Around how much difference between two classes can be accounted as an imbalanced dataset?
In general there will be not a hard rule about this, but this dataset seems to be like balanced.
The point about disbalanced is that you have to keep in mind that the accuracy of your model will have a different starting point. For this python has the function to run a baseline with dummy classification. https://scikit-learn.org/stable/modules/generated/sklearn.dummy.DummyClassifier.html. This gives you a good indication what is your baseline (if you choose the the strategy to most_frequent). In your case, any prediction model which always forecast class A, would have a accuracy of: 17/(10+17) = 0,6296... , so any binary classification with a score under this value would be really bad