Two approaches to Logging when Unit Testing with Python
According to the logging docs:


  The logger name hierarchy is analogous to the Python package hierarchy, and identical to it if you organise your loggers on a per-module basis using the recommended construction logging.getLogger(__name__). That’s because in a module, __name__ is the module’s name in the Python package namespace.


Based on my experience, I would say that you should always use logging.getLogger(__name__) for bigger projects, as it'll make logging modularization easier.

As your question is broad, I recommend you to read the Logging Cookbook, in this link, as it holds many important use cases in which you could optimize the way you use logging.

It's also possible to mix both cases in order to add a timestamp, in example, which is an improved way of using this module:

#!/usr/bin/env python
import logging
import unittest

class GetLoggerTest(unittest.TestCase):
    logger = logging.getLogger(__name__)
    logging.basicConfig(format = '%(asctime)s %(module)s %(levelname)s: %(message)s',
                    datefmt = '%m/%d/%Y %I:%M:%S %p', level = logging.INFO)

    def test_logger(self):
        self.logger.info("self.logger.info test_logger")
        pass