Define a retry strategy on a task#

We sometimes know in advance that a task may fail randomly. For example a task fetching resources on another network. You can define a retry strategy on a task and Procrastinate will enforce it.

Note that a job waiting to be retried lives in the database. It will persist across app / machine reboots.

Simple strategies#

  • Retry 5 times (so 6 attempts total):

    @app.task(retry=5)
def flaky_task():
    if random.random() > 0.9:
        raise Exception("Who could have seen this coming?")
    print("Hello world")

  • Retry indefinitely:

    @app.task(retry=True)
def flaky_task():
    if random.random() > 0.9:
        raise Exception("Who could have seen this coming?")
    print("Hello world")

Advanced strategies#

Advanced strategies let you:

  • define a maximum number of retries (if you don’t, jobs will be retried indefinitely until they pass)

  • define the retry delay, with constant, linear and exponential backoff options (if you don’t, jobs will be retried immediately)

  • define the exception types you want to retry on (if you don’t, jobs will be retried on any type of exceptions)

Define your precise strategy using a RetryStrategy instance:

from procrastinate import RetryStrategy

@app.task(retry=procrastinate.RetryStrategy(
    max_attempts=10,
    wait=5,
    retry_exceptions={ConnectionError, IOError}
))
def my_other_task():
    print("Hello world")

RetryStrategy takes 3 parameters related to how long it will wait between retries:

  • wait=5 to wait 5 seconds before each retry

  • linear_wait=5 to wait 5 seconds then 10 then 15 and so on

  • exponential_wait=5 to wait 5 seconds then 25 then 125 and so on

Implementing your own strategy#

  • If you want to go for a fully fledged custom retry strategy, you can implement your own retry strategy (though we recommend always keeping a max_retry):

    import random

class RandomRetryStrategy(procrastinate.BaseRetryStrategy):
    max_attempts = 3
    min = 1
    max = 10

    def get_schedule_in(self, *, exception:Exception, attempts: int, **kwargs) -> int:
        if attempts >= max_attempts:
            return None

        return random.uniform(self.min, self.max)

It’s interesting to add a catch-all parameter **kwargs to make your strategy more resilient to possible changes of Procrastinate in the future.