python retry 和 retrying（失败重试）

retry

官：https://pypi.org/project/retry/

译：https://spaces.ac.cn/archives/3902

Easy to use retry decorator.

Features

• No external dependency (stdlib only).
• (Optionally) Preserve function signatures (pip install decorator).
• Original traceback, easy to debug.

Installation

$ pip install retry

Examples

from retry import retry

@retry()
def make_trouble():
    '''Retry until succeed'''

@retry(ZeroDivisionError, tries=3, delay=2)
def make_trouble():
    '''Retry on ZeroDivisionError, raise error after 3 attempts, sleep 2 seconds between attempts.'''

@retry((ValueError, TypeError), delay=1, backoff=2)
def make_trouble():
    '''Retry on ValueError or TypeError, sleep 1, 2, 4, 8, ... seconds between attempts.'''

@retry((ValueError, TypeError), delay=1, backoff=2, max_delay=4)
def make_trouble():
    '''Retry on ValueError or TypeError, sleep 1, 2, 4, 4, ... seconds between attempts.'''

@retry(ValueError, delay=1, jitter=1)
def make_trouble():
    '''Retry on ValueError, sleep 1, 2, 3, 4, ... seconds between attempts.'''

# If you enable logging, you can get warnings like 'ValueError, retrying in
# 1 seconds'
if __name__ == '__main__':
    import logging
    logging.basicConfig()
    make_trouble()

retry_call

def retry_call(f, fargs=None, fkwargs=None, exceptions=Exception, tries=-1, delay=0, max_delay=None, backoff=1,
               jitter=0,
               logger=logging_logger):
    """
    Calls a function and re-executes it if it failed.

    :param f: the function to execute.
    :param fargs: the positional arguments of the function to execute.
    :param fkwargs: the named arguments of the function to execute.
    :param exceptions: an exception or a tuple of exceptions to catch. default: Exception.
    :param tries: the maximum number of attempts. default: -1 (infinite).
    :param delay: initial delay between attempts. default: 0.
    :param max_delay: the maximum value of delay. default: None (no limit).
    :param backoff: multiplier applied to delay between attempts. default: 1 (no backoff).
    :param jitter: extra seconds added to delay between attempts. default: 0.
                   fixed if a number, random if a range tuple (min, max)
    :param logger: logger.warning(fmt, error, delay) will be called on failed attempts.
                   default: retry.logging_logger. if None, logging is disabled.
    :returns: the result of the f function.
    """

This is very similar to the decorator, except that it takes a function and its arguments as parameters. The use case behind it is to be able to dynamically adjust the retry arguments.

import requests

from retry.api import retry_call


def make_trouble(service, info=None):
    if not info:
        info = ''
    r = requests.get(service + info)
    return r.text


def what_is_my_ip(approach=None):
    if approach == "optimistic":
        tries = 1
    elif approach == "conservative":
        tries = 3
    else:
        # skeptical
        tries = -1
    result = retry_call(make_trouble, fargs=["http://ipinfo.io/"], fkwargs={"info": "ip"}, tries=tries)
    print(result)

what_is_my_ip("conservative")

retrying

官：https://pypi.org/project/retrying/

译：https://www.jianshu.com/p/364377ffdcc1

Project description

Retrying is an Apache 2.0 licensed general-purpose retrying library, written in Python, to simplify the task of adding retry behavior to just about anything.

The simplest use case is retrying a flaky function whenever an Exception occurs until a value is returned.

import random
from retrying import retry

@retry
def do_something_unreliable():
    if random.randint(0, 10) > 1:
        raise IOError("Broken sauce, everything is hosed!!!111one")
    else:
        return "Awesome sauce!"

print do_something_unreliable()

Features

• Generic Decorator API
• Specify stop condition (i.e. limit by number of attempts)
• Specify wait condition (i.e. exponential backoff sleeping between attempts)
• Customize retrying on Exceptions
• Customize retrying on expected returned result

Installation

To install retrying, simply:

$ pip install retrying

Or, if you absolutely must:

$ easy_install retrying

But, you might regret that later.

Examples

As you saw above, the default behavior is to retry forever without waiting.

@retry
def never_give_up_never_surrender():
    print "Retry forever ignoring Exceptions, don't wait between retries"

Let’s be a little less persistent and set some boundaries, such as the number of attempts before giving up.

@retry(stop_max_attempt_number=7)
def stop_after_7_attempts():
    print "Stopping after 7 attempts"

We don’t have all day, so let’s set a boundary for how long we should be retrying stuff.

@retry(stop_max_delay=10000)
def stop_after_10_s():
    print "Stopping after 10 seconds"

Most things don’t like to be polled as fast as possible, so let’s just wait 2 seconds between retries.

@retry(wait_fixed=2000)
def wait_2_s():
    print "Wait 2 second between retries"

Some things perform best with a bit of randomness injected.

@retry(wait_random_min=1000, wait_random_max=2000)
def wait_random_1_to_2_s():
    print "Randomly wait 1 to 2 seconds between retries"

Then again, it’s hard to beat exponential backoff when retrying distributed services and other remote endpoints.

@retry(wait_exponential_multiplier=1000, wait_exponential_max=10000)
def wait_exponential_1000():
    print "Wait 2^x * 1000 milliseconds between each retry, up to 10 seconds, then 10 seconds afterwards"

We have a few options for dealing with retries that raise specific or general exceptions, as in the cases here.

def retry_if_io_error(exception):
    """Return True if we should retry (in this case when it's an IOError), False otherwise"""
    return isinstance(exception, IOError)

@retry(retry_on_exception=retry_if_io_error)
def might_io_error():
    print "Retry forever with no wait if an IOError occurs, raise any other errors"

@retry(retry_on_exception=retry_if_io_error, wrap_exception=True)
def only_raise_retry_error_when_not_io_error():
    print "Retry forever with no wait if an IOError occurs, raise any other errors wrapped in RetryError"

We can also use the result of the function to alter the behavior of retrying.

def retry_if_result_none(result):
    """Return True if we should retry (in this case when result is None), False otherwise"""
    return result is None

@retry(retry_on_result=retry_if_result_none)
def might_return_none():
    print "Retry forever ignoring Exceptions with no wait if return value is None"

Any combination of stop, wait, etc. is also supported to give you the freedom to mix and match.