Wednesday, 27 January 2016

Using a context manager for selective logging

There are times when it would be useful to temporarily change the logging configuration and revert it back after doing something. For this, a context manager is the most obvious way of saving and restoring the logging context. Here is a simple example of such a context manager, which allows you to optionally change the logging level and add a logging handler purely in the scope of the context manager:

import logging
import sys

class LoggingContext(object):
    def __init__(self, logger, level=None, handler=None, close=True):
        self.logger = logger
        self.level = level
        self.handler = handler
        self.close = close

    def __enter__(self):
        if self.level is not None:
            self.old_level = self.logger.level
            self.logger.setLevel(self.level)
        if self.handler:
            self.logger.addHandler(self.handler)

    def __exit__(self, et, ev, tb):
        if self.level is not None:
            self.logger.setLevel(self.old_level)
        if self.handler:
            self.logger.removeHandler(self.handler)
        if self.handler and self.close:
            self.handler.close()
        # implicit return of None => don't swallow exceptions

If you specify a level value, the logger's level is set to that value in the scope of the with block covered by the context manager. If you specify a handler, it is added to the logger on entry to the block and removed on exit from the block. You can also ask the manager to close the handler for you on block exit - you could do this if you don't need the handler any more.

To illustrate how it works, we can add the following block of code to the above:

if __name__ == '__main__':
    logger = logging.getLogger('foo')
    logger.addHandler(logging.StreamHandler())
    logger.setLevel(logging.INFO)
    logger.info('1. This should appear just once on stderr.')
    logger.debug('2. This should not appear.')
    with LoggingContext(logger, level=logging.DEBUG):
        logger.debug('3. This should appear once on stderr.')
    logger.debug('4. This should not appear.')
    h = logging.StreamHandler(sys.stdout)
    with LoggingContext(logger, level=logging.DEBUG, handler=h, close=True):
        logger.debug('5. This should appear twice - once on stderr and once on stdout.')
    logger.info('6. This should appear just once on stderr.')
    logger.debug('7. This should not appear.')

We initially set the logger's level to INFO, so message #1 appears and message #2 doesn't. We then change the level to DEBUG temporarily in the following with block, and so message #3 appears. After the block exits, the logger's level is restored to INFO and so message #4 doesn't appear. In the next with block, we set the level to DEBUG again but also add a handler writing to sys.stdout. Thus, message #5 appears twice on the console (once via stderr and once via stdout). After the with statement's completion, the status is as it was before so message #6 appears (like message #1) whereas message #7 doesn't (just like message #2).

If we run the resulting script, the result is as follows:

vinay@ubuntu:~/projects/scratch$ python logctx.py 
1. This should appear just once on stderr.
3. This should appear once on stderr.
5. This should appear twice - once on stderr and once on stdout.
5. This should appear twice - once on stderr and once on stdout.
6. This should appear just once on stderr.

If we run it again, but pipe stderr to /dev/null, we see the following, which is the only message written to stdout:

vinay@ubuntu:~/projects/scratch$ python logctx.py 2>/dev/null
5. This should appear twice - once on stderr and once on stdout.

Once again, but piping stdout to /dev/null, we get:

vinay@ubuntu:~/projects/scratch$ python logctx.py >/dev/null
1. This should appear just once on stderr.
3. This should appear once on stderr.
5. This should appear twice - once on stderr and once on stdout.
6. This should appear just once on stderr.

In this case, the message #5 printed to stdout doesn't appear, as expected.

Of course, the approach described here can be generalised, for example to attach logging filters temporarily. The content of this post will shortly be added to the Logging Cookbook in the Python documentation. Note that the code works in Python 2 as well as Python 3.

2 comments:

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