django-gearman is a convenience wrapper for the Gearman Python Bindings.
With django-gearman, you can code jobs as well as clients in a Django project with minimal overhead in your application. Server connections etc. all take place in django-gearman and don't unnecessarily clog your application code.
It's the same for both the client and worker instances of your django project:
pip install -e git://github.com/fwenzel/django-gearman.git#egg=django-gearman
Add django_gearman to the INSTALLED_APPS section of settings.py.
Specify the following setting in your local settings.py file:
# One or more gearman servers
GEARMAN_SERVERS = ['127.0.0.1']
Create a file gearman_jobs.py in any of your django apps, and define as many
jobs as functions as you like. The jobs must accept a single argument as
passed by the caller and must return the result of the operation, if
applicable. (Note: It must accept an argument, even if you don't use it).
Mark each of these functions as gearman jobs by decorating them with
django_gearman.decorators.gearman_job.
For an example, look at the gearman_example app's gearman_jobs.py file.
The tasks are given a default name of their import path, with the phrase
'gearman_jobs' stripped out of them, for readability reasons. You can override
the task name by specifying name parameter of the decorator. Here's how:
@gearman_job(name='my-task-name')
def my_task_function(foo):
pass
The setting GEARMAN_JOB_NAME is a function which takes the original task
name as an argument and returns the gearman-internal version of that task
name. This allows you to map easily usable names in your application to more
complex, unique ones inside gearman.
The default behavior of this method is as follows:
new_task_name = '%s.%s' % (crc32(getcwd()), task_name)
This way several instances of the same application can be run on the same server. You may want to change it if you have several, independent instances of the same application run against a shared gearman server.
If you would like to change this behavior, simply define the
GEARMAN_JOB_NAME function in the settings.py:
GEARMAN_JOB_NAME = lambda name: name
which would leave the internal task name unchanged.
The gearman docs specify that the job function can accept only one parameter
(usually refered to as the data parameter). Additionally, that parameter
may only be a string. Sometimes that may not be enough. What if you would like
to pass an array or a dict? You would need to serialize and deserialize them.
Fortunately, django-gearman can take care of this, so that you can spend
all of your time on coding the actual task.
@gearman_job(name='my-task-name')
def my_task_function(foo):
pass
client.submit_job('my-task-name', {'foo': 'becomes', 'this': 'dict'})
client.submit_job('my-task-name', Decimal(1.0))
You can pass as many arguments as you want, of whatever (serializable) type you like. Here's an example job definition:
@gearman_job(name='my-task-name')
def my_task_function(one, two, three):
pass
You can execute this function in two different ways:
client.submit_job('my-task-name', one=1, two=2, three=3)
client.submit_job('my-task-name', args=[1, 2, 3])
Unfortunately, executing it like this:
client.submit_job('my-task-name', 1, 2, 3)
would produce the error, because submit_job from Gearman's Python bindings
contains a lot of arguments and it's much easier to specify them via
keyword names or a special args keyword than to type something like seven
Nones instead:
client.submit_job('my-task-name', None, None, None, None, None, None, None, 1, 2, 3)
The only limitation that you have are gearman reserved keyword parameters. As of Gearman 2.0.2 these are:
* data
* unique
* priority
* background
* wait_until_complete
* max_retries
* poll_timeout
So, if you want your job definition to have, for example, unique or
background keyword parameters, you need to execute the job in a special,
more verbose way. Here's an example of such a job and its execution.
@gearman_job(name='my-task-name')
def my_task_function(background, unique):
pass
client.submit_job('my-task-name', kwargs={"background": True, "unique": False})
client.submit_job('my-task-name', args=[True, False])
Finally:
client.submit_job('my-task-name', background=True, unique=True, kwargs={"background": False, "unique": False})
Don't panic, your task is safe! That's because you're using kwargs
directly. Therefore, Gearman's bindings would receive True for
submit_job function, while your task would receive False.
Always remember to double-check your parameter names with the reserved words list.
To start a worker, run python manage.py gearman_worker. It will start
serving all registered jobs.
To spawn more than one worker (if, e.g., most of your jobs are I/O bound),
use the -w option:
python manage.py gearman_worker -w 5
will start five workers.
Since the process will keep running while waiting for and executing jobs, you probably want to run this in a screen session or similar.
Queues are a virtual abstraction layer built on top of gearman tasks. An
easy way to describe it is the following example: Imagine you have a task
for fetching e-mails from the server, another task for sending the emails
and one more task for sending SMS via an SMS gateway. A problem you may
encounter is that the email fetching tasks may effectively "block" the worker
(there could be so many of them, it could be so time-consuming, that no other
task would be able to pass through). Of course, one solution would be to add
more workers (via the -w parameter), but that would only temporarily
solve the problem. This is where queues come in.
The first thing to do is to pass a queue name into the job description, like this:
@gearman_job(queue="my-queue-name")
def some_job(some_arg):
pass
You may then proceed to starting the worker that is bound to the specific queue:
python manage.py gearman_worker -w 5 -q my-queue-name
Be aware of the fact that when you don't specify the queue name, the worker will take care of all tasks.
To make your workers work, you need a client app passing data to them. Create
and instance of the django_gearman.GearmanClient class and execute a
django_gearman.Task with it:
from django_gearman import GearmanClient, Task
client = GearmanClient()
res = client.do_task(Task("gearman_example.reverse", sentence))
print "Result: '%s'" % res
The notation for the task name is appname.jobname, no matter what pattern
you have defined in GEARMAN_JOB_NAME.
Dispatching a background event without waiting for the result is easy as well:
client.dispatch_background_task('gearman_example.background_counting', None)
For a live example look at the gearman_example app, in the
management/commands/gearman_example_client.py file.
For a full, working, example application, add gearman_example to your
INSTALLED_APPS, then run a worker in one shell:
python manage.py gearman_worker -w 4
and execute the example app in another:
python manage.py gearman_example_client
You can see the client sending data and the worker(s) working on it.
This software is licensed under the Mozilla Tri-License:
***** BEGIN LICENSE BLOCK *****
Version: MPL 1.1/GPL 2.0/LGPL 2.1
The contents of this file are subject to the Mozilla Public License Version
1.1 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.mozilla.org/MPL/
Software distributed under the License is distributed on an "AS IS" basis,
WITHOUT WARRANTY OF ANY KIND, either express or implied. See the License
for the specific language governing rights and limitations under the
License.
The Original Code is django-gearman.
The Initial Developer of the Original Code is Mozilla.
Portions created by the Initial Developer are Copyright (C) 2010
the Initial Developer. All Rights Reserved.
Contributor(s):
Frederic Wenzel <[email protected]>
Alternatively, the contents of this file may be used under the terms of
either the GNU General Public License Version 2 or later (the "GPL"), or
the GNU Lesser General Public License Version 2.1 or later (the "LGPL"),
in which case the provisions of the GPL or the LGPL are applicable instead
of those above. If you wish to allow use of your version of this file only
under the terms of either the GPL or the LGPL, and not to allow others to
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