Request: metadata indicating number of targets

First, THANK YOU for such an awesome project! OpenML has already saved me days and days of work -- it is amazing.

I'm going through lots of datasets doing binary classification with the Python API, predicting the default target attribute with

X, y, categorical = dataset.get_data(target=dataset.default_target_attribute, return_categorical_indicator=True)

The only issue is this fails if default_target_attribute contains multiple targets, i.e., for multi-target (multi-label, multi-output) tasks. For example, for the image dataset (id 40592), default_target_attribute is "desert,mountains,sea,sunset,trees", meaning the problem has five targets.

Unfortunately there doesn't seem to be any metadata field to filter out such datasets; a field indicating the number of targets would be great.

I work around it (and also filter out datasets with a null default_target_attribute) with this test:

dataset.default_target_attribute in (f.name for f in dataset.features.values())

Start with the Python API usage of dataset.default_target_attribute and dataset.features, using dataset ID 40592 as the multi-target example. Trace how dataset metadata is represented and filtered, then add or expose a target-count field that distinguishes single-target, multi-target, and null-target datasets.