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Autologging makes logging and tracing Python classes easy.

Project description

Autologging eliminates boilerplate logging setup code and tracing code, and provides a means to separate application logging from program flow and data tracing.

Python modules that make use of Autologging are cleaner, leaner, and more resilient to changes that would otherwise require updating tracing statements.

Autologging allows for tracing to be configured (and controlled) independently from application logging. Toggle tracing on/off, write trace log records to a separate log, and use different formatting for trace log entries - all via standard Python logging facilities, and without affecting your application logging.

Autologging exposes two decorators and a custom log level:

@logged Decorate a class to create a __log member. The logger is named by default to match the dotted-name of the containing class. A function may also be decorated, creating a _log attribute on the function object whose default name matches the containing module. A specifically-named logger may also be passed to the decorator (i.e. @logged(my_logger)).

@traced Decorate a class to provide automatic method call/return tracing. By default, all class, static, and instance methods are traced (excluding “__special__” methods, with the exception of __init__). As with the logged decorator, the default name of the tracing logger matches the dotted-name of the containing class and may be overridden by passing a specifically-named logger to the decorator. Additionally, this decorator accepts multiple string arguments that explicitly name the methods to be traced (and may even name “__special__” methods). Module-level functions may also be traced using this decorator.

TRACE The autologging.TRACE (level 1) log level is registered with the Python logging module when Autologging is imported so that tracing can be configured and controlled independently of application logging.

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