A Django app to run new background tasks from either admin or cron, and inspect task history from admin
Project description
A Django app to run new background tasks from either admin or cron, and inspect task history from admin
Documentation
TODO
The full documentation is at https://django-task.readthedocs.io.
Quickstart
Install Django Task:
pip install django-task
Add it to your INSTALLED_APPS:
INSTALLED_APPS = (
...
'django_rq',
'django_task',
...
)Add Django Task’s URL patterns:
urlpatterns = [
...
url(r'^django_task/', include('django_task.urls', namespace='django_task')),
...
]Features
Purposes
create async tasks programmatically
create and monitor async tasks from admin
log all tasks in the database for later inspection
Details
each specific job is described my a Model derived from models.Task, which is responsible for:
selecting the name for the consumer queue among available queues
collecting and saving all parameters required by the associated job
running the specific job asyncronously
a new job can be run either:
creating a Task from the Django admin
creating a Task from code, then calling Task.run()
scheduling directly the executio of a job; i.e.: count_beans.delay(100)
In the latter case, a new Task is automatically created by the job for logging purposes.
job responsibilities (optional):
Before execution, each job will either recover or create a corresponding tasks
During execution, the job can notify the state and progress to the app by calling Task.set_state() and Task.set_progress()
See example.jobs.count_beans for an example
Execute
Run consumer:
python manage.py runserverRun worker(s):
python manage.py rqworker low high default
python manage.py rqworker low high default
...Howto separate jobs for different instances on the same machine
To sepatare jobs for different instances on the same machine (or more precisely for the same redis connection), override queues names for each instance;
for example:
# file "settings.py"
#
# RQ config
#
SESSION_COOKIE_NAME = 'primary_sid'
REDIS_URL = 'redis://localhost:6379/0'
RQ_PREFIX = "primary_"
QUEUE_DEFAULT = RQ_PREFIX + 'default'
...
RQ_QUEUES = {
QUEUE_DEFAULT: {
'URL': REDIS_URL,
'DEFAULT_TIMEOUT': 360,
},
...
}
RQ_SHOW_ADMIN_LINK = Truethen run worker as follows:
python manage.py rqworker primary_defaultHowto run jobs programmatically
python manage.py shellthen:
from .jobs import count_beans
count_beans.delay(num_beans=1000)or, for finer control:
import django_rq
from .jobs import count_beans
queue = django_rq.get_queue('high')
queue.enqueue(count_beans, num_beans=1000)Howto schedule jobs with cron
Call management command ‘count_beans’, which in turn executes the required job.
For example:
SHELL=/bin/bash
PATH=/usr/local/sbin:/usr/local/bin:/sbin:/bin:/usr/sbin:/usr/bin
0 * * * * {{username}} timeout 55m {{django.pythonpath}}/python {{django.website_home}}/manage.py count_beans 1000 >> {{django.logto}}/cron.log 2>&1
A base class TaskCommand has been provided to simplify the creation of any specific task-related management commad;
a derived management command is only responsible for:
defining suitable command-line parameters
selecting the specific Task class and job function
for example:
from django_task.task_command import TaskCommand
class Command(TaskCommand):
def add_arguments(self, parser):
super(Command, self).add_arguments(parser)
parser.add_argument('num_beans', type=int)
def handle(self, *args, **options):
from tasks.models import CountBeansTask
self.run_task(CountBeansTask, **options)
# or:
# from tasks.jobs import count_beans
# self.run_job(CountBeansTask, count_beans, **options)Screenshots
Running Tests
TODO
Does the code actually work?
source <YOURVIRTUALENV>/bin/activate (myenv) $ pip install tox (myenv) $ tox
Credits
References:
Tools used in rendering this package:
History
0.1.5
fixes for Django 1.10
send_email management command example added
0.1.4
Fix OneToOneRel import for Django < 1.9
0.1.3
Polymorphic behaviour or Task.get_child() restored
0.1.2
TaskCommand.run_task() renamed as TaskCommand.run_job()
New TaskCommand.run_task() creates a Task, then runs it; this guarantees that something is traced even when background job will fail
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