michaelbrooks/rq-scheduler

RQ Scheduler

RQ Scheduler is a small package that adds job scheduling capabilities to RQ, a Redis based Python queuing library.

Requirements

Installation

You can install RQ Scheduler via pip:

pip install rq-scheduler

Or you can download the latest stable package from PyPI.

Usage

Schedule a job involves doing two different things:

Putting a job in the scheduler
Running a scheduler that will move scheduled jobs into queues when the time comes

Scheduling a Job

There are two ways you can schedule a job. The first is using RQ Scheduler's enqueue_at:

from rq import use_connection
from rq_scheduler import Scheduler
from datetime import datetime

use_connection() # Use RQ's default Redis connection
scheduler = Scheduler() # Get a scheduler for the "default" queue

# Puts a job into the scheduler. The API is similar to RQ except that it
# takes a datetime object as first argument. So for example to schedule a
# job to run on Jan 1st 2020 we do:
scheduler.enqueue_at(datetime(2020, 1, 1), func)

# Here's another example scheduling a job to run at a specific date and time,
# complete with args and kwargs
scheduler.enqueue_at(datetime(2020, 1, 1, 3, 4), func, foo, bar=baz)

The second way is using enqueue_in. Instead of taking a datetime object, this method expects a timedelta and schedules the job to run at X seconds/minutes/hours/days/weeks later. For example, if we want to monitor how popular a tweet is a few times during the course of the day, we could do something like:

from datetime import timedelta

# Schedule a job to run 10 minutes, 1 hour and 1 day later
scheduler.enqueue_in(timedelta(minutes=10), count_retweets, tweet_id)
scheduler.enqueue_in(timedelta(hours=1), count_retweets, tweet_id)
scheduler.enqueue_in(timedelta(days=1), count_retweets, tweet_id)

You can also explicitly pass in connection to use a different Redis server:

from redis import Redis
from rq_scheduler import Scheduler
from datetime import datetime

scheduler = Scheduler('default', connection=Redis('192.168.1.3', port=123))
scheduler.enqueue_at(datetime(2020, 01, 01, 1, 1), func)

Periodic & Repeated Jobs

As of version 0.3, RQ Scheduler also supports creating periodic and repeated jobs. You can do this via the schedule method. Note that this feature needs RQ >= 0.3.1.

This is how you do it:

scheduler.schedule(
    scheduled_time=datetime.now(), # Time for first execution
    func=func,                     # Function to be queued
    args=[arg1, arg2],             # Arguments passed into function when executed
    kwargs={'foo': 'bar'},       # Keyword arguments passed into function when executed
    interval=60,                   # Time before the function is called again, in seconds
    repeat=10                      # Repeat this number of times (None means repeat forever)
)

Retrieving scheduled jobs

Sometimes you need to know which jobs have already been scheduled. You can get a list of enqueued jobs with the get_jobs method:

list_of_job_instances = scheduler.get_jobs()

In it's simplest form (as seen in the above example) this method returns a list of all job instances that are currently scheduled for execution.

Additionally the method takes two optional keyword arguments until and with_times. The first one specifies up to which point in time scheduled jobs should be returned. It can be given as either a datetime / timedelta instance or an integer denoting the number of seconds since epoch (1970-01-01 00:00:00). The second argument is a boolen that determines whether the scheduled execution time should be returned along with the job instances.

Example:

# get all jobs until 2012-11-30 10:00:00
list_of_job_instances = scheduler.get_jobs(until=datetime(2012, 10, 30, 10))

# get all jobs for the next hour
list_of_job_instances = scheduler.get_jobs(until=timedelta(hours=1))

# get all jobs with execution times
jobs_and_times = scheduler.get_jobs(with_times=True)
# returns a list of tuples:
# [(<rq.job.Job object at 0x123456789>, datetime.datetime(2012, 11, 25, 12, 30)), ...]

Checking if a job is scheduled

You can check whether a specific job instance or job id is scheduled for execution using the familiar python in operator:

if job_instance in scheduler:
    # Do something
# or
if job_id in scheduler:
    # Do something

Canceling a job

To cancel a job, simply do:

scheduler.cancel(job)

Running the scheduler

RQ Scheduler comes with a script rqscheduler that runs a scheduler process that polls Redis once every minute and move scheduled jobs to the relevant queues when they need to be executed:

# This runs a scheduler process using the default Redis connection
rqscheduler

If you want to use a different Redis server you could also do:

rqscheduler --host localhost --port 6379 --db 0

The script accepts these arguments:

-H or --host: Redis server to connect to
-p or --port: port to connect to
-d or --db: Redis db to use
-P or --password: password to connect to Redis

Changelog

Version 0.4.0

Supports Python 3!
Scheduler.schedule now allows job timeout to be specified
rqscheduler allows Redis connection to be specified via --url argument
rqscheduler now accepts --path argument

Version 0.3.6

Scheduler key is not set to expire a few seconds after the next scheduling operation. This solves the issue of rqscheduler refusing to start after an unexpected shut down.

Version 0.3.5

Support StrictRedis

Version 0.3.4

Scheduler related job attributes (interval and repeat) are now stored in job.meta introduced in RQ 0.3.4

Version 0.3.3

You can now check whether a job is scheduled for execution using job in scheduler syntax
Added scheduler.get_jobs method
scheduler.enqueue and scheduler.enqueue_periodic will now raise a DeprecationWarning, please use scheduler.schedule instead

Version 0.3.2

Periodic jobs now require RQ >= 0.3.1

Version 0.3

Added the capability to create periodic (cron) and repeated job using scheduler.enqueue

michaelbrooks / rq-scheduler