User Guide

To follow along with this guide you’ll need to install and run RabbitMQ and then set up a new virtual environment in which you’ll have to install Remoulade and Requests:

$ pip install 'remoulade[rabbitmq]' requests

Actors

As a quick and dirty example of a task that’s worth processing in the background, let’s write a function that counts the “words” at a particular URL:

count_words.py

import requests

def count_words(url):
  response = requests.get(url)
  count = len(response.text.split(" "))
  print(f"There are {count} words at {url!r}.")

There’s not a ton going on here. We just grab the response content at that URL and print out how many space-separated chunks there are in that response. Sure enough, running this in the interactive interpreter yields about what we expect:

>>> from count_words import count_words
>>> count_words("http://example.com")
There are 338 words at 'http://example.com'.

To turn this into a function that can be processed asynchronously using Remoulade, all we have to do is decorate it with actor and declare it to the broker:

count_words.py

import remoulade
import requests
from remoulade import get_broker()

@remoulade.actor
def count_words(url):
  response = requests.get(url)
  count = len(response.text.split(" "))
  print(f"There are {count} words at {url!r}.")

remoulade.declare_actors([count_words])

Like before, if we call the function in the interactive interpreter, it will run synchronously and we’ll get the same result out:

>>> count_words("http://example.com")
There are 338 words at 'http://example.com'.

What’s changed is we’re now able to tell the function to run asynchronously by calling its send method:

>>> count_words.send("http://example.com")
Message(
  queue_name='default',
  actor_name='count_words',
  args=('http://example.com',), kwargs={}, options={},
  message_id='8cdcae57-af36-40ba-9616-849a336a4316',
  message_timestamp=1498557015410)

Doing so immediately enqueues a message (via our local RabbitMQ server) that can be processed asynchronously but doesn’t actually run the function. In order to run it, we’ll have to boot up a Remoulade worker.

Note

Because all messages have to be sent over the network, any arguments you send to an actor must be JSON-encodable.

If you want messages from an actor to be enqueued in a specific queue (and not ‘default’, the default queue), you can specify the queue in the actor decorator:

@remoulade.actor(queue_name="my_queue")
def count_words(url):
   ...

You can also choose to enqueue a message in another queue when sending it. First, you have to specify in the actor decorator the queues this message is allowed to be enqueued into:

@remoulade.actor(queue_name="first_queue", alternative_queues=["second_queue", "third_queue"])
def count_words(url):
   ...

By default, messages from this actor will be enqueued into the first_queue queue. But they can also be enqueued into the second_queue and third_queue by adding the queue_name options:

count_words.send_with_options(queue_name="second_queue")

Workers

Remoulade comes with a command line utility called, predictably, remoulade. This utility is able to spin up multiple concurrent worker processes that pop messages off the queue and send them to actor functions for execution.

To spawn workers for our count_words.py example, run the following command in a new terminal window:

$ remoulade count_words

This will spin up a process on your machine with 8 worker threads per process. Run remoulade -h if you want to see a list of the available command line flags.

As soon as you run that command you’ll see log output along these lines:

[2017-11-19 13:03:48,188] [PID 22370] [MainThread] [remoulade.MainProcess] [INFO] Remoulade '0.13.1' is booting up.
[2017-11-19 13:03:48,349] [PID 22377] [MainThread] [remoulade.WorkerProcess(3)] [INFO] Worker process is ready for action.
[2017-11-19 13:03:48,350] [PID 22375] [MainThread] [remoulade.WorkerProcess(1)] [INFO] Worker process is ready for action.
[2017-11-19 13:03:48,357] [PID 22376] [MainThread] [remoulade.WorkerProcess(2)] [INFO] Worker process is ready for action.
[2017-11-19 13:03:48,357] [PID 22374] [MainThread] [remoulade.WorkerProcess(0)] [INFO] Worker process is ready for action.
[2017-11-19 13:03:48,358] [PID 22379] [MainThread] [remoulade.WorkerProcess(5)] [INFO] Worker process is ready for action.
[2017-11-19 13:03:48,362] [PID 22381] [MainThread] [remoulade.WorkerProcess(7)] [INFO] Worker process is ready for action.
[2017-11-19 13:03:48,364] [PID 22380] [MainThread] [remoulade.WorkerProcess(6)] [INFO] Worker process is ready for action.
[2017-11-19 13:03:48,366] [PID 22378] [MainThread] [remoulade.WorkerProcess(4)] [INFO] Worker process is ready for action.
[2017-11-19 13:03:48,369] [PID 22377] [Thread-4] [count_words.count_words] [INFO] Received args=('http://example.com',) kwargs={}.
There are 338 words at 'http://example.com'.
[2017-11-19 13:03:48,679] [PID 22377] [Thread-4] [count_words.count_words] [INFO] Completed after 310.42ms.

