Explains openml-python logging, and shows how to configure it.


Openml-python uses the Python logging module to provide users with log messages. Each log message is assigned a level of importance, see the table in Python’s logging tutorial here.

By default, openml-python will print log messages of level WARNING and above to console. All log messages (including DEBUG and INFO) are also saved in a file, which can be found in your cache directory (see also the introduction tutorial). These file logs are automatically deleted if needed, and use at most 2MB of space.

It is possible to configure what log levels to send to console and file. When downloading a dataset from OpenML, a DEBUG-level message is written:

# License: BSD 3-Clause

import openml

# With default configuration, the above example will show no output to console.
# However, in your cache directory you should find a file named 'openml_python.log',
# which has a DEBUG message written to it. It should be either like
# "[DEBUG] [10:46:19:openml.datasets.dataset] Saved dataset 61: iris to file ..."
# or like
# "[DEBUG] [10:49:38:openml.datasets.dataset] Data pickle file already exists and is up to date."
# , depending on whether or not you had downloaded iris before.
# The processed log levels can be configured programmatically:

import logging

# Now the log level that was previously written to file should also be shown in the console.
# The message is now no longer written to file as the `file_log` was set to level `WARNING`.
# It is also possible to specify the desired log levels through the configuration file.
# This way you will not need to set them on each script separately.
# Add the  line **verbosity = NUMBER** and/or **file_verbosity = NUMBER** to the config file,
# where 'NUMBER' should be one of:
# * 0: `logging.WARNING` and up.
# * 1: `logging.INFO` and up.
# * 2: `logging.DEBUG` and up (i.e. all messages).

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