Merge pull request #84 from Koed00/dev

Adds cached result backend
This commit is contained in:
Ilan Steemers
2015-10-04 14:43:20 +02:00
10 changed files with 519 additions and 36 deletions
+1 -1
View File
@@ -15,7 +15,7 @@ Features
- Asynchronous tasks
- Scheduled and repeated tasks
- Encrypted and compressed packages
- Failure and success database
- Failure and success database or cache
- Result hooks and groups
- Django Admin integration
- PaaS compatible with multiple instances
+43 -2
View File
@@ -325,7 +325,11 @@ def monitor(result_queue, broker=None):
if ack_id:
broker.acknowledge(ack_id)
# save the result
save_task(task)
if task.get('cached', False):
save_cached(task, broker)
else:
save_task(task)
# log the result
if task['success']:
logger.info(_("Processed [{}]").format(task['name']))
else:
@@ -384,7 +388,7 @@ def worker(task_queue, result_queue, timer, timeout=Conf.TIMEOUT):
def save_task(task):
"""
Saves the task package to Django
Saves the task package to Django or the cache
"""
# SAVE LIMIT < 0 : Don't save success
if not task.get('save', Conf.SAVE_LIMIT > 0) and task['success']:
@@ -409,6 +413,43 @@ def save_task(task):
logger.error(e)
def save_cached(task, broker):
task_key = '{}:{}'.format(broker.list_key, task['id'])
timeout = task['cached']
if timeout is True:
timeout = None
try:
group = task.get('group', False)
iter_count = task.get('iter_count', None)
# if it's a group append to the group list
if group:
task_key = '{}:{}:{}'.format(broker.list_key, group, task['id'])
group_key = '{}:{}:keys'.format(broker.list_key, group)
group_list = broker.cache.get(group_key) or []
# if it's an inter group, check if we are ready
if iter_count and len(group_list) == iter_count-1:
group_args = '{}:{}:args'.format(broker.list_key, group)
# collate the results into a Task result
results = [signing.SignedPackage.loads(broker.cache.get(k))['result'] for k in group_list]
results.append(task['result'])
task['result'] = results
task['id'] = group
task['args'] = signing.SignedPackage.loads(broker.cache.get(group_args))
save_task(task)
broker.cache.delete_many(group_list)
broker.cache.delete_many([group_key, group_args])
return
# save the group list
group_list.append(task_key)
broker.cache.set(group_key, group_list)
# save the task
broker.cache.set(task_key,
signing.SignedPackage.dumps(task),
timeout)
except Exception as e:
logger.error(e)
def scheduler(broker=None):
"""
Creates a task from a schedule at the scheduled time and schedules next run
+4
View File
@@ -113,6 +113,10 @@ class Conf(object):
# The Django cache to use
CACHE = conf.get('cache', 'default')
# Use the cache as result backend. Can be 'True' or an integer representing the global cache timeout.
# i.e 'cached: 60' , will make all results go the cache and expire in 60 seconds.
CACHED = conf.get('cached', False)
# If set to False the scheduler won't execute tasks in the past.
# Instead it will run once and reschedule the next run in the future. Defaults to True.
CATCH_UP = conf.get('catch_up', True)
+225 -11
View File
@@ -1,4 +1,4 @@
"""Provides task functionalities."""
"""Provides task functionality."""
from multiprocessing import Queue, Value
# django
@@ -15,7 +15,7 @@ from django_q.brokers import get_broker
def async(func, *args, **kwargs):
"""Send a task to the cluster."""
"""Queue a task for the cluster."""
