基于装饰器的重试

Tenacity使程序员能够使用Python装饰器向函数或方法添加重试逻辑。 因此，可以简单地为特定动作添加重试行为，而无需更改原始代码。

可调整的重试计划

Tenacity提供了几个可调整的参数来指定重试计划。 开发人员可以自定义重试的最大次数、重试之间的时间间隔以及重试发生的情况。

指数回退

Tenacity支持指数退避，这是一种流行的当前重试调用技术，其中重试之间的间隔随着每次尝试的次数呈指数增长。 这样做可以避免在流量大或拥堵时向目标服务发送过多请求。

抖动和随机性

Tenacity提供了引入抖动和随机性的选项，以避免重试延迟引起的同步问题和雷击效应。 这减少了多个客户端同时重试的可能性，避免了重试努力同时爆发。

重试条件和异常

开发人员可以根据操作的返回值或任何引发的异常创建独特的重试条件。 这样可以精确控制重试应该在何时和什么条件下进行。

超时和截止日期

Tenacity促进了通用操作超时和截止日期的创建，保证重试尝试不会无限期进行，并且如果操作超过预定阈值将最终终止。

与流行的Python框架的集成

Flask、Django和Celery只是Tenacity轻松交互的一些框架。 这使得开发人员可以轻松地在后台操作、网络端点或他们系统的任何其他部分添加重试逻辑。

创建和配置Tenacity

from tenacity import retry, wait_exponential

# Decorate the function with a retry mechanism
@retry(wait=wait_exponential(multiplier=1, min=1, max=10))
def my_function():
    # Your code logic here
    pass

# Explanation:
# - `multiplier`: Used to increase the interval between retries.
# - `min`: Minimum wait time in seconds between retries.
# - `max`: Maximum wait time allowed between retries.

from tenacity import retry, wait_exponential

# Decorate the function with a retry mechanism
@retry(wait=wait_exponential(multiplier=1, min=1, max=10))
def my_function():
    # Your code logic here
    pass

# Explanation:
# - `multiplier`: Used to increase the interval between retries.
# - `min`: Minimum wait time in seconds between retries.
# - `max`: Maximum wait time allowed between retries.

from tenacity import retry, wait_random

@retry(wait=wait_random(min=1, max=10))
def my_function():
    # Your code logic here
    pass

# Explanation:
# - `min`: Minimum random wait time in seconds between retries.
# - `max`: Maximum random wait time in seconds between retries.

from tenacity import retry, wait_random

@retry(wait=wait_random(min=1, max=10))
def my_function():
    # Your code logic here
    pass

# Explanation:
# - `min`: Minimum random wait time in seconds between retries.
# - `max`: Maximum random wait time in seconds between retries.

from tenacity import retry, retry_if_exception_type

# Retry on specific exceptions like ConnectionError
@retry(retry=retry_if_exception_type(ConnectionError))
def my_function():
    # Your code logic here
    pass

# Explanation:
# Retry only if a ConnectionError exception is raised during the function execution.

from tenacity import retry, retry_if_exception_type

# Retry on specific exceptions like ConnectionError
@retry(retry=retry_if_exception_type(ConnectionError))
def my_function():
    # Your code logic here
    pass

# Explanation:
# Retry only if a ConnectionError exception is raised during the function execution.

from tenacity import retry, retry_if_result

@retry(retry=retry_if_result(lambda result: result is None))
def my_function():
    # Your code logic here
    return some_result

# Explanation:
# Retry if the function result is `None`.

from tenacity import retry, retry_if_result

@retry(retry=retry_if_result(lambda result: result is None))
def my_function():
    # Your code logic here
    return some_result

# Explanation:
# Retry if the function result is `None`.

from tenacity import retry, stop_after_delay

@retry(stop=stop_after_delay(30))
def my_function():
    # Your code logic here
    pass

# Explanation:
# Stop retrying after 30 seconds have elapsed since the first attempt.

from tenacity import retry, stop_after_delay

@retry(stop=stop_after_delay(30))
def my_function():
    # Your code logic here
    pass

# Explanation:
# Stop retrying after 30 seconds have elapsed since the first attempt.

from tenacity import retry, after_log
import logging

logger = logging.getLogger(__name__)

@retry(after=after_log(logger, logging.DEBUG))
def my_function():
    # Your code logic here
    pass

# Explanation:
# Use a logger to log details of each retry attempt at the DEBUG level.

from tenacity import retry, after_log
import logging

logger = logging.getLogger(__name__)

@retry(after=after_log(logger, logging.DEBUG))
def my_function():
    # Your code logic here
    pass

# Explanation:
# Use a logger to log details of each retry attempt at the DEBUG level.

开始

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