mirror of
https://github.com/dptech-corp/Uni-Lab-OS.git
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5179a7e48e
fix upload workflow json save class name when deserialize & protocol execute test Support root node change pos add unilabos_class gather query
316 lines
9.8 KiB
Python
316 lines
9.8 KiB
Python
"""
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JSON 工作流转换模块
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将 workflow/reagent 格式的 JSON 转换为统一工作流格式。
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输入格式:
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{
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"workflow": [
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{"action": "...", "action_args": {...}},
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...
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],
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"reagent": {
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"reagent_name": {"slot": int, "well": [...], "labware": "..."},
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...
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}
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}
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"""
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import json
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from os import PathLike
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from pathlib import Path
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from typing import Any, Dict, List, Optional, Tuple, Union
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from unilabos.workflow.common import WorkflowGraph, build_protocol_graph
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from unilabos.registry.registry import lab_registry
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# ==================== 字段映射配置 ====================
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# action 到 resource_name 的映射
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ACTION_RESOURCE_MAPPING: Dict[str, str] = {
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# 生物实验操作
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"transfer_liquid": "liquid_handler.prcxi",
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"transfer": "liquid_handler.prcxi",
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"incubation": "incubator.prcxi",
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"move_labware": "labware_mover.prcxi",
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"oscillation": "shaker.prcxi",
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# 有机化学操作
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"HeatChillToTemp": "heatchill.chemputer",
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"StopHeatChill": "heatchill.chemputer",
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"StartHeatChill": "heatchill.chemputer",
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"HeatChill": "heatchill.chemputer",
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"Dissolve": "stirrer.chemputer",
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"Transfer": "liquid_handler.chemputer",
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"Evaporate": "rotavap.chemputer",
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"Recrystallize": "reactor.chemputer",
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"Filter": "filter.chemputer",
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"Dry": "dryer.chemputer",
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"Add": "liquid_handler.chemputer",
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}
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# action_args 字段到 parameters 字段的映射
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# 格式: {"old_key": "new_key"}, 仅映射需要重命名的字段
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ARGS_FIELD_MAPPING: Dict[str, str] = {
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# 如果需要字段重命名，在这里配置
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# "old_field_name": "new_field_name",
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}
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# 默认工作站名称
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DEFAULT_WORKSTATION = "PRCXI"
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# ==================== 核心转换函数 ====================
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def get_action_handles(resource_name: str, template_name: str) -> Dict[str, List[str]]:
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"""
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从 registry 获取指定设备和动作的 handles 配置
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Args:
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resource_name: 设备资源名称，如 "liquid_handler.prcxi"
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template_name: 动作模板名称，如 "transfer_liquid"
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Returns:
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包含 source 和 target handler_keys 的字典:
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{"source": ["sources_out", "targets_out", ...], "target": ["sources", "targets", ...]}
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"""
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result = {"source": [], "target": []}
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device_info = lab_registry.device_type_registry.get(resource_name, {})
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if not device_info:
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return result
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action_mappings = device_info.get("class", {}).get("action_value_mappings", {})
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action_config = action_mappings.get(template_name, {})
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handles = action_config.get("handles", {})
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if isinstance(handles, dict):
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for handle in handles.get("input", []):
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handler_key = handle.get("handler_key", "")
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if handler_key:
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result["source"].append(handler_key)
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for handle in handles.get("output", []):
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handler_key = handle.get("handler_key", "")
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if handler_key:
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result["target"].append(handler_key)
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return result
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def validate_workflow_handles(graph: WorkflowGraph) -> Tuple[bool, List[str]]:
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"""
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校验工作流图中所有边的句柄配置是否正确
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Args:
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graph: 工作流图对象
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Returns:
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(is_valid, errors): 是否有效，错误信息列表
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"""
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errors = []
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nodes = graph.nodes
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for edge in graph.edges:
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left_uuid = edge.get("source")
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right_uuid = edge.get("target")
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right_source_conn_key = edge.get("target_handle_key", "")
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left_target_conn_key = edge.get("source_handle_key", "")
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left_node = nodes.get(left_uuid, {})
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right_node = nodes.get(right_uuid, {})
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left_res_name = left_node.get("resource_name", "")
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left_template_name = left_node.get("template_name", "")
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right_res_name = right_node.get("resource_name", "")
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right_template_name = right_node.get("template_name", "")
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left_node_handles = get_action_handles(left_res_name, left_template_name)
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target_valid_keys = left_node_handles.get("target", [])
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target_valid_keys.append("ready")
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right_node_handles = get_action_handles(right_res_name, right_template_name)
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source_valid_keys = right_node_handles.get("source", [])
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source_valid_keys.append("ready")
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# 验证目标节点（right）的输入端口
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if not right_source_conn_key:
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node_name = right_node.get("name", right_uuid[:8])
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errors.append(f"目标节点 '{node_name}' 的输入端口 (target_handle_key) 为空，应设置为: {source_valid_keys}")
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elif right_source_conn_key not in source_valid_keys:
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node_name = right_node.get("name", right_uuid[:8])
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errors.append(
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f"目标节点 '{node_name}' 的输入端口 '{right_source_conn_key}' 不存在，支持的输入端口: {source_valid_keys}"
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)
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# 验证源节点（left）的输出端口
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if not left_target_conn_key:
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node_name = left_node.get("name", left_uuid[:8])
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errors.append(f"源节点 '{node_name}' 的输出端口 (source_handle_key) 为空，应设置为: {target_valid_keys}")
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elif left_target_conn_key not in target_valid_keys:
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node_name = left_node.get("name", left_uuid[:8])
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errors.append(
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f"源节点 '{node_name}' 的输出端口 '{left_target_conn_key}' 不存在，支持的输出端口: {target_valid_keys}"
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)
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return len(errors) == 0, errors
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def normalize_workflow_steps(workflow: List[Dict[str, Any]]) -> List[Dict[str, Any]]:
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"""
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将 workflow 格式的步骤数据规范化
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输入格式:
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[{"action": "...", "action_args": {...}}, ...]
