Module madsci.workcell_manager.workcell_engine

Engine Class and associated helpers and data

Classes¶

Engine(state_handler: madsci.workcell_manager.state_handler.WorkcellStateHandler, data_client: madsci.client.data_client.DataClient)

Handles scheduling workflows and executing steps on the workcell. Pops incoming workflows off a redis-based queue and executes them.

Initialize the scheduler.

Methods¶

finalize_step(self, workflow_id: str, step: madsci.common.types.step_types.Step) ‑> None

Finalize the step, updating the workflow based on the results (setting status, updating index, etc.)

handle_data_and_files(self, step: madsci.common.types.step_types.Step, wf: madsci.common.types.workflow_types.Workflow, response: madsci.common.types.action_types.ActionResult) ‑> madsci.common.types.action_types.ActionResult

Upload non-datapoint results as datapoints and consolidate all datapoint IDs.

This method ensures that all results (JSON data, files) are stored as datapoints in the data manager, following the principle of getting data into the data manager ASAP. The response datapoints field will contain only ULID strings for efficient storage.

handle_response(self, wf: madsci.common.types.workflow_types.Workflow, step: madsci.common.types.step_types.Step, response: madsci.common.types.action_types.ActionResult) ‑> madsci.common.types.action_types.ActionResult | None

Handle the response from the node

monitor_action_progress(self, wf: madsci.common.types.workflow_types.Workflow, step: madsci.common.types.step_types.Step, node: madsci.common.types.node_types.Node, client: madsci.client.node.abstract_node_client.AbstractNodeClient, response: madsci.common.types.action_types.ActionResult, request: madsci.common.types.action_types.ActionRequest, action_id: str) ‑> None

Monitor the progress of the action, querying the action result until it is terminal

reset_disconnects(self) ‑> None

Reset all disconnected nodes to initializing state.

run_next_step(self, await_step_completion: bool = False) ‑> madsci.common.types.workflow_types.Workflow | None

Runs the next step in the workflow with the highest priority. Returns information about the workflow it ran, if any.

run_step(self, workflow_id: str) ‑> None

Run a step in a standalone thread, updating the workflow as needed

run_workcell_action(self, step: madsci.common.types.step_types.Step) ‑> madsci.common.types.step_types.Step

Runs one of the built-in workcell actions

spin(self) ‑> None

Continuously loop, updating node states every Config.update_interval seconds. If the state of the workcell has changed, update the active modules and run the scheduler.

update_active_nodes(self, state_manager: madsci.workcell_manager.state_handler.WorkcellStateHandler, update_info: bool = False) ‑> None

Update all active nodes in the workcell.

Args: state_manager: The workcell state handler update_info: Whether to update node info in addition to status and state (default: False)

update_node(self, node_name: str, node: madsci.common.types.node_types.Node, state_manager: madsci.workcell_manager.state_handler.WorkcellStateHandler, update_info: bool = False) ‑> None

Update a single node’s status, state, and optionally info.

Args: node_name: The name of the node to update node: The node object to update state_manager: The workcell state handler update_info: Whether to update node info (default: False). Node info changes infrequently, so it’s updated less often to reduce network overhead.

update_param_value_from_datapoint(self, wf: madsci.common.types.workflow_types.Workflow, datapoint: madsci.common.types.datapoint_types.DataPoint, parameter: madsci.common.types.parameter_types.ParameterFeedForwardJson | madsci.common.types.parameter_types.ParameterFeedForwardFile) ‑> madsci.common.types.workflow_types.Workflow

Updates the parameters in a workflow

update_step(self, wf: madsci.common.types.workflow_types.Workflow, step: madsci.common.types.step_types.Step) ‑> None

Update the step in the workflow