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level, as appropriate 2 Create Handler objects by instantiating one of the various types of handlers (FileHandler, StreamHandler, SocketHandler, and so on) and set an appropriate level 3 Create message Formatter objects and attach them to the Handler objects using the setFormatter() method 4 Attach the Handler objects to the Logger objects using the addHandler() method Because the configuration of each step can be somewhat involved, your best bet is to put all the logging configuration into a single well-documented location For example, you might create a file applogconfigpy that is imported by the main program of your application:
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# applogconfigpy import logging import sys # Set the message format format = loggingFormatter("%(levelname)-10s %(asctime)s %(message)s") # Create a handler that prints CRITICAL level messages to stderr crit_hand = loggingStreamHandler(sysstderr) crit_handsetLevel(loggingCRITICAL) crit_handsetFormatter(format) # Create a handler that prints messages to a file applog_hand = loggingFileHandler('applog') applog_handsetFormatter(format) # Create a top-level logger called 'app' app_log = logginggetLogger("app") app_logsetLevel(loggingINFO) app_logaddHandler(applog_hand) app_logaddHandler(crit_hand) # Change the level on the 'appnet' logger logginggetLogger("appnet")setLevel(loggingERROR)
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If changes need to be made to any part of the logging configuration, having everything in one location makes things easier to maintain Keep in mind that this special file only needs to be imported once and in only one location in the program In other parts of the code where you want to issue log messages, you simply include code like this:
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import logging app_log = logginggetLogger("app") app_logcritical("An error occurred")
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The loggingconfig Submodule
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As an alternative to hard-coding the logging configuration in Python code, it is also possible to configure the logging module through the use of an INI-format configuration fileTo do this, use the following functions found in loggingconfig
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fileConfig(filename [, defaults [, disable_existing_loggers]])
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Reads the logging configuration from the configuration file filename defaults is a
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dictionary of default configuration parameters for use in the config fileThe specified filename is read using the ConfigParser module disable_existing_loggers is a Boolean flag that specifies whether or not any existing loggers are disabled when new configuration data is read By default, this is True The online documentation for the logging module goes into some detail on the expected format of configuration files However, experienced programmers can probably extrapolate from the following example, which is a configuration file version of applogconfigpy shown in the previous section
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; applogconfigini ; ; Configuration file for setting up logging ; The following sections provide names for Logger, Handler, and Formatter ; objects that will be configured later in the file [loggers] keys=root,app,app_net [handlers] keys=crit,applog [formatters] keys=format [logger_root] level=NOTSET handlers= [logger_app] level=INFO propagate=0 qualname=app handlers=crit,applog [logger_app_net] level=ERROR propagate=1 qualname=appnet handlers= [handler_crit] class=StreamHandler level=CRITICAL formatter=format args=(sysstderr,) [handler_applog] class=FileHandler level=NOTSET formatter=format args=('applog',) [formatter_format] format=%(levelname)-10s %(asctime)s %(message)s datefmt=
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To read this configuration file and set up logging, you would use this code:
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import loggingconfig
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loggingconfigfileConfig('applogconfigini')
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As before, modules that want to issue log messages do not need to worry about the details of loading the logging configurationThey merely import the logging module and get a reference to the appropriate Logger object For example:
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import logging app_log = logginggetLogger("app") app_logcritical("An error occurred")
Performance Considerations
Adding logging to an application can severely degrade its performance if you aren t careful However, there are some techniques that can be used to reduce the overhead First, Python s optimized mode (-O) removes all code that is conditionally executed using statements such as if _ _debug_ _: statements If the sole purpose of logging is debugging, you could conditionally execute all of the logging calls and have the calls removed in optimized mode A second technique would be to use a Null object in place of a Logger object when logging is to be completely disabledThis is different than using None Instead, you want to use an instance of an object that silently swallows all operations that get performed on it For example:
class Null(object): def _ _init_ _(self, *args, **kwargs): pass def _ _call_ _(self, *args, **kwargs): return self def _ _getattribute_ _(self, name): return self def _ _setattr_ _(self, name, value): pass def _ _delattr_ _(self,name): pass log = Null() logcritical("An error occurred")