diff --git a/unilabos/devices/workstation/bioyond_studio/bioyond_cell/bioyond_cell_workstation.py b/unilabos/devices/workstation/bioyond_studio/bioyond_cell/bioyond_cell_workstation.py index ac3ea5b9..4a343e71 100644 --- a/unilabos/devices/workstation/bioyond_studio/bioyond_cell/bioyond_cell_workstation.py +++ b/unilabos/devices/workstation/bioyond_studio/bioyond_cell/bioyond_cell_workstation.py @@ -825,12 +825,221 @@ class BioyondCellWorkstation(BioyondWorkstation): logger.warning("超时未找到成功的物料转移任务") return False + def create_solid_materials(self, material_names: List[str], type_id: str = "3a190ca0-b2f6-9aeb-8067-547e72c11469") -> List[Dict[str, Any]]: + """ + 批量创建固体物料 + + Args: + material_names: 物料名称列表 + type_id: 物料类型ID（默认为固体物料类型） + + Returns: + 创建的物料列表，每个元素包含物料信息和ID + """ + created_materials = [] + total = len(material_names) + + for i, name in enumerate(material_names, 1): + # 根据接口文档构建完整的请求体 + material_data = { + "typeId": type_id, + "name": name, + "unit": "g", # 添加单位 + "quantity": 1, # 添加数量（默认1） + "parameters": "" # 参数字段（空字符串表示无参数） + } + + logger.info(f"正在创建第 {i}/{total} 个固体物料: {name}") + result = self._post_lims("/api/lims/storage/material", material_data) + + if result and result.get("code") == 1: + # data 字段可能是字符串（物料ID）或字典（包含id字段） + data = result.get("data") + if isinstance(data, str): + # data 直接是物料ID字符串 + material_id = data + elif isinstance(data, dict): + # data 是字典，包含id字段 + material_id = data.get("id") + else: + material_id = None + + if material_id: + created_materials.append({ + "name": name, + "materialId": material_id, + "typeId": type_id + }) + logger.info(f"✓ 成功创建物料: {name}, ID: {material_id}") + else: + logger.error(f"✗ 创建物料失败: {name}, 未返回ID") + logger.error(f" 响应数据: {result}") + else: + error_msg = result.get("error") or result.get("message", "未知错误") + logger.error(f"✗ 创建物料失败: {name}") + logger.error(f" 错误信息: {error_msg}") + logger.error(f" 完整响应: {result}") + + # 避免请求过快 + time.sleep(0.3) + + logger.info(f"物料创建完成，成功创建 {len(created_materials)}/{total} 个固体物料") + return created_materials + + def create_and_inbound_materials_from_csv( + self, + csv_path: str = "solid_materials.csv", + type_id: str = "3a190ca0-b2f6-9aeb-8067-547e72c11469", + warehouse_name: str = "粉末加样头堆栈" + ) -> Dict[str, Any]: + """ + 从CSV文件读取物料列表，创建物料并批量入库到指定堆栈 + + Args: + csv_path: CSV文件路径 + type_id: 物料类型ID（默认为固体物料类型） + warehouse_name: 仓库名称（默认为"粉末加样头堆栈"） + + Returns: + 包含执行结果的字典 + """ + logger.info("=" * 60) + logger.info(f"开始执行：从CSV读取物料列表并批量创建入库到 {warehouse_name}") + logger.info("=" * 60) + + # 从配置中获取位置ID列表 + warehouse_mapping = self.bioyond_config.get("warehouse_mapping", WAREHOUSE_MAPPING) + + if warehouse_name not in warehouse_mapping: + error_msg = f"配置中未找到仓库: {warehouse_name}" + logger.error(error_msg) + logger.info(f"可用的仓库: {list(warehouse_mapping.keys())}") + return {"success": False, "error": error_msg} + + warehouse_config = warehouse_mapping[warehouse_name] + site_uuids = warehouse_config.get("site_uuids", {}) + + if not site_uuids: + error_msg = f"仓库 {warehouse_name} 没有配置位置" + logger.error(error_msg) + return {"success": False, "error": error_msg} + + # 按顺序获取位置ID（A01, B01, C01...） + all_location_ids = [] + position_names = [] + for key in sorted(site_uuids.keys()): + all_location_ids.append(site_uuids[key]) + position_names.append(key) + + logger.info(f"✓ 从配置文件加载 {len(all_location_ids)} 个位置") + logger.info(f" 仓库: {warehouse_name}") + logger.info(f" 位置范围: {position_names[0]} ~ {position_names[-1]}") + + # 读取CSV文件 + csv_file_path = Path(csv_path) + material_names = [] + + try: + df_materials = pd.read_csv(csv_file_path) + if 'material_name' in df_materials.columns: + material_names = df_materials['material_name'].dropna().astype(str).str.strip().tolist() + logger.info(f"✓ 成功从CSV文件读取 {len(material_names)} 个物料名称") + logger.info(f" 文件路径: {csv_file_path}") + else: + logger.error(f"✗ CSV文件缺少 'material_name' 列") + return {"success": False, "error": "CSV文件缺少 'material_name' 列"} + except FileNotFoundError: + logger.error(f"✗ 未找到CSV文件: {csv_file_path}") + logger.info("请创建CSV文件，格式：") + logger.info(" material_name") + logger.info(" LiPF6") + logger.info(" LiDFOB") + logger.info(" ...") + return {"success": False, "error": f"未找到CSV文件: {csv_file_path}"} + except Exception as e: + logger.error(f"✗ 读取CSV文件失败: {e}") + return {"success": False, "error": f"读取CSV文件失败: {e}"} + + if not material_names: + logger.error("CSV文件中没有有效的物料名称") + return {"success": False, "error": "CSV文件中没有有效的物料名称"} + + # 检查物料数量 + if len(material_names) > len(all_location_ids): + logger.warning(f"物料数量({len(material_names)})超过可用位置数量({len(all_location_ids)})！") + logger.warning(f"将仅创建前 {len(all_location_ids)} 个物料") + material_names = material_names[:len(all_location_ids)] + + # 准备位置信息 + location_ids = all_location_ids[:len(material_names)] + selected_positions = position_names[:len(material_names)] + + # 步骤1: 创建固体物料 + logger.info(f"\n【步骤1/2】创建 {len(material_names)} 个固体物料...") + logger.info(f"物料类型ID: {type_id}") + logger.info(f"物料列表: {', '.join(material_names)}") + + created_materials = self.create_solid_materials( + material_names=material_names, + type_id=type_id + ) + + if len(created_materials) != len(material_names): + logger.warning(f"创建的物料数量({len(created_materials)})与计划数量({len(material_names)})不匹配！") + logger.warning("将仅对成功创建的物料进行入库操作") + + if not created_materials: + logger.error("没有成功创建任何物料") + return {"success": False, "error": "没有成功创建任何物料"} + + # 步骤2: 批量入库到指定位置 + logger.info(f"\n【步骤2/2】批量入库物料到 {warehouse_name}...") + inbound_items = [] + + for idx, material in enumerate(created_materials): + if idx < len(location_ids): + inbound_items.append({ + "materialId": material["materialId"], + "locationId": location_ids[idx] + }) + logger.info(f" - {material['name']} (ID: {material['materialId'][:8]}...) → 位置 {selected_positions[idx]}") + + logger.info(f"\n正在执行批量入库，共 {len(inbound_items)} 条记录...") + result = self.storage_batch_inbound(inbound_items) + + if result.get("code") == 1: + logger.info(f"✓ 批量入库成功！") + logger.info(f" 响应数据: {result.get('data', {})}") + else: + logger.error(f"✗ 批量入库失败！") + logger.error(f" 响应: {result}") + + logger.info("\n" + "=" * 