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Autologging is a lightweight Python module that comes with two decorators and a metaclass. It can automatically name the logger to match the class name. Additionally, it adds automatic tracing to some class methods, defines a log level in order to toggle on or off all traced messages, provides call and return tracing and logs record attributes.
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If the logger's name equals the class name, then it will be autologged, that is, the class name will be the logger name. If you decorate a method, then Autologging Serial Key will be done for the decorated method, and the class name will be used to autologge the logger. If you decorate a method, then you may add arguments to the Autologging Crack For Windows decorator. The additional arguments will be passed along with the name of the method, that is, the class name will be used to autologge the logger. If you use a metaclass, then it will add autologging to all class methods that are defined by that metaclass. And now, for the code. import autologging # decorator for class methods def autologging_method(func): """decorator for class methods """ class _AutologgingMethodClass(type): _fields = ["_logger", "func"] def __init__(cls, name, bases, dict): # create and return the logger, initializing the current # logger name to name if provided. _logger = cls._logger = logging.getLogger(name) _logger._loggerName = name cls.func = func cls.__name__ = name cls.__doc__ = func.__doc__ return cls @autologging_method class _AutologgingMethodClass(): classmethod: def classmethod(cls, name, bases, dict): cls._logger = logging.getLogger(name) cls._logger._loggerName = name cls.__name__ = name cls.__doc__ = func.__doc__ cls.__init__ = classmethod.__init__ return cls metaclass: class _AutologgingMethodClass(type): _fields = ["_logger", "func"] def __new__(cls, name, bases, dict): _logger = cls._logger = logging.getLogger(name) _logger._loggerName = name cls.func = func cls.__name__ = name cls.
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KEY = keyword: indicates a piece of additional information to be placed in the log record. Ex: KEY = *mylogger*: my class name In this case, mylogger is always written in the log as a string. DESCRIPTION Autologging is a lightweight Python module that comes with two decorators and a metaclass. It can automatically name the logger to match the class name. Additionally, it adds automatic tracing to some class methods, defines a log level in order to toggle on or off all traced messages, provides call and return tracing and logs record attributes. It can automatically name the logger to match the class name. * Autologging.autologger(): The Autologger object, used to name the logger. * metaclass.AutologgingMetaClass(): The default metaclass. * decorators.autologger(**args): The decorator that registers the Autologger object as the log handler. * decorators.trace(obj): Determines whether to log the function’s arguments, as well as any arguments to the function call. * decorators.returntrace(obj): Determines whether to log the function’s return value. * decorators.calltrace(obj): Determines whether to log the function’s arguments, as well as any arguments to the function call. * decorators.record(obj): This decorator adds a new attribute to the function’s metaclass. The attribute is called record, and it can be used to record which attributes are set in the function’s arguments. The default value of record is False. * autologger.level(level): The level of the record log. Either OFF, ON, L0, L1 or L2. Defaults to ON. Autologger.level(level): The level of the record log. Either OFF, ON, L0, L1 or L2. Defaults to ON. autologger.level(level): The level of the record log. Either OFF, ON, L0, L1 or L2. Defaults to ON. THE AUTOLOGGER OBJECT class Autologger: NAME = "mylogger" def __init__(self, prefix=None, level 1d6a3396d6
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autologging automates and makes easier logging of Python classes. Usage: >>> import autologging >>> >>> class MyClass(object): ... def methodA(self, value1, value2, value3): ... print "values:", value1, value2, value3 ... return "end" >>> >>> autologging.autologging(MyClass) >>> >>> MyClass.methodA("myValue1", "myValue2", "myValue3") values: myValue1 myValue2 myValue3 end >>> >>> MyClass.methodA("myValue1", "myValue2", "myValue3") Traceback (most recent call last): ... autologging.LoggerNotFound: No logger found for 'MyClass' (printStacktrace) Autologging is a good way to trace Python class methods. Because, while a class method is executing, its internal state is constantly being accessed. Therefore, it is important to log those operations. Autologging provides trace decorator for that purpose. >>> @autologging.trace >>> class MyClass(object): ... def methodA(self, value1, value2, value3): ... print "values:", value1, value2, value3 ... return "end" ... >>> MyClass.methodA("myValue1", "myValue2", "myValue3") values: myValue1 myValue2 myValue3 end Autologging: Debugging class method If you want to debug a class method from time to time, you can use the autologging.Trace decorator with a function and call it each time you want to debug the execution of that class method. >>> @autologging.trace >>> def setUp(): ... print "This is a DEBUG message" >>> >>> class MyClass(object): ... def methodA(self, value1, value2, value
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Autologging is an extension to the logging package that, besides being a simple callable class decorator, also provides automatic tracing for method calls and return values. Also autologging provides a couple of helpers that should ease the adoption of such package. Autologging can be configured to automatically log (this can be performed by providing an attribute to an object or defining a property in the class) a record of the following information: ✓ Function calls ✓ Return values ✓ Parameter values ✓ Attribute accesses ✓ Formatters/handlers ✓ Call times ✓ Source code location ✓ Call and return arguments ✓ Test cases execution results There are two ways to decorate class methods. The first one is the easy one and can be performed by just providing a callable, in order to log such a function. The second one is slightly more complex, but enables to add additional information to the logged messages. # Using the decorator to log a function and # adding a "prefix" to the logged name.# Example: Define a function "log_function" to log the name # of the function that contains the decorator. And log the name of # the method that called it, plus the returned value.# Class must be Autologging, and the log_function # class function decorator will be used.# class A(Autologging):...#def log_function(self):... # Using the @autologging.add_call_trace decorator. # Define a function with no parameters and no return value. # The decorator will log the call to that function. # # The function will define a class log_decorator # It will add a "call trace" with the following format: # log_decorator__. # It will also add an attribute in this way: # log_decorator___log_obj # where obj_name is the object that does the decorating. # For example, log_decorator_a_a_log_obj_obj. # # The function will define a class "log_decorator". # The decorator will log the call to the decorator that calls # the decorated method. The "log_decorator" attribute in the # log_decorator class will include the caller object name. # # This decorator is similar to the # @autologging.add_call_trace(True) decorator,
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Windows OS: Mac OS: Standalone Build: NetEase Build: Android Build: Steam Build: Steam Keys are available for purchase on our website, Steam Keys are available for purchase on our website, HERE Are you okay with giving up your privacy? Are you aware that you must be 18 years of age or older in order to download and install this software? As an added note, the permission system on Windows is different than other operating systems. If you
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