houhuan
e4d62df7e3
- 智能供应商识别（蓉城易购/烟草/杨碧月/通用） - 百度 OCR 表格识别集成 - 规则引擎（列映射/数据清洗/单位转换/规格推断） - 条码映射管理与云端同步（Gitea REST API） - 云端同步支持：条码映射、供应商配置、商品资料、采购模板 - 拖拽一键处理（图片→OCR→Excel→合并） - 191 个单元测试 - 移除无用的模板管理功能 - 清理 IDE 产物目录 Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
246 lines
10 KiB
Python
246 lines
10 KiB
Python
"""
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订单服务模块
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---------
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提供订单处理服务，协调Excel处理和订单合并流程。
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"""
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import os
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from typing import Dict, List, Optional, Tuple, Union, Any, Callable
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from ..config.settings import ConfigManager
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from ..core.utils.log_utils import get_logger
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from ..core.excel.processor import ExcelProcessor
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from ..core.excel.merger import PurchaseOrderMerger
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from ..core.db.product_db import ProductDatabase
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logger = get_logger(__name__)
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class OrderService:
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"""
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订单服务：协调Excel处理和订单合并流程
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"""
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def __init__(self, config: Optional[ConfigManager] = None):
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"""
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初始化订单服务
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Args:
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config: 配置管理器，如果为None则创建新的
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"""
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logger.info("初始化OrderService")
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self.config = config or ConfigManager()
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# 创建Excel处理器和采购单合并器
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self.excel_processor = ExcelProcessor(self.config)
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self.order_merger = PurchaseOrderMerger(self.config)
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logger.info("OrderService初始化完成")
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def get_latest_excel(self) -> Optional[str]:
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"""
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获取最新的Excel文件
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Returns:
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最新Excel文件路径，如果未找到则返回None
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"""
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return self.excel_processor.get_latest_excel()
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def process_excel(self, file_path: Optional[str] = None, progress_cb: Optional[Callable[[int], None]] = None) -> Optional[str]:
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"""
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处理Excel订单文件，生成标准采购单
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Args:
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file_path: Excel文件路径，如果为None则处理最新的文件
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Returns:
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输出采购单文件路径，如果处理失败则返回None
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"""
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if not file_path:
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file_path = self.excel_processor.get_latest_excel()
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if not file_path:
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logger.warning("未找到可处理的Excel文件")
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return None
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logger.info("OrderService开始处理最新Excel文件")
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else:
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logger.info(f"OrderService开始处理指定Excel文件: {file_path}")
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# 检查是否需要特殊的供应商预处理（如杨碧月）
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try:
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from .special_suppliers_service import SpecialSuppliersService
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special_service = SpecialSuppliersService(self.config)
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# 尝试识别并预处理（注意：这里不再传入 progress_cb 避免无限递归或重复进度条，
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# 或者我们在 special_service 内部逻辑中处理完后直接返回结果）
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# 为了避免循环调用，我们在 SpecialSuppliersService 内部不再调用 process_excel，
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# 而是让 process_excel 识别后自己决定是否处理预处理后的文件。
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# 我们新增一个 check_and_preprocess 方法
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preprocessed_path = self._check_special_preprocess(file_path)
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if preprocessed_path:
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logger.info(f"检测到特殊供应商，已生成预处理文件: {preprocessed_path}")
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file_path = preprocessed_path
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except Exception as e:
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logger.error(f"检查特殊预处理时出错: {e}")
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return self.excel_processor.process_specific_file(file_path, progress_cb=progress_cb)
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def _check_special_preprocess(self, file_path: str) -> Optional[str]:
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"""检查并执行特殊的预处理（支持杨碧月、烟草公司、蓉城易购）"""
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try:
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from app.core.utils.file_utils import smart_read_excel
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import pandas as pd
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import re
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# 仅读取前 50 行进行智能识别 (header=None 确保能读到第一行内容)
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df_head = smart_read_excel(file_path, nrows=50, header=None)
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df_str = df_head.astype(str)
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# 1. 识别：烟草公司 (Tobacco)
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# 特征：内容中包含“专卖证号”或特定证号“510109104938”
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is_tobacco = df_str.apply(lambda x: x.str.contains('专卖证号|510109104938')).any().any()
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if is_tobacco:
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logger.info("识别到烟草公司订单，执行专用预处理...")
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from .tobacco_service import TobaccoService
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tobacco_svc = TobaccoService(self.config)
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return tobacco_svc.preprocess_tobacco_order(file_path)
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# 2. 识别：蓉城易购 (Rongcheng Yigou)
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# 特征：内容中包含单号标识“RCDH”
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is_rongcheng = df_str.apply(lambda x: x.str.contains('RCDH')).any().any()
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if is_rongcheng:
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logger.info("识别到蓉城易购订单，执行专用预处理...")
