text: # -*- coding: utf-8 -*-
  #!/usr/bin/env python
  #
  # Copyright 2015-2020 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.
  
  
  """ Testing dataset creation with unicode characters
  
  """
  from __future__ import absolute_import
  
  
  from bigmler.tests.world import (world, common_setup_module,
                                   common_teardown_module, teardown_class)
  
  
  import bigmler.tests.dataset_advanced_steps as dataset_adv
  import bigmler.tests.basic_tst_prediction_steps as test_pred
  
  
  def setup_module():
      """Setup for the module
  
      """
      common_setup_module()
  
  def teardown_module():
      """Teardown for the module
  
      """
      common_teardown_module()
  
  class TestUnicode(object):
  
      def teardown(self):
          """Calling generic teardown for every method
  
          """
          print "\nEnd of tests in: %s\n-------------------\n" % __name__
          teardown_class()
  
      def setup(self):
          """
              Debug information
          """
          print "\n-------------------\nTests in: %s\n" % __name__
  
      def test_scenario1(self):
          """
              Scenario: Successfully building test predictions from dataset specifying objective field and model fields
                  Given I create a BigML dataset from "<data>" and store logs in "<output_dir>"
                  And I check that the source has been created
                  And I check that the dataset has been created
                  And I create BigML resources using dataset, objective field <objective> and model fields <fields> to test "<test>" and log predictions in "<output>"
                  And I check that the model has been created
                  And I check that the predictions are ready
                  Then the local prediction file is like "<predictions_file>"
  
                  Examples:
                  |data    | output_dir               | test                    | output                         |predictions_file                        | objective | fields   |
                  | ../data/iris_2fb.csv| ./scénario1 | ../data/test_iris2fb.csv   | ./scénario1/predictions.csv   | ./check_files/predictions_iris_2fb.csv   | spécies     | "pétal width" |
          """
          print self.test_scenario1.__doc__
          examples = [
              ['data/iris_2fb.csv', u'scénario1', 'data/test_iris2fb.csv', u'scénario1/predictions.csv', 'check_files/predictions_iris_2fb.csv', u'spécies', u'"pétal width"']]
          for example in examples:
              print "\nTesting with:\n", example
              dataset_adv.i_create_dataset(self, data=example[0], output_dir=example[1])
              test_pred.i_check_create_source(self)
              test_pred.i_check_create_dataset(self, suffix=None)
              test_pred.i_create_resources_from_dataset_objective_model(self, objective=example[5], fields=example[6], test=example[2], output=example[3])
              test_pred.i_check_create_model(self)
              test_pred.i_check_create_predictions(self)
              test_pred.i_check_predictions(self, example[4])
  