171 lines
4.9 KiB
Markdown
171 lines
4.9 KiB
Markdown
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# Python:如何创建异常日志装饰器
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> 原文：<https://www.blog.pythonlibrary.org/2016/06/09/python-how-to-create-an-exception-logging-decorator/>
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前几天，我决定创建一个装饰器来捕捉异常并记录它们。我在 [Github](https://gist.github.com/diosmosis/1148066) 上找到了一个相当复杂的例子，我用它来思考如何完成这项任务，并得出了以下结论:
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```py
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# exception_decor.py
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import functools
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import logging
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def create_logger():
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"""
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Creates a logging object and returns it
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"""
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logger = logging.getLogger("example_logger")
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logger.setLevel(logging.INFO)
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# create the logging file handler
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fh = logging.FileHandler("/path/to/test.log")
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fmt = '%(asctime)s - %(name)s - %(levelname)s - %(message)s'
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formatter = logging.Formatter(fmt)
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fh.setFormatter(formatter)
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# add handler to logger object
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logger.addHandler(fh)
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return logger
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def exception(function):
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"""
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A decorator that wraps the passed in function and logs
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exceptions should one occur
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"""
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@functools.wraps(function)
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def wrapper(*args, **kwargs):
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logger = create_logger()
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try:
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return function(*args, **kwargs)
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except:
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# log the exception
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err = "There was an exception in "
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err += function.__name__
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logger.exception(err)
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# re-raise the exception
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raise
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return wrapper
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```
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在这段代码中，我们有两个函数。第一个创建一个日志对象并返回它。第二个函数是我们的装饰函数。这里，我们将传入的函数包装在一个 try/except 中，并使用我们的记录器记录发生的任何异常。您会注意到，我还记录了发生异常的函数名。
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现在我们只需要测试一下这个装饰器。为此，您可以创建一个新的 Python 脚本，并向其中添加以下代码。确保将它保存在与上面代码相同的位置。
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```py
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from exception_decor import exception
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@exception
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def zero_divide():
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1 / 0
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if __name__ == '__main__':
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zero_divide()
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```
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当您从命令行运行此代码时，您应该得到一个包含以下内容的日志文件:
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```py
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2016-06-09 08:26:50,874 - example_logger - ERROR - There was an exception in zero_divide
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Traceback (most recent call last):
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File "/home/mike/exception_decor.py", line 29, in wrapper
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return function(*args, **kwargs)
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File "/home/mike/test_exceptions.py", line 5, in zero_divide
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1 / 0
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ZeroDivisionError: integer division or modulo by zero
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```
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我认为这是一个方便的代码，我希望你会发现它也很有用！
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**UPDATE** :一位敏锐的读者指出，将这个脚本一般化是一个好主意，这样您就可以向装饰者传递一个 logger 对象。让我们来看看它是如何工作的！
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### 将一个记录器传递给我们的装饰者
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首先，让我们将我们的日志代码分离到它自己的模块中。姑且称之为 **exception_logger.py** 。下面是放入该文件的代码:
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```py
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# exception_logger.py
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import logging
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def create_logger():
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"""
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Creates a logging object and returns it
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"""
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logger = logging.getLogger("example_logger")
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logger.setLevel(logging.INFO)
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# create the logging file handler
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fh = logging.FileHandler(r"/path/to/test.log")
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fmt = '%(asctime)s - %(name)s - %(levelname)s - %(message)s'
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formatter = logging.Formatter(fmt)
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fh.setFormatter(formatter)
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# add handler to logger object
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logger.addHandler(fh)
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return logger
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logger = create_logger()
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```
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接下来，我们需要修改装饰器代码，这样我们就可以接受一个日志记录器作为参数。务必将其保存为 **exception_decor.py**
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```py
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# exception_decor.py
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import functools
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def exception(logger):
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"""
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A decorator that wraps the passed in function and logs
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exceptions should one occur
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@param logger: The logging object
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"""
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def decorator(func):
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def wrapper(*args, **kwargs):
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try:
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return func(*args, **kwargs)
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except:
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# log the exception
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err = "There was an exception in "
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err += func.__name__
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logger.exception(err)
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# re-raise the exception
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raise
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return wrapper
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return decorator
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```
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你会注意到这里有多层嵌套函数。请务必仔细研究，以了解发生了什么。最后我们需要修改我们的测试脚本:
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```py
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from exception_decor import exception
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from exception_logger import logger
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@exception(logger)
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def zero_divide():
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1 / 0
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if __name__ == '__main__':
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zero_divide()
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```
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这里我们导入了我们的装饰器和记录器。然后我们装饰我们的函数，并把 logger 对象传递给 decorator。如果运行这段代码，您应该会看到与第一个示例中生成的文件相同的文件。玩得开心！
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