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。
- 1 #装饰器模式,对需要重试的函数,利用retry注解返回
- 2 def retry(*dargs, **dkw):
- 3 """
- 4 Decorator function that instantiates the Retrying object
- 5 @param *dargs: positional arguments passed to Retrying object
- 6 @param **dkw: keyword arguments passed to the Retrying object
- 7 """
- 8 # support both @retry and @retry() as valid syntax
- 9 #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
- 10 if len(dargs) == 1 and callable(dargs[0]):
- 11 def wrap_simple(f):
- 12
- 13 @six.wraps(f)#注解用于将函数f的签名复制到新函数wrapped_f
- 14 def wrapped_f(*args, **kw):
- 15 return Retrying().call(f, *args, **kw)
- 16
- 17 return wrapped_f
- 18
- 19 return wrap_simple(dargs[0])
- 20
- 21 else:#当用法为@retry()带括号时走这条路径,返回函数对象wrapped_f
- 22 def wrap(f):
- 23
- 24 @six.wraps(f)#注解用于将函数f的签名复制到新函数wrapped_f
- 25 def wrapped_f(*args, **kw):
- 26 return Retrying(*dargs, **dkw).call(f, *args, **kw)
- 27
- 28 return wrapped_f
- 29
- 30 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:
- 1 def call(self, fn, *args, **kwargs):
- 2 start_time = int(round(time.time() * 1000))
- 3 attempt_number = 1
- 4 while True:
- 5 #_before_attempts为@retry传进来的before_attempts,在每次调用函数前执行一些操作
- 6 if self._before_attempts:
- 7 self._before_attempts(attempt_number)
- 8
- 9 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
- 10 attempt = Attempt(fn(*args, **kwargs), attempt_number, False)
- 11 except:
- 12 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)
- 13 attempt = Attempt(tb, attempt_number, True)
- 14
- 15 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
- 16 return attempt.get(self._wrap_exception)
- 17
- 18 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
- 19 self._after_attempts(attempt_number)
- 20
- 21 delay_since_first_attempt_ms = int(round(time.time() * 1000)) - start_time
- 22 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
- 23 if not self._wrap_exception and attempt.has_exception:
- 24 # get() on an attempt with an exception should cause it to be raised, but raise just in case
- 25 raise attempt.get()
- 26 else:
- 27 raise RetryError(attempt)
- 28 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
- 29 sleep = self.wait(attempt_number, delay_since_first_attempt_ms)
- 30 if self._wait_jitter_max:
- 31 jitter = random.random() * self._wait_jitter_max
- 32 sleep = sleep + max(0, jitter)
- 33 time.sleep(sleep / 1000.0)
- 34
- 35 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