Here is an update to my seven years old answer:

You can run a worker in a separate thread via a pytest fixture:

https://docs.celeryq.dev/en/v5.2.6/userguide/testing.html#celery-worker-embed-live-worker

According to the docs, you should not use "always_eager" (see the top of the page of the above link).

Old answer:

I use this:

with mock.patch('celeryconfig.CELERY_ALWAYS_EAGER', True, create=True):
        ...

Docs: https://docs.celeryq.dev/en/3.1/configuration.html#celery-always-eager

CELERY_ALWAYS_EAGER lets you run your task synchronously, and you don't need a celery server.

Depends on what exactly you want to be testing.

• Test the task code directly. Don't call "task.delay(...)" just call "task(...)" from your unit tests.
• Use CELERY_ALWAYS_EAGER. This will cause your tasks to be called immediately at the point you say "task.delay(...)", so you can test the whole path (but not any asynchronous behavior).

For those on Celery 4 it's:

@override_settings(CELERY_TASK_ALWAYS_EAGER=True)

Because the settings names have been changed and need updating if you choose to upgrade, see

https://docs.celeryproject.org/en/latest/history/whatsnew-4.0.html?highlight=what%20is%20new#lowercase-setting-names

unittest

import unittest

from myproject.myapp import celeryapp

class TestMyCeleryWorker(unittest.TestCase):

  def setUp(self):
      celeryapp.conf.update(CELERY_ALWAYS_EAGER=True)

py.test fixtures

# conftest.py
from myproject.myapp import celeryapp

@pytest.fixture(scope='module')
def celery_app(request):
    celeryapp.conf.update(CELERY_ALWAYS_EAGER=True)
    return celeryapp

# test_tasks.py
def test_some_task(celery_app):
    ...

Addendum: make send_task respect eager

from celery import current_app

def send_task(name, args=(), kwargs={}, **opts):
    # https://github.com/celery/celery/issues/581
    task = current_app.tasks[name]
    return task.apply(args, kwargs, **opts)

current_app.send_task = send_task

As of Celery 3.0, one way to set CELERY_ALWAYS_EAGER in Django is:

from django.test import TestCase, override_settings

from .foo import foo_celery_task

class MyTest(TestCase):

    @override_settings(CELERY_ALWAYS_EAGER=True)
    def test_foo(self):
        self.assertTrue(foo_celery_task.delay())

Since Celery v4.0, py.test fixtures are provided to start a celery worker just for the test and are shut down when done:

def test_myfunc_is_executed(celery_session_worker):
    # celery_session_worker: <Worker: [email protected] (running)>
    assert myfunc.delay().wait(3)

Among other fixtures described on http://docs.celeryproject.org/en/latest/userguide/testing.html#py-test, you can change the celery default options by redefining the celery_config fixture this way:

@pytest.fixture(scope='session')
def celery_config():
    return {
        'accept_content': ['json', 'pickle'],
        'result_serializer': 'pickle',
    }

By default, the test worker uses an in-memory broker and result backend. No need to use a local Redis or RabbitMQ if not testing specific features.

reference using pytest.

def test_add(celery_worker):
    mytask.delay()

if you use flask, set the app config

    CELERY_BROKER_URL = 'memory://'
    CELERY_RESULT_BACKEND = 'cache+memory://'

and in conftest.py

@pytest.fixture
def app():
    yield app   # Your actual Flask application

@pytest.fixture
def celery_app(app):
    from celery.contrib.testing import tasks   # need it
    yield celery_app    # Your actual Flask-Celery application

In my case (and I assume many others), all I wanted was to test the inner logic of a task using pytest.

TL;DR; ended up mocking everything away (OPTION 2)

Example Use Case:

proj/tasks.py

@shared_task(bind=True)
def add_task(self, a, b):
    return a+b;

tests/test_tasks.py

from proj import add_task

def test_add():
    assert add_task(1, 2) == 3, '1 + 2 should equal 3'

but, since shared_task decorator does a lot of celery internal logic, it isn't really a unit tests.

So, for me, there were 2 options:

OPTION 1: Separate internal logic

proj/tasks_logic.py

def internal_add(a, b):
    return a + b;

proj/tasks.py

from .tasks_logic import internal_add

@shared_task(bind=True)
def add_task(self, a, b):
    return internal_add(a, b);

This looks very odd, and other than making it less readable, it requires to manually extract and pass attributes that are part of the request, for instance the task_id in case you need it, which make the logic less pure.

OPTION 2: mocks
mocking away celery internals

tests/__init__.py

# noinspection PyUnresolvedReferences
from celery import shared_task

from mock import patch


def mock_signature(**kwargs):
    return {}


def mocked_shared_task(*decorator_args, **decorator_kwargs):
    def mocked_shared_decorator(func):
        func.signature = func.si = func.s = mock_signature
        return func

    return mocked_shared_decorator

patch('celery.shared_task', mocked_shared_task).start()

which then allows me to mock the request object (again, in case you need things from the request, like the id, or the retries counter.

tests/test_tasks.py

from proj import add_task

class MockedRequest:
    def __init__(self, id=None):
        self.id = id or 1


class MockedTask:
    def __init__(self, id=None):
        self.request = MockedRequest(id=id)


def test_add():
    mocked_task = MockedTask(id=3)
    assert add_task(mocked_task, 1, 2) == 3, '1 + 2 should equal 3'

This solution is much more manual, but, it gives me the control I need to actually unit test, without repeating myself, and without losing the celery scope.

I see a lot of CELERY_ALWAYS_EAGER = true in unit tests methods as a solution for unit tests, but since the version 5.0.5 is available there are a lot of changes which makes most of the old answers deprecated and for me a time consuming nonsense, so for everyone here searching a Solution, go to the Doc and read the well documented unit test examples for the new Version:

https://docs.celeryproject.org/en/stable/userguide/testing.html

And to the Eager Mode with Unit Tests, here a quote from the actual docs:

Eager mode

The eager mode enabled by the task_always_eager setting is by definition not suitable for unit tests.

When testing with eager mode you are only testing an emulation of what happens in a worker, and there are many discrepancies between the emulation and what happens in reality.

Another option is to mock the task if you do not need the side effects of running it.

from unittest import mock


@mock.patch('module.module.task')
def test_name(self, mock_task): ...