The current TransformerScheduler class uses a multiprocess version of pandas apply, imported from melusine.utils.multiprocessing
Actually scikit-learn already provides a high level interface for multiprocess/multithread processing over numpy/pandas, accessible from the external namespace
from sklearn.externals import joblib
using joblib would reduce the code base and improve compatibility with the sklearn ecosystem
The current
TransformerScheduler
class uses a multiprocess version of pandas apply, imported frommelusine.utils.multiprocessing
Actually scikit-learn already provides a high level interface for multiprocess/multithread processing over numpy/pandas, accessible from the external namespace
using joblib would reduce the code base and improve compatibility with the sklearn ecosystem