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Logging enhancements #701

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haim-cohen-moonactive
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The idea is not to set logging configuration in the code. As a library mljar should not set logging preferences, and let the application do it. In addition, verbose_print messages should go to logger so the application can get those messages if required.
Proposed changes:

  • Remove calls to basicConfig on automl.py and exceptions.py
  • Change verbose_print to use logger.

@pplonski
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Thank you @haim-cohen-moonactive. I would like to keep some default logging configuration for the library. Do you have any proposal on how to do this?

@haim-cohen-moonactive
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haim-cohen-moonactive commented Jan 31, 2024 via email

@pplonski
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Thanks. I understand your point. Most of users are importing package in their script/notebook and just call constructor and fit(). I would leave default logging for them, and I prefer to make it configurable. The same with verbose_print() - it should print message to terminal by default and it should be configurable.

@DanielAvdar
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Thanks. I understand your point. Most of users are importing package in their script/notebook and just call constructor and fit(). I would leave default logging for them, and I prefer to make it configurable. The same with verbose_print() - it should print message to terminal by default and it should be configurable.

There are users who like to productionize their work. Not adhering to logging standards might lead to problems with productionizing applications dependent on MLjar.

@pplonski
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pplonski commented Feb 5, 2024

OK, so we need to update the code in that why to have:

  • default logging for users that just call AutoML to build models,
  • and configurable logging for users that integrate AutoML in their packages.

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