# get options from q_options dict or direct from kwargs
options = kwargs.pop('q_options', kwargs)
hook = options.pop('hook', None)
@@ -23,6 +23,8 @@ def async(func, *args, **kwargs):
sync = options.pop('sync', False)
group = options.pop('group', None)
save = options.pop('save', None)
cached = options.pop('cached', Conf.CACHED)
iter_count = options.pop('iter_count', None)
# get an id
tag = uuid()
# build the task package
@@ -38,6 +40,10 @@ def async(func, *args, **kwargs):
task['group'] = group
if save is not None:
task['save'] = save
if cached:
task['cached'] = cached
if iter_count:
task['iter_count'] = iter_count
# sign it
pack = signing.SignedPackage.dumps(task)
if sync or Conf.SYNC:
@@ -83,7 +89,7 @@ def schedule(func, *args, **kwargs):
)
def result(task_id, wait=0):
def result(task_id, wait=0, cached=Conf.CACHED):
"""
Return the result of the named task.
@@ -91,9 +97,12 @@ def result(task_id, wait=0):
:param task_id: the task name or uuid
:type wait: int
:param wait: number of milliseconds to wait for a result
:param bool cached: run this against the cache backend
:return: the result object of this task
:rtype: object
"""
if cached:
return result_cached(task_id, wait)
start = time.time()
while True:
r = Task.get_result(task_id)
@@ -104,18 +113,76 @@ def result(task_id, wait=0):
time.sleep(0.01)
def result_group(group_id, failures=False):
def result_cached(task_id, wait=0, broker=None):
"""
Return the result from the cache backend
"""
if not broker:
broker = get_broker()
start = time.time()
while True:
r = broker.cache.get('{}:{}'.format(broker.list_key, task_id))
if r:
return signing.SignedPackage.loads(r)['result']
if (time.time() - start) * 1000 >= wait:
break
time.sleep(0.01)
def result_group(group_id, failures=False, wait=0, count=None, cached=Conf.CACHED):
"""
Return a list of results for a task group.
:param str group_id: the group id
:param bool failures: set to True to include failures
:param int count: Block until there are this many results in the group
:param bool cached: run this against the cache backend
:return: list or results
"""
return Task.get_result_group(group_id, failures)
if cached:
return result_group_cached(group_id, failures, wait, count)
start = time.time()
if count:
while True:
if count_group(group_id) == count or wait and (time.time() - start) * 1000 >= wait:
break
time.sleep(0.01)
while True:
r = Task.get_result_group(group_id, failures)
if r:
return r
if (time.time() - start) * 1000 >= wait:
break
time.sleep(0.01)
def fetch(task_id, wait=0):
def result_group_cached(group_id, failures=False, wait=0, count=None, broker=None):
"""
Return a list of results for a task group from the cache backend
"""
if not broker:
broker = get_broker()
start = time.time()
if count:
while True:
if count_group_cached(group_id) == count or wait and (time.time() - start) * 1000 >= wait:
break
time.sleep(0.01)
while True:
group_list = broker.cache.get('{}:{}:keys'.format(broker.list_key, group_id))
if group_list:
result_list = []
for task_key in group_list:
task = signing.SignedPackage.loads(broker.cache.get(task_key))
if task['success'] or failures:
result_list.append(task['result'])
return result_list
if (time.time() - start) * 1000 >= wait:
break
time.sleep(0.01)
def fetch(task_id, wait=0, cached=Conf.CACHED):
"""
Return the processed task.
@@ -123,9 +190,12 @@ def fetch(task_id, wait=0):
:type task_id: str or uuid
:param wait: the number of milliseconds to wait for a result
:type wait: int
:param bool cached: run this against the cache backend
:return: the full task object
:rtype: Task
"""
if cached:
return fetch_cached(task_id, wait)
start = time.time()
while True:
t = Task.get_task(task_id)
@@ -136,45 +206,169 @@ def fetch(task_id, wait=0):
time.sleep(0.01)
def fetch_group(group_id, failures=True):
def fetch_cached(task_id, wait=0, broker=None):
"""
Return the processed task from the cache backend
"""
if not broker:
broker = get_broker()
start = time.time()
while True:
r = broker.cache.get('{}:{}'.format(broker.list_key, task_id))
if r:
task = signing.SignedPackage.loads(r)
t = Task(id=task['id'],
name=task['name'],
func=task['func'],
hook=task.get('hook'),
args=task['args'],
kwargs=task['kwargs'],
started=task['started'],
stopped=task['stopped'],
result=task['result'],
success=task['success'])
return t
if (time.time() - start) * 1000 >= wait:
break
time.sleep(0.01)
def fetch_group(group_id, failures=True, wait=0, count=None, cached=Conf.CACHED):
"""
Return a list of Tasks for a task group.
