from sqlalchemy.orm import Session from sqlalchemy import text, MetaData, Table, Column, create_engine, inspect from sqlalchemy.exc import SQLAlchemyError from typing import List, Dict, Any, Optional from ..core.database import engine from ..utils.file_import import FileImportUtils import pandas as pd class DatabaseService: @staticmethod def execute_sql(db: Session, sql: str) -> Dict[str, Any]: """执行SQL语句""" try: result = db.execute(text(sql)) # 判断是否为SELECT查询 if sql.strip().upper().startswith('SELECT'): data = [] columns = result.keys() for row in result: data.append(dict(zip(columns, row))) return { "success": True, "message": "查询成功", "data": data } else: # 非SELECT语句，提交事务 db.commit() return { "success": True, "message": "执行成功", "rows_affected": result.rowcount } except SQLAlchemyError as e: db.rollback() return { "success": False, "message": f"SQL执行失败: {str(e)}" } except Exception as e: db.rollback() return { "success": False, "message": f"未知错误: {str(e)}" } @staticmethod def get_table_data(db: Session, table_name: str, limit: int = 100, offset: int = 0) -> Dict[str, Any]: """获取表数据""" try: # 先检查表是否存在 inspector = inspect(engine) if table_name not in inspector.get_table_names(): return { "success": False, "message": f"表 {table_name} 不存在" } # 获取总数 count_sql = f"SELECT COUNT(*) as total FROM {table_name}" count_result = db.execute(text(count_sql)).fetchone() total_count = count_result.total if count_result else 0 # 获取数据 sql = f"SELECT * FROM {table_name} LIMIT {limit} OFFSET {offset}" result = db.execute(text(sql)) data = [] columns = result.keys() for row in result: data.append(dict(zip(columns, row))) return { "success": True, "message": "获取数据成功", "data": data, "total_count": total_count } except SQLAlchemyError as e: return { "success": False, "message": f"获取表数据失败: {str(e)}" } except Exception as e: return { "success": False, "message": f"未知错误: {str(e)}" } @staticmethod def create_table(db: Session, table_name: str, columns: Dict[str, str], primary_key: Optional[str] = None) -> Dict[str, Any]: """创建表""" try: # 构建CREATE TABLE语句 column_definitions = [] for col_name, col_type in columns.items(): column_definitions.append(f"{col_name} {col_type}") if primary_key: column_definitions.append(f"PRIMARY KEY ({primary_key})") sql = f"CREATE TABLE {table_name} ({', '.join(column_definitions)})" db.execute(text(sql)) db.commit() return { "success": True, "message": f"表 {table_name} 创建成功" } except SQLAlchemyError as e: db.rollback() return { "success": False, "message": f"创建表失败: {str(e)}" } except Exception as e: db.rollback() return { "success": False, "message": f"未知错误: {str(e)}" } @staticmethod def drop_table(db: Session, table_name: str) -> Dict[str, Any]: """删除表""" try: sql = f"DROP TABLE IF EXISTS {table_name}" db.execute(text(sql)) db.commit() return { "success": True, "message": f"表 {table_name} 删除成功" } except SQLAlchemyError as e: db.rollback() return { "success": False, "message": f"删除表失败: {str(e)}" } except Exception as e: db.rollback() return { "success": False, "message": f"未知错误: {str(e)}" } @staticmethod def import_data(db: Session, table_name: str, data: List[Dict[str, Any]]) -> Dict[str, Any]: """导入数据到表""" try: if not data: return { "success": False, "message": "导入数据不能为空" } # 使用pandas DataFrame来处理数据导入 df = pd.DataFrame(data) # 使用pandas的to_sql方法 df.to_sql(table_name, engine, if_exists='append', index=False) return { "success": True, "message": f"成功导入 {len(data)} 条数据到表 {table_name}" } except SQLAlchemyError as e: db.rollback() return { "success": False, "message": f"导入数据失败: {str(e)}" } except Exception as e: db.rollback() return { "success": False, "message": f"未知错误: {str(e)}" } @staticmethod def get_table_list() -> Dict[str, Any]: """获取所有表名及字段信息""" try: inspector = inspect(engine) # 排除mysql的系统表和accounts表 table_names = [table for table in inspector.get_table_names() if not table.startswith('mysql') and table != 'accounts' and table != 'apscheduler_jobs'] tables_info = [] for table_name in table_names: # 获取表的列信息 columns = inspector.get_columns(table_name) column_info = [] for column in columns: column_info.append({ "name": column['name'], "type": str(column['type']), "nullable": column['nullable'], "default": column['default'] }) tables_info.append({ "table_name": table_name, "columns": column_info }) return { "success": True, "message": "获取表名及字段信息成功", "data": tables_info } except Exception as e: return { "success": False, "message": f"获取表名失败: {str(e)}" } @staticmethod def import_file_to_database(db: Session, filename: str, file_content: str, table_name: Optional[str] = None, force_overwrite: bool = False) -> Dict[str, Any]: """从文件导入数据到数据库""" try: # 解析文件内容 file_data = FileImportUtils.parse_file(filename, file_content) if not file_data: return { "success": False, "message": "文件中没有找到有效数据" } results = [] inspector = inspect(engine) existing_tables = inspector.get_table_names() for item in file_data: final_table_name = table_name if table_name else item["table_name"] data = item["data"] columns = item["columns"] if not data: continue # 检查表是否存在 if final_table_name in existing_tables and not force_overwrite: return { "success": False, "message": f"表 {final_table_name} 已存在，请使用 force_overwrite=true 覆盖或选择其他表名" } # 如果需要覆盖，先删除表 if final_table_name in existing_tables and force_overwrite: db.execute(text(f"DROP TABLE IF EXISTS `{final_table_name}`")) db.commit() # 准备列类型定义 column_types = FileImportUtils.prepare_table_columns(data, columns) # 创建表 column_definitions = [] for col in columns: col_type = column_types.get(col, "TEXT") column_definitions.append(f"`{col}` {col_type}") create_table_sql = f""" CREATE TABLE `{final_table_name}` ( id INT AUTO_INCREMENT PRIMARY KEY, {', '.join(column_definitions)} ) """ db.execute(text(create_table_sql)) db.commit() # 导入数据 df_clean = pd.DataFrame(data) # 使用pandas的to_sql方法批量导入 df_clean.to_sql(final_table_name, engine, if_exists='append', index=False, method='multi', chunksize=1000) results.append({ "table_name": final_table_name, "rows_imported": len(data), "columns": columns }) # 返回结果 if len(results) == 1: result = results[0] return { "success": True, "message": f"成功导入 {result['rows_imported']} 行数据到表 {result['table_name']}", "table_name": result["table_name"], "rows_imported": result["rows_imported"], "columns": result["columns"] } else: total_rows = sum(r["rows_imported"] for r in results) table_names = [r["table_name"] for r in results] return { "success": True, "message": f"成功导入 {total_rows} 行数据到 {len(results)} 个表", "tables": results, "total_rows": total_rows, "table_names": table_names } except ValueError as e: return { "success": False, "message": str(e) } except SQLAlchemyError as e: db.rollback() return { "success": False, "message": f"数据库操作失败: {str(e)}" } except Exception as e: db.rollback() return { "success": False, "message": f"导入失败: {str(e)}" }