60) + logger.info("固体物料创建和入库流程完成") + logger.info("=" * 60 + "\n") + + return { + "success": result.get("code") == 1, + "created_materials": created_materials, + "inbound_result": result, + "total_created": len(created_materials), + "total_inbound": len(inbound_items), + "warehouse": warehouse_name, + "positions": selected_positions + } + # -------------------------------- + + if __name__ == "__main__": ws = BioyondCellWorkstation() logger.info(ws.scheduler_start()) - #TODO：新建入库 + + # 从CSV文件读取物料列表并批量创建入库 + result = ws.create_and_inbound_materials_from_csv() + + # 继续后续流程 logger.info(ws.auto_feeding4to3()) #搬运物料到3号箱 # 使用正斜杠或 Path 对象来指定文件路径 excel_path = Path("unilabos/devices/workstation/bioyond_studio/bioyond_cell/2025092701.xlsx") diff --git a/unilabos/devices/workstation/bioyond_studio/bioyond_cell/solid_materials.csv b/unilabos/devices/workstation/bioyond_studio/bioyond_cell/solid_materials.csv new file mode 100644 index 00000000..8db9a5cb --- /dev/null +++ b/unilabos/devices/workstation/bioyond_studio/bioyond_cell/solid_materials.csv @@ -0,0 +1,7 @@ +material_name +LiPF6 +LiDFOB +DTD +LiFSI +LiPO2F2 + diff --git a/unilabos/devices/workstation/bioyond_studio/config.py b/unilabos/devices/workstation/bioyond_studio/config.py index ed14f7b2..92943005 100644 --- a/unilabos/devices/workstation/bioyond_studio/config.py +++ b/unilabos/devices/workstation/bioyond_studio/config.py @@ -25,7 +25,7 @@ BIOYOND_FULL_CONFIG = { # HTTP 服务配置 "HTTP_host": os.getenv("BIOYOND_HTTP_HOST", "0.0.0.0"), # HTTP服务监听地址（0.0.0.0 表示监听所有网络接口） "HTTP_port": int(os.getenv("BIOYOND_HTTP_PORT", "8080")), - "report_ip": os.getenv("BIOYOND_REPORT_IP", "172.21.32.57"), # 报送给 Bioyond 的本机IP地址（留空则自动检测） + "report_ip": os.getenv("BIOYOND_REPORT_IP", "172.21.32.172"), # 报送给 Bioyond 的本机IP地址（留空则自动检测） # 调试模式 "debug_mode": os.getenv("BIOYOND_DEBUG_MODE", "False").lower() == "true", @@ -112,6 +112,31 @@ WAREHOUSE_MAPPING = { "B3": "3a14198c-c2d0-725e-523d-34c037ac2440", "B4": "3a14198c-c2d0-efce-0939-69ca5a7dfd39" } + }, + "粉末加样头堆栈": { + "uuid": "", + "site_uuids": { + "A01": "3a19da56-1379-20c8-5886-f7c4fbcb5733", + "B01": "3a19da56-1379-2424-d751-fe6e94cef938", + "C01": "3a19da56-1379-271c-03e3-6bdb590e395e", + "D01": "3a19da56-1379-277f-2b1b-0d11f7cf92c6", + "E01": "3a19da56-1379-2f1c-a15b-e01db90eb39a", + "F01": "3a19da56-1379-3fa1-846b-088158ac0b3d", + "G01": "3a19da56-1379-5aeb-d0cd-d3b4609d66e1", + "H01": "3a19da56-1379-6077-8258-bdc036870b78", + "I01": "3a19da56-1379-863b-a120-f606baf04617", + "J01": "3a19da56-1379-8a74-74e5-35a9b41d4fd5", + "K01": "3a19da56-1379-b270-b7af-f18773918abe", + "L01": "3a19da56-1379-ba54-6d78-fd770a671ffc", + "M01": "3a19da56-1379-c22d-c96f-0ceb5eb54a04", + "N01": "3a19da56-1379-d64e-c6c5-c72ea4829888", + "O01": "3a19da56-1379-d887-1a3c-6f9cce90f90e", + "P01": "3a19da56-1379-e77d-0e65-7463b238a3b9", + "Q01": "3a19da56-1379-edf6-1472-802ddb628774", + "R01": "3a19da56-1379-f281-0273-e0ef78f0fd97", + "S01": "3a19da56-1379-f924-7f68-df1fa51489f4", + "T01": "3a19da56-1379-ff7c-1745-07e200b44ce2" + } } }