:param str group_id: the group id
:param bool failures: set to False to exclude failures
:param bool cached: run this against the cache backend
:return: list of Tasks
"""
return Task.get_task_group(group_id, failures)
if cached:
return fetch_group_cached(group_id, failures, wait, count)
start = time.time()
if count:
while True:
if count_group(group_id) == count or wait and (time.time() - start) * 1000 >= wait:
break
time.sleep(0.01)
while True:
r = Task.get_task_group(group_id, failures)
if r:
return r
if (time.time() - start) * 1000 >= wait:
break
time.sleep(0.01)
def count_group(group_id, failures=False):
def fetch_group_cached(group_id, failures=True, wait=0, count=None, broker=None):
"""
Return a list of Tasks for a task group in the cache backend
"""
if not broker:
broker = get_broker()
start = time.time()
if count:
while True:
if count_group_cached(group_id) == count or wait and (time.time() - start) * 1000 >= wait:
break
time.sleep(0.01)
while True:
group_list = broker.cache.get('{}:{}:keys'.format(broker.list_key, group_id))
if group_list:
task_list = []
for task_key in group_list:
task = signing.SignedPackage.loads(broker.cache.get(task_key))
if task['success'] or failures:
t = Task(id=task['id'],
name=task['name'],
func=task['func'],
hook=task.get('hook'),
args=task['args'],
kwargs=task['kwargs'],
started=task['started'],
stopped=task['stopped'],
result=task['result'],
group=task.get('group'),
success=task['success'])
task_list.append(t)
return task_list
if (time.time() - start) * 1000 >= wait:
break
time.sleep(0.01)
def count_group(group_id, failures=False, cached=Conf.CACHED):
"""
Count the results in a group.
:param str group_id: the group id
:param bool failures: Returns failure count if True
:param bool cached: run this against the cache backend
:return: the number of tasks/results in a group
:rtype: int
"""
if cached:
return count_group_cached(group_id, failures)
return Task.get_group_count(group_id, failures)
def delete_group(group_id, tasks=False):
def count_group_cached(group_id, failures=False, broker=None):
"""
Count the results in a group in the cache backend
"""
if not broker:
broker = get_broker()
group_list = broker.cache.get('{}:{}:keys'.format(broker.list_key, group_id))
if group_list:
if not failures:
return len(group_list)
failure_count = 0
for task_key in group_list:
task = signing.SignedPackage.loads(broker.cache.get(task_key))
if not task['success']:
failure_count += 1
return failure_count
def delete_group(group_id, tasks=False, cached=Conf.CACHED):
"""
Delete a group.
:param str group_id: the group id
:param bool tasks: If set to True this will also delete the group tasks.
Otherwise just the group label is removed.
:param bool cached: run this against the cache backend
:return:
"""
if cached:
return delete_group_cached(group_id)
return Task.delete_group(group_id, tasks)
def delete_group_cached(group_id, broker=None):
"""
Delete a group from the cache backend
"""
if not broker:
broker = get_broker()
group_key = '{}:{}:keys'.format(broker.list_key, group_id)
group_list = broker.cache.get(group_key)
broker.cache.delete_many(group_list)
broker.cache.delete(group_key)
def delete_cached(task_id, broker=None):
"""
Delete a task from the cache backend
"""
if not broker:
broker = get_broker()
return broker.cache.delete('{}:{}'.format(broker.list_key, task_id))
def queue_size(broker=None):
"""
Returns the current queue size.
Note that this doesn't count any tasks currently being processed by workers.
Note that this doesn't count any tasks curren key = 'django_q:{}:results'.format(broker.list_key)tly being processed by workers.
