Usage¶

Enqueue jobs from code¶

from scheduler import job


@job
def long_running_func():
    pass


long_running_func.delay()  # Enqueue function in "default" queue

Specifying the queue where the job should be queued:

@job('high')
def long_running_func():
    pass


long_running_func.delay()  # Enqueue function in "high" queue

You can pass in any arguments that RQ's job decorator accepts:

from scheduler import job


@job('default', timeout=3600)
def long_running_func():
    pass


long_running_func.delay()  # Enqueue function with a timeout of 3600 seconds.

You can set in settings.py a default value for DEFAULT_RESULT_TTL and DEFAULT_TIMEOUT.

# settings.py
SCHEDULER_CONFIG = {
    'DEFAULT_RESULT_TTL': 360,
    'DEFAULT_TIMEOUT': 60,
}

Scheduling a job Through django-admin¶

Sign in to the Django Admin site (e.g., http://localhost:8000/admin/) and locate the Tasks Scheduler section.
Click on the Add link for the type of job you want to add (Scheduled Task - run once, Repeatable Task - run multiple times, Cron Task - Run based on cron schedule).
Enter a unique name for the job in the Name field.
In the Callable field, enter a Python dot notation path to the method that defines the job. For the example
above, that would be myapp.jobs.count
Choose your Queue. The queues listed are defined in your app settings.py under SCHEDULER_QUEUES.
Enter the time in UTC the job is to be executed in the Scheduled time field.

Optional fields:¶

Select whether the job should take priority over existing queued jobs when it is queued (jobs waiting to be executed) by using at front.
Timeout specifies the maximum time in seconds the job is allowed to run. blank value means it can run forever.
Result TTL (Time to live): The time to live value (in seconds) of the job result.
- -1: Result never expires, you should delete jobs manually.
- 0: Result gets deleted immediately.
- n (where n > 0) : Result expires after n seconds.

Once you are done, click Save and your job will be persisted to django database.

Support for arguments for jobs¶

django-tasks-scheduler supports scheduling jobs calling methods with arguments, as well as arguments that should be calculated in runtime.

Scheduled Task: run once¶

No additional steps are required.

Repeatable Task: Run a job multiple time based on interval¶

These additional fields are required:

Enter an Interval, and choose the Interval unit. This will calculate the time before the function is called
again.
In the Repeat field, enter the number of time the job is to be run. Leaving the field empty, means the job will
be scheduled to run forever.

Cron Task: Run a job multiple times based on cron¶

These additional fields are required:

In the Repeat field, enter the number of time the job is to be run. Leaving the field empty, means the job will be scheduled to run forever.
In the cron string field, enter a cron string describing how often the job should run.

Enqueue jobs using the command line¶

It is possible to queue a job to be executed from the command line using django management command:

python manage.py run_job -q {queue} -t {timeout} -r {result_ttl} {callable} {args}

Running a worker to process queued jobs in the background¶

Create a worker to execute queued jobs on specific queues using:

python manage.py rqworker [-h] [--pid PIDFILE] [--burst] [--name NAME] [--worker-ttl WORKER_TTL] [--max-jobs MAX_JOBS] [--fork-job-execution FORK_JOB_EXECUTION]
                          [--job-class JOB_CLASS] [--version] [-v {0,1,2,3}] [--settings SETTINGS] [--pythonpath PYTHONPATH] [--traceback] [--no-color] [--force-color]
                          [--skip-checks]
                          [queues ...]

More information about the different parameters can be found in the commands documentation.

Running multiple workers as unix/linux services using systemd¶

You can have multiple workers running as system services. To have multiple rqworkers, edit the /etc/systemd/system/rqworker@.service file, make sure it ends with @.service, the following is example:

# /etc/systemd/system/rqworker@.service
[Unit]
Description = rqworker daemon
After = network.target

[Service]
WorkingDirectory = {{ path_to_your_project_folder } }
ExecStart = /home/ubuntu/.virtualenv/{ { your_virtualenv } }/bin/python \
            {{ path_to_your_project_folder } }/manage.py \
            rqworker high default low
# Optional 
# {{user to run rqworker as}}
User = ubuntu
# {{group to run rqworker as}}
Group = www-data
# Redirect logs to syslog
StandardOutput = syslog
StandardError = syslog
SyslogIdentifier = rqworker
Environment = OBJC_DISABLE_INITIALIZE_FORK_SAFETY = YES
Environment = LC_ALL = en_US.UTF-8
Environment = LANG = en_US.UTF-8

[Install]
WantedBy = multi-user.target

After you are done editing the file, reload the settings and start the new workers:

sudo systemctl daemon-reload
sudo systemctl start rqworker@{1..3}

You can target a specific worker using its number:

sudo systemctl stop rqworker@2