remove openml version from dependencies, add to external version

Author: mfeurer

openml/flows/sklearn_converter.py

@@ -198,8 +198,7 @@ def _serialize_model(model):
     external_version = _get_external_version_string(model, sub_components)
 
     dependencies = [_format_external_version('sklearn', sklearn.__version__),
-                    'numpy>=1.6.1', 'scipy>=0.9',
-                    _format_external_version('openml', openml.__version__)]
+                    'numpy>=1.6.1', 'scipy>=0.9']
     dependencies = '\n'.join(dependencies)
 
     flow = OpenMLFlow(name=name,
@@ -237,8 +236,10 @@ def _get_external_version_string(model, sub_components):
     model_package_version_number = module.__version__
     external_version = _format_external_version(model_package_name,
                                                 model_package_version_number)
+    openml_version = _format_external_version('openml', openml.__version__)
     external_versions = set()
     external_versions.add(external_version)
+    external_versions.add(openml_version)
     for visitee in sub_components.values():
         for external_version in visitee.external_version.split(','):
             external_versions.add(external_version)
@@ -429,13 +430,8 @@ def _check_dependencies(dependencies):
             raise NotImplementedError(
                 'operation \'%s\' is not supported' % operation)
         if not check:
-            if dependency_name == 'openml':
-                warnings.warn('De-serializing a flow which was created with '
-                              'openml==%s, this is openml==%s.' %
-                              (openml.__version__, version))
-            else:
-                raise ValueError('Trying to deserialize a model with dependency '
-                                 '%s not satisfied.' % dependency_string)
+            raise ValueError('Trying to deserialize a model with dependency '
+                             '%s not satisfied.' % dependency_string)
 
 
 def serialize_type(o):

tests/test_flows/test_sklearn.py

@@ -64,8 +64,8 @@ def test_serialize_model(self, check_dependencies_mock):
 
         fixture_name = 'sklearn.tree.tree.DecisionTreeClassifier'
         fixture_description = 'Automatically created scikit-learn flow.'
-        version_fixture = 'sklearn==%s\nnumpy>=1.6.1\nscipy>=0.9\nopenml==%s' \
-                          '' % (sklearn.__version__, openml.__version__)
+        version_fixture = 'sklearn==%s\nnumpy>=1.6.1\nscipy>=0.9' \
+                          % sklearn.__version__
         fixture_parameters = \
             OrderedDict((('class_weight', 'null'),
                          ('criterion', '"entropy"'),
@@ -522,7 +522,8 @@ def test_subflow_version_propagated(self):
         # I put the alternative travis-ci answer here as well. While it has a
         # different value, it is still correct as it is a propagation of the
         # subclasses' module name
-        self.assertEqual(flow.external_version, '%s,%s' % (
+        self.assertEqual(flow.external_version, '%s,%s,%s' % (
+            _format_external_version('openml', openml.__version__),
             _format_external_version('sklearn', sklearn.__version__),
             _format_external_version('tests', '0.1')))
 
@@ -531,13 +532,6 @@ def test_check_dependencies(self, warnings_mock):
         dependencies = ['sklearn==0.1', 'sklearn>=99.99.99', 'sklearn>99.99.99']
         for dependency in dependencies:
             self.assertRaises(ValueError, _check_dependencies, dependency)
-        dependency = 'openml==0.0.12345'
-        _check_dependencies(dependency)
-        self.assertEqual(warnings_mock.call_count, 1)
-        self.assertEqual(warnings_mock.call_args[0][0],
-                         'De-serializing a flow which was created with '
-                         'openml==%s, this is openml==%s.' % (
-                             openml.__version__, '0.0.12345'))
 
     def test_illegal_parameter_names(self):
         # illegal name: estimators