# -*- coding: utf-8 -*-

"""
票据理赔自动化最小化实现
功能清单
https://liubiren.feishu.cn/docx/WFjTdBpzroUjQvxxrNIcKvGnneh?from=from_copylink
"""
from datetime import datetime
from pathlib import Path
from typing import Any, Dict, List

import pandas
from jinja2 import Environment, FileSystemLoader

from common import dossier, rule_engine
from image import image_classify
from image import image_recognize

if __name__ == "__main__":
    # 初始化工作目录路径
    workplace_path = Path("directory")
    workplace_path.mkdir(parents=True, exist_ok=True)  # 若工作目录不存在则创建

    # 实例化JINJA2环境
    environment = Environment(loader=FileSystemLoader("."))
    # 添加DATE过滤器
    environment.filters["date"] = lambda date: (
        date.strftime("%Y-%m-%d") if date else "长期"
    )
    # 加载赔案档案模版
    template = environment.get_template("template.html")

    # -------------------------
    # 自定义方法
    # -------------------------

    # noinspection PyShadowingNames
    def case_adjust() -> None:
        """
        理算赔案并整合至赔案档案
        :return: 无
        """

        def receipt_adjust(row: pandas.Series) -> List[Dict[str, Any]]:
            """
            票据理算
            :param row: 票据
            :return: 理算记录
            """
            date = row["date"]
            current_type = row["就诊类型"]
            current_amount = row["合理金额"]
            remaining_claim = current_amount
            claim_details = []

            if current_amount <= 0:
                return []

            # 筛选有效保单并排序
            valid_rules = sorted(
                [
                    r
                    for r in policy_rules
                    if current_type in r["就诊类型"]
                    and r["生效日期"] <= current_date <= r["失效日期"]
                    and r["剩余额度"] > 0.0
                ],
                key=lambda x: x["剩余额度"],
                reverse=True,
            )

            # 循环分摊赔付，生成分明细列表
            for rule in valid_rules:
                if remaining_claim <= 0.0:
                    break

                pay_ratio = rule["赔付比例"]
                rule_name = rule["责任名称"]
                remaining_quota = rule["剩余额度"]

                max_payable = remaining_claim * pay_ratio
                actual_pay = min(remaining_quota, max_payable)

                if actual_pay > 0.0:
                    corresponding_actual_amount = actual_pay / pay_ratio
                    # 构建明细字典（字段与后续DataFrame列对应）
                    detail = {
                        "就诊类型": current_type,
                        "就诊合理金额": current_amount,
                        "保单责任名称": rule_name,
                        "保单赔付比例": pay_ratio,
                        "保单本次赔付金额": round(actual_pay, 2),
                        "本次对应合理金额部分": round(corresponding_actual_amount, 2),
                        "保单赔付后剩余额度": round(remaining_quota - actual_pay, 2),
                    }
                    claim_details.append(detail)

                    # 更新保单额度和剩余待赔付金额
                    rule["剩余额度"] -= actual_pay
                    remaining_claim -= corresponding_actual_amount

            return claim_details

        # 基于据拒付规则评估
        if not (result := rule_engine.evaluate(decision="拒付", inputs=dossier)):
            # TODO: 若评估结果为空值（保险分公司未配置拒付规则）则流转至人工处理
            raise

        dossier["adjustment_layer"].update(
            {
                "conclusion": result["conclusion"],  # 理赔结论
                "explanation": result["explanation"],  # 结论说明
            }
        )
        if result["conclusion"] == "拒付":
            return

        adjustments = (
            pandas.DataFrame(dossier["receipts_layer"]).assing(
                adjustments=lambda dataframe: dataframe.apply(
                    receipt_adjust, axis="columns"
                )
            )
        ).explode("adjustments", ignore_index=True)
        print(adjustments)

    # 遍历工作目录中赔案目录并创建赔案档案（模拟自动化域就待自动化任务创建理赔档案）
    for case_path in [x for x in workplace_path.iterdir() if x.is_dir()]:
        # 初始化赔案档案（保险公司将提供投保公司、保险分公司和报案时间等，TPA作业系统签收后生成赔案号）
        dossier["report_layer"].update(
            {
                "report_time": datetime(2025, 7, 25, 12, 0, 0),  # 指定报案时间
                "case_number": case_path.stem,  # 设定：赔案目录名称为赔案号
                "insurer_company": (
                    insurer_company := "中银保险有限公司苏州分公司"
                ),  # 指定保险分公司
            }
        )
        # 遍历赔案目录中影像件
        for image_index, image_path in enumerate(
            sorted(
                [
                    x
                    for x in case_path.glob(pattern="*")
                    if x.is_file() and x.suffix.lower() in [".jpg", ".jpeg", ".png"]
                ],  # 实际作业亦仅支持JPG、JPEG或PNG
                key=lambda x: x.stat().st_ctime,  # 根据影像件创建时间顺序排序
            ),
            1,
        ):
            # 分类影像件并旋正（较初审自动化无使能检查）
            image_classify(image_index, image_path)

        # 就影像件层按照影像件类型指定排序
        dossier["images_layer"].sort(
            key=lambda x: [
                "居民户口簿",
                "居民身份证(国徽面)",
                "居民身份证(头像面)",
                "居民身份证(国徽、头像面)",
                "中国港澳台地区及境外护照",
                "理赔申请书",
                "增值税发票",
                "医疗门诊收费票据",
                "医疗住院收费票据",
                "医疗费用清单",
                "银行卡",
                "其它",
            ].index(x["image_type"])
        )

        # 遍历影像件层中影像件
        for image in dossier["images_layer"]:
            # 识别影像件并整合至赔案档案
            image_recognize(
                image,
                insurer_company,
            )

        # 就票据层按照开票日期和票据号顺序排序
        dossier["receipts_layer"].sort(key=lambda x: (x["date"], x["number"]))

        print(dossier["insured_persons_layer"])
        exit()

        # 理算
        case_adjust()

        print(dossier["adjustment_layer"])

        for receipt in dossier["receipts_layer"]:
            print(receipt)

        print(dossier["report_layer"])
        print(dossier["insured_person_layer"])
        print(dossier["insured_persons_layer"])

        dossier.pop("images_layer")
        dossier.pop("receipts_layer")