Django Background Tasks for Amazon Elastic Beanstalk.
Created by Alexey "DataGreed" Strelkov.
django-eb-sqs-worker lets you handle background jobs on Elastic Beanstalk Worker Environment sent via SQS and provides methods to send tasks to worker.
You can use the same Django codebase for both your Web Tier and Worker Tier environments and send tasks from Web environment to Worker environment. Amazon fully manages autoscaling for you.
Tasks are sent via Amazon Simple Queue Service and are delivered to your worker with Elastic Beanstalk's SQS daemon. Periodic tasks are also supported.
Here's the diagram of how tasks move through the system, tasks movement is represented by arrows:
Install using pip (only python3.x+ is supported):
pip install django-eb-sqs-worker
Add eb_sqs_worker
to settings.INSTALLED_APPS
:
INSTALLED_APPS = [
# ...
"eb_sqs_worker",
]
Add localhost
to settings.ALLOWED_HOSTS
so SQS Daemon can post tasks from
the queue to your worker:
ALLOWED_HOSTS = [
# ...
"localhost",
]
Update your settings.py
for both Worker and Web EB environments:
# region where your elastic beanstalk environments are deployed, e.g. "us-west-1"
AWS_EB_DEFAULT_REGION = "your default region"
# your aws access key id
AWS_ACCESS_KEY_ID = "insert your key id here"
# your aws access key
AWS_SECRET_ACCESS_KEY = "insert your key here"
# queue name to use - queues that don't exist will be created automatically
AWS_EB_DEFAULT_QUEUE_NAME = "any_queue_name_to_use"
In the settings file for your Web tier environment add the following setting (this is important due to possible security problems if you don't set this):
# never set to True on Web environment. Use True only on Worker env and local development env
AWS_EB_HANDLE_SQS_TASKS=False
In the setting files used by your Worker environments add the following setting:
# never set to True on Web environment. Use True only on Worker env and local development env
AWS_EB_HANDLE_SQS_TASKS=True
Add eb-sqs-worker urls to your project's main urls.py
module:
# urls.py
urlpatterns = [
# your url patterns
# ...
]
from eb_sqs_worker.urls import urlpatterns as eb_sqs_urlpatterns
urlpatterns += eb_sqs_urlpatterns
Navigate to your Worker environment in Elastic Beanstalk Web console, then go to Configuration > Worker
and set HTTP path to /sqs/
.
You should also select the queue to use here corresponding to your AWS_EB_DEFAULT_QUEUE_NAME
or, if you prefer to use the autogenerated one, you can copy its name and set as your AWS_EB_DEFAULT_QUEUE_NAME
.
If you don't see your AWS_EB_DEFAULT_QUEUE_NAME
here, try sending first task to it (see "Queueing tasks" section)
and it will be automatically created for you (you may need to reload the page for it to appear here).
Apply changes.
To define a job create a function decorated by task
decorator:
from eb_sqs_worker.decorators import task
@task
def some_task(**kwargs):
# define your task here
print(f"The decorated test task is being run with kwargs {kwargs} and will echo them back")
return kwargs
Make sure the module with your tasks is imported so they will register correctly.
The best practice is to do it as soon as django loads, e.g. in your app's models.py
or in corresponding AppConfig
.
If the task was defined using @task
decorator, you can send it to background queue like this:
# sends the task to SQS queue where it will be automatically picked up and executed by worker
some_task(foo="bar")
You can set settings.AWS_EB_RUN_TASKS_LOCALLY
to True
in development – this will force all tasks to execute
locally in sync mode without sending them to the queue. This is useful for testing.
If you need to execute the function synchronously just one time somewhere in your code without changing this setting, you can do it like this:
# runs the task function synchronously without sending it to the queue and returns result
result = some_task.execute(foo="bar")
Note: don't supply positional arguments to the task, always use keyword arguments.
