Decorator是一个很好的方法。

from functools import wraps
import time

class retry:
    def __init__(self, success=lambda r:True, times=3, delay=1, raiseexception=True, echo=True):
        self.success = success
        self.times = times
        self.raiseexception = raiseexception
        self.echo = echo
        self.delay = delay
    def retry(fun, *args, success=lambda r:True, times=3, delay=1, raiseexception=True, echo=True, **kwargs):
        ex = Exception(f"{fun} failed.")
        r = None
        for i in range(times):
            if i > 0:
                time.sleep(delay*2**(i-1))
            try:
                r = fun(*args, **kwargs)
                s = success(r)
            except Exception as e:
                s = False
                ex = e
                # raise e
            if not s:
                continue
            return r
        else:
            if echo:
                print(f"{fun} failed.", "args:", args, kwargs, "\nresult: %s"%r)
            if raiseexception:
                raise ex
    def __call__(self, fun):
        @wraps(fun)
        def wraper(*args, retry=0, **kwargs):
            retry = retry if retry>0 else self.times
            return self.__class__.retry(fun, *args, 
                                        success=self.success, 
                                        times=retry,
                                        delay=self.delay,
                                        raiseexception = self.raiseexception,
                                        echo = self.echo,
                                        **kwargs)
        return wraper

一些用法示例:

@retry(success=lambda x:x>3, times=4, delay=0.1)
def rf1(x=[]):
    x.append(1)
    print(x)
    return len(x)
> rf1()

[1]
[1, 1]
[1, 1, 1]
[1, 1, 1, 1]

4

@retry(success=lambda x:x>3, times=4, delay=0.1)
def rf2(l=[], v=1):
    l.append(v)
    print(l)
    assert len(l)>4
    return len(l)
> rf2(v=2, retry=10) #overwite times=4

[2]
[2, 2]
[2, 2, 2]
[2, 2, 2, 2]
[2, 2, 2, 2, 2]

5

> retry.retry(lambda a,b:a+b, 1, 2, times=2)

3

> retry.retry(lambda a,b:a+b, 1, "2", times=2)

TypeError: unsupported operand type(s) for +: 'int' and 'str'

不使用那些丑陋的while循环的更“功能性”的方法:

def tryAgain(retries=0):
    if retries > 10: return
    try:
        # Do stuff
    except:
        retries+=1
        tryAgain(retries)

tryAgain()

最清晰的方法是显式地设置i。例如:

i = 0
while i < 100:
    i += 1
    try:
        # do stuff

    except MyException:
        continue

我使用这个，它可以用于任何函数:

def run_with_retry(func: callable, max_retries: int = 3, wait_seconds: int = 2, **func_params):
num_retries = 1
while True:
    try:
        return func(*func_params.values())
    except Exception as e:
        if num_retries > max_retries:
            print('we have reached maximum errors and raising the exception')
            raise e
        else:
            print(f'{num_retries}/{max_retries}')
            print("Retrying error:", e)
            num_retries += 1
            sleep(wait_seconds)

像这样调用:

    def add(val1, val2):
        return val1 + val2

    run_with_retry(func=add, param1=10, param2=20)

这里有一个快速装饰器来处理这个问题。7行，没有依赖关系。

def retry(exception=Exception, retries=3, delay=0):
    def wrap(func):
        for i in range(retries):
            try:
                return func()
            except exception as e:
                print(f'Retrying {func.__name__}: {i}/{retries}')
                time.sleep(delay)
        raise e
    return wrap

@retry()
def do_something():
  ...
@retry(HTTPError, retries=100, delay=3)
def download_something():
  ...

可以添加的一个功能是扩展异常以处理多个异常(splat一个列表)。

你可以使用Python重试包。 重试

它是用Python编写的，目的是简化向几乎任何东西添加重试行为的任务。