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输出格式:
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[{"action": "...", "parameters": {...}, "step_number": int}, ...]
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Args:
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workflow: workflow 数组
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Returns:
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规范化后的步骤列表
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"""
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normalized = []
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for idx, step in enumerate(workflow):
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action = step.get("action")
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if not action:
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continue
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# 获取参数: action_args
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raw_params = step.get("action_args", {})
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params = {}
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# 应用字段映射
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for key, value in raw_params.items():
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mapped_key = ARGS_FIELD_MAPPING.get(key, key)
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params[mapped_key] = value
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step_dict = {
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"action": action,
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"parameters": params,
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"step_number": idx + 1,
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}
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# 保留描述字段
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if "description" in step:
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step_dict["description"] = step["description"]
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normalized.append(step_dict)
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return normalized
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def convert_from_json(
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data: Union[str, PathLike, Dict[str, Any]],
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workstation_name: str = DEFAULT_WORKSTATION,
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validate: bool = True,
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) -> WorkflowGraph:
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"""
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从 JSON 数据或文件转换为 WorkflowGraph
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JSON 格式:
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{"workflow": [...], "reagent": {...}}
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Args:
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data: JSON 文件路径、字典数据、或 JSON 字符串
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workstation_name: 工作站名称，默认 "PRCXi"
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validate: 是否校验句柄配置，默认 True
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Returns:
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WorkflowGraph: 构建好的工作流图
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Raises:
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ValueError: 不支持的 JSON 格式
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FileNotFoundError: 文件不存在
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json.JSONDecodeError: JSON 解析失败
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"""
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# 处理输入数据
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if isinstance(data, (str, PathLike)):
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path = Path(data)
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if path.exists():
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with path.open("r", encoding="utf-8") as fp:
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json_data = json.load(fp)
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elif isinstance(data, str):
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json_data = json.loads(data)
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else:
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raise FileNotFoundError(f"文件不存在: {data}")
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elif isinstance(data, dict):
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json_data = data
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else:
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raise TypeError(f"不支持的数据类型: {type(data)}")
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# 校验格式
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if "workflow" not in json_data or "reagent" not in json_data:
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raise ValueError(
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"不支持的 JSON 格式。请使用标准格式:\n"
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'{"workflow": [{"action": "...", "action_args": {...}}, ...], '
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'"reagent": {"name": {"slot": int, "well": [...], "labware": "..."}, ...}}'
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)
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# 提取数据
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workflow = json_data["workflow"]
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reagent = json_data["reagent"]
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# 规范化步骤数据
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protocol_steps = normalize_workflow_steps(workflow)
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# reagent 已经是字典格式，直接使用
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labware_info = reagent
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# 构建工作流图
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graph = build_protocol_graph(
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labware_info=labware_info,
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protocol_steps=protocol_steps,
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workstation_name=workstation_name,
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action_resource_mapping=ACTION_RESOURCE_MAPPING,
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)
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# 校验句柄配置
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if validate:
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is_valid, errors = validate_workflow_handles(graph)
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if not is_valid:
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import warnings
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for error in errors:
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warnings.warn(f"句柄校验警告: {error}")
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return graph
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def convert_json_to_node_link(
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data: Union[str, PathLike, Dict[str, Any]],
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workstation_name: str = DEFAULT_WORKSTATION,
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) -> Dict[str, Any]:
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"""
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将 JSON 数据转换为 node-link 格式的字典
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Args:
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data: JSON 文件路径、字典数据、或 JSON 字符串
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workstation_name: 工作站名称，默认 "PRCXi"
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Returns:
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Dict: node-link 格式的工作流数据
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"""
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graph = convert_from_json(data, workstation_name)
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return graph.to_node_link_dict()
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def convert_json_to_workflow_list(
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data: Union[str, PathLike, Dict[str, Any]],
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workstation_name: str = DEFAULT_WORKSTATION,
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) -> List[Dict[str, Any]]:
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"""
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将 JSON 数据转换为工作流列表格式
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Args:
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data: JSON 文件路径、字典数据、或 JSON 字符串
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workstation_name: 工作站名称，默认 "PRCXi"
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Returns:
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List: 工作流节点列表
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"""
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graph = convert_from_json(data, workstation_name)
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return graph.to_dict()
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