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community.general/plugins/module_utils/cloud.py

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Python

# -*- coding: utf-8 -*-
#
# Copyright (c) 2016 Allen Sanabria, <asanabria@linuxdynasty.org>
# GNU General Public License v3.0+ (see LICENSES/GPL-3.0-or-later.txt or https://www.gnu.org/licenses/gpl-3.0.txt)
# SPDX-License-Identifier: GPL-3.0-or-later
from __future__ import (absolute_import, division, print_function)
__metaclass__ = type
"""
This module adds shared support for generic cloud modules
In order to use this module, include it as part of a custom
module as shown below.
from ansible.module_utils.cloud import CloudRetry
The 'cloud' module provides the following common classes:
* CloudRetry
- The base class to be used by other cloud providers, in order to
provide a backoff/retry decorator based on status codes.
- Example using the AWSRetry class which inherits from CloudRetry.
@AWSRetry.exponential_backoff(retries=10, delay=3)
get_ec2_security_group_ids_from_names()
@AWSRetry.jittered_backoff()
get_ec2_security_group_ids_from_names()
"""
import random
from functools import wraps
import syslog
import time
def _exponential_backoff(retries=10, delay=2, backoff=2, max_delay=60):
""" Customizable exponential backoff strategy.
Args:
retries (int): Maximum number of times to retry a request.
delay (float): Initial (base) delay.
backoff (float): base of the exponent to use for exponential
backoff.
max_delay (int): Optional. If provided each delay generated is capped
at this amount. Defaults to 60 seconds.
Returns:
Callable that returns a generator. This generator yields durations in
seconds to be used as delays for an exponential backoff strategy.
Usage:
>>> backoff = _exponential_backoff()
>>> backoff
<function backoff_backoff at 0x7f0d939facf8>
>>> list(backoff())
[2, 4, 8, 16, 32, 60, 60, 60, 60, 60]
"""
def backoff_gen():
for retry in range(0, retries):
sleep = delay * backoff ** retry
yield sleep if max_delay is None else min(sleep, max_delay)
return backoff_gen
def _full_jitter_backoff(retries=10, delay=3, max_delay=60, _random=random):
""" Implements the "Full Jitter" backoff strategy described here
https://www.awsarchitectureblog.com/2015/03/backoff.html
Args:
retries (int): Maximum number of times to retry a request.
delay (float): Approximate number of seconds to sleep for the first
retry.
max_delay (int): The maximum number of seconds to sleep for any retry.
_random (random.Random or None): Makes this generator testable by
allowing developers to explicitly pass in the a seeded Random.
Returns:
Callable that returns a generator. This generator yields durations in
seconds to be used as delays for a full jitter backoff strategy.
Usage:
>>> backoff = _full_jitter_backoff(retries=5)
>>> backoff
<function backoff_backoff at 0x7f0d939facf8>
>>> list(backoff())
[3, 6, 5, 23, 38]
>>> list(backoff())
[2, 1, 6, 6, 31]
"""
def backoff_gen():
for retry in range(0, retries):
yield _random.randint(0, min(max_delay, delay * 2 ** retry))
return backoff_gen
class CloudRetry(object):
""" CloudRetry can be used by any cloud provider, in order to implement a
backoff algorithm/retry effect based on Status Code from Exceptions.
"""
# This is the base class of the exception.
# AWS Example botocore.exceptions.ClientError
base_class = None
@staticmethod
def status_code_from_exception(error):
""" Return the status code from the exception object
Args:
error (object): The exception itself.
"""
pass
@staticmethod
def found(response_code, catch_extra_error_codes=None):
""" Return True if the Response Code to retry on was found.
Args:
response_code (str): This is the Response Code that is being matched against.
"""
pass
@classmethod
def _backoff(cls, backoff_strategy, catch_extra_error_codes=None):
""" Retry calling the Cloud decorated function using the provided
backoff strategy.
Args:
backoff_strategy (callable): Callable that returns a generator. The
generator should yield sleep times for each retry of the decorated
function.
"""
def deco(f):
@wraps(f)
def retry_func(*args, **kwargs):
for delay in backoff_strategy():
try:
return f(*args, **kwargs)
except Exception as e:
if isinstance(e, cls.base_class): # pylint: disable=isinstance-second-argument-not-valid-type
response_code = cls.status_code_from_exception(e)
if cls.found(response_code, catch_extra_error_codes):
msg = "{0}: Retrying in {1} seconds...".format(str(e), delay)
syslog.syslog(syslog.LOG_INFO, msg)
time.sleep(delay)
else:
# Return original exception if exception is not a ClientError
raise e
else:
# Return original exception if exception is not a ClientError
raise e
return f(*args, **kwargs)
return retry_func # true decorator
return deco
@classmethod
def exponential_backoff(cls, retries=10, delay=3, backoff=2, max_delay=60, catch_extra_error_codes=None):
"""
Retry calling the Cloud decorated function using an exponential backoff.
Kwargs:
retries (int): Number of times to retry a failed request before giving up
default=10
delay (int or float): Initial delay between retries in seconds
default=3
backoff (int or float): backoff multiplier e.g. value of 2 will
double the delay each retry
default=1.1
max_delay (int or None): maximum amount of time to wait between retries.
default=60
"""
return cls._backoff(_exponential_backoff(
retries=retries, delay=delay, backoff=backoff, max_delay=max_delay), catch_extra_error_codes)
@classmethod
def jittered_backoff(cls, retries=10, delay=3, max_delay=60, catch_extra_error_codes=None):
"""
Retry calling the Cloud decorated function using a jittered backoff
strategy. More on this strategy here:
https://www.awsarchitectureblog.com/2015/03/backoff.html
Kwargs:
retries (int): Number of times to retry a failed request before giving up
default=10
delay (int): Initial delay between retries in seconds
default=3
max_delay (int): maximum amount of time to wait between retries.
default=60
"""
return cls._backoff(_full_jitter_backoff(
retries=retries, delay=delay, max_delay=max_delay), catch_extra_error_codes)
@classmethod
def backoff(cls, tries=10, delay=3, backoff=1.1, catch_extra_error_codes=None):
"""
Retry calling the Cloud decorated function using an exponential backoff.
Compatibility for the original implementation of CloudRetry.backoff that
did not provide configurable backoff strategies. Developers should use
CloudRetry.exponential_backoff instead.
Kwargs:
tries (int): Number of times to try (not retry) before giving up
default=10
delay (int or float): Initial delay between retries in seconds
default=3
backoff (int or float): backoff multiplier e.g. value of 2 will
double the delay each retry
default=1.1
"""
return cls.exponential_backoff(
retries=tries - 1, delay=delay, backoff=backoff, max_delay=None, catch_extra_error_codes=catch_extra_error_codes)