Cacher is the code snippet organizer for pro developers

import logging
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

logger.info('Start reading database')
# read database here
records = {'john': 55, 'tom': 66}
logger.debug('Records: %s', records)
logger.info('Updating records ...')
# update records here
logger.info('Finish updating records')
You can run it and see

INFO:__main__:Start reading database
INFO:__main__:Updating records ...
INFO:__main__:Finish updating records
What’s different between the “print” approach you asked. Well, of course there are benefits:

You can control message level and filter out not important ones
You can decide where and how to output later
There are different importance levels you can use, debug, info, warning, error and critical. By giving different level to logger or handler, you can write only error messages to specific log file, or record debug details when debugging. Let’s change the logger level to DEBUG and see the output again

logging.basicConfig(level=logging.DEBUG)
The output:

INFO:__main__:Start reading database
DEBUG:__main__:Records: {'john': 55, 'tom': 66}
INFO:__main__:Updating records ...
INFO:__main__:Finish updating records
As you can see, we adjust the logger level to DEBUG, then debug records appear in output. You can also decide how these messages are processed. For example, you can use a FileHandler to write records to a file.

import logging

logger = logging.getLogger(__name__)
logger.setLevel(logging.INFO)

# create a file handler
handler = logging.FileHandler('hello.log')
handler.setLevel(logging.INFO)

# create a logging format
formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')
handler.setFormatter(formatter)

# add the handlers to the logger
logger.addHandler(handler)

logger.info('Hello baby')