
        ("评分品类", normalize_category(product.product_category) or "无法归类，品类维度使用默认 50 分"),
        ("规格", product.specification),
        ("包装原文", product.material_type),
        ("评分物料标签", normalize_material(product.material_type)),
        ("供应商", product.supplier),
        ("加工厂", product.factory),
        ("开发阶段", product.stage_new),
        ("已知缺陷等级", product.defect_level),
        ("评估人", operator_name),
        ("数据截止日期", as_of),
        ("评估背景", product.description),
    )
    lines = ["# 新品风险评估报告", "", "## 一、评估信息", "", "| 项目 | 内容 |", "|---|---|"]
    lines.extend(f"| {label} | {md_text(value)} |" for label, value in info)
    lines.extend(
        [
            "",
            "## 二、综合风险结论",
            "",
            f"- 综合安全得分：{result.score:.2f}（越高风险越低）",
            f"- 风险等级：{LEVEL_LABELS[result.level.value]}",
            f"- 模型版本：{md_text(result.model_version)}",
        ]
    )
    if result.alert_text:
        lines.append(f"- 数据与建议提示：{md_text(result.alert_text)}")
    lines.extend(
        [
            "",
            "## 三、七维风险评分",
            "",
            "| 风险维度 | 得分 | 权重 | 数据状态 | 说明 |",
            "|---|---:|---:|---|---|",
        ]
    )
    lines.extend(
        f"| {md_text(item.dimension)} | {item.score:.2f} | {item.weight:g}% | "
        f"{md_text(item.status)} | {md_text(item.reason)} |"
        for item in result.dimension_scores
    )
    lines.extend(["", "## 四、历史统计与相似异常案例", ""])
    if result.category_warning:
        lines.append(f"- 评分品类历史异常：{result.category_warning.anomaly_count} 条。")
    if result.supplier_freq:
        freq = result.supplier_freq
        lines.extend(
            [
                f"- 供应商：{md_text(freq.supplier_name)}；合作次数：{md_text(freq.cooperation_count)}；"
                f"历史异常：{md_text(freq.anomaly_count)}。",
                f"- 供应商统计说明：{md_text(freq.note)}",
            ]
        )
    lines.extend(["", "| 日期 | 产品 | 异常现象 | 原因 | 历史处理方案 | 相似度 |", "|---|---|---|---|---|---:|"])
    for case in result.similar_cases:
        similarity = f"{case.similarity:.1%}" if case.similarity is not None else "未提供"
        lines.append(
            "| "
            + " | ".join(
                md_text(value)
                for value in (
                    case.date,
                    case.product,
                    case.problem or case.description,
                    case.root_cause,
                    case.solution,
                    similarity,
                )
            )
            + " |"
        )
    if not result.similar_cases:
        lines.extend(["", "暂无匹配的历史案例，不能据此认定产品无风险。"])
    lines.extend(["", "## 五、标准规则", "", "| 风险点 | 判定规则 | 来源 | 状态 |", "|---|---|---|---|"])
    lines.extend(
        "| "
        + " | ".join(
            md_text(value)
            for value in (
                rule.risk_point,
                rule.rule,
                rule.source,
                rule.status,
            )
        )
        + " |"
        for rule in result.standard_judgment
    )
    if not result.standard_judgment:
        lines.extend(["", "暂无匹配标准，需由品控补充核验；不代表已通过合规或检测判定。"])
    lines.extend(["", "## 六、风险预防建议", ""])
    lines.extend(f"{index}. {md_text(value)}" for index, value in enumerate(result.ai_suggestions, 1))
    lines.extend(
        [
            "",
            "## 七、数据口径说明",
            "",
            f"- 数据来自风险平台本地异常案例、采购订单及启用的标准规则；统计区间为 {start} 至 {as_of}。",
            "- 沿用现有评分口径，以截止年份往前 3 年的 1 月 1 日为区间起点。",
            "- 包装组合沿用现有关键词归一化规则，只使用一个匹配物料标签进行评分。",
            "- 缺少巡检、检测结果或可用历史记录的维度按现有默认分处理，并在明细中标注。",
            "- 缺陷维度基于历史 A/B/C 记录计算，不预测新品实际缺陷等级。",
            "- 标准匹配和预防建议不替代实际检测与品控审核；最终放行由业务和品控人员确认。",
            "",
        ]
    )
    return "\n".join(lines)