Logging Context Manager

Create a service/logs.py file to manage a logging process.

Create a function called log with a level argument.

Retrieve the root logger and the current logging level of the logger.

Set the logging level to the specified level.

In the try block, yield the logger itself.

In the finally block, set the logging level to its original state.

Remember to implement unit tests for a log method, use pytest for tests.

Create a configurator/settings/base.py file to configure logging configuration.

Create a LOGGING variable to declare initialization for StreamHandler.

LOGGING field must be in dict type.

Inside this dictionary, you must set version, disable_existing_loggers, handlers, formatters and loggers.

The format of the formatter must be like {datetime - level_name - log_message}

Remember to implement unit tests for messages, use pytest for tests.

Create a domain/models.py file to manage log levels.

Create a LogLevel class that inherits from the Enum class.

Use the enum to set and check logging levels.

Logging levels must be DEBUG, INFO, WARNING, ERROR, CRITICAL from logging module.

__str__ method has to return “{class_name}.{enum_type_name}”.

Remember to implement unit tests for enum levels, use pytest for tests.

Create a domain/validators.py file to validate the level of the log.

Create a decorator called validate_log_level.

Check if the level is in the kwargs or not. If it is, it must be set to kwargs.

Check if the level is validated or not. If it"s not, raise KeyError. If it"s, return the LogLevel value for the corresponding level

The last process has to be in the different function to reduce complexity.

The validate_log_level method has to be called before log method.

Remember to implement unit tests for a validate_log_level method, use pytest for tests.