def setUpClass(cls):
httpretty.enable()
dataset = {'dataset': DatasetFactory.build(
database_code='NSE', dataset_code='OIL')}
httpretty.register_uri(httpretty.GET,
re.compile(
'https://www.quandl.com/api/v3/datasets/*'),
body=json.dumps(dataset))
dataset_code = Dataset.get_code_from_meta(dataset['dataset'])
cls.dataset_instance = Dataset(dataset_code, dataset['dataset'])
def setUpClass(cls):
httpretty.enable()
dataset = {'dataset': DatasetFactory.build(
database_code='NSE', dataset_code='OIL')}
httpretty.register_uri(httpretty.GET,
re.compile(
'https://www.quandl.com/api/v3/datasets/*'),
body=json.dumps(dataset))
dataset_code = Dataset.get_code_from_meta(dataset['dataset'])
cls.dataset_instance = Dataset(dataset_code, dataset['dataset'])
def test_meta_attributes_can_be_accessed(self):
results = Dataset.all()
self.assertEqual(results.meta['current_page'], 1)
self.assertEqual(results.current_page, 1)
def test_values_exist(self):
results = Dataset.all()
self.assertIsInstance(results.values, list)
self.assertIsInstance(results.values[0], Dataset)
def setupDatasetsTest(unit_test, httpretty):
httpretty.reset()
httpretty.enable()
unit