python重试库retryiny源码剖析

上篇博文介绍了常见需要进行请求重试的场景，本篇博文试着剖析有名的python第三方库retrying源码。

在剖析其源码之前，有必要讲一下retrying的用法，方便理解。

安装：

pip install retrying

或者

easy_install retrying

一些用法实例如下:

#example 1
from retrying import retry

@retry
def never_give_up_never_surrender():
     print "一直重试且两次重试之间无需等待"

#example 2
from retrying import retry

@retry(stop_max_attempt_number=7)
def stop_after_7_attempts():
    print "重试七次后停止"

#example 3
from retrying import retry

@retry(stop_max_delay=10000)
def stop_after_10_s():
    print "十秒之后停止重试"

#example 4
from retrying import retry

@retry(wait_fixed=2000)
def wait_2_s():
    print "每次重试间隔两秒"

#example 5
from retrying import retry

@retry(wait_random_min=1000, wait_random_max=2000)
def wait_random_1_to_2_s():
    print "每次重试随机等待1到2秒"

#example 6
from retrying import retry

@retry(wait_exponential_multiplier=1000, wait_exponential_max=10000)
def wait_exponential_1000():
    print "指数退避，每次重试等待 2^x * 1000 毫秒，上限是10秒，达到上限后每次都等待10秒"

#example 7
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 "IO异常则重试，并且将其它异常抛出"

@retry(retry_on_exception=retry_if_io_error, wrap_exception=True)
def only_raise_retry_error_when_not_io_error():
    print "IO异常则重试，并且将其它异常用RetryError对象包裹"

#exampe 8，根据返回结果判断是否重试
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 "若返回结果为None则重试"

上面八个例子是retrying的用法,只需在要重试的方法上加上@retry注解，并以相应的条件为参数即可,那么@retry背后到底是如何实现的呢?下面给出@retry注解实现的方法。

 #装饰器模式,对需要重试的函数,利用retry注解返回
 def retry(*dargs, **dkw):
     """
     Decorator function that instantiates the Retrying object
     @param *dargs: positional arguments passed to Retrying object
     @param **dkw: keyword arguments passed to the Retrying object
     """
     # support both @retry and @retry() as valid syntax
     #当用法为@retry不带括号时走这条路径,dargs[0]为retry注解的函数,返回函数对象wrapped_f
     if len(dargs) == 1 and callable(dargs[0]):
         def wrap_simple(f):

             @six.wraps(f)#注解用于将函数f的签名复制到新函数wrapped_f
             def wrapped_f(*args, **kw):
                 return Retrying().call(f, *args, **kw)

             return wrapped_f

         return wrap_simple(dargs[0])

     else:#当用法为@retry()带括号时走这条路径，返回函数对象wrapped_f
         def wrap(f):

             @six.wraps(f)#注解用于将函数f的签名复制到新函数wrapped_f
             def wrapped_f(*args, **kw):
                 return Retrying(*dargs, **dkw).call(f, *args, **kw)

             return wrapped_f

         return wrap

当用@retry标记函数时，例如实例1，其实执行了

never_give_up_never_surrender = retry(never_give_up_never_surrender)

此时的never_give_up_never_surrender函数实际上是10-19行返回的wrapped_f函数，后续对never_give_up_never_surrender函数的调用都是调用的14行的wrapped_f函数。

当使用@retry()或者带参数的@retry(params)时，如实例2,实际执行了:

stop_after_7_attempts = retry(stop_max_attempt_number)(stop_after_7_attempts)

此时的stop_after_7_attempts函数实际上是22-29行的wrapped_f函数，后续对stop_after_7_attempts函数的调用都是对25行的wrapped_f函数调用。

可以看到实际上@retry将对需要重试的函数调用转化为对Retrying类中call函数的调用，重试逻辑也在这个函数实现,实现对逻辑代码的无侵入，代码如下:

 def call(self, fn, *args, **kwargs):
         start_time = int(round(time.time() * 1000))
         attempt_number = 1
         while True:
             #_before_attempts为@retry传进来的before_attempts，在每次调用函数前执行一些操作
             if self._before_attempts:
                 self._before_attempts(attempt_number)

             try:#Attempt将函数执行结果或者异常信息以及执行次数作为内部状态,用True或False标记是内部存的值正常执行结果还是异常
                 attempt = Attempt(fn(*args, **kwargs), attempt_number, False)
             except:
                 tb = sys.exc_info()#获取异常堆栈信息，sys.exc_info()返回type(异常类型), value(异常说明), traceback(traceback对象，包含更丰富的信息)
                 attempt = Attempt(tb, attempt_number, True)

             if not self.should_reject(attempt):#根据本次执行结果或异常类型判断是否应该停止
                 return attempt.get(self._wrap_exception)

             if self._after_attempts:#_after_attempts为@retry传进来的after_attempts，在每次调用函数后执行一些操作
                 self._after_attempts(attempt_number)

