#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
家庭收支表合并脚本
读取两张招行储蓄卡流水CSV，过滤内部转账、理财调拨等，生成家庭收支明细和月度汇总。
"""

import csv
import os
import sys
from collections import defaultdict
from datetime import datetime, timedelta

# 修复Windows控制台编码
sys.stdout.reconfigure(encoding="utf-8")

DATA_DIR = os.path.join(os.path.dirname(os.path.abspath(__file__)), "data")

FILE_1207 = os.path.join(DATA_DIR, "CMB_6214--------1207_20250726_20260726.csv")
FILE_1617 = os.path.join(DATA_DIR, "CMB_6214--------1617_20250726_20260726.csv")

OUT_DETAIL = os.path.join(DATA_DIR, "家庭收支明细.csv")
OUT_SUMMARY = os.path.join(DATA_DIR, "家庭月度汇总.csv")
OUT_LOG = os.path.join(DATA_DIR, "处理日志.txt")


def parse_cmb_csv(filepath, account):
    """解析招行CSV，返回交易列表。"""
    transactions = []
    with open(filepath, "r", encoding="utf-8") as f:
        lines = f.readlines()

    # 跳过前7行注释，从第8行(index=7)开始是表头+数据
    reader = csv.reader(lines[7:])
    header = next(reader)  # 表头行

    for fields in reader:
        # 跳过空行或字段不足的行
        if not fields or len(fields) < 7:
            continue

        date_str = fields[0].strip()
        time_str = fields[1].strip()
        income = fields[2].strip()
        expense = fields[3].strip()
        balance = fields[4].strip()
        tx_type = fields[5].strip()
        remark = fields[6].strip()

        # 跳过空行（只有空白tab）
        if not date_str:
            continue

        # 解析金额
        amount = 0.0
        direction = ""
        if income and float(income) > 0:
            amount = float(income)
            direction = "收入"
        elif expense and float(expense) > 0:
            amount = float(expense)
            direction = "支出"
        else:
            continue

        # 解析日期
        try:
            tx_date = datetime.strptime(date_str, "%Y%m%d")
        except ValueError:
            continue

        tx = {
            "date": date_str,
            "date_obj": tx_date,
            "time": time_str,
            "account": account,
            "direction": direction,
            "amount": amount,
            "balance": balance,
            "tx_type": tx_type,
            "remark": remark,
            "category": "",
            "excluded": False,
            "exclude_reason": "",
        }
        transactions.append(tx)

    return transactions


def classify_transaction(tx):
    """
    对单笔交易进行分类，返回 (category, excluded, exclude_reason)。
    分类按优先级匹配。
    """
    tx_type = tx["tx_type"]
    remark = tx["remark"]
    account = tx["account"]
    direction = tx["direction"]

    # === 1. 理财投资类（排除） ===
    investment_keywords = ["理财申购", "理财赎回", "理财还本", "朝朝宝", "朝朝盈", "快速赎回", "银证转账", "银转证", "证转银", "基金赎回", "基金申购", "基金还本", "个人养老金缴存"]
    for kw in investment_keywords:
        if kw in tx_type:
            return "理财投资", True, f"理财调拨({tx_type})"

    # 银联代付-上海天天基金 = 基金赎回款，排除
    if tx_type == "银联代付" and "天天基金" in remark:
        return "理财投资", True, f"基金赎回款({remark})"

    # 朝朝宝赎回在1617卡非常多，也需要排除
    if "赎回" in tx_type and ("朝朝" in tx_type or "理财" in tx_type):
        return "理财投资", True, f"理财调拨({tx_type})"

    # === 2. 夫妻间内部转账（排除） ===
    # 1207 → 1617 的各种转账
    if account == "丈夫-1207":
        if "张青" in remark:
            return "内部转账", True, f"夫妻间转账({tx_type}: {remark})"
        # 1207卡的微信转账（全部是给媳妇儿的）
        if "微信转账" in remark and direction == "支出":
            return "内部转账", True, f"夫妻间微信转账({remark})"
        # 1207卡的微信转账退款
        if "微信转账" in remark and direction == "收入" and tx_type == "网联退款":
            return "内部转账", True, f"夫妻间微信转账退款({remark})"

    # 1617卡：刘鑫(妻子)微信零钱提现回卡，属内部转账
    if account == "妻子-1617" and direction == "收入" and "刘鑫" in remark:
        return "内部转账", True, f"微信零钱提现({remark})"

    # === 3. 信用卡还款（保留，但单独分类） ===
    if "信用卡还款" in remark or "信用卡自动还款" in tx_type or "信用卡自扣" in tx_type:
        return "信用卡还款", False, ""

