Result Handling

TaskResult[T, E]

Every task must return TaskResult[T, TaskError] where:

• T is the success type
• TaskError is the error type (always TaskError)

A TaskResult contains exactly one of:

• ok: The success value (type T)
• err: The error value (type TaskError)

from horsies import TaskResult, TaskError

@app.task("divide")
def divide(a: int, b: int) -> TaskResult[float, TaskError]:
    if b == 0:
        return TaskResult(err=TaskError(
            error_code="DIVISION_BY_ZERO",
            message="Cannot divide by zero",
        ))
    return TaskResult(ok=a / b)

Checking Results

from horsies import Ok, Err

match divide.send(10, 2):
    case Ok(handle):
        result = handle.get()

        if result.is_ok():
            print(f"Result: {result.ok_value}")
        else:
            error = result.err_value
            print(f"Error: {error.error_code} - {error.message}")
    case Err(send_err):
        print(f"Send failed: {send_err.code} - {send_err.message}")

TaskError Structure

TaskError is a Pydantic model with optional fields:

Field	Type	Purpose
error_code	str or BuiltInTaskCode	Identifies the error type
message	str	Human-readable description
data	Any	Additional context (dict, list, etc.)
exception	BaseException or dict	Original exception if applicable

return TaskResult(err=TaskError(
    error_code="VALIDATION_FAILED",
    message="Input validation failed",
    data={"field": "email", "reason": "invalid format"},
))

Built-In Error Codes

When the library itself encounters an error (not your task code), it uses one of four error code families. The umbrella type alias BuiltInTaskCode covers all of them.

OperationalErrorCode

Code	When
UNHANDLED_EXCEPTION	Task raised an uncaught exception
TASK_EXCEPTION	Task function threw an exception
WORKER_CRASHED	Worker process died (detected via heartbeat)
BROKER_ERROR	Broker failed while retrieving the result
WORKER_RESOLUTION_ERROR	Worker couldn’t find the task in registry
WORKER_SERIALIZATION_ERROR	Result couldn’t be serialized
RESULT_DESERIALIZATION_ERROR	Stored result JSON is corrupt or could not be deserialized
WORKFLOW_ENQUEUE_FAILED	Workflow node failed during enqueue/build
SUBWORKFLOW_LOAD_FAILED	Subworkflow definition could not be loaded

ContractCode

Code	When
RETURN_TYPE_MISMATCH	Returned value doesn’t match declared type
PYDANTIC_HYDRATION_ERROR	Task succeeded but return value could not be rehydrated to declared type
WORKFLOW_CTX_MISSING_ID	Workflow context is missing required ID

RetrievalCode

Returned by handle.get() for issues retrieving results:

Code	When
WAIT_TIMEOUT	Timeout elapsed while waiting for result (task may still be running)
TASK_NOT_FOUND	Task ID doesn’t exist in database
WORKFLOW_NOT_FOUND	Workflow ID doesn’t exist in database
RESULT_NOT_AVAILABLE	Result cache is empty for an immediate/sync handle
RESULT_NOT_READY	Result not yet available; task is still running

OutcomeCode

Code	When
TASK_CANCELLED	Task was cancelled before completion
WORKFLOW_PAUSED	Workflow was paused
WORKFLOW_FAILED	Workflow failed
WORKFLOW_CANCELLED	Workflow was cancelled
UPSTREAM_SKIPPED	Upstream task in workflow was skipped
SUBWORKFLOW_FAILED	Subworkflow failed
WORKFLOW_SUCCESS_CASE_NOT_MET	Workflow success condition was not satisfied

Domain Errors vs Library Errors

Domain errors: Your task returns an error for business logic reasons.

@app.task("transfer_funds")
def transfer_funds(amount: float) -> TaskResult[str, TaskError]:
    if amount <= 0:
        # This is a domain error - expected, handled
        return TaskResult(err=TaskError(
            error_code="INVALID_AMOUNT",
            message="Amount must be positive",
        ))
    return TaskResult(ok="Transfer complete")

Built-in errors: Something went wrong in the infrastructure.

# If your task raises an exception:
@app.task("buggy_task")
def buggy_task() -> TaskResult[str, TaskError]:
    raise ValueError("Oops")  # Becomes UNHANDLED_EXCEPTION

Both cases result in TaskResult(err=...), but the error codes differ.

Runtime Type Validation

Horsies validates that your returned value matches the declared type:

@app.task("typed_task")
def typed_task() -> TaskResult[int, TaskError]:
    return TaskResult(ok="not an int")  # RETURN_TYPE_MISMATCH error

This validation happens at runtime using Pydantic’s TypeAdapter.

None as Valid Success

TaskResult[None, TaskError] is valid for tasks that don’t return a value:

@app.task("fire_and_forget")
def fire_and_forget() -> TaskResult[None, TaskError]:
    do_something()
    return TaskResult(ok=None)

Convenience Properties

result = handle.get()

# Check state
result.is_ok()    # True if success
result.is_err()   # True if error

# Access values (raises ValueError if wrong state)
result.ok_value   # Success value
result.err_value  # Error value

# Unwrap shortcuts (raises ValueError if wrong state)
result.unwrap()       # Returns ok value, raises if err
result.unwrap_err()   # Returns err value, raises if ok

unwrap() and unwrap_err() are equivalent to ok_value and err_value — use whichever reads better in context. Both raise ValueError when called on the wrong variant, so always check is_ok()/is_err() first or use pattern matching.