from sklearn.datasets import load_iris
from sklearn.ensemble import RandomForestClassifier
from sklearn.model_selection import StratifiedKFold
from sklearn.feature_selection import RFECV

X, y = load_iris(return_X_y=True)
model = RandomForestClassifier(random_state=42)
cv = StratifiedKFold(n_splits=5)

rfecv = RFECV(
    estimator=model,
    step=8,
    cv=cv,
    scoring='accuracy',
    n_jobs=-1,
    verbose=10
)
rfecv.fit(X, y)

print(rfecv.cv_results_["n_features"])
print(rfecv.n_features_)