def test_scenario1(self): """ Scenario 1: Successfully creating an optiml from a dataset: Given I create a data source uploading a "<data>" file And I wait until the source is ready less than <time_1> secs And I create a dataset And I wait until the dataset is ready less than <time_2> secs And I create an optiml from a dataset And I wait until the optiml is ready less than <time_3> secs And I update the optiml name to "<optiml_name>" When I wait until the optiml is ready less than <time_4> secs Then the optiml name is "<optiml_name>" Examples: | data | time_1 | time_2 | time_3 | time_4 | optiml_name | | ../data/iris.csv | 10 | 10 | 2000 | 20 | my new optiml name | """ print self.test_scenario1.__doc__ examples = [ ['data/iris.csv', '10', '10', '10000', '20', 'my new optiml name']] for example in examples: print "\nTesting with:\n", example source_create.i_upload_a_file(self, example[0]) source_create.the_source_is_finished(self, example[1]) dataset_create.i_create_a_dataset(self) dataset_create.the_dataset_is_finished_in_less_than(self, example[2]) model_create.i_create_an_optiml_with_objective_and_params( \ self, parms='{"max_training_time": %s, "model_types": ' '["model", "logisticregression"]}' % \ (int(float(example[3])/1000) - 1)) model_create.the_optiml_is_finished_in_less_than(self, example[3]) model_create.i_update_optiml_name(self, example[5]) model_create.the_optiml_is_finished_in_less_than(self, example[4]) model_create.i_check_optiml_name(self, example[5])