Retry Helpers#

class redis.retry.AbstractRetry(backoff, retries, supported_errors)[source]#

Retry a specific number of times after a failure

Parameters

  • backoff (AbstractBackoff) –

  • retries (int) –

  • supported_errors (Tuple[Type[E], ...]) –

get_retries()[source]#

Get the number of retries.

Return type

int

update_retries(value)[source]#

Set the number of retries.

Parameters

value (int) –

Return type

None

update_supported_errors(specified_errors)[source]#

Updates the supported errors with the specified error types

Parameters

specified_errors (Iterable[Type[E]]) –

Return type

None

class redis.retry.Retry(backoff, retries, supported_errors=(<class 'redis.exceptions.ConnectionError'>, <class 'redis.exceptions.TimeoutError'>, <class 'TimeoutError'>))[source]#
Parameters

  • backoff (AbstractBackoff) –

  • retries (int) –

  • supported_errors (Tuple[Type[Exception], ...]) –

call_with_retry(do, fail, is_retryable=None, with_failure_count=False)[source]#

Execute an operation that might fail and returns its result, or raise the exception that was thrown depending on the Backoff object. do: the operation to call. Expects no argument. fail: the failure handler, expects the last error that was thrown is_retryable: optional function to determine if an error is retryable with_failure_count: if True, the failure count is passed to the failure handler

Parameters

  • do (Callable[[], T]) –

  • fail (Union[Callable[[Exception], Any], Callable[[Exception, int], Any]]) –

  • is_retryable (Optional[Callable[[Exception], bool]]) –

  • with_failure_count (bool) –

Return type

T

Retry in Redis Standalone#

>>> from redis.backoff import ExponentialBackoff
>>> from redis.retry import Retry
>>> from redis.client import Redis
>>> from redis.exceptions import (
>>>    BusyLoadingError,
>>>    RedisError,
>>> )
>>>
>>> # Run 3 retries with exponential backoff strategy
>>> retry = Retry(ExponentialBackoff(), 3)
>>> # Redis client with retries on custom errors in addition to the errors
>>> # that are already retried by default
>>> r = Redis(host='localhost', port=6379, retry=retry, retry_on_error=[BusyLoadingError, RedisError])

As you can see from the example above, Redis client supports 2 parameters to configure the retry behaviour:

  • retry: Retry instance with a Backoff strategy and the max number of retries

    • The Retry instance has default set of Exceptions to retry on, which can be overridden by passing a tuple with Exceptions to the supported_errors parameter.

  • retry_on_error: list of additional Exceptions to retry on

If no retry is provided, a default one is created with ExponentialWithJitterBackoff as backoff strategy and 3 retries.

Retry in Redis Cluster#

>>> from redis.backoff import ExponentialBackoff
>>> from redis.retry import Retry
>>> from redis.cluster import RedisCluster
>>>
>>> # Run 3 retries with exponential backoff strategy
>>> retry = Retry(ExponentialBackoff(), 3)
>>> # Redis Cluster client with retries
>>> rc = RedisCluster(host='localhost', port=6379, retry=retry)

Retry behaviour in Redis Cluster is a little bit different from Standalone:

  • retry: Retry instance with a Backoff strategy and the max number of retries, default value is Retry(ExponentialWithJitterBackoff(base=1, cap=10), cluster_error_retry_attempts)

  • cluster_error_retry_attempts: number of times to retry before raising an error when TimeoutError, ConnectionError, ClusterDownError or SlotNotCoveredError are encountered, default value is 3

    • This argument is deprecated - it is used to initialize the number of retries for the retry object, only in the case when the retry object is not provided. When the retry argument is provided, the cluster_error_retry_attempts argument is ignored!

  • The retry object is not yet fully utilized in the cluster client. The retry object is used only to determine the number of retries for the cluster level calls.

Let’s consider the following example:

>>> from redis.backoff import ExponentialBackoff
>>> from redis.retry import Retry
>>> from redis.cluster import RedisCluster
>>>
>>> rc = RedisCluster(host='localhost', port=6379, retry=Retry(ExponentialBackoff(), 6))
>>> rc.set('foo', 'bar')

  1. the client library calculates the hash slot for key ‘foo’.

  2. given the hash slot, it then determines which node to connect to, in order to execute the command.

  3. during the connection, a ConnectionError is raised.

  4. because we set retry=Retry(ExponentialBackoff(), 6), the cluster client starts a cluster update, removes the failed node from the startup nodes, and re-initializes the cluster.

  5. the cluster client retries the command until it either succeeds or the max number of retries is reached.