If you open your Python interpreter back up and send the actor some more URLs to process:

>>> urls = [
...   "https://news.ycombinator.com",
...   "https://xkcd.com",
...   "https://rabbitmq.com",
... ]
>>> [count_words.send(url) for url in urls]
[Message(queue_name='default', actor_name='count_words', args=('https://news.ycombinator.com',), kwargs={}, options={}, message_id='a99a5b2d-d2da-407b-be55-f2925266e216', message_timestamp=1498557998218),
 Message(queue_name='default', actor_name='count_words', args=('https://xkcd.com',), kwargs={}, options={}, message_id='0ec93dcb-2f9f-414f-99ec-7035e3b1ac5a', message_timestamp=1498557998218),
 Message(queue_name='default', actor_name='count_words', args=('https://rabbitmq.com',), kwargs={}, options={}, message_id='d3dd9799-1ea5-4b00-a70b-2cd6f6f634ed', message_timestamp=1498557998218)]

and then switch back to the worker terminal, you’ll see nine new lines:

[2017-11-19 13:10:02,620] [PID 24357] [Thread-4] [count_words.count_words] [INFO] Received args=('https://rabbitmq.com',) kwargs={}.
[2017-11-19 13:10:02,621] [PID 24357] [Thread-6] [count_words.count_words] [INFO] Received args=('https://xkcd.com',) kwargs={}.
[2017-11-19 13:10:02,621] [PID 24357] [Thread-5] [count_words.count_words] [INFO] Received args=('https://news.ycombinator.com',) kwargs={}.
There are 888 words at 'https://rabbitmq.com'.
[2017-11-19 13:10:02,757] [PID 24357] [Thread-4] [count_words.count_words] [INFO] Completed after 137.26ms.
There are 461 words at 'https://xkcd.com'.
[2017-11-19 13:10:02,841] [PID 24357] [Thread-6] [count_words.count_words] [INFO] Completed after 219.76ms.
There are 3598 words at 'https://news.ycombinator.com'.
[2017-11-19 13:10:03,297] [PID 24357] [Thread-5] [count_words.count_words] [INFO] Completed after 675.19ms.

At this point, you’re probably wondering what happens if you send the actor an invalid URL. Let’s try it:

>>> count_words.send("foo")

Message Retries

If an error occurs during message processing, it will be terminated with a failure message. Alternatively, you can add the Retries Middleware to the broker and set the max_retries or retry_when option to automatically retry your message on failure.

You can specify how failures should be retried on a per-actor basis. For example, if you want to limit the maximum number of retries for count_words you can pass the max_retries keyword argument to actor:

@remoulade.actor(max_retries=3)
def count_words(url):
  ...

If you want to retry certain exceptions and not others, you can pass a predicate function via the retry_when parameter:

def should_retry(retries_so_far, exception):
  return retries_so_far < 3 and isinstance(exception, HttpTimeout)

@remoulade.actor(retry_when=should_retry)
def count_words(url):
  ...

If you want to use a different strategy than the default exponential backoff to define how long to wait between retries, you can pass the backoff_strategy keyword argument to actor. For instance to retry every minute:

@remoulade.actor(min_backoff=60000, backoff_strategy='constant')
def count_words(URL):
  ...

The following retry options are configurable on a per-actor basis:

max_retries

The maximum number of times a message should be retried. Default to 0.

min_backoff

The minimum number of milliseconds of backoff to apply between retries. Must be greater than 100 milliseconds. Defaults to 15 seconds.

max_backoff

The maximum number of milliseconds of backoff to apply between retries. Higher values are less reliable. Defaults to 1 hour.

retry_when

A callable that takes the number of retries so far and the exception as an input, and expects a boolean that determines whether or not the message will be retried as an output. When this is set, max_retries is ignored. Defaults to None.

backoff_strategy

The strategy used to compute the backoff. Defaults to exponential. The available strategies are :

• constant: constant backoff, equal to min_backoff.

• linear: linear backoff, starting from min_backoff.

• spread_linear: linear backoff, linearly spread between min_backoff and max_backoff.

• exponential: exponential backoff, starting from min_backoff.

• spread_exponential: exponential backoff, exponentially spread between min_backoff and max_backoff.

jitter

When True, a small random value will be added to the backoff to avoid mass simultaneous retries. Defaults to True.

Message Age Limits

Instead of limiting the number of times messages can be retried, you might want to expire old messages. You can specify the max_age of messages (given in milliseconds) on a per-actor basis:

@remoulade.actor(max_age=3600000)
def count_words(url):
  ...

Dead Letters

Once a message has exceeded its retry or age limits, it gets moved to the dead letter queue where it’s kept for up to 7 days and then automatically dropped from the message broker. From here, you can manually inspect the message and decide whether or not it should be put back on the queue.

Message Time Limits

In count_words, we didn’t set an explicit timeout for the outbound request which means that it can take a very long time to complete if the server we’re requesting is timing out. Remoulade has a default actor time limit of 30 minutes, which means that any actor running for longer than 30 minutes is killed with a TimeLimitExceeded error.

