[MRG+1] MAINT Parametrize common estimator tests with pytest (#11063)

doc/developers/tips.rst

@@ -64,8 +64,22 @@ will be displayed as a color background behind the line number.
 Useful pytest aliases and flags
 -------------------------------
 
-We recommend using pytest to run unit tests. When a unit tests fail, the
-following tricks can make debugging easier:
+The full test suite takes fairly long to run. For faster iterations,
+it is possibly to select a subset of tests using pytest selectors.
+In particular, one can run a `single test based on its node ID
+<https://docs.pytest.org/en/latest/example/markers.html#selecting-tests-based-on-their-node-id>`_::
+
+  pytest -v sklearn/linear_model/tests/test_logistic.py::test_sparsify
+
+or use the `-k pytest parameter
+<https://docs.pytest.org/en/latest/example/markers.html#using-k-expr-to-select-tests-based-on-their-name>`_
+to select tests based on their name. For instance,::
+
+  pytest sklearn/tests/test_common.py -v -k LogisticRegression
+
+will run all :term:`common tests` for the ``LogisticRegression`` estimator.
+
+When a unit tests fail, the following tricks can make debugging easier:
 
   1. The command line argument ``pytest -l`` instructs pytest to print the local
      variables when a failure occurs.

sklearn/tests/test_common.py

@@ -13,6 +13,8 @@
 import re
 import pkgutil
 
+import pytest
+
 from sklearn.utils.testing import assert_false, clean_warning_registry
 from sklearn.utils.testing import all_estimators
 from sklearn.utils.testing import assert_equal
@@ -41,34 +43,57 @@ def test_all_estimator_no_base_class():
 
 
 def test_all_estimators():
-    # Test that estimators are default-constructible, cloneable
-    # and have working repr.
     estimators = all_estimators(include_meta_estimators=True)
 
     # Meta sanity-check to make sure that the estimator introspection runs
     # properly
     assert_greater(len(estimators), 0)
 
-    for name, Estimator in estimators:
-        # some can just not be sensibly default constructed
-        yield check_parameters_default_constructible, name, Estimator
 
+@pytest.mark.parametrize(
+        'name, Estimator',
+        all_estimators(include_meta_estimators=True)
+)
+def test_parameters_default_constructible(name, Estimator):
+    # Test that estimators are default-constructible
+    check_parameters_default_constructible(name, Estimator)
 
-def test_non_meta_estimators():
-    # input validation etc for non-meta estimators
-    estimators = all_estimators()
-    for name, Estimator in estimators:
+
+def _tested_non_meta_estimators():
+    for name, Estimator in all_estimators():
         if issubclass(Estimator, BiclusterMixin):
             continue
         if name.startswith("_"):
             continue
+        yield name, Estimator
+
+
+def _generate_checks_per_estimator(check_generator, estimators):
+    for name, Estimator in estimators:
         estimator = Estimator()
-        # check this on class
-        yield check_no_attributes_set_in_init, name, estimator
+        for check in check_generator(name, estimator):
+            yield name, Estimator, check
 
-        for check in _yield_all_checks(name, estimator):
-            set_checking_parameters(estimator)
-            yield check, name, estimator
+
+@pytest.mark.parametrize(
+        "name, Estimator, check",
+        _generate_checks_per_estimator(_yield_all_checks,
+                                       _tested_non_meta_estimators())
+)
+def test_non_meta_estimators(name, Estimator, check):
+    # Common tests for non-meta estimators
+    estimator = Estimator()
+    set_checking_parameters(estimator)
+    check(name, estimator)
+
+
+@pytest.mark.parametrize("name, Estimator",
+                         _tested_non_meta_estimators())
+def test_no_attributes_set_in_init(name, Estimator):
+    # input validation etc for non-meta estimators
+    estimator = Estimator()
+    # check this on class
+    check_no_attributes_set_in_init(name, estimator)
 
 
 def test_configure():
@@ -95,19 +120,21 @@ def test_configure():
         os.chdir(cwd)
 
 
-def test_class_weight_balanced_linear_classifiers():
+def _tested_linear_classifiers():
     classifiers = all_estimators(type_filter='classifier')
 
     clean_warning_registry()
     with warnings.catch_warnings(record=True):
-        linear_classifiers = [
-            (name, clazz)
-            for name, clazz in classifiers
+        for name, clazz in classifiers:
             if ('class_weight' in clazz().get_params().keys() and
-                issubclass(clazz, LinearClassifierMixin))]
+                    issubclass(clazz, LinearClassifierMixin)):
+                yield name, clazz
+
 
-    for name, Classifier in linear_classifiers:
-        yield check_class_weight_balanced_linear_classifier, name, Classifier
+@pytest.mark.parametrize("name, Classifier",
+                         _tested_linear_classifiers())
+def test_class_weight_balanced_linear_classifiers(name, Classifier):
+    check_class_weight_balanced_linear_classifier(name, Classifier)
 
 
 @ignore_warnings