    # === 4. 退款（待配对） ===
    # 携程部分退款——用户确认排除
    if "退款" in tx_type and "携程" in remark:
        return "退款", True, f"携程部分退款排除({remark})"
    if "退款" in tx_type:
        return "退款", False, ""  # 暂时保留，后续配对处理

    # === 5. 对外转账（1617卡微信转出，保留） ===
    if account == "妻子-1617" and "微信转账" in remark and direction == "支出":
        return "对外转账", False, ""

    # === 6. 收入分类 ===
    if direction == "收入":
        # 汇入汇款-芒果光线：用户确认为之前支付宝消费退款，排除
        if "汇入汇款" in tx_type and "芒果光线" in remark:
            return "退款", True, f"支付宝退款-原消费退回({remark})"
        # 银联代付（非理财类）单独分类
        if tx_type == "银联代付":
            return "银联代付收入", False, ""
        # 股权结汇收益单独分类
        if "结汇" in tx_type or "结汇" in remark or "股权" in remark:
            return "股权结汇收益", False, ""
        if tx_type == "工资" or "代发工资" in tx_type or "薪金" in remark or "EBPR" in remark or "工资" in remark or "代发" in remark:
            return "工资收入", False, ""
        if "保险" in remark or "理赔" in remark or "平安" in remark:
            return "保险理赔", False, ""
        if "公积金" in tx_type or "公积金" in remark:
            return "公积金提取", False, ""
        return "其他收入", False, ""

    # === 7. 孩子零花钱 ===
    if "支付宝-特约商户" in remark and tx["amount"] == 1.00:
        return "孩子零花钱", False, ""

    # === 8. 微信红包 ===
    if "微信红包" in remark:
        return "微信红包", False, ""

    # === 9. 默认：日常消费 ===
    return "日常消费", False, ""


def match_refunds(transactions):
    """
    退款配对：对于退款收入，在同账户或跨账户的消费中查找同金额、相近日期(±3天)、同商户的交易。
    配对成功则双双排除。
    返回排除的交易集合。
    """
    refunds = [tx for tx in transactions if tx["category"] == "退款" and not tx["excluded"]]
    consumptions = [tx for tx in transactions if tx["direction"] == "支出" and not tx["excluded"]]

    # 按金额建立消费索引
    amount_index = defaultdict(list)
    for i, tx in enumerate(consumptions):
        amount_index[round(tx["amount"], 2)].append(i)

    paired_consumption_ids = set()
    paired_refund_ids = set()

    for refund in refunds:
        r_amount = round(refund["amount"], 2)
        r_date = refund["date_obj"]
        # 从备注中提取商户名
        r_merchant = refund["remark"]

        candidates = amount_index.get(r_amount, [])
        found = False
        for ci in candidates:
            tx = consumptions[ci]
            if id(tx) in paired_consumption_ids:
                continue
            # 日期在±3天内
            if abs((tx["date_obj"] - r_date).days) <= 3:
                # 商户名匹配（备注完全相同或包含关系）
                if tx["remark"] == r_merchant or r_merchant in tx["remark"] or tx["remark"] in r_merchant:
                    paired_consumption_ids.add(id(tx))
                    paired_refund_ids.add(id(refund))
                    tx["excluded"] = True
                    tx["exclude_reason"] = f"退款配对(退款日期{refund['date']})"
                    refund["excluded"] = True
                    refund["exclude_reason"] = f"退款配对(消费日期{tx['date']})"
                    found = True
                    break

        # 如果精确商户没匹配到，尝试同金额同日期范围（不同商户）
        if not found:
            for ci in candidates:
                tx = consumptions[ci]
                if id(tx) in paired_consumption_ids:
                    continue
                if abs((tx["date_obj"] - r_date).days) <= 1:
                    paired_consumption_ids.add(id(tx))
                    paired_refund_ids.add(id(refund))
                    tx["excluded"] = True
                    tx["exclude_reason"] = f"退款配对-近似(退款日期{refund['date']})"
                    refund["excluded"] = True
                    refund["exclude_reason"] = f"退款配对-近似(消费日期{tx['date']})"
                    break

    return len(paired_refund_ids)


def generate_detail_csv(transactions, output_path):
    """生成明细CSV。"""
    kept = [tx for tx in transactions if not tx["excluded"]]
    kept.sort(key=lambda x: (x["date_obj"], x["time"]))

    with open(output_path, "w", encoding="utf-8-sig", newline="") as f:
        writer = csv.writer(f)
        writer.writerow(["日期", "时间", "账户", "收支方向", "金额", "交易类型", "交易备注", "分类"])
        for tx in kept:
            writer.writerow([
                tx["date"],
                tx["time"],
                tx["account"],
                tx["direction"],
                f"{tx['amount']:.2f}",
                tx["tx_type"],
                tx["remark"],
                tx["category"],
            ])

    return len(kept)


def generate_summary_csv(transactions, output_path):
    """生成月度汇总CSV。"""
    kept = [tx for tx in transactions if not tx["excluded"]]

