python logging with yaml

Recently, I was made a service which can provide a simple way to get best model. so, i spent lot of time to read source code of auto-sklearn, auto-sklearn is an automated machine learning toolkit and a drop-in replacement for a scikit-learn estimator.

when I write my logging module I found the logging module of auto-sklearn which used yaml file as config, the config file：

 ---

 version: 1

 disable_existing_loggers: False

 formatters:

   simple:

     format: '[%(asctime)s: %(levelname)s] %(message)s'

 handlers:

   console:

     class: logging.StreamHandler

     level: WARNING

     formatter: simple

     stream: ext://sys.stdout

   file_handler:

     class: logging.FileHandler

     level: DEBUG

     formatter: simple

     filename: autosklearn.log

 root:

   level: ERROR

   handlers: [console, file_handler]

 loggers:

   server:

     level: INFO

     handlers: [file_handler]

     propagate: no

the caller can define loggers、handlers、formatters here, after that, caller need write setup code and get logger code.

 # -*- encoding: utf-8 -*-

 import logging

 import logging.config

 import os

 import yaml

 def setup_logger(output_file=None, logging_config=None):

     # logging_config must be a dictionary object specifying the configuration

     if not os.path.exists(os.path.dirname(output_file)):

         os.makedirs(os.path.dirname(output_file))

     if logging_config is not None:

         if output_file is not None:

             logging_config['handlers']['file_handler']['filename'] = output_file

         logging.config.dictConfig(logging_config)

     else:

         with open(os.path.join(os.path.dirname(__file__), 'logging.yaml'),

                   'r') as fh:

             logging_config = yaml.safe_load(fh)

         if output_file is not None:

             logging_config['handlers']['file_handler']['filename'] = output_file

         logging.config.dictConfig(logging_config)

 def _create_logger(name):

     return logging.getLogger(name)

 def get_logger(name):

     logger = PickableLoggerAdapter(name)

     return logger

 class PickableLoggerAdapter(object):

     def __init__(self, name):

         self.name = name

         self.logger = _create_logger(name)

     def __getstate__(self):

         """

         Method is called when pickle dumps an object.

         Returns

         -------

         Dictionary, representing the object state to be pickled. Ignores

         the self.logger field and only returns the logger name.

         """

         return {'name': self.name}

     def __setstate__(self, state):

         """

         Method is called when pickle loads an object. Retrieves the name and

         creates a logger.

         Parameters

         ----------

         state - dictionary, containing the logger name.

         """

         self.name = state['name']

         self.logger = _create_logger(self.name)

     def debug(self, msg, *args, **kwargs):

         self.logger.debug(msg, *args, **kwargs)

     def info(self, msg, *args, **kwargs):

         self.logger.info(msg, *args, **kwargs)

     def warning(self, msg, *args, **kwargs):

         self.logger.warning(msg, *args, **kwargs)

     def error(self, msg, *args, **kwargs):

         self.logger.error(msg, *args, **kwargs)

     def exception(self, msg, *args, **kwargs):

         self.logger.exception(msg, *args, **kwargs)

     def critical(self, msg, *args, **kwargs):

         self.logger.critical(msg, *args, **kwargs)

     def log(self, level, msg, *args, **kwargs):

         self.logger.log(level, msg, *args, **kwargs)

     def isEnabledFor(self, level):

         return self.logger.isEnabledFor(level)

get_logger return a logger object, setup_logger setup logger handler which define output where.

when you use it,like this

 from .util import get_logger, setup_logger

 APP_DIR = os.path.dirname(os.path.abspath(__file__))

 setup_logger(output_file=os.path.join(APP_DIR, 'logs', 'server.log'))

 LOG = get_logger("server")

Define a global variable LOG for other modules to call.

all done.

巴特西

python logging with yaml

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