How to ensemble classifier incorporating all features in python?
Boosting - is the ensemble which tries to add new models that do well where previous models lack. Bagging in scikit lets you send the base classifier as the parameter. Go through 1.11 of the link to understand more!

But since, you already have in mind that SVM performs better Voting Classifier which is present in sklearn.ensemble lets you give weights to the classifiers which you seem to be performing well. For instance in your question, SVM can be given more weight. It also has another parameter 'voting'. If hard, uses predicted class labels for majority rule voting else if soft, predicts the class label based on the argmax of the sums of the predicted probabilities.