Cross validation while preserving a column (not the target ) distribution
One idea would be to combine the two columns (one predictor and the target) and then stratify using the combined column.

Example: say for some observations, the target and the column take the following values: target = [0,1,0] and column = [A,A,B]. Then the combined column could look something like [A0,A1,B0] and could be used for stratification.

I'm obviously assuming that the predictor column is categorical - you might have to take a different approach for a continuous variable.