BIPAuto/utils/discrete_material_plan/excel_converter.py

"""
Excel 报表数据转换工具组件
将 Excel 报表数据转换为数据库记录形式
"""

import pandas as pd
import openpyxl
from typing import List, Dict, Optional
import os


class ExcelConverter:
    """Excel 报表数据转换器"""

    # 字段名称映射（解决字段名冲突）
    FIELD_NAME_MAPPING = {"计划数量": "产品计划数量", "单位": "产品单位"}

    def __init__(self, verbose: bool = True):
        """
        初始化转换器

        Args:
            verbose: 是否打印详细日志
        """
        self.verbose = verbose

    def _print(self, *args, **kwargs):
        """打印日志（如果 verbose=True）"""
        if self.verbose:
            print(*args, **kwargs)

    def convert(self, input_file: str, output_file: str = None) -> pd.DataFrame:
        """
        转换 Excel 文件

        Args:
            input_file: 输入文件路径
            output_file: 输出文件路径（可选，不指定则不保存）

        Returns:
            转换后的 DataFrame
        """
        # 处理输出文件名
        if output_file:
            output_file = self._handle_output_file(output_file)

        # 读取工作表
        wb = openpyxl.load_workbook(input_file)
        ws = wb.active

        # 解析订单数据
        orders = self._parse_sheet(ws)

        # 转换为 DataFrame
        df = self._convert_to_dataframe(orders)

        if not df.empty:
            # 保存文件
            if output_file:
                df.to_excel(output_file, index=False)

        # 打印汇总报告
        self._print("=" * 60)
        self._print("转换完成")
        self._print("=" * 60)
        self._print(f"订单数: {len(orders)}")
        self._print(f"数据行数: {len(df)}")
        self._print(f"输出文件: {output_file if output_file else 'N/A'}")
        self._print("=" * 60)

        return df

    def _handle_output_file(self, output_file: str) -> str:
        """
        处理输出文件，如果文件存在则尝试删除

        Args:
            output_file: 输出文件路径

        Returns:
            实际使用的输出文件路径
        """
        if os.path.exists(output_file):
            try:
                os.remove(output_file)
            except PermissionError:
                self._print(f"警告: 无法删除 {output_file}，可能文件被其他程序打开")
                # 修改文件名
                base, ext = os.path.splitext(output_file)
                output_file = f"{base}_new{ext}"
        return output_file

    def _parse_sheet(self, ws) -> List[Dict]:
        """
        解析一个工作表，返回所有订单的数据

        每个订单包含:
        - order_info: 订单头信息（包括页脚）
        - materials: 物料数据列表

        Args:
            ws: openpyxl 工作表对象

        Returns:
            订单列表
        """
        orders = []
        all_rows = list(ws.iter_rows(values_only=True))

        # 逐行扫描，按订单结构解析
        i = 0
        while i < len(all_rows):
            row = all_rows[i]

            # 检查是否是订单标题行
            if row and "离散备料计划" in str(row[0]):
                # 解析订单头信息（接下来的4行）
                order_info = {}
                for j in range(1, 5):
                    if i + j < len(all_rows) and all_rows[i + j]:
                        self._parse_header_row(all_rows[i + j], order_info)

                # 跳过空行，找到表格标题行
                table_row = i + 5
                while table_row < len(all_rows) and (
                    not all_rows[table_row] or not all_rows[table_row][0]
                ):
                    table_row += 1

                # 检查是否是表格标题行
                if (
                    table_row < len(all_rows)
                    and all_rows[table_row]
                    and all_rows[table_row][0] == "序号"
                ):
                    # 检查表头下一行是否为空，判断是否存在数据
                    next_row = table_row + 1
                    is_empty_row = (
                        next_row < len(all_rows)
                        and all_rows[next_row]
                        and all(
                            cell is None or str(cell).strip() == ""
                            for cell in all_rows[next_row]
                        )
                    )

                    if is_empty_row:
                        # 没有数据，查找页脚信息
                        materials = []
                        footer_info = {}
                        data_row = next_row + 1
                        while data_row < len(all_rows) and all_rows[data_row]:
                            if all_rows[data_row][0] and (
                                "制单人" in str(all_rows[data_row][0])
                                or "打印人" in str(all_rows[data_row][0])
                            ):
                                self._parse_header_row(all_rows[data_row], footer_info)
                                if (
                                    data_row + 1 < len(all_rows)
                                    and all_rows[data_row + 1]
                                ):
                                    self._parse_header_row(
                                        all_rows[data_row + 1], footer_info
                                    )
                                break
                            data_row += 1

                        orders.append(
                            {
                                "order_info": {**order_info, **footer_info},
                                "materials": materials,
                            }
                        )
                    else:
                        # 有数据，开始提取物料
                        materials = []
                        footer_info = {}  # 页脚信息
                        data_row = table_row + 1
                        while data_row < len(all_rows) and all_rows[data_row]:
                            # 检查是否是页脚信息（制单人、打印人）
                            if all_rows[data_row + 1][0] and "制单人" in str(
                                all_rows[data_row + 1][0]
                            ):
                                # 解析页脚信息
                                self._parse_header_row(all_rows[data_row], footer_info)
                                # 检查下一行是否也是页脚信息
                                if (
                                    data_row + 1 < len(all_rows)
                                    and all_rows[data_row + 1]
                                ):
                                    self._parse_header_row(
                                        all_rows[data_row + 1], footer_info
                                    )
                                break

                            # 提取物料数据
                            material_row = all_rows[data_row]
                            material = {
                                "序号": material_row[0],
                                "材料编码": material_row[1],
                                "材料名称": material_row[2],
                                "规格": material_row[3],
                                "型号": material_row[4],
                                "图号": material_row[5],
                                "物料材质": material_row[6],
                                "计划数量": material_row[7],
                                "单位": material_row[8],
                                "需用日期": material_row[9],
                                "发料仓库": material_row[10],
                                "单位用量": material_row[11],
                                "累计出库数量": material_row[12],
                            }
                            materials.append(material)

                            data_row += 1

                        orders.append(
                            {
                                "order_info": {**order_info, **footer_info},
                                "materials": materials,
                            }
                        )

            i += 1

        return orders

    def _parse_header_row(self, row: tuple, info: Dict):
        """
        解析订单头信息的一行（字段名和值交错排列）

        Args:
            row: 行数据
            info: 存储解析结果的字典
        """
        i = 0
        while i < len(row):
            cell = row[i]
            if cell and str(cell).strip() and "：" in str(cell):
                # 找到字段名
                field_name = str(cell).replace("：", "").strip()

                # 应用字段名映射
                if field_name in self.FIELD_NAME_MAPPING:
                    field_name = self.FIELD_NAME_MAPPING[field_name]

                # 跳过空单元格，找到第一个非字段名的值
                j = i + 1
                while j < len(row) and (
                    not row[j] or not str(row[j]).strip() or "：" in str(row[j])
                ):
                    j += 1
                if j < len(row) and row[j] and not "：" in str(row[j]):
                    info[field_name] = str(row[j]).strip()
                # 跳过已处理的值，继续找下一个字段名
                i = j + 1
            else:
                i += 1

    def _convert_to_dataframe(self, orders: List[Dict]) -> pd.DataFrame:
        """
        将订单数据转换为扁平化的 DataFrame

        Args:
            orders: 订单列表

        Returns:
            扁平化的 DataFrame
        """
        all_records = []

        for order in orders:
            order_info = order["order_info"]
            materials = order["materials"]

            for material in materials:
                record = {**order_info, **material}
                all_records.append(record)

        return pd.DataFrame(all_records)