After in-depth data exploration and feature engineering I often spent hours or days experimenting with various sklearn models and performing hyper parameter grid search. Now I use an open source package, TPOT (
https://epistasislab.github.io/tpot/), that fully automates not only grid search but also selection of the learning algorithm (SVM, Random Forest, K-NN, etc). If your data set is small enough for sklearn, then you should not be writing sklearn code manually.
For those that are interested, TPOT uses evolutionary algorithms to perform its search.