Example #1
0
    def test_scenario9(self):
        """
            Scenario: Successfully building a batch prediction reify output in python
                Given I create a BigML batch prediction from a model with data "<data>" and params "<params>"
                And I check that the source has been created
                And I check that the dataset has been created
                And I check that the model has been created
                And I check that the batch prediction has been created
                Then I create a reify output in "<output>" for "<language>"
                And the "<output>" file is like "<check_file>"

                Examples:
                | data | output | params |check_file | language
                | data/iris.csv | scenario_re9/reify.py | {"name": "my_batch_prediction_name"}|../check_files/reify_batch_prediction.py | python
        """
        print self.test_scenario9.__doc__
        examples = [
            ['data/iris.csv', 'scenario_re9/reify.py', {"name": "my_batch_prediction_name"}, 'check_files/reify_batch_prediction.py', 'python']]

        for example in examples:
            print "\nTesting with:\n", example
            test_reify.create_batch_prediction(example[0],
                                               output=example[1],
                                               args=example[2])
            test_reify.i_create_output(self, example[1], example[4],
                                       resource_type='batch_prediction')
            test_reify.i_check_output_file(self, output=example[1],
                                           check_file=example[3])
Example #2
0
    def test_scenario9(self):
        """
            Scenario: Successfully building a batch prediction reify output in python
                Given I create a BigML batch prediction from a model with data "<data>" and params "<params>"
                And I check that the source has been created
                And I check that the dataset has been created
                And I check that the model has been created
                And I check that the batch prediction has been created
                Then I create a reify output in "<output>" for "<language>"
                And the "<output>" file is like "<check_file>"

                Examples:
                | data | output | params |check_file | language
                | data/iris.csv | scenario_re9/reify.py | {"name": "my_batch_prediction_name"}|../check_files/reify_batch_prediction.py | python
        """
        print self.test_scenario9.__doc__
        examples = [
            ['data/iris.csv', 'scenario_re9/reify.py', {"name": "my_batch_prediction_name"}, 'check_files/reify_batch_prediction.py', 'python']]

        for example in examples:
            print "\nTesting with:\n", example
            test_reify.create_batch_prediction(example[0],
                                               output=example[1],
                                               args=example[2])
            test_reify.i_create_output(self, example[1], example[4],
                                       resource_type='batch_prediction')
            test_reify.i_check_output_file(self, output=example[1],
                                           check_file=example[3])