Tasks

async()

Use async() from your code to quickly offload tasks to the Cluster:

from django_q.tasks import async, result

# create the task
async('math.copysign', 2, -2)

# or with import and storing the id
import math.copysign

task_id = async(copysign, 2, -2)

# get the result
task_result = result(task_id)

# result returns None if the task has not been executed yet
# you can wait for it
task_result = result(task_id, 200)

# but in most cases you will want to use a hook:

async('math.modf', 2.5, hook='hooks.print_result')

# hooks.py
def print_result(task):
    print(task.result)

async() can take the following optional keyword arguments:

hook

The function to call after the task has been executed. This function gets passed the complete Task object as its argument.

group

A group label. Check Groups for group functions.

save

Overrides the result backend’s save setting for this task.

timeout

Overrides the cluster’s timeout setting for this task.

ack_failure

Overrides the cluster’s ack_failures setting for this task.

sync

Simulates a task execution synchronously. Useful for testing. Can also be forced globally via the 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.

task_name

Optionally overwrites the auto-generated task name.

q_options

None of the option keywords get passed on to the task function. As an alternative you can also put them in a single keyword dict named q_options. This enables you to use these keywords for your function call:

# Async options in a dict

opts = {'hook': 'hooks.print_result',
        'group': 'math',
        'timeout': 30}

async('math.modf', 2.5, q_options=opts)

Please note that this will override any other option keywords.

Note

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 sync option.

Async

Optionally you can use the Async class to instantiate a task and keep everything in a single object.:

# Async class instance example
from django_q.tasks import Async

# instantiate an async task
a = Async('math.floor', 1.5, group='math')

# you can set or change keywords afterwards
a.cached = True

# run it
a.run()

# wait indefinitely for the result and print it
print(a.result(wait=-1))

# change the args
a.args = (2.5,)

# run it again
a.run()

# wait max 10 seconds for the result and print it

print(a.result(wait=10))
1
2

Once you change any of the parameters of the task after it has run, the result is invalidated and you will have to Async.run() it again to retrieve a new result.

Cached operations

You can run your tasks results against the Django cache backend instead of the database backend by either using the global 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 e.g. 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)

# or fetch the task object
task = fetch(id, cached=True)

# and then save it to the database
task.save()

As you can see you can easily turn a cached result into a permanent database result by calling save() on it.

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)

If you don’t need hooks, that exact same result can be achieved by using the more convenient async_iter().

Synchronous testing

async() can be instructed to execute a task immediately by setting the optional keyword sync=True. The task will then be injected straight into a worker and the result saved by a monitor instance:

from django_q.tasks import async, fetch

# create a synchronous task
task_id = async('my.buggy.code', sync=True)

# the task will then be available immediately
task = fetch(task_id)

# and can be examined
if not task.success:
    print('An error occurred: {}'.format(task.result))
An error occurred: ImportError("No module named 'my'",)

Note that async() will block until the task is executed and saved. This feature bypasses the broker and is intended for debugging and development. Instead of setting sync on each individual async you can also configure sync as a global override.

Connection pooling

Django Q tries to pass broker instances around its parts as much as possible to save you from running out of connections. When you are making individual calls to async() a lot though, it can help to set up a broker to reuse for async():

# broker connection economy example
from django_q.tasks import async
from django_q.brokers import get_broker

broker = get_broker()
for i in range(50):
    async('math.modf', 2.5, broker=broker)

Tip

If you are using django-redis and the redis broker, you can configure Django Q to use its connection pool.

Reference

async(func, *args, hook=None, group=None, timeout=None, save=None, sync=False, cached=False, broker=None, q_options=None, **kwargs)
Puts a task in the cluster queue
Parameters:
  • func (object) – The task function to execute
  • args (tuple) – The arguments for the task function
  • hook (object) – Optional function to call after execution
  • group (str) – An optional group identifier
  • timeout (int) – Overrides global cluster timeout.
  • save (bool) – Overrides global save setting for this task.
  • ack_failure (bool) – Overrides the global ack_failures setting for this task.
  • sync (bool) – If set to True, async will simulate a task execution
  • cached – Output the result to the cache backend. Bool or timeout in seconds
  • broker – Optional broker connection from brokers.get_broker()
  • q_options (dict) – Options dict, overrides option keywords
  • kwargs (dict) – Keyword arguments for the task function
Returns:

The uuid of the task

Return type:

str

result(task_id, wait=0, cached=False)

Gets the result of a previously executed task

Parameters:
  • task_id (str) – the uuid or name of the task
  • wait (int) – optional milliseconds to wait for a result. -1 for indefinite
  • cached (bool) – run this against the cache backend.
Returns:

The result of the executed task

fetch(task_id, wait=0, cached=False)

Returns a previously executed task

Parameters:
  • task_id (str) – the uuid or name of the task
  • wait (int) – optional milliseconds to wait for a result. -1 for indefinite
  • cached (bool) – run this against the cache backend.
Returns:

A task object

Return type:

Task

Changed in version 0.2.0.