             delay_since_first_attempt_ms = int(round(time.time() * 1000)) - start_time
             if self.stop(attempt_number, delay_since_first_attempt_ms):#根据重试次数和延迟判断是否应该停止
                 if not self._wrap_exception and attempt.has_exception:
                     # get() on an attempt with an exception should cause it to be raised, but raise just in case
                     raise attempt.get()
                 else:
                     raise RetryError(attempt)
             else:#不停止则等待一定时间，延迟时间根据wait函数返回值和_wait_jitter_max计算
                 sleep = self.wait(attempt_number, delay_since_first_attempt_ms)
                 if self._wait_jitter_max:
                     jitter = random.random() * self._wait_jitter_max
                     sleep = sleep + max(0, jitter)
                 time.sleep(sleep / 1000.0)

             attempt_number += 1 #进行下一轮重试

9-13行将函数执行返回结果或异常存入Attempt对象attempt中,Attempt类如下:

class Attempt(object):
    """
    An Attempt encapsulates a call to a target function that may end as a
    normal return value from the function or an Exception depending on what
    occurred during the execution.
    """
    #value值为函数返回结果或异常，根据has_exception判断
    def __init__(self, value, attempt_number, has_exception):
        self.value = value
        self.attempt_number = attempt_number
        self.has_exception = has_exception
    #返回函数执行结果或异常，并根据wrap_exception参数对异常用RetryError包裹
    def get(self, wrap_exception=False):
        """
        Return the return value of this Attempt instance or raise an Exception.
        If wrap_exception is true, this Attempt is wrapped inside of a
        RetryError before being raised.
        """
        if self.has_exception:
            if wrap_exception:
                raise RetryError(self)
            else:#重新构造原异常抛出
                six.reraise(self.value[0], self.value[1], self.value[2])
        else:
            return self.value

    def __repr__(self):
        if self.has_exception:
            return "Attempts: {0}, Error:\n{1}".format(self.attempt_number, "".join(traceback.format_tb(self.value[2])))
        else:
            return "Attempts: {0}, Value: {1}".format(self.attempt_number, self.value)

15行根据should_reject函数的返回值判断是否停止重试，代码如下:

 def should_reject(self, attempt):
        reject = False
        #假如异常在retry_on_exception参数中返回True，则重试,默认不传异常参数时，发生异常一直重试
        if attempt.has_exception:
            reject |= self._retry_on_exception(attempt.value[1])
        else:#假如函数返回结果在retry_on_result参数函数中为True，则重试
            reject |= self._retry_on_result(attempt.value) 

        return reject

22行根据重试次数和延迟判断是否应该停止重试，self.stop的赋值代码在构造函数中，代码片段如下:

        stop_funcs = []
        if stop_max_attempt_number is not None:
            stop_funcs.append(self.stop_after_attempt)

        if stop_max_delay is not None:
            stop_funcs.append(self.stop_after_delay)

        if stop_func is not None:
            self.stop = stop_func

        elif stop is None:#执行次数和延迟任何一个达到限制则停止
            self.stop = lambda attempts, delay: any(f(attempts, delay) for f in stop_funcs)

        else:
            self.stop = getattr(self, stop)

def stop_after_attempt(self, previous_attempt_number, delay_since_first_attempt_ms):
        """Stop after the previous attempt >= stop_max_attempt_number."""
        return previous_attempt_number >= self._stop_max_attempt_number

    def stop_after_delay(self, previous_attempt_number, delay_since_first_attempt_ms):
        """Stop after the time from the first attempt >= stop_max_delay."""
        return delay_since_first_attempt_ms >= self._stop_max_delay

29-33行等待一段时间再次重试，其中延迟时间重点是根据29行的wait函数计算，wait函数在构造函数中赋值，代码片段如下:

wait_funcs = [lambda *args, **kwargs: 0]
        if wait_fixed is not None:
            wait_funcs.append(self.fixed_sleep)

        if wait_random_min is not None or wait_random_max is not None:
            wait_funcs.append(self.random_sleep)

        if wait_incrementing_start is not None or wait_incrementing_increment is not None:
            wait_funcs.append(self.incrementing_sleep)

        if wait_exponential_multiplier is not None or wait_exponential_max is not None:
            wait_funcs.append(self.exponential_sleep)

        if wait_func is not None:
            self.wait = wait_func

        elif wait is None:#返回几个函数的最大值,作为等待时间
            self.wait = lambda attempts, delay: max(f(attempts, delay) for f in wait_funcs)

        else:
            self.wait = getattr(self, wait)

其中最值得研究的是指数退避延迟时间计算方法，函数为exponential_sleep,代码如下:

def exponential_sleep(self, previous_attempt_number, delay_since_first_attempt_ms):
        exp = 2 ** previous_attempt_number
        result = self._wait_exponential_multiplier * exp #延迟时间为_wait_exponential_multiplier*2^x
        if result > self._wait_exponential_max:#假如大于退避上限_wait_exponential_max,则result为上限值
            result = self._wait_exponential_max
        if result < 0:
            result = 0
        return result