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For some use cases it might be useful have access to the current job ID or instance from within the job function itself. Or to store arbitrary data on jobs.

RQ’s Job Object

Job Creation

When you enqueue a function, a job will be returned. You may then access the id property, which can later be used to retrieve the job.

from rq import Queue
from redis import Redis
from somewhere import count_words_at_url

redis_conn = Redis()
q = Queue(connection=redis_conn)  # no args implies the default queue

# Delay execution of count_words_at_url('')
job = q.enqueue(count_words_at_url, '')
print('Job id: %s' %

Or if you want a predetermined job id, you may specify it when creating the job.

job = q.enqueue(count_words_at_url, '', job_id='my_job_id')

A job can also be created directly with Job.create().

from rq.job import Job

job = Job.create(count_words_at_url, '')
print('Job id: %s' %

# create a job with a predetermined id
job = Job.create(count_words_at url, '', id='my_job_id')

The keyword arguments accepted by create() are:

In the last case, if you want to pass description and ttl keyword arguments to your job and not to RQ’s enqueue function, this is what you do:

job = Job.create(count_words_at_url,
          ttl=30,  # This ttl will be used by RQ
              'description': 'Function description', # This is passed on to count_words_at_url
              'ttl': 15  # This is passed on to count_words_at_url function

Retrieving Jobs

All job information is stored in Redis. You can inspect a job and its attributes by using Job.fetch().

from redis import Redis
from rq.job import Job

redis = Redis()
job = Job.fetch('my_job_id', connection=redis)
print('Status: %s' % job.get_status())

Some interesting job attributes include:

If you want to efficiently fetch a large number of jobs, use Job.fetch_many().

jobs = Job.fetch_many(['foo_id', 'bar_id'], connection=redis)
for job in jobs:
    print('Job %s: %s' % (, job.func_name))

Job Status

The status of a job can be one of the following:

These statuses can also be accessed from the job object using boolean properties, such as job.is_finished.

Stopping a Currently Executing Job

New in version 1.7.0

You can use send_stop_job_command() to tell a worker to immediately stop a currently executing job. A job that’s stopped will be sent to FailedJobRegistry.

from redis import Redis
from rq.command import send_stop_job_command

redis = Redis()

# This will raise an exception if job is invalid or not currently executing
send_stop_job_command(redis, job_id)

Unlike failed jobs, stopped jobs will not be automatically retried if retry is configured. Subclasses of Worker which override handle_job_failure() should likewise take care to handle jobs with a stopped status appropriately.

Canceling a Job

New in version 1.10.0

To prevent a job from running, cancel a job, use job.cancel().

from redis import Redis
from rq.job import Job
from rq.registry import CanceledJobRegistry
from .queue import Queue

redis = Redis()
job = Job.fetch('my_job_id', connection=redis)

job.get_status()  # Job status is CANCELED

registry = CanceledJobRegistry(job.origin, connection=job.connection)
print(job in registry)  # Job is in CanceledJobRegistry

Canceling a job will remove:

  1. Sets job status to CANCELED
  2. Removes job from queue
  3. Puts job into CanceledJobRegistry

Note that job.cancel() does not delete the job itself from Redis. If you want to delete the job from Redis and reclaim memory, use job.delete().

Note: if you want to enqueue the dependents of the job you are trying to cancel use the following:

from rq import cancel_job

Job / Queue Creation with Custom Serializer

When creating a job or queue, you can pass in a custom serializer that will be used for serializing / de-serializing job arguments. Serializers used should have at least loads and dumps method. The default serializer used is pickle.

from rq import Queue
from rq.job import Job
from rq.serializers import JSONSerializer

job = Job(id="my-job", connection=connection, serializer=JSONSerializer)
queue = Queue(connection=connection, serializer=JSONSerializer)

Accessing The “current” Job from within the job function

Since job functions are regular Python functions, you must retrieve the job in order to inspect or update the job’s attributes. To do this from within the function, you can use:

from rq import get_current_job

def add(x, y):
    job = get_current_job()
    print('Current job: %s' % (,))
    return x + y

Note that calling get_current_job() outside of the context of a job function will return None.

Storing arbitrary data on jobs

Improved in 0.8.0.

To add/update custom status information on this job, you have access to the meta property, which allows you to store arbitrary pickleable data on the job itself:

import socket

def add(x, y):
    job = get_current_job()
    job.meta['handled_by'] = socket.gethostname()

    # do more work
    return x + y

Time to live for job in queue

A job has two TTLs, one for the job result, result_ttl, and one for the job itself, ttl. The latter is used if you have a job that shouldn’t be executed after a certain amount of time.

# When creating the job:
job = Job.create(func=say_hello,
                 result_ttl=600,  # how long (in seconds) to keep the job (if successful) and its results
                 ttl=43,  # maximum queued time (in seconds) of the job before it's discarded.

# or when queueing a new job:
job = q.enqueue(count_words_at_url,
                result_ttl=600,  # how long to keep the job (if successful) and its results
                ttl=43  # maximum queued time

Job Position in Queue

For user feedback or debuging it is possible to get the position of a job within the work queue. This allows to track the job processing through the queue.

This function iterates over all jobs within the queue and therefore does perform poorly on very large job queues.

from rq import Queue
from redis import Redis
from hello import say_hello

redis_conn = Redis()
q = Queue(connection=redis_conn)

job = q.enqueue(say_hello)
job2 = q.enqueue(say_hello)

# returns 1

# return 0

Failed Jobs

If a job fails during execution, the worker will put the job in a FailedJobRegistry. On the Job instance, the is_failed property will be true. FailedJobRegistry can be accessed through queue.failed_job_registry.

from redis import Redis
from rq import Queue
from rq.job import Job

def div_by_zero(x):
    return x / 0

connection = Redis()
queue = Queue(connection=connection)
job = queue.enqueue(div_by_zero, 1)
registry = queue.failed_job_registry

worker = Worker([queue])

assert len(registry) == 1  # Failed jobs are kept in FailedJobRegistry

By default, failed jobs are kept for 1 year. You can change this by specifying failure_ttl (in seconds) when enqueueing jobs.

job = queue.enqueue(foo_job, failure_ttl=300)  # 5 minutes in seconds

Requeuing Failed Jobs

If you need to manually requeue failed jobs, here’s how to do it:

from redis import Redis
from rq import Queue

connection = Redis()
queue = Queue(connection=connection)
registry = queue.failed_job_registry

# This is how to get jobs from FailedJobRegistry
for job_id in registry.get_job_ids():
    registry.requeue(job_id)  # Puts job back in its original queue

assert len(registry) == 0  # Registry will be empty when job is requeued

Starting from version 1.5.0, RQ also allows you to automatically retry failed jobs.

Requeuing Failed Jobs via CLI

RQ also provides a CLI tool that makes requeuing failed jobs easy.

# This will requeue foo_job_id and bar_job_id from myqueue's failed job registry
rq requeue --queue myqueue -u redis://localhost:6379 foo_job_id bar_job_id

# This command will requeue all jobs in myqueue's failed job registry
rq requeue --queue myqueue -u redis://localhost:6379 --all