Logging

Sacred used the python logging module to log some basic information about the execution. It also makes it easy for you to integrate that logging with your code.

Adjusting Log-Levels from command line

If you run the hello_world example you will see the following output:

>> python hello_world.py
INFO - hello_world - Running command 'main'
INFO - hello_world - Started
Hello world!
INFO - hello_world - Completed after 0:00:00

The lines starting with INFO are logging outputs. They can be suppressed by adjusting the loglevel. This can be done via the command-line like with the --loglevel (-l for short) option:

>> python hello_world -l ERROR
Hello world!

The specified level can be either a string or an integer:

Level	Numeric value
CRITICAL	50
ERROR	40
WARNING	30
INFO	20
DEBUG	10
NOTSET	0

Adjusting Log-Levels from python

If you prefer, you can also adjust the logging level from python when running an experiment by passing the long version of the log level command line parameter as an option, as follows:

ex.run(options={'--loglevel': 'ERROR'})

Note that this can only be done when using Experiment.run, not when using Experiment.main or Experiment.automain.

Integrate Logging Into Your Experiment

If you want to make use of the logging mechanism for your own experiments the easiest way is to use the special _log argument in your captured functions:

@ex.capture
def some_function(_log):
    _log.warning('My warning message!')

This will by default print a line like this:

WARNING - some_function - My warning message!

The _log is a standard Logger object for your function, as a child logger of the experiments main logger. So it allows calls to debug, info, warning, error, critical and some more. Check out the documentation to see what you can do with them.

Customize the Logger

It is easy to customize the logging behaviour of your experiment by just providing a custom Logger object to your experiment:

import logging
logger = logging.getLogger('my_custom_logger')
## configure your logger here
ex.logger = logger

The custom logger will be used to generate all the loggers for all captured functions. This way you can use all the features of the logging package. See the examples/log_example.py file for an example of this.