from sklearn.svm import SVC
from sklearn.preprocessing import StandardScaler
from sklearn.datasets import make_classification
from sklearn.model_selection import train_test_split
from sklearn.pipeline import Pipeline

X, y = make_classification(random_state=1)
X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=1)

steps = [
    ('scaler', StandardScaler()), 
    ('SVM', SVC())
    ]

pipe = Pipeline(steps)

pipe.fit(X_train, y_train)
print(pipe.score(X_test, y_test))