scikit-learn · rth · Dec 6, 2019 · Oct 28, 2019 · Oct 28, 2019 · Oct 28, 2019
diff --git a/sklearn/tests/test_common.py b/sklearn/tests/test_common.py
@@ -78,8 +78,6 @@ def _tested_estimators():
     for name, Estimator in all_estimators():
         if issubclass(Estimator, BiclusterMixin):
             continue
-        if name.startswith("_"):
-            continue
         try:
             estimator = _construct_instance(Estimator)
         except SkipTest:

diff --git a/sklearn/utils/__init__.py b/sklearn/utils/__init__.py
@@ -3,6 +3,7 @@
 """
 import pkgutil
 import inspect
+from importlib import import_module
 from operator import itemgetter
 from collections.abc import Sequence
 from contextlib import contextmanager
@@ -12,6 +13,7 @@
 import platform
 import struct
 import timeit
+from pathlib import Path
 
 import warnings
 import numpy as np
@@ -1155,7 +1157,6 @@ def all_estimators(include_meta_estimators=None,
         and ``class`` is the actuall type of the class.
     """
     # lazy import to avoid circular imports from sklearn.base
-    import sklearn
     from ._testing import ignore_warnings
     from ..base import (BaseEstimator, ClassifierMixin, RegressorMixin,
                         TransformerMixin, ClusterMixin)
@@ -1183,20 +1184,29 @@ def is_abstract(c):
                       DeprecationWarning)
 
     all_classes = []
-    # get parent folder
-    path = sklearn.__path__
-    for importer, modname, ispkg in pkgutil.walk_packages(
-            path=path, prefix='sklearn.', onerror=lambda x: None):
-        if ".tests." in modname or "externals" in modname:
-            continue
-        if IS_PYPY and ('_svmlight_format' in modname or
-                        'feature_extraction._hashing' in modname):
-            continue
-        # Ignore deprecation warnings triggered at import time.
-        with ignore_warnings(category=FutureWarning):
-            module = __import__(modname, fromlist="dummy")
-        classes = inspect.getmembers(module, inspect.isclass)
-        all_classes.extend(classes)
+    modules_to_ignore = {"tests", "externals", "setup", "conftest"}
+    root = str(Path(__file__).parent.parent)  # sklearn package
+    # Ignore deprecation warnings triggered at import time and from walking
+    # packages
+    with ignore_warnings(category=FutureWarning):
+        for importer, modname, ispkg in pkgutil.walk_packages(
+                path=[root], prefix='sklearn.'):
+            mod_parts = modname.split(".")
+            if (any(part in modules_to_ignore for part in mod_parts)
+                    or '._' in modname):
+                continue
+            module = import_module(modname)
+            classes = inspect.getmembers(module, inspect.isclass)
+            classes = [(name, est_cls) for name, est_cls in classes
+                       if not name.startswith("_")]
+
+            # TODO: Remove when FeatureHasher is implemented in PYPY
+            # Skips FeatureHasher for PYPY
+            if IS_PYPY and 'feature_extraction' in modname:
+                classes = [(name, est_cls) for name, est_cls in classes
+                           if name == "FeatureHasher"]
+
+            all_classes.extend(classes)
 
     all_classes = set(all_classes)
 

diff --git a/sklearn/utils/tests/test_estimator_checks.py b/sklearn/utils/tests/test_estimator_checks.py
@@ -34,6 +34,7 @@
 from sklearn.neighbors import KNeighborsRegressor
 from sklearn.tree import DecisionTreeClassifier
 from sklearn.utils.validation import check_X_y, check_array
+from sklearn.utils import all_estimators
 
 
 class CorrectNotFittedError(ValueError):
@@ -572,6 +573,14 @@ def test_check_class_weight_balanced_linear_classifier():
                         BadBalancedWeightsClassifier)
 
 
+def test_all_estimators_all_public():
+    # all_estimator should not fail when pytest is not installed and return
+    # only public estimators
+    estimators = all_estimators()
+    for est in estimators:
+        assert not est.__class__.__name__.startswith("_")
+
+
 if __name__ == '__main__':
     # This module is run as a script to check that we have no dependency on
     # pytest for estimator checks.