Struct WorkflowExecutor

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pub struct WorkflowExecutor {
    storage: Arc<Storage>,
    scheduler: Arc<Scheduler>,
    num_workers: usize,
    registry: Arc<NodeRegistry>,
    running: Arc<Mutex<bool>>,
    python_manager: Arc<Mutex<Option<Arc<PythonManager>>>>,
}

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§storage: Arc<Storage>§scheduler: Arc<Scheduler>§num_workers: usize§registry: Arc<NodeRegistry>§running: Arc<Mutex<bool>>§python_manager: Arc<Mutex<Option<Arc<PythonManager>>>>

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impl WorkflowExecutor

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pub fn new( storage: Arc<Storage>, num_workers: usize, registry: Arc<NodeRegistry>, ) -> Self

Create an asynchronous executor with storage and workers

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pub async fn set_python_manager(&self, manager: Arc<PythonManager>)

Set the Python manager for script execution

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pub async fn get_python_manager(&self) -> Option<Arc<PythonManager>>

Get the Python manager if available

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pub async fn submit(&self, workflow_id: String, input: Value) -> Result<String>

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pub async fn submit_with_execution_id( &self, workflow_id: String, input: Value, execution_id: String, ) -> Result<String>

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pub async fn submit_node(&self, node: Node, input: Value) -> Result<String>

Submit a single node for execution

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pub async fn start(&self)

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async fn submit_async( &self, workflow_id: String, input: Value, ) -> Result<String>

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async fn submit_async_with_id( &self, workflow_id: String, input: Value, execution_id: String, ) -> Result<String>

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async fn try_start(&self) -> bool

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fn recover_stalled_tasks(&self)

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async fn spawn_workers(&self, num_workers: usize)

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async fn execute_node( node: &Node, input: &NodeInput, context: &mut ExecutionContext, registry: Arc<NodeRegistry>, ) -> Result<NodeOutput>

Resolves Templated fields in NodeInput using execution context, then delegates to node-specific executor for actual execution.

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pub async fn get_task_status(&self, task_id: &str) -> Result<Task>

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pub async fn get_execution_status( &self, execution_id: &str, ) -> Result<Vec<Task>>

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pub async fn list_tasks( &self, workflow_id: Option<&str>, status: Option<TaskStatus>, ) -> Result<Vec<Task>>

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