Splunk® Machine Learning Toolkit

ML-SPL API Guide

This documentation does not apply to the most recent version of Splunk® Machine Learning Toolkit. For documentation on the most recent version, go to the latest release.

Custom logging

For more detailed logging, you can also use a logger with a custom name as in the following example: 

from cexc import get_logger


logger = get_logger('MyCustomLogging')
logger.warn('warning!')
logger.error('error!')
logger.debug('info!')

These messages will be logged to $SPLUNK_HOME/var/log/mlspl.log.

Alongside the name provided in get_logger, the function we're inside of (in this case the __init__ method) is also recorded: 

1491862833.627798 2017-04-10 15:20:33,627 WARNING [mlspl.MyCustomLogging] [__init__] warning!
1491862833.627949 2017-04-10 15:20:33,627 ERROR [mlspl.MyCustomLogging] [__init__] error!
1491862833.628024 2017-04-10 15:20:33,628 DEBUG [mlspl.MyCustomLogging] [__init__] info!

When all else fails, the best place to look is search.log. If you are still stuck, try posting your question on Splunk Answers.

Last modified on 03 July, 2019
User facing messages   Custom algorithms using PSC libraries

This documentation applies to the following versions of Splunk® Machine Learning Toolkit: 2.3.0, 2.4.0, 3.0.0, 3.1.0, 3.2.0, 3.3.0, 3.4.0, 4.0.0, 4.1.0, 4.2.0, 4.3.0

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