scikit-learn · petrushev · Mar 9, 2017 · Mar 10, 2017 · Mar 10, 2017 · Mar 10, 2017
diff --git a/doc/modules/pipeline.rst b/doc/modules/pipeline.rst
@@ -47,7 +47,7 @@ is an estimator object::
     >>> pipe # doctest: +NORMALIZE_WHITESPACE, +ELLIPSIS
     Pipeline(memory=None,
              steps=[('reduce_dim', PCA(copy=True,...)),
-                    ('clf', SVC(C=1.0,...))])
+                    ('clf', SVC(C=1.0,...))], verbose=False)
 
 The utility function :func:`make_pipeline` is a shorthand
 for constructing pipelines;
@@ -62,7 +62,7 @@ filling in the names automatically::
              steps=[('binarizer', Binarizer(copy=True, threshold=0.0)),
                     ('multinomialnb', MultinomialNB(alpha=1.0,
                                                     class_prior=None,
-                                                    fit_prior=True))])
+                                                    fit_prior=True))], verbose=False)
 
 The estimators of a pipeline are stored as a list in the ``steps`` attribute::
 
@@ -82,7 +82,8 @@ Parameters of the estimators in the pipeline can be accessed using the
     >>> pipe.set_params(clf__C=10) # doctest: +NORMALIZE_WHITESPACE, +ELLIPSIS
     Pipeline(memory=None,
              steps=[('reduce_dim', PCA(copy=True, iterated_power='auto',...)),
-                    ('clf', SVC(C=10, cache_size=200, class_weight=None,...))])
+                    ('clf', SVC(C=10, cache_size=200, class_weight=None,...))],
+                    verbose=False)
 
 Attributes of named_steps map to keys, enabling tab completion in interactive environments::
 
@@ -160,7 +161,7 @@ object::
     >>> pipe # doctest: +NORMALIZE_WHITESPACE, +ELLIPSIS
     Pipeline(...,
              steps=[('reduce_dim', PCA(copy=True,...)),
-                    ('clf', SVC(C=1.0,...))])
+                    ('clf', SVC(C=1.0,...))], verbose=False)
     >>> # Clear the cache directory when you don't need it anymore
     >>> rmtree(cachedir)
 
@@ -177,7 +178,7 @@ object::
      >>> pipe.fit(digits.data, digits.target)
      ... # doctest: +NORMALIZE_WHITESPACE, +ELLIPSIS
      Pipeline(memory=None,
-              steps=[('reduce_dim', PCA(...)), ('clf', SVC(...))])
+              steps=[('reduce_dim', PCA(...)), ('clf', SVC(...))], verbose=False)
      >>> # The pca instance can be inspected directly
      >>> print(pca1.components_) # doctest: +NORMALIZE_WHITESPACE, +ELLIPSIS
          [[ -1.77484909e-19  ... 4.07058917e-18]]
@@ -199,7 +200,7 @@ object::
      >>> cached_pipe.fit(digits.data, digits.target)
      ... # doctest: +NORMALIZE_WHITESPACE, +ELLIPSIS
       Pipeline(memory=...,
-               steps=[('reduce_dim', PCA(...)), ('clf', SVC(...))])
+               steps=[('reduce_dim', PCA(...)), ('clf', SVC(...))], verbose=False)
      >>> print(cached_pipe.named_steps['reduce_dim'].components_)
      ... # doctest: +NORMALIZE_WHITESPACE, +ELLIPSIS
          [[ -1.77484909e-19  ... 4.07058917e-18]]
@@ -253,7 +254,7 @@ and ``value`` is an estimator object::
     FeatureUnion(n_jobs=1,
                  transformer_list=[('linear_pca', PCA(copy=True,...)),
                                    ('kernel_pca', KernelPCA(alpha=1.0,...))],
-                 transformer_weights=None)
+                 transformer_weights=None, verbose=False)
 
