Splunk® Machine Learning Toolkit

ML-SPL API Guide

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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.
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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
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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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