def test_scenario9(self):
"""
Scenario 9: Successfully creating a local association from an exported file:
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 time series
And I wait until the time series is ready less than <time_3> secs
And I export the time series to "<exported_file>"
When I create a local time series from the file "<exported_file>"
Then the time series ID and the local time series ID match
Examples:
| data | time_1 | time_2 | time_3 | exported_file
| ../data/iris.csv | 10 | 10 | 50 | ./tmp/time_series.json
"""
print self.test_scenario9.__doc__
examples = [
['data/iris.csv', '10', '10', '500', './tmp/time_series.json']]
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])
timeseries_create.i_create_a_time_series(self)
timeseries_create.the_time_series_is_finished_in_less_than(self, example[3])
timeseries_create.i_export_time_series(self, example[4])
timeseries_create.i_create_local_time_series_from_file(self, example[4])
timeseries_create.check_time_series_id_local_id(self)
def test_scenario9(self):
"""
Scenario 9: Successfully creating a local association from an exported file:
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 time series
And I wait until the time series is ready less than <time_3> secs
And I export the time series to "<exported_file>"
When I create a local time series from the file "<exported_file>"
Then the time series ID and the local time series ID match
Examples:
| data | time_1 | time_2 | time_3 | exported_file
| ../data/iris.csv | 10 | 10 | 50 | ./tmp/time_series.json
"""
print self.test_scenario9.__doc__
examples = [
['data/iris.csv', '10', '10', '500', './tmp/time_series.json']]
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])
timeseries_create.i_create_a_time_series(self)
timeseries_create.the_time_series_is_finished_in_less_than(self, example[3])
timeseries_create.i_export_time_series(self, example[4])
timeseries_create.i_create_local_time_series_from_file(self, example[4])
timeseries_create.check_time_series_id_local_id(self)
def test_scenario1(self):
"""
Scenario: Successfully creating forecasts 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 time-series from a dataset
And I wait until the time series is ready less than <time_3> secs
And I update the time series name to "<time_series_name>"
When I wait until the time series is ready less than <time_4> secs
Then the time series name is "<time_series_name>"
And I create a forecast for "<input_data>"
Then the forecasts are "<forecast_points>"
Examples:
| data | time_1 | time_2 | time_3 | time_4 | time_series_name |input_data | forecast_points
| ../data/grades.csv | 10 | 10 | 20 | 50 | my new time_series name |
{"000005": {"horizon": 5}], {}}
"""
print self.test_scenario1.__doc__
examples = [[
'data/grades.csv', '30', '30', '50', '50',
'my new time series name', '{"000005": {"horizon": 5}}',
'{"000005": [{"point_forecast": [73.96192, 74.04106, 74.12029, 74.1996, 74.27899], "model": "M,M,N"}]}'
]]
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])
time_series_create.i_create_a_time_series(self)
time_series_create.the_time_series_is_finished_in_less_than(
self, example[3])
time_series_create.i_update_time_series_name(self, example[5])
time_series_create.the_time_series_is_finished_in_less_than(
self, example[4])
time_series_create.i_check_time_series_name(self, example[5])
forecast_create.i_create_a_forecast(self, example[6])
forecast_create.the_forecast_is(self, example[7])
def test_scenario1(self):
"""
Scenario: Successfully creating forecasts 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 time-series from a dataset
And I wait until the time series is ready less than <time_3> secs
And I update the time series name to "<time_series_name>"
When I wait until the time series is ready less than <time_4> secs
Then the time series name is "<time_series_name>"
And I create a forecast for "<input_data>"
Then the forecasts are "<forecast_points>"
Examples:
| data | time_1 | time_2 | time_3 | time_4 | time_series_name |input_data | forecast_points
| ../data/grades.csv | 10 | 10 | 20 | 50 | my new time_series name |
{"000005": {"horizon": 5}], {}}
"""
print self.test_scenario1.__doc__
examples = [
['data/grades.csv', '10', '10', '20', '50', 'my new time series name',
'{"000005": {"horizon": 5}}', '{"000005": [{"point_forecast": [68.53181, 68.53181, 68.53181, 68.53181, 68.53181], "model": "A,N,N"}]}']]
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])
time_series_create.i_create_a_time_series(self)
time_series_create.the_time_series_is_finished_in_less_than(self, example[3])
time_series_create.i_update_time_series_name(self, example[5])
time_series_create.the_time_series_is_finished_in_less_than(self, example[4])
time_series_create.i_check_time_series_name(self, example[5])
forecast_create.i_create_a_forecast(self, example[6])
forecast_create.the_forecast_is(self, example[7])