 
 Like pipelines, feature unions have a shorthand constructor called
@@ -268,7 +269,7 @@ and ignored by setting to ``None``::
     FeatureUnion(n_jobs=1,
                  transformer_list=[('linear_pca', PCA(copy=True,...)),
                                    ('kernel_pca', None)],
-                 transformer_weights=None)
+                 transformer_weights=None, verbose=False)
 
 .. topic:: Examples:
 

diff --git a/doc/whats_new.rst b/doc/whats_new.rst
@@ -48,6 +48,18 @@ Model evaluation and meta-estimators
 - A scorer based on :func:`metrics.brier_score_loss` is also available.
   :issue:`9521` by :user:`Hanmin Qin <qinhanmin2014>`.
 
+Miscellaneous
+
+- Added optional parameter ``verbose`` in :class:`pipeline.Pipeline` and
+  :class:`pipeline.FeatureUnion` for showing progress and timing of each
+     step. :issue:`8568` by :user:`Karan Desai <karandesai-96>`.
+
+- Added optional parameter ``verbose`` in functions `pipeline.make_pipeline`
+  and `pipeline.make_union` to extend the same functionality as the
+  corresponding classes. :issue:`9668` by
+  :user:`Baze Petrushev <petrushev>` and :user:`Karan Desai <karandesai-96>`.
+
+
 Bug fixes
 .........
 
@@ -5754,3 +5766,4 @@ David Huard, Dave Morrill, Ed Schofield, Travis Oliphant, Pearu Peterson.
 
 .. _Neeraj Gangwar: http://neerajgangwar.in
 .. _Arthur Mensch: https://amensch.fr
+.. _Karan Desai: https://www.github.com/karandesai-96
diff --git a/sklearn/cross_validation.py b/sklearn/cross_validation.py
@@ -22,7 +22,8 @@
 import scipy.sparse as sp
 
 from .base import is_classifier, clone
-from .utils import indexable, check_random_state, safe_indexing
+from .utils import (indexable, check_random_state, safe_indexing,
+                    message_with_time)
 from .utils.validation import (_is_arraylike, _num_samples,
                                column_or_1d)
 from .utils.multiclass import type_of_target
@@ -1700,8 +1701,7 @@ def _fit_and_score(estimator, X, y, scorer, train, test, verbose,
     if verbose > 2:
         msg += ", score=%f" % test_score
     if verbose > 1:
-        end_msg = "%s -%s" % (msg, logger.short_format_time(scoring_time))
-        print("[CV] %s %s" % ((64 - len(end_msg)) * '.', end_msg))
+        print(message_with_time('CV', msg, scoring_time))
 
     ret = [train_score] if return_train_score else []
     ret.extend([test_score, _num_samples(X_test), scoring_time])

diff --git a/sklearn/model_selection/_validation.py b/sklearn/model_selection/_validation.py
@@ -20,10 +20,11 @@
 import scipy.sparse as sp
 
 from ..base import is_classifier, clone
-from ..utils import indexable, check_random_state, safe_indexing
+from ..utils import (indexable, check_random_state, safe_indexing,
+                     message_with_time)
 from ..utils.validation import _is_arraylike, _num_samples
 from ..utils.metaestimators import _safe_split
-from ..externals.joblib import Parallel, delayed, logger
+from ..externals.joblib import Parallel, delayed
 from ..externals.six.moves import zip
 from ..metrics.scorer import check_scoring, _check_multimetric_scoring
 from ..exceptions import FitFailedWa
6D40
rning
@@ -480,8 +481,7 @@ def _fit_and_score(estimator, X, y, scorer, train, test, verbose,
             msg += ", score=%s" % test_scores
     if verbose > 1:
         total_time = score_time + fit_time
-        end_msg = "%s, total=%s" % (msg, logger.short_format_time(total_time))
-        print("[CV] %s %s" % ((64 - len(end_msg)) * '.', end_msg))
+        print(message_with_time('CV', msg, total_time))
 
     ret = [train_scores, test_scores] if return_train_score else [test_scores]