:param broker: optional broker
:return: current queue size
@@ -185,6 +379,26 @@ def queue_size(broker=None):
return broker.queue_size()
def async_iter(func, args_iter, **kwargs):
iter_count = len(args_iter)
iter_group = uuid()[1]
# clean up the kwargs
options = kwargs.get('q_options', kwargs)
options.pop('hook', None)
options['broker'] = options.get('broker', get_broker())
options['group'] = iter_group
options['iter_count'] = iter_count
options['cached'] = True
# save the original arguments
broker = options['broker']
broker.cache.set('{}:{}:args'.format(broker.list_key, iter_group), signing.SignedPackage.dumps(args_iter))
for args in args_iter:
if type(args) is not tuple:
args = (args,)
async(func, *args, **options)
return iter_group
def _sync(pack):
"""Simulate a package travelling through the cluster."""
task_queue = Queue()
+87
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@@ -0,0 +1,87 @@
from multiprocessing import Event
import pytest
from django_q.cluster import Sentinel
from django_q.conf import Conf
from django_q.tasks import async, result, fetch, count_group, result_group, fetch_group, delete_group, delete_cached, \
async_iter
from django_q.brokers import get_broker
@pytest.fixture
def broker():
Conf.DISQUE_NODES = None
Conf.IRON_MQ = None
Conf.SQS = None
Conf.ORM = None
Conf.MONGO = None
Conf.DJANGO_REDIS = 'default'
return get_broker()
@pytest.mark.django_db
def test_cached(broker):
broker.purge_queue()
broker.cache.clear()
group = 'cache_test'
# queue the tests
task_id = async('math.copysign', 1, -1, cached=True, broker=broker)
async('math.copysign', 1, -1, cached=True, broker=broker, group=group)
async('math.copysign', 1, -1, cached=True, broker=broker, group=group)
async('math.copysign', 1, -1, cached=True, broker=broker, group=group)
async('math.copysign', 1, -1, cached=True, broker=broker, group=group)
async('math.copysign', 1, -1, cached=True, broker=broker, group=group)
async('math.popysign', 1, -1, cached=True, broker=broker, group=group)
# test wait on cache
# test wait timeout
assert result(task_id, wait=10, cached=True) is None
assert fetch(task_id, wait=10, cached=True) is None
assert result_group(group, wait=10, cached=True) is None
assert result_group(group, count=2, wait=10, cached=True) is None
assert fetch_group(group, wait=10, cached=True) is None
assert fetch_group(group, count=2, wait=10, cached=True) is None
# run a single cluster
start_event = Event()
stop_event = Event()
stop_event.set()
Sentinel(stop_event, start_event, broker=broker)
# assert results
assert result(task_id, wait=500, cached=True) == -1
assert fetch(task_id, wait=500, cached=True).result == -1
# make sure it's not in the db backend
assert fetch(task_id) is None
# assert group
assert count_group(group, cached=True) == 6
assert count_group(group, cached=True, failures=True) == 1
assert result_group(group, cached=True) == [-1, -1, -1, -1, -1]
assert len(result_group(group, cached=True, failures=True)) == 6
assert len(fetch_group(group, cached=True)) == 6
assert len(fetch_group(group, cached=True, failures=False)) == 5
delete_group(group, cached=True)
assert count_group(group, cached=True) is None
delete_cached(task_id)
assert result(task_id, cached=True) is None
assert fetch(task_id, cached=True) is None
broker.cache.clear()
@pytest.mark.django_db
def test_iter(broker):
broker.purge_queue()
broker.cache.clear()
it = [i for i in range(10)]
it2 = [(1, -1), (2, -1), (3, -4), (5, 6)]
it3 = (1, 2, 3, 4, 5)
t = async_iter('math.floor', it, sync=True)
t2 = async_iter('math.copysign', it2, sync=True)
t3 = async_iter('math.floor', it3, sync=True)
t4 = async_iter('math.floor', (1,), sync=True)
result_t = result(t)
assert result_t is not None
task_t = fetch(t)
assert task_t. __unicode__ is not None
assert task_t.result == result_t
assert result(t2) is not None
assert result(t3) is not None
assert result(t4)[0] == 1
+7
View File
@@ -160,6 +160,13 @@ def test_async(broker, admin_user):
assert broker.queue_size() == 0
assert task_queue.qsize() == task_count
task_queue.put('STOP')
# test wait timeout
assert result(j, wait=10) is None
assert fetch(j, wait=10) is None
assert result_group('test_j', wait=10) is None
assert result_group('test_j', count=2, wait=10) is None
assert fetch_group('test_j', wait=10) is None
assert fetch_group('test_j', count=2, wait=10) is None
# let a worker handle them
result_queue = Queue()
worker(task_queue, result_queue, Value('f', -1))
+7
View File
@@ -308,6 +308,13 @@ cache
For some brokers, you will need to set up the Django `cache framework <https://docs.djangoproject.com/en/1.8/topics/cache/#setting-up-the-cache>`__
to gather statistics for the monitor. You can indicate which cache to use by setting this value. Defaults to ``default``.
