In sklearn, for logistic regression, you can define the penalty, the regularization rate and other variables. Is there a way to set the learning rate?
sklearn.linear_model.LogisticRegression doesn't use SGD, so there's no learning rate.
sklearn.linear_model.SGDClassifier is what you need, which is a linear classifier with SGD training.
According to sklearn's Logistic source code, the solver used to minimize the loss function is the SAG solver (Stochastic Average Gradient). This paper defines this method, and in this link there is the implementation of the sag solver. This implementation of the solver uses a method to obtain the step size (learning rate), so there is not a way that you can change the learning rate (unless you want to change the source code).