You can control these time limits at the individual actor level by specifying the time_limit (in milliseconds) of each one:

@remoulade.actor(time_limit=60000)
def count_words(url):
  ...

Note

While this will keep our actor from running forever, remember that you should take care to always specify a timeout for the request itself, and this is not a good way to handle request timeouts in production code.

Warning

Time limits are best-effort. They cannot cancel system calls or any function that doesn’t currently hold the GIL under CPython.

For more information, see the section on Message Interrupts.

Note

If time limit fail to stop the execution via TimeLimitExceeded (see warning), a SIGKILL will be sent to the worker after 10 seconds (by default). This delay can be set with the sigkill_delay of TimeLimit, or feature can be disabled by setting sigkill_delay to None.

Handling Time Limits

If you want to gracefully handle time limits within an actor, you can wrap its source code in a try block and catch TimeLimitExceeded:

from remoulade.middleware import TimeLimitExceeded

@remoulade.actor(time_limit=1000)
def long_running():
  try:
    setup_missiles()
    time.sleep(2)
    launch_missiles()    # <- this will not run
  except TimeLimitExceeded:
    teardown_missiles()  # <- this will run

Scheduling Messages

You can schedule messages to run some time in the future by calling send_with_options on actors and providing a delay (in milliseconds):

>>> count_words.send_with_options(args=("https://example.com",), delay=10000)
Message(
  queue_name='default',
  actor_name='count_words',
  args=('https://example.com',), kwargs={},
  options={'eta': 1498560453548},
  message_id='7387dc76-8ebe-426e-aec1-db34c236563c',
  message_timestamp=1498560443548)

Keep in mind that your message broker is not a database. Scheduled messages should represent a small subset of all your messages.

Prioritizing Messages

Say your app has some actors that are higher priority than others: for example, actors that affect your UI and make users wait, or are otherwise user-facing, versus actors that aren’t. When choosing between two concurrent messages to run, Remoulade will run the Message that belongs to the actor with the highest priority.

You can set an Actor’s priority via the priority keyword argument:

@remoulade.actor(priority=1)
def generate_report(user_id):
  ...

@remoulade.actor(priority=0) # 0 is the default
def sync_order_to_warehouse(order_id):
  ...

That way if both generate_report and sync_order_to_warehouse are scheduled to run at the same time but there’s only capacity to run one of them, generate_report will always run first.

Although all positive integers represent valid priorities, if you’re going to use this feature, I’d recommend setting up constants for the various priorities you plan to use:

PRIO_LO = 0 PRIO_MED = 1 PRIO_HI = 2

Rabbitmq also have a support for priorities, to take advantage of it you need to set max_priority

broker = RabbitmqBroker(url=”rabbitmq”, max_priority=PRIO_HI)

In priority documentation, you will see that recommended value for max_priority is between 1 and 10 (max: 255). You should try to use the minimum max_priority possible and not use priority values bigger than max_priority as they will be considered as max_priority.

Important

The bigger the numeric value, the higher priority!

Message Brokers

Remoulade abstracts over the notion of a message broker and currently supports RabbitMQ out of the box.

RabbitMQ Broker

To configure the RabbitMQ host, instantiate a RabbitmqBroker and set it as the global broker as early as possible during your program’s execution:

import remoulade

from remoulade.brokers.rabbitmq import RabbitmqBroker

rabbitmq_broker = RabbitmqBroker(url="rabbitmq")
remoulade.set_broker(rabbitmq_broker)

Local Broker

If you just want to execute the actors when the message is enqueued without running any Worker (for example in a development environment):

import remoulade

from remoulade.brokers.local import LocalBroker
from remoulade.results.backends import LocalBackend
from remoulade.cancel.backends import StubBackend

local_broker = LocalBroker(middleware=[])
broker.add_middleware(Results(backend=LocalBackend()))
broker.add_middleware(Cancel(backend=StubBackend()))
remoulade.set_broker(local_broker)

Unit Testing

Remoulade provides a StubBroker that can be used in unit tests so you don’t have to have a running RabbitMQ or Redis instance in order to run your tests. My recommendation is to use it in conjunction with pytest fixtures:

broker.py

import os

from remoulade.brokers.rabbitmq import RabbitmqBroker
from remoulade.brokers.stub import StubBroker

if os.getenv("UNIT_TESTS") == "1":
  broker = StubBroker()
  broker.emit_after("process_boot")
else:
  broker = RabbitmqBroker()

conftest.py

import remoulade
import pytest

from remoulade import Worker
from yourapp import broker

@pytest.fixture()
def stub_broker():
  broker.flush_all()
  return broker

@pytest.fixture()
def stub_worker():
  worker = Worker(broker, worker_timeout=100)
  worker.start()
  yield worker
  worker.stop()

Then you can inject and use those fixtures in your tests:

def test_count_words(stub_broker, stub_worker):
  count_words.send("http://example.com")
  stub_broker.join(count_words.queue_name)
  stub_worker.join()

Because all actors are callable, you can of course also unit test them synchronously by calling them as you would normal functions.