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from .special_suppliers_service import SpecialSuppliersService
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special_svc = SpecialSuppliersService(self.config)
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return special_svc.preprocess_rongcheng_yigou(file_path)
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# 3. 识别：杨碧月 (Yang Biyue)
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# 特征：经手人列包含“杨碧月”
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handler_col = None
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for col in df_head.columns:
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# 在前50行中搜索“经手人”关键字
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if df_head[col].astype(str).str.contains('经手人').any():
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handler_col = col
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break
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if handler_col is not None:
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# 检查该列是否有“杨碧月”
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if df_head[handler_col].astype(str).str.contains('杨碧月').any():
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logger.info("识别到杨碧月订单，执行专用预处理...")
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from .special_suppliers_service import SpecialSuppliersService
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special_svc = SpecialSuppliersService(self.config)
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return special_svc.process_yang_biyue_only(file_path)
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except Exception as e:
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logger.warning(f"智能预处理识别失败: {e}")
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return None
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def get_purchase_orders(self) -> List[str]:
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"""
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获取采购单文件列表
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Returns:
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采购单文件路径列表
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"""
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return self.order_merger.get_purchase_orders()
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def merge_purchase_orders(self, file_paths: List[str], progress_cb: Optional[Callable[[int], None]] = None) -> Optional[str]:
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"""
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合并指定的采购单文件
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Args:
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file_paths: 采购单文件路径列表
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Returns:
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合并后的采购单文件路径，如果合并失败则返回None
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"""
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logger.info(f"OrderService开始合并指定采购单: {file_paths}")
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return self.merge_orders(file_paths, progress_cb)
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def merge_all_purchase_orders(self, progress_cb: Optional[Callable[[int], None]] = None) -> Optional[str]:
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"""
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合并所有可用的采购单文件
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Returns:
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合并后的采购单文件路径，如果合并失败则返回None
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"""
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logger.info("OrderService开始合并所有采购单")
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return self.merge_orders(None, progress_cb)
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def merge_orders(self, file_paths: Optional[List[str]] = None, progress_cb: Optional[Callable[[int], None]] = None) -> Optional[str]:
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"""
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合并采购单
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Args:
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file_paths: 采购单文件路径列表，如果为None则处理所有采购单
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Returns:
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合并后的采购单文件路径，如果合并失败则返回None
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"""
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if file_paths:
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logger.info(f"OrderService开始合并指定采购单: {file_paths}")
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else:
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logger.info("OrderService开始合并所有采购单")
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return self.order_merger.process(file_paths, progress_cb)
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def validate_unit_price(self, result_path: str) -> List[str]:
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"""
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校验采购单单价与商品资料进货价的差异
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Args:
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result_path: 待校验的采购单路径
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Returns:
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差异信息列表，无差异返回空列表
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"""
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try:
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import pandas as pd
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import os
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from app.core.utils.file_utils import smart_read_excel
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from app.core.handlers.column_mapper import ColumnMapper as CM
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config = ConfigManager()
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template_folder = config.get('Paths', 'template_folder', fallback='templates')
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item_data = config.get('Templates', 'item_data', fallback='商品资料.xlsx')
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item_path = os.path.join(template_folder, item_data)
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product_db_path = config.get('Paths', 'product_db', fallback='data/product_cache.db')
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# 使用 SQLite 查询商品进货价
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product_db = ProductDatabase(product_db_path, item_path)
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# 读取待校验的采购单
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df_res = smart_read_excel(result_path)
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res_barcode_col = CM.find_column(list(df_res.columns), 'barcode')
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res_price_col = CM.find_column(list(df_res.columns), 'unit_price')
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if not res_barcode_col or not res_price_col:
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logger.warning("未能在采购单中找到条码或单价列")
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return []
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# 批量查询进货价
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barcodes = df_res[res_barcode_col].astype(str).str.strip().tolist()
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item_prices = product_db.get_prices(barcodes)
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results = []
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for _, row in df_res.iterrows():
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bc = str(row[res_barcode_col]).strip()
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if bc not in item_prices:
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continue
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try:
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res_price = float(row[res_price_col])
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except (ValueError, TypeError):
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continue
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item_price = item_prices[bc]
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diff = abs(res_price - item_price)
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if diff > 1.0:
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results.append(f"条码 {bc}: 采购单价={res_price} vs 进货价={item_price} 差异={diff:.2f}")
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return results
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except Exception as e:
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logger.error(f"单价校验过程中发生错误: {e}")
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return []
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