#!/usr/bin/env python3
"""比对生成环境交车数据 vs 交车任务列表(已交车) 车牌差异"""

import re
from pathlib import Path

import pandas as pd
from openpyxl import load_workbook
from openpyxl.styles import Font, PatternFill

FILE_PROD = Path(
    "/Users/sylvawong/Library/Containers/com.tencent.xinWeChat/Data/Documents/"
    "xwechat_files/wxid_l80gh7d3x7u012_385c/temp/drag/生成环境-交车数据.xlsx"
)
FILE_TASK = Path(
    "/Users/sylvawong/Library/Containers/com.tencent.xinWeChat/Data/Documents/"
    "xwechat_files/wxid_l80gh7d3x7u012_385c/temp/drag/"
    "交车任务列表-导出-2026-05-26 (5).xlsx"
)
OUT = Path("/Users/sylvawong/Desktop/交车数据车牌差异报告.xlsx")
OUT_PROJ = Path("/Users/sylvawong/Desktop/CURSOR/ONE-OS/交车数据车牌差异报告.xlsx")

RED = PatternFill(start_color="FF9999", end_color="FF9999", fill_type="solid")
GREEN = PatternFill(start_color="C6EFCE", end_color="C6EFCE", fill_type="solid")
YELLOW = PatternFill(start_color="FFFF00", end_color="FFFF00", fill_type="solid")


def norm_plate(v) -> str:
    if pd.isna(v):
        return ""
    return re.sub(r"[\s\-·]", "", str(v).strip().upper())


def load_prod():
    df = pd.read_excel(FILE_PROD, sheet_name=0)
    df = df.copy()
    df["_plate_key"] = df["plate_number"].map(norm_plate)
    df = df[df["_plate_key"] != ""]
    return df


def load_task_delivered():
    df = pd.read_excel(FILE_TASK, sheet_name=0)
    df = df[df["交车许可"].astype(str).str.strip() == "已交车"].copy()
    df["_plate_key"] = df["车牌号"].map(norm_plate)
    df = df[df["_plate_key"] != ""]
    return df


def norm_str(v) -> str:
    if pd.isna(v):
        return ""
    return str(v).strip()


def norm_contract(v) -> str:
    s = norm_str(v).upper().replace(" ", "")
    return re.sub(r"[^A-Z0-9]", "", s)


def run_field_diff(both_prod, both_task):
    """匹配车牌上关键字段差异"""
    rows = []
    for key in both_prod["_plate_key"].unique():
        rp = both_prod[both_prod["_plate_key"] == key].iloc[0]
        rt = both_task[both_task["_plate_key"] == key].iloc[0]
        notes = []
        if norm_contract(rp.get("contract_code")) != norm_contract(rt.get("合同编码")):
            notes.append(
                f"合同:生成[{norm_str(rp.get('contract_code'))}]≠任务[{norm_str(rt.get('合同编码'))}]"
            )
        if norm_str(rp.get("vin")).upper() != norm_str(rt.get("车架号")).upper():
            notes.append(
                f"车架:生成[{norm_str(rp.get('vin'))}]≠任务[{norm_str(rt.get('车架号'))}]"
            )
        if norm_str(rp.get("customer_name")) != norm_str(rt.get("客户名称")):
            notes.append(
                f"客户:生成[{norm_str(rp.get('customer_name'))}]≠任务[{norm_str(rt.get('客户名称'))}]"
            )
        if notes:
            rows.append(
                {
                    "车牌号": rp.get("plate_number"),
                    "生成环境_合同": rp.get("contract_code"),
                    "交车任务_合同": rt.get("合同编码"),
                    "生成环境_车架": rp.get("vin"),
                    "交车任务_车架": rt.get("车架号"),
                    "生成环境_客户": rp.get("customer_name"),
                    "交车任务_客户": rt.get("客户名称"),
                    "生成环境_交车时间": rp.get("delivery_time"),
                    "交车任务_交车时间": rt.get("交车时间"),
                    "差异说明": "；".join(notes),
                }
            )
    return pd.DataFrame(rows)


def dedupe_by_plate(df, plate_col):
    """同一车牌多行时保留首行，并标注重复数"""
    counts = df["_plate_key"].value_counts()
    df = df.copy()
    df["_dup_count"] = df["_plate_key"].map(counts)
    first_idx = df.drop_duplicates(subset=["_plate_key"], keep="first")
    return first_idx, counts[counts > 1]


def run():
    df_prod = load_prod()
    df_task = load_task_delivered()

    prod_unique, prod_dups = dedupe_by_plate(df_prod, "plate_number")
    task_unique, task_dups = dedupe_by_plate(df_task, "车牌号")

    set_prod = set(prod_unique["_plate_key"])
    set_task = set(task_unique["_plate_key"])

    only_prod_keys = sorted(set_prod - set_task)
    only_task_keys = sorted(set_task - set_prod)
    both_keys = sorted(set_prod & set_task)

