Python脚本开发文件初始化

IMULinkdata/.gitignore

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+/build/*
+/build
+/dist/*
+/dist
+/source/*
+/source
+
+
+LINLinkData_V2.py

IMULinkdata/LINLinkData_V1.py

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+import os
+import pandas as pd
+from datetime import datetime
+import argparse
+
+import re
+import time
+import argparse
+from datetime import datetime
+from collections import defaultdict
+
+import numpy as np
+import pandas as pd
+import openpyxl
+
+
+class ExcelProcessor:
+    def __init__(self, file_path):
+        self.file_path = file_path
+        self.df = None
+        self.output_folder = None
+        self.output_file = None
+        self.timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
+        self.processed_data = {}  # 存储处理后的数据
+
+
+    def load_data(self):
+        """加载Excel文件数据"""
+        print(f"正在加载文件: {self.file_path}")
+        try:
+            # 尝试读取指定sheet，如果不存在则尝试读取第一个sheet
+            try:
+                # 建议使用 engine='openpyxl'，pandas 会尽可能把 Excel 的日期单元格读成 datetime
+                # self.df = pd.read_excel(self.file_path, sheet_name='LinkdataAll', engine='openpyxl')
+
+                # 获取所有工作表名称
+                sheet_names = pd.ExcelFile(self.file_path, engine='openpyxl').sheet_names
+                # 查找包含'LINK'的工作表（不区分大小写）
+                target_sheet = next((sheet for sheet in sheet_names if 'link' in sheet.lower()), None)
+                if target_sheet is None:
+                    raise ValueError(f"未找到包含'LINK'的工作表")
+
+                self.df = pd.read_excel(self.file_path, sheet_name=target_sheet, engine='openpyxl')
+            except Exception as e:
+                print("提示: 未找到包含'LINK' sheet，请检查文件内容。")
+                return False
+
+            # 确保有 PartNumber 列（兼容 LinkObject）
+            if 'PartNumber' not in self.df.columns and 'LinkObject' in self.df.columns:
+                self.df['PartNumber'] = self.df['LinkObject']
+
+            # 检查必要的列是否存在
+            required_cols = ["PartNumber", "ChildSN", "linkDate"]
+            missing = [c for c in required_cols if c not in self.df.columns]
+            if missing:
+                raise ValueError(f"数据表中缺少必要列: {', '.join(missing)}")
+
+            # 解析 linkDate 为 datetime（支持 AM/PM）
+            # 注：pd.to_datetime 能解析大多数常见格式，包括 "5/24/2025 6:00:13 PM"
+            # 如果有极端异构格式，可在这里加更精细的清洗逻辑
+            # errors='coerce' 会把无法解析的值变为 NaT
+            # self.df['linkDate'] = pd.to_datetime(self.df['linkDate'], errors='coerce')
+
+            self.df['linkDate'] = pd.to_datetime(
+                self.df['linkDate'],
+                format='%m/%d/%Y %I:%M:%S %p',  # 月/日/年 12小时制+AM/PM
+                errors='coerce'
+            )
+
+            # 提示解析情况
+            total = len(self.df)
+            invalid = int(self.df['linkDate'].isna().sum())
+            print(f"文件加载成功，总行数: {total}，日期解析失败: {invalid} 行")
+
+            # 添加备注列
+            if '备注' not in self.df.columns:
+                self.df['备注'] = ''
+
+            return True
+        except Exception as e:
+            print(f"加载文件失败: {str(e)}")
+            return False
+
+    def create_output_folder(self):
+        """准备输出目录和文件名"""
+
+        # 先去除扩展名，再截取前10个字符
+        # base_name = os.path.splitext(os.path.basename(self.file_path))[0]
+        original_name = os.path.splitext(os.path.basename(self.file_path))[0]
+
+        # base_name = original_name[:10]
+        base_name = original_name[:20]
+
+        output_folder_name = f"{base_name} output_{self.timestamp}"
+
+        # self.output_folder = os.path.join(os.path.dirname(self.file_path), output_folder_name)
+        self.output_folder = os.path.dirname(self.file_path)
+
+        self.output_file = os.path.join(self.output_folder, f"{original_name}_split_by_PartNumber_{self.timestamp}.xlsx")
+
+        if not os.path.exists(self.output_folder):
+            os.makedirs(self.output_folder)
+            print(f"已创建输出文件夹: {self.output_folder}")
+
+
+    def _safe_sheet_name(self, name):
+        """清理为合法的 Excel sheet 名称（<=31字符，无非法字符）"""
+        # 转为字符串
+        s = str(name)
+        # 替换非法字符：: \ / ? * [ ]
+        s = re.sub(r'[:\\/\?\*\[\]]', '_', s)
+        # 去除首尾空格
+        s = s.strip()
+        # 截断到 31 个字符
+        if len(s) > 31:
+            s = s[:31]
+        # 空名兜底
+        if not s:
+            s = 'Sheet'
+        return s
+
+    def process_data(self):
+        """处理数据并拆分到不同sheet"""