.. _cached:
cached
~~~~~~
Switches all task and result functions from using the database backend to the cache backend. This is the same as setting the keyword ``cached=True`` on all task functions.
Instead of a bool this can also be set to the number of seconds you want the cache to retain results. e.g. ``cached=60``
scheduler
~~~~~~~~~
You can disable the scheduler by setting this option to ``False``. This will reduce a little overhead if you're not using schedules, but is most useful if you want to temporarily disable all schedules.
+27 -11
View File
@@ -253,8 +253,7 @@ Adapted from `Sebastian Raschka's blog <http://sebastianraschka.com/Articles/201
# Group example with Parzen-window estimation
import numpy
from django_q.tasks import async, result_group,\
count_group, delete_group
from django_q.tasks import async, result_group, delete_group
# the estimation function
def parzen_estimation(x_samples, point_x, h):
@@ -268,30 +267,47 @@ Adapted from `Sebastian Raschka's blog <http://sebastianraschka.com/Articles/201
k_n += 1
return h, (k_n / len(x_samples)) / (h ** point_x.shape[1])
# create 100 calculations and send them to the cluster
def parzen_async():
# clear the previous results
delete_group('parzen', tasks=True)
delete_group('parzen', cached=True)
mu_vec = numpy.array([0, 0])
cov_mat = numpy.array([[1, 0], [0, 1]])
sample = numpy.random.\
sample = numpy.random. \
multivariate_normal(mu_vec, cov_mat, 10000)
widths = numpy.linspace(1.0, 1.2, 100)
x = numpy.array([[0], [0]])
# async them with a group label and a hook
# async them with a group label to the cache backend
for w in widths:
async(parzen_estimation, sample, x, w,
group='parzen', hook=parzen_hook)
group='parzen', cached=True)
# return after 100 results
return result_group('parzen', count=100, cached=True)
# wait for 100 results to return and print it.
def parzen_hook(task):
if task.group_count() == 100:
print(task.group_result())
Django Q is not optimized for distributed computing, but this example will give you an idea of what you can do with task :ref:`groups`.
Alternatively the ``parzen_async()`` function can also be written with :func:`async_iter`, which automatically utilizes the cache backend and groups to return a single result from an iterable:
.. code-block:: python
# create 100 calculations and send them to the cluster
# with async_iter
def parzen_async():
mu_vec = numpy.array([0, 0])
cov_mat = numpy.array([[1, 0], [0, 1]])
sample = numpy.random. \
multivariate_normal(mu_vec, cov_mat, 10000)
widths = numpy.linspace(1.0, 1.2, 100)
x = numpy.array([[0], [0]])
# async them with async iterable
args = [(sample, x, w) for w in widths]
result_id = async_iter(parzen_estimation, args)
# return the result or timeout after 10 seconds
return result(result_id, wait=10000)
.. note::
If you have an example you want to share, please submit a pull request on `github <https://github.com/Koed00/django-q/>`__.
