text: # -*- coding: utf-8 -*-
  #!/usr/bin/env python
  #
  # Copyright 2015-2018 BigML
  #
  # Licensed under the Apache License, Version 2.0 (the "License"); you may
  # not use this file except in compliance with the License. You may obtain
  # a copy of the License at
  #
  #     http://www.apache.org/licenses/LICENSE-2.0
  #
  # Unless required by applicable law or agreed to in writing, software
  # distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
  # WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
  # License for the specific language governing permissions and limitations
  # under the License.
  
  
  """ Downloading dataset
  
  """
  from world import world, setup_module, teardown_module
  import create_source_steps as source_create
  import create_dataset_steps as dataset_create
  import create_model_steps as model_create
  
  
  class TestDownload(object):
  
      def setup(self):
          """
              Debug information
          """
          print "\n-------------------\nTests in: %s\n" % __name__
  
      def teardown(self):
          """
              Debug information
          """
          print "\nEnd of tests in: %s\n-------------------\n" % __name__
  
      def test_scenario1(self):
          """
  
              Scenario: Successfully exporting 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 download the dataset file to "<local_file>"
                  Then file "<local_file>" is like file "<data>"
  
                  Examples:
                  | data             | time_1  | time_2 | local_file |
                  | ../data/iris.csv | 30      | 30     | ./tmp/exported_iris.csv |
          """
          print self.test_scenario1.__doc__
          examples = [
              ['data/iris.csv', '30', '30', 'tmp/exported_iris.csv']]
          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])
              dataset_create.i_export_a_dataset(self, example[3])
              dataset_create.files_equal(self, example[3], example[0])
  
      def test_scenario2(self):
          """
              Scenario: Successfully creating a model and exporting it:
                  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 a model
                  And I wait until the model is ready less than <time_3> secs
                  And I export the <"pmml"> model to file "<expected_file>"
                  Then I check the model is stored in "<expected_file>" file in <"pmml">
  
                  Examples:
                  | data                   | time_1  | time_2 | time_3 | expected_file         | pmml
                  | data/iris.csv          | 10      | 10     | 10     | tmp/model/iris.json   | false
                  | data/iris_sp_chars.csv | 10      | 10     | 10     | tmp/model/iris_sp_chars.pmml   | true
  
          """
          print self.test_scenario2.__doc__
          examples = [
              ['data/iris.csv', '30', '30', '30', 'tmp/model/iris.json', False],
              ['data/iris_sp_chars.csv', '30', '30', '30', 'tmp/model/iris_sp_chars.pmml', True]]
          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_a_model(self)
              model_create.the_model_is_finished_in_less_than(self, example[3])
              model_create.i_export_model(self, example[5], example[4])
              model_create.i_check_model_stored(self, example[4], example[5])
  