Renamed from get_task

queue_size()

Returns the size of the broker queue. Note that this does not count tasks currently being processed.

Returns:The amount of task packages in the broker
Return type:int
delete_cached(task_id, broker=None)

Deletes a task from the cache backend

Parameters:
  • task_id (str) – the uuid of the task
  • broker – an optional broker instance
class Task

Database model describing an executed task

id

An uuid.uuid4() identifier

name

The name of the task as a humanized version of the id

Note

This is for convenience and can be used as a parameter for most functions that take a task_id. Keep in mind that it is not guaranteed to be unique if you store very large amounts of tasks in the database.

func

The function or reference that was executed

hook

The function to call after execution.

args

Positional arguments for the function.

kwargs

Keyword arguments for the function.

result

The result object. Contains the error if any occur.

started

The moment the task was created by an async command

stopped

The moment a worker finished this task

success

Was the task executed without problems?

time_taken()

Calculates the difference in seconds between started and stopped.

Note

Time taken represents the time a task spends in the cluster, this includes any time it may have waited in the queue.

group_result(failures=False)

Returns a list of results from this task’s group. Set failures to True to include failed results.

group_count(failures=False)

Returns a count of the number of task results in this task’s group. Returns the number of failures when failures=True

group_delete(tasks=False)

Resets the group label on all the tasks in this task’s group. If tasks=True it will also delete the tasks in this group from the database, including itself.

classmethod get_result(task_id)

Gets a result directly by task uuid or name.

classmethod get_result_group(group_id, failures=False)

Returns a list of results from a task group. Set failures to True to include failed results.

classmethod get_task(task_id)

Fetches a single task object by uuid or name.

classmethod get_task_group(group_id, failures=True)

Gets a queryset of tasks with this group id. Set failures to False to exclude failed tasks.

classmethod get_group_count(group_id, failures=False)

Returns a count of the number of tasks results in a group. Returns the number of failures when failures=True

classmethod delete_group(group_id, objects=False)

Deletes a group label only, by default. If objects=True it will also delete the tasks in this group from the database.

class Success

A proxy model of Task with the queryset filtered on Task.success is True.

class Failure

A proxy model of Task with the queryset filtered on Task.success is False.

class Async(func, *args, **kwargs)

A class wrapper for the async() function.

Parameters:
  • func (object) – The task function to execute
  • args (tuple) – The arguments for the task function
  • kwargs (dict) – Keyword arguments for the task function, including async options
id

The task unique identifier. This will only be available after it has been run()

started

Bool indicating if the task has been run with the current parameters

func

The task function to execute

args

A tuple of arguments for the task function

kwargs

Keyword arguments for the function. Can include any of the optional async keyword attributes directly or in a q_options dictionary.

broker

Optional Broker instance to use

sync

Run this task inline instead of asynchronous.

save

Overrides the global save setting.

hook

Optional function to call after a result is available. Takes the result Task as the first argument.

group

Optional group identifier

cached

Run the task against the cache result backend.

run()

Send the task to a worker cluster for execution

result(wait=0)

The task result. Always returns None if the task hasn’t been run with the current parameters.

param int wait:the number of milliseconds to wait for a result. -1 for indefinite
fetch(wait=0)

Returns the full Task result instance.

param int wait:the number of milliseconds to wait for a result. -1 for indefinite
result_group(failures=False, wait=0, count=None)

Returns a list of results from this task’s group.

param bool failures:
 set this to True to include failed results
param int wait:optional milliseconds to wait for a result or count. -1 for indefinite
param int count:
 block until there are this many results in the group
fetch_group(failures=True, wait=0, count=None)

Returns a list of task results from this task’s group

param bool failures:
 set this to False to exclude failed tasks
param int wait:optional milliseconds to wait for a task or count. -1 for indefinite
param int count:
 block until there are this many tasks in the group