    # 按月统计
    monthly = defaultdict(lambda: {
        "income": 0.0, "expense": 0.0,
        "categories": defaultdict(lambda: {"income": 0.0, "expense": 0.0})
    })

    for tx in kept:
        month = tx["date"][:6]  # YYYYMM
        m = f"{month[:4]}-{month[4:6]}"
        if tx["direction"] == "收入":
            monthly[m]["income"] += tx["amount"]
            monthly[m]["categories"][tx["category"]]["income"] += tx["amount"]
        else:
            monthly[m]["expense"] += tx["amount"]
            monthly[m]["categories"][tx["category"]]["expense"] += tx["amount"]

    # 收集所有出现过的分类
    all_income_cats = set()
    all_expense_cats = set()
    for m_data in monthly.values():
        for cat, vals in m_data["categories"].items():
            if vals["income"] > 0:
                all_income_cats.add(cat)
            if vals["expense"] > 0:
                all_expense_cats.add(cat)

    all_income_cats = sorted(all_income_cats)
    all_expense_cats = sorted(all_expense_cats)

    with open(output_path, "w", encoding="utf-8-sig", newline="") as f:
        writer = csv.writer(f)

        # 表头
        header = ["月份", "总收入", "总支出"]
        for cat in all_income_cats:
            header.append(f"收入-{cat}")
        for cat in all_expense_cats:
            header.append(f"支出-{cat}")
        header.append("净结余")
        writer.writerow(header)

        for m in sorted(monthly.keys()):
            data = monthly[m]
            row = [m, f"{data['income']:.2f}", f"{data['expense']:.2f}"]
            for cat in all_income_cats:
                row.append(f"{data['categories'][cat]['income']:.2f}")
            for cat in all_expense_cats:
                row.append(f"{data['categories'][cat]['expense']:.2f}")
            row.append(f"{data['income'] - data['expense']:.2f}")
            writer.writerow(row)

        # 合计行
        total_income = sum(d["income"] for d in monthly.values())
        total_expense = sum(d["expense"] for d in monthly.values())
        total_row = ["合计", f"{total_income:.2f}", f"{total_expense:.2f}"]
        for cat in all_income_cats:
            total_row.append(f"{sum(d['categories'][cat]['income'] for d in monthly.values()):.2f}")
        for cat in all_expense_cats:
            total_row.append(f"{sum(d['categories'][cat]['expense'] for d in monthly.values()):.2f}")
        total_row.append(f"{total_income - total_expense:.2f}")
        writer.writerow(total_row)

    return len(monthly)


def generate_log(transactions, excluded_stats, output_path):
    """生成处理日志。"""
    lines = []
    lines.append("=" * 70)
    lines.append("家庭收支表处理日志")
    lines.append("=" * 70)
    lines.append("")

    # 概况
    total_1207 = sum(1 for tx in transactions if tx["account"] == "丈夫-1207")
    total_1617 = sum(1 for tx in transactions if tx["account"] == "妻子-1617")
    lines.append(f"原始交易总数：{len(transactions)} 笔")
    lines.append(f"  丈夫-1207卡：{total_1207} 笔")
    lines.append(f"  妻子-1617卡：{total_1617} 笔")
    lines.append("")

    # 排除统计
    excluded = [tx for tx in transactions if tx["excluded"]]
    lines.append(f"排除交易总数：{len(excluded)} 笔")
    lines.append("-" * 50)

    for cat, stats in sorted(excluded_stats.items()):
        lines.append(f"  {cat}: {stats['count']} 笔, 金额 ¥{stats['amount']:.2f}")

    lines.append("")

    # 保留统计
    kept = [tx for tx in transactions if not tx["excluded"]]
    lines.append(f"保留交易总数：{len(kept)} 笔")
    lines.append("-" * 50)

    kept_stats = defaultdict(lambda: {"count": 0, "income": 0.0, "expense": 0.0})
    for tx in kept:
        kept_stats[tx["category"]]["count"] += 1
        if tx["direction"] == "收入":
            kept_stats[tx["category"]]["income"] += tx["amount"]
        else:
            kept_stats[tx["category"]]["expense"] += tx["amount"]

    total_income = sum(s["income"] for s in kept_stats.values())
    total_expense = sum(s["expense"] for s in kept_stats.values())
    for cat, stats in sorted(kept_stats.items()):
        lines.append(f"  {cat}: {stats['count']} 笔, 收入 ¥{stats['income']:.2f}, 支出 ¥{stats['expense']:.2f}")

    lines.append("")
    lines.append(f"  家庭总收入：¥{total_income:.2f}")
    lines.append(f"  家庭总支出：¥{total_expense:.2f}")
    lines.append(f"  家庭净结余：¥{total_income - total_expense:.2f}")
    lines.append("")