+        if self.df is None:
+            raise ValueError("数据未加载，请先调用 load_data() 方法")
+
+        # 确保有PartNumber列
+        if 'PartNumber' not in self.df.columns:
+            if 'LinkObject' in self.df.columns:
+                self.df['PartNumber'] = self.df['LinkObject']
+            else:
+                raise ValueError("数据表中既没有PartNumber也没有LinkObject列")
+
+        # 添加备注列
+        self.df['备注'] = ''
+
+        # 按 PartNumber 分组
+        grouped = self.df.groupby('PartNumber', dropna=False)
+        total_groups = len(grouped)
+        print(f"开始处理数据，共 {total_groups} 个分组...")
+
+        # 使用上下文管理器，自动保存关闭
+        # print(f"输出文件信息，self.output_folder：{self.output_folder}")
+        print(f"输出文件信息，self.output_file：{self.output_file}")
+        # output_path = os.path.join(self.output_folder, self.output_file)
+        output_path =  self.output_file
+
+        writer = pd.ExcelWriter(output_path, engine='openpyxl')
+
+        for i, (name, group) in enumerate(grouped):
+            print(f"正在处理分组 {i + 1}/{total_groups}: {name}")
+
+            # 处理重复 ChildSN（根据最新 linkDate 保留一条）
+            group_processed = self.process_duplicates(group)
+
+            # 输出前，把 linkDate 格式化为 yyyy-mm-dd hh:mm:ss 的字符串
+            group_out = group_processed.copy()
+            group_out['linkDate'] = group_out['linkDate'].apply(
+            	lambda x: x.strftime('%Y-%m-%d %H:%M:%S') if pd.notnull(x) else ''
+            	)
+
+            # 写入sheet
+            safe_name = self._safe_sheet_name(name)
+            group_out.to_excel(writer, sheet_name=safe_name, index=False)
+
+        # 保存文件
+        writer.close()
+        print(f"处理完成! 结果已保存到: {output_path}")
+
+    def process_duplicates(self, group):
+        """处理重复的 ChildSN，优化备注信息：保留最新 linkDate 的一行"""
+        # 找出重复 ChildSN
+        duplicates = group[group.duplicated('ChildSN', keep=False)]
+
+        if not duplicates.empty:
+            print(f"  发现 {len(duplicates)} 行重复数据，正在处理...")
+
+            # 遍历每个重复 ChildSN 的分组
+            for child_sn, dup_group in duplicates.groupby('ChildSN'):
+                # 按 linkDate 排序，保留最新（降序）
+                # 若 linkDate 有 NaT，会排在末尾
+                dup_group = dup_group.sort_values('linkDate', ascending=False)
+
+                # 获取最新行
+                latest_row = dup_group.iloc[0]
+
+                # 差异字段收集（除 ChildSN、备注）
+                diff_info = {}
+                for col in dup_group.columns:
+                    if col in ['ChildSN', '备注']:
+                        continue
+                    unique_values = dup_group[col].unique()
+                    if len(unique_values) > 1:
+                        # 对 linkDate 做专门格式化，其他列保持原样转字符串
+                        if col == 'linkDate':
+                            vals = []
+                            for v in unique_values:
+                                if pd.isna(v):
+                                    vals.append('')
+                                elif isinstance(v, pd.Timestamp):
+                                    vals.append(v.strftime('%Y-%m-%d %H:%M:%S'))
+                                else:
+                                    vals.append(str(v))
+                            diff_info[col] = f"{col}: {', '.join(vals)}"
+                        else:
+                            diff_info[col] = f"{col}: {', '.join(map(str, unique_values))}"
+
+                # 生成备注信息
+                note = f"重复行数: {len(dup_group)}"
+                if diff_info:
+                    note += "; 差异内容: " + "; ".join(diff_info.values())
+
+                # 更新最新行的备注（给该 ChildSN 的所有行先写备注，再删除）
+                group.loc[group['ChildSN'] == child_sn, '备注'] = note
+
+                # 删除除最新以外的行
+                drop_indices = dup_group.index[1:]
+                group = group.drop(drop_indices)
+
+        return group
+
+
+def main():
+    print("=== Excel拆分工具 ===")
+    file_path = input("请输入Excel文件路径: ").strip('"')
+    if not os.path.exists(file_path):
+        print("文件不存在，请检查路径")
+        return
+
+    start_time = time.time()
+
+    try:
+        # 创建处理器实例
+        processor = ExcelProcessor(file_path)
+
+        # 执行处理流程
+        if not processor.load_data():
+            return
+
+        processor.create_output_folder()
+        processor.process_data()
+
+        print("所有处理已完成!")
+    except Exception as e:
+        print(f"处理过程中发生错误: {e}")
+
+    end_time = time.time()
+    print(f"总耗时: {end_time - start_time:.2f}秒")
+
+
+if __name__ == "__main__":
+    main()