Periodic tasks are defined the same way as regular task, but it's better to supply a custom name for them:
from eb_sqs_worker.decorators import task
@task(task_name="some_periodic_task")
def periodic_task():
# define your periodic task here
print(f"Periodic test task is being run ")
return True
Add cron.yaml
to the root of the project:
version: 1
cron:
- name: "some_periodic_task"
url: "/sqs/"
schedule: "0 23 * * *"
Deploy your project to elastic beanstalk and your task will run every day at 23:00.
Refer to the documentation for more info on periodic tasks.
Note: periodic tasks don't support arguments passing
#TODO describe
(add link to https://docs.aws.amazon.com/elasticbeanstalk/latest/dg/using-features-managing-env-tiers.html#worker-periodictasks), explain configuration
#TODO describe
#TODO describe
#TODO describe
#TODO: add info on arguments
#TODO: add info on arguments
If set to True
, tasks will be accepted and handled on this instance. If set to False
, the URL for handling
tasks will return 404. Defaults to False
.
Important: set this to True
only on your Worker environment
Dictionary of enabled tasks. Routes task names to actual task methods.
If you register your tasks using the task
decorator, you don't need to worry about this setting at all,
it will be set automatically by the decorator.
E.g.:
AWS_EB_ENABLED_TASKS = {
# name used in serialization # path to actual method that does the job
"accounts_confirmation_email": "accounts.tasks.send_confirmation_email",
"analytics_track_event": "analytics.tasks.track_event"
}
Default Elastic Beanstalk Region. Use the one that your app id deployed in.
Name of the queue used by default. If the queue with specified name does not exist, it will be created automatically when the first task is queued.
Amazon Access Key Id, refer to the docs
Amazon Secret Access Key, refer to the docs
If set to true, all tasks will be run locally and synchronnously instead of being sent to SQS Queue. Defaults to False
Set this to the maximum number of seconds the job is supposed to run. If the job finishes requires more time to finish ADMINS will be notified by email.
Always set AWS_EB_HANDLE_SQS_TASKS=False
on Web Tier Environment so the tasks could not be spoofed!
Web Tier environments are typically used for hosting publici websites and can be accessed by anoyone on the Internet,
meaning that anyone can send any jobs to your site if you leave this option on on Web environment.
Worker environments can only be accessed internally, e.g. via SQS Daemon that POSTs, so AWS_EB_HANDLE_SQS_TASKS=True
should be set only on worker environments.
Use Elastic Beanstalk Environment properties to supply different setting files for Web and Worker environments. See also: docs on designating the Django settings
#TODO
You will probably want your worker environment to have access to the same database as your web tier environment.
Assuming you have a web tier environment and a worker environment with the same Django apps deployed
(if you don't have a worker environment, yet, you can create it using eb create -t worker <environment name>
)
and the web tier environment has an
attached database
set up via Elastic Beanstalk with database connection settings populated from environmantal variables,
do the following:
eb ssh
and getting it using cat /opt/python/current/env
RDS_PORT
,RDS_PASSWORD
,RDS_USERNAME
,
RDS_DB_NAME
, RDS_HOSTNAME
) and hit "Apply"eb deploy
to make sure that everything works as expected.#TODO
#TODO
When developing on local machine it might be a good idea to set AWS_EB_RUN_TASKS_LOCALLY=True
, so all the tasks
that should normally be sent to queue will be executed locally on the same machine in sync mode. This lets you test
your actual task methods in integration tests.
Clone the repository.
git clone https://github.com/DataGreed/django-eb-sqs-worker.git
Install requirements (use python virtual environment)
cd django-eb-sqs-worker
pip install -r requirements.txt
Run tests
sh test.sh
If you would like to contribute, please make a Pull Request with the description of changes and add tests to cover these changes.
Feel free to open issues if you have any problems or questions with this package.
Search tags
Django Elastic Beanstalk Worker Web Tier Asynchronous celery async django-q Jobs Background Tasks SQS