def generate_pipeline_code(pipeline):
        """Generate recommended pipeline code.

    Parameters
    ----------
    pipeline: tuple
        name and recommended pipeline configuration

    Returns
    -------
    code: String
        The Python code recommended pipeline
    """

        code= """
# NOTE: Make sure that the target column is labeled 'class' in the data file
data = pd.read_csv('Dataset path')

X = data.drop('class', axis=1)
y = data['class']

X_train, X_test, Y_train, Y_test = train_test_split(X, y, test_size=0.3, random_state=42)


model= {}
model.fit(X_train, Y_train)

Y_pred = model.predict(X_test)
score = model.score(X_test, Y_test)

print(classification_report(Y_test, Y_pred))
print(' Pipeline test accuracy:  %.3f' % score)

                 """.format(pipeline)
        return code