    # 明细行
    cols_prod_show = [
        "plate_number",
        "vin",
        "delivery_status_text",
        "delivery_time",
        "contract_code",
        "customer_name",
        "delivery_no",
        "delivery_task_id",
    ]
    cols_task_show = [
        "车牌号",
        "车架号",
        "交车许可",
        "交车时间",
        "合同编码",
        "客户名称",
        "任务类型",
        "车辆状态",
    ]

    def pick_cols(df, cols):
        exist = [c for c in cols if c in df.columns]
        extra = ["_plate_key", "_dup_count"] if "_dup_count" in df.columns else ["_plate_key"]
        return df[exist + [c for c in extra if c in df.columns]]

    only_prod_all = df_prod[df_prod["_plate_key"].isin(only_prod_keys)].copy()
    only_prod_all.insert(0, "差异类型", "仅生成环境有")
    only_prod_df = prod_unique[prod_unique["_plate_key"].isin(only_prod_keys)].copy()
    only_prod_df.insert(0, "差异类型", "仅生成环境有(去重)")

    only_task_df = task_unique[task_unique["_plate_key"].isin(only_task_keys)].copy()
    only_task_df.insert(0, "差异类型", "仅交车任务(已交车)有")

    # 两边都有
    both_prod = prod_unique[prod_unique["_plate_key"].isin(both_keys)].copy()
    both_task = task_unique[task_unique["_plate_key"].isin(both_keys)].copy()
    both_merged = both_prod[cols_prod_show + ["_plate_key"]].merge(
        both_task[cols_task_show + ["_plate_key"]],
        on="_plate_key",
        how="inner",
        suffixes=("_生成环境", "_交车任务"),
    )
    both_merged.insert(0, "差异类型", "两边均有")
    field_diff_df = run_field_diff(both_prod, both_task)

    summary = pd.DataFrame(
        [
            ["生成环境-交车数据 总行数", len(df_prod)],
            ["生成环境 唯一车牌数", len(set_prod)],
            ["生成环境 重复车牌数(键)", len(prod_dups)],
            ["交车任务(交车许可=已交车) 总行数", len(df_task)],
            ["交车任务 唯一车牌数", len(set_task)],
            ["交车任务 重复车牌数(键)", len(task_dups)],
            ["—", "—"],
            ["仅生成环境有(车牌)", len(only_prod_keys)],
            ["仅交车任务已交车有(车牌)", len(only_task_keys)],
            ["两边均有(车牌)", len(both_keys)],
            ["匹配车牌但字段不一致", len(field_diff_df)],
        ],
        columns=["项目", "数量"],
    )

    detail_prod = pick_cols(only_prod_all, cols_prod_show)
    detail_task = pick_cols(only_task_df, cols_task_show)

    OUT.parent.mkdir(parents=True, exist_ok=True)
    with pd.ExcelWriter(OUT, engine="openpyxl") as w:
        summary.to_excel(w, sheet_name="比对汇总", index=False)
        detail_prod.to_excel(w, sheet_name="仅生成环境有", index=False)
        detail_task.to_excel(w, sheet_name="仅交车任务已交车有", index=False)
        both_merged.to_excel(w, sheet_name="两边均有", index=False)
        field_diff_df.to_excel(w, sheet_name="匹配记录字段差异", index=False)
        if len(prod_dups):
            pd.DataFrame({"重复车牌": prod_dups.index, "行数": prod_dups.values}).to_excel(
                w, sheet_name="生成环境重复车牌", index=False
            )
        if len(task_dups):
            pd.DataFrame({"重复车牌": task_dups.index, "行数": task_dups.values}).to_excel(
                w, sheet_name="交车任务重复车牌", index=False
            )

    # 标色仅* sheet 整行红
    wb = load_workbook(OUT)
    for sheet_name in ["仅生成环境有", "仅交车任务已交车有"]:
        if sheet_name in wb.sheetnames:
            ws = wb[sheet_name]
            for row in range(2, ws.max_row + 1):
                for col in range(1, ws.max_column + 1):
                    ws.cell(row=row, column=col).fill = RED
    if "匹配记录字段差异" in wb.sheetnames and len(field_diff_df):
        ws = wb["匹配记录字段差异"]
        for row in range(2, ws.max_row + 1):
            for col in range(1, ws.max_column + 1):
                ws.cell(row=row, column=col).fill = YELLOW
    wb.save(OUT)

    import shutil

    shutil.copy(OUT, OUT_PROJ)
    print(f"已输出: {OUT}")
    print(summary.to_string(index=False))


if __name__ == "__main__":
    run()