    # 列出排除的明细（按类别分组）
    lines.append("=" * 70)
    lines.append("排除交易明细")
    lines.append("=" * 70)

    by_cat = defaultdict(list)
    for tx in excluded:
        by_cat[tx["category"]].append(tx)

    for cat in sorted(by_cat.keys()):
        lines.append(f"\n【{cat}】({len(by_cat[cat])} 笔)")
        for tx in sorted(by_cat[cat], key=lambda x: x["date_obj"]):
            lines.append(f"  {tx['date']} {tx['time']} | {tx['account']} | {tx['direction']} ¥{tx['amount']:.2f} | {tx['tx_type']} | {tx['remark']} | 原因: {tx['exclude_reason']}")

    # 列出保留的大额交易（>5000元），供用户核查
    lines.append("")
    lines.append("=" * 70)
    lines.append("保留的大额交易（>5000元）供核查")
    lines.append("=" * 70)

    big_txs = sorted([tx for tx in kept if tx["amount"] > 5000], key=lambda x: -x["amount"])
    for tx in big_txs:
        lines.append(f"  {tx['date']} {tx['time']} | {tx['account']} | {tx['direction']} ¥{tx['amount']:.2f} | {tx['tx_type']} | {tx['remark']} | 分类: {tx['category']}")

    with open(output_path, "w", encoding="utf-8") as f:
        f.write("\n".join(lines))


def main():
    print("=" * 60)
    print("家庭收支表合并脚本")
    print("=" * 60)

    # 1. 解析CSV
    print("\n[1] 解析CSV文件...")
    txs_1207 = parse_cmb_csv(FILE_1207, "丈夫-1207")
    txs_1617 = parse_cmb_csv(FILE_1617, "妻子-1617")
    all_txs = txs_1207 + txs_1617
    print(f"  1207卡: {len(txs_1207)} 笔")
    print(f"  1617卡: {len(txs_1617)} 笔")
    print(f"  合计: {len(all_txs)} 笔")

    # 2. 分类
    print("\n[2] 交易分类...")
    for tx in all_txs:
        cat, excluded, reason = classify_transaction(tx)
        tx["category"] = cat
        tx["excluded"] = excluded
        tx["exclude_reason"] = reason

    # 3. 退款配对
    print("\n[3] 退款配对...")
    refund_count_before = sum(1 for tx in all_txs if tx["category"] == "退款" and not tx["excluded"])
    paired = match_refunds(all_txs)
    print(f"  待配对退款: {refund_count_before} 笔")
    print(f"  成功配对: {paired} 笔")
    print(f"  未配对退款(保留为收入): {refund_count_before - paired} 笔")

    # 未配对退款重新分类
    for tx in all_txs:
        if tx["category"] == "退款" and not tx["excluded"]:
            tx["category"] = "其他收入"

    # 4. 统计排除项
    print("\n[4] 统计...")
    excluded_stats = defaultdict(lambda: {"count": 0, "amount": 0.0})
    for tx in all_txs:
        if tx["excluded"]:
            excluded_stats[tx["category"]]["count"] += 1
            excluded_stats[tx["category"]]["amount"] += tx["amount"]

    for cat, stats in sorted(excluded_stats.items()):
        print(f"  排除-{cat}: {stats['count']} 笔, ¥{stats['amount']:.2f}")

    kept_count = sum(1 for tx in all_txs if not tx["excluded"])
    print(f"  保留: {kept_count} 笔")

    # 5. 生成输出
    print("\n[5] 生成输出文件...")
    detail_count = generate_detail_csv(all_txs, OUT_DETAIL)
    print(f"  家庭收支明细.csv: {detail_count} 笔")

    summary_count = generate_summary_csv(all_txs, OUT_SUMMARY)
    print(f"  家庭月度汇总.csv: {summary_count} 个月")

    generate_log(all_txs, excluded_stats, OUT_LOG)
    print(f"  处理日志.txt")

    print("\n" + "=" * 60)
    print("完成！输出文件位于 data/ 目录下。")
    print("=" * 60)


if __name__ == "__main__":
    main()