parallel processing using joblib

from joblib import Parallel, delayed
import numpy as np
import time
from mne_features.feature_extraction import FeatureExtractor
feature=['mean','variance','std']
fe = FeatureExtractor(sfreq=1024, selected_funcs=feature)



def f(x):
    l =np.random.randint(0, 100, size=(100, 64, 3000))
    return np.std(l[:,x,:],-1)

st=time.time()
results = Parallel(n_jobs=-1)(delayed(f)(i) for i in range(64))
print(time.time()-st)