def test_request_schema(self):
model = mock.Mock()
model_name = api_version = mock.MagicMock()
mock_additional_checks = mock.Mock()
feature_schema = schemas.Object(properties=dict(
x=schemas.Integer(),
y=schemas.Number(),
z=schemas.String(),
))
with mock.patch('porter.services.BaseService.add_request_schema') as mock_add_request_schema:
prediction_service = PredictionService(
model=model,
name=model_name,
api_version=api_version,
meta={},
preprocessor=None,
postprocessor=None,
batch_prediction=False,
feature_schema=feature_schema,
)
request_schema = prediction_service.request_schema
request = dict(id=1, x=2, y=3.5, z='4')
request_schema.validate(request)
with self.assertRaisesRegex(ValueError, 'data must contain'):
request = dict(x=2, y=3.5, z='4')
request_schema.validate(request)
def test__add_feature_schema_batch(self):
model = mock.Mock()
model_name = api_version = mock.MagicMock()
mock_additional_checks = mock.Mock()
feature_schema = schemas.Object(properties=dict(
x=schemas.Integer(),
y=schemas.Number(),
z=schemas.String(),
))
with mock.patch('porter.services.BaseService.add_request_schema') as mock_add_request_schema:
prediction_service = PredictionService(
model=model,
name=model_name,
api_version=api_version,
meta={},
preprocessor=None,
postprocessor=None,
batch_prediction=True,
feature_schema=feature_schema,
)
args = mock_add_request_schema.call_args_list[0][0]
self.assertEqual(args[0].upper(), 'POST')
request_obj = args[1]
self.assertIsInstance(request_obj, schemas.Array)
item_obj = request_obj.item_type
self.assertIn('id', item_obj.properties)
self.assertIn('x', item_obj.properties)
self.assertIn('y', item_obj.properties)
self.assertIn('z', item_obj.properties)
def setUpClass(cls):
service1 = PredictionService(
name='service1',
api_version='2',
model=None, # we're not going to make calls for predictions here
feature_schema=sc.Object(properties={
'a': sc.Integer(),
'b': sc.Integer(),
'c': sc.Number()
}))
service1 = PredictionService(
namespace='ns',
name='service2',
api_version='1',
model=None, # we're not going to make calls for predictions here
feature_schema=sc.Object(properties={
'a': sc.Integer(),
'b': sc.Integer()
}))
def test_add_request_schema(self):
input_schema = schemas.Object(properties=dict(
x=schemas.Integer(),
y=schemas.Number(),
z=schemas.String()
))
service = mock.MagicMock()
service.request_schemas = {}
BaseService.add_request_schema(
service, 'post', input_schema, description='test')
request_schema = service.request_schemas['POST']
self.assertIsInstance(request_schema, schemas.RequestSchema)
self.assertEqual(request_schema.description, 'test')
self.assertIs(request_schema.api_obj, input_schema)
def test_get_post_data_validation(self, mock_request_json):
# this test also implicitly covers BaseService.get_post_data
mock_model = mock.Mock()
mock_model.predict.return_value = []
mock_name = mock_version = mock.MagicMock()
feature_schema = schemas.Object(properties=dict(x=schemas.Integer()))
prediction_service = PredictionService(
model=mock_model,
name=mock_name,
api_version=mock_version,
meta={},
preprocessor=None,
postprocessor=None,
batch_prediction=True,
feature_schema=feature_schema,
additional_checks=None
)
# Succeed
mock_request_json.return_value = [{'id': 1, 'x': 37}]
prediction_service.get_post_data()
# Succeed
mock_request_json.return_value = [{'id': 1, 'x': 3.7}]
prediction_service.get_post_data()
# Fail
prediction_service = PredictionService(
model=mock_model,
name=mock_name,
api_version=mock_version + 1,
meta={},
preprocessor=None,
postprocessor=None,
batch_prediction=True,
feature_schema=feature_schema,
validate_request_data=True,
additional_checks=None)
with self.assertRaises(werkzeug_exc.UnprocessableEntity):
prediction_service.get_post_data()