![]() ![]() The predefined values include, from highest to lowest severity: Logging.getLevelName( logging_level) returns the textual representation of the severity called logging_level. LogWithLevelName = logging.getLogger( 'myLoggerSample') Setting level names: This supports you in maintaining your own dictionary of log messages and reduces the possibility of typo errors. ![]() The following are some tips for best practices, so you can take the most from Python logging: The possibilities with Python logging are endless and you can customize them to your needs. Since the Python Client for Stackdriver Logging library also does logging, you may get a recursive loop if the root logger uses your log handler. When developing your logger, take into account that the root logger doesn’t use your log handler. ![]() Currently in beta release, you can write logs to Stackdriver Logging from Python applications by using Google’s Python logging handler included with the Stackdriver Logging client library, or by using the client library to access the API directly. If your goals are aimed at the Cloud, you can take advantage of Python’s set of logging handlers to redirect content. Logging.basicConfig(level=logging.DEBUG, format= '%(asctime)s - %(levelname)s - %(message)s') This is an example of a basic logger in Python: The message then propagates up the logger tree until it hits the root logger, or a logger up in the tree that is configured with propagate=False. When you send a message into one of the loggers, the message gets output on all of that logger’s handlers, using a formatter that’s attached to each handler. These multiple logger objects are organized into a tree that represents various parts of your system and different third-party libraries that you have installed.
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