code: def test_pipeline(print_changed_only_false):
      # Render a pipeline object
      pipeline = make_pipeline(
          StandardScaler(), LogisticRegression(C=999)
      )
      expected = """
  Pipeline(memory=None,
           steps=[('standardscaler',
                   StandardScaler(copy=True, with_mean=True, with_std=True)),
                  ('logisticregression',
                   LogisticRegression(C=999, class_weight=None, dual=False,
                                      fit_intercept=True, intercept_scaling=1,
                                      l1_ratio=None, max_iter=100,
                                      multi_class='warn', n_jobs=None,
                                      penalty='l2', random_state=None,
                                      solver='warn', tol=0.0001, verbose=0,
                                      warm_start=False))],
           verbose=False)"""
  
      expected = expected[1:]  # remove first \n
      assert pipeline.__repr__() == expected
  
imports: import re
  from pprint import PrettyPrinter
  import numpy
  from sklearn.utils._pprint import _EstimatorPrettyPrinter
  from sklearn.linear_model import LogisticRegressionCV
  from sklearn.pipeline import make_pipeline
  from sklearn.base import BaseEstimator, TransformerMixin
  from sklearn.feature_selection import SelectKBest, chi2
  from sklearn import config_context
label_desc: Use image node_id 3 for calling a global function with example usage: test_pipeline(print_changed_only_false) without return types