Testing Tasks

Sheppy is built with testing in mind. The TestQueue provides a synchronous, deterministic API that makes testing tasks easy and straightforward.

This guide covers testing strategies from basic unit tests to complex retry logic.

Basic Testing

Here's a simple task to test:

tasks.py

from sheppy import task

@task
async def add(x: int, y: int) -> int:
    return x + y

Testing it is straightforward with TestQueue:

tests/test_tasks.py

from sheppy import TestQueue
from tasks import add

def test_add():
    q = TestQueue()

    # instantiate task
    t = add(1, 2)

    # add to the test queue
    q.add(t)

    # process the next task in the queue
    processed_task = q.process_next()

    # verify the task result
    assert processed_task.status == 'completed'
    assert processed_task.error is None
    assert processed_task.result == 3

Key differences from production Queue:

• Synchronous API (no await needed)
• Explicit task processing with process_next() or process_all()
• Tasks execute immediately in the test process without needing background workers
• Perfect for fast, deterministic unit tests

Testing Task Failures

Tasks can fail, and you should test that they fail correctly:

tests/test_failure.py

from sheppy import TestQueue, task


@task
def divide(x: int, y: int) -> float:
    return x / y


def test_divide_by_zero():
    q = TestQueue()

    # instantiate two tasks
    t1 = divide(1, 2)
    t2 = divide(1, 0)

    # add both tasks to the test queue
    q.add([t1, t2])

    # process all tasks in the queue (processed in order)
    processed_tasks = q.process_all()

    # verify the first task result
    assert processed_tasks[0].status == 'completed'
    assert processed_tasks[0].error is None
    assert processed_tasks[0].result == 0.5

    # verify the second task result (should fail)
    assert processed_tasks[1].status == 'failed'
    assert processed_tasks[1].error == "ZeroDivisionError: division by zero"

When a task fails, the exception is captured in the error attribute. You can assert on this to verify correct error handling.

Testing Retry Logic

Test that retry configuration works as expected:

tests/test_retry_logic.py

from sheppy import TestQueue, task

FAIL_COUNTER = 0

@task(retry=2, retry_delay=0)
def fail_once() -> str:
    global FAIL_COUNTER

    if FAIL_COUNTER < 1:
        FAIL_COUNTER += 1
        raise ValueError("task failed")

    return "success"

def test_fail_once():
    q = TestQueue()

    # instantiate the task
    t = fail_once()

    # add the task to the test queue
    q.add(t)

    assert q.size() == 1  # one task in the queue

    # process all tasks in the queue
    processed = q.process_all()

    # there should be two processed tasks: the original + one retry
    assert len(processed) == 2

    # verify the task result
    assert processed[0].status == 'failed'
    assert processed[0].error == "ValueError: task failed"

    # retry should succeed
    assert processed[1].status == 'completed'
    assert processed[1].error is None
    assert processed[1].result == "success"

    # both processed tasks should have the same id
    assert processed[0].id == processed[1].id

When using TaskQueue, retries happen immediately with no delay, keeping tests fast while still validating retry behavior.