+1 -1
View File
@@ -15,7 +15,7 @@ Features
- Asynchronous tasks
- Scheduled and repeated tasks
- Encrypted and compressed packages
- Failure and success database
- Failure and success database or cache
- Result hooks and groups
- Django Admin integration
- PaaS compatible with multiple instances
+117 -10
View File
@@ -59,6 +59,12 @@ sync
Simulates a task execution synchronously. Useful for testing.
Can also be forced globally via the :ref:`sync` configuration option.
cached
""""""
Redirects the result to the cache backend instead of the database if set to ``True`` or to an integer indicating the cache timeout in seconds.
e.g. ``cached=60``. Especially useful with large and group operations where you don't need the all results in your
database and want to take advantage of the speed of your cache backend.
broker
""""""
A broker instance, in case you want to control your own connections.
@@ -83,6 +89,28 @@ Please not that this will override any other option keywords.
For tasks to be processed you will need to have a worker cluster running in the background using ``python manage.py qcluster``
or you need to configure Django Q to run in synchronous mode for testing using the :ref:`sync` option.
Async Iterable
--------------
If you have an iterable object with arguments for a function, you can use :func:`async_iter` to async them with a single command::
# Async Iterable example
from django_q.tasks import async_iter, result
# set up a list of arguments for math.floor
iter = [i for i in range(100)]
# async iter them
id=async_iter('math.floor',iter)
# wait for the collated result for 1 second
result_list = result(id, wait=1000)
This will individually queue 100 tasks to the worker cluster, which will save their results in the cache backend for speed.
Once all the 100 results are in the cache, they are collated into a list and saved as a single result in the database. The cache results are then cleared.
Needs the Django cache framework.
.. _groups:
Groups
@@ -97,14 +125,16 @@ You can group together results by passing :func:`async` the optional ``group`` k
for i in range(4):
async('math.modf', i, group='modf')
# after the tasks have finished you can get the group results
result = result_group('modf')
# wait until the group has 4 results
result = result_group('modf', count=4)
print(result)
.. code-block:: python
[(0.0, 0.0), (0.0, 1.0), (0.0, 2.0), (0.0, 3.0)]
Note that the same can be achieved much faster with :func:`async_iter`
Take care to not limit your results database too much and call :func:`delete_group` before each run, unless you want your results to keep adding up.
Instead of :func:`result_group` you can also use :func:`fetch_group` to return a queryset of :class:`Task` objects.:
@@ -149,6 +179,54 @@ You can also access group functions from a task result instance:
task.group_delete()
print('Deleted group {}'.format(task.group))
Cached operations
-----------------
You can run your tasks results against the Django cache backend instead of the database backend by either using the global :ref:`cached` setting or by supplying the ``cached`` keyword to individual functions.
This can be useful if you are not interested in persistent results or if you run large group tasks where you only want the final result.
By using a cache backend like Redis or Memcached you can speed up access to your task results significantly compared to a relational database.
When you set ``cached=True``, results will be saved permanently in the cache and you will have to rely on your backend's cleanup strategies (like LRU) to
manage stale results.
You can also opt to set a manual timeout on the results, by setting ``cached=60``. Meaning the result will be evicted from the cache after 60 seconds.
This works both globally or on individual async executions.::
# simple cached example
from django_q.tasks import async, result
# cache the result for 10 seconds
id = async('math.floor', 100, cached=10)
# wait max 50ms for the result to appear in the cache
result(id, wait=50, cached=True)
# o fetch the task object
task = fetch(id, cache=True)
# and then save it to the database
task.save()
This also works for group actions::
# cached group example
from django_q.tasks import async, result_group
from django_q.brokers import get_broker
# set up a broker instance for better performance
broker = get_broker()
# async a hundred functions under a group label
for i in range(100):
async('math.frexp',
i,
group='frexp',
cached=True,
broker=broker)
# wait max 50ms for one hundred results to return
result_group('frexp', wait=50, count=100, cached=True)
Note that exact same result can be achieved by using the more convenient :func:`async_iter` in this case, but without hook support.
Synchronous testing
-------------------
@@ -199,7 +277,7 @@ Reference
---------
.. py:function:: async(func, *args, hook=None, group=None, timeout=None,\
save=None, sync=False, broker=None, q_options=None, **kwargs)
save=None, sync=False, cached=False, broker=None, q_options=None, **kwargs)
Puts a task in the cluster queue
@@ -210,26 +288,29 @@ Reference
:param int timeout: Overrides global cluster :ref:`timeout`.
:param bool save: Overrides global save setting for this task.
:param bool sync: If set to True, async will simulate a task execution
:param cached: Output the result to the cache backend. Bool or timeout in seconds
:param broker: Optional broker connection from :func:`brokers.get_broker`
:param dict q_options: Options dict, overrides option keywords
:param dict kwargs: Keyword arguments for the task function
:returns: The uuid of the task
:rtype: str
.. py:function:: result(task_id, wait=0)
.. py:function:: result(task_id, wait=0, cached=False)
Gets the result of a previously executed task
:param str task_id: the uuid or name of the task
:param int wait: optional milliseconds to wait for a result
:param bool cached: run this against the cache backend.
:returns: The result of the executed task
.. py:function:: fetch(task_id, wait=0)
.. py:function:: fetch(task_id, wait=0, cached=False)
Returns a previously executed task
:param str name: the uuid or name of the task
:param int wait: optional milliseconds to wait for a result
:param bool cached: run this against the cache backend.
:returns: A task object
:rtype: Task
@@ -237,6 +318,16 @@ Reference
Renamed from get_task
.. py:function:: async_iter(func, args_iter,**kwargs)
Runs iterable arguments against the cache backend and returns a single collated result
:param object func: The task function to execute
:param args: An iterable containing arguments for the task function
:param dict kwargs: Keyword arguments for the task function. Ignores ``cached`` and ``hook``.
:returns: The uuid of the task
:rtype: str
.. py:function:: queue_size()
Returns the size of the broker queue.
@@ -245,42 +336,58 @@ Reference
:returns: The amount of task packages in the broker
:rtype: int
.. py:function:: result_group(group_id, failures=False)
.. py:function:: result_group(group_id, failures=False, wait=0, count=None, cached=False)
Returns the results of a task group
:param str group_id: the group identifier
:param bool failures: set this to ``True`` to include failed results
:param int wait: optional milliseconds to wait for a result or count
:param int count: block until there are this many results in the group
:param bool cached: run this against the cache backend
:returns: a list of results
:rtype: list
.. py:function:: fetch_group(group_id, failures=True)
.. py:function:: fetch_group(group_id, failures=True, wait=0, count=None, cached=False)
Returns a list of tasks in a group
:param str group_id: the group identifier
:param bool failures: set this to ``False`` to exclude failed tasks
:returns: a list of Tasks
:param int wait: optional milliseconds to wait for a task or count
:param int count: block until there are this many tasks in the group
:param bool cached: run this against the cache backend.
:returns: a list of :class:`Task`
:rtype: list
.. py:function:: count_group(group_id, failures=False)
.. py:function:: count_group(group_id, failures=False, cached=False)
Counts the number of task results in a group.
:param str group_id: the group identifier
:param bool failures: counts the number of failures if ``True``
:param bool cached: run this against the cache backend.
:returns: the number of tasks or failures in a group
:rtype: int
.. py:function:: delete_group(group_id, tasks=False)
.. py:function:: delete_group(group_id, tasks=False, cached=False)
Deletes a group label from the database.
:param str group_id: the group identifier
:param bool tasks: also deletes the associated tasks if ``True``
:param bool cached: run this against the cache backend.
:returns: the numbers of tasks affected
:rtype: int
.. py:function:: delete_cached(task_id, broker=None)
Deletes a task from the cache backend
:param task_id: the uuid of the task
:param broker: an optional broker instance
.. py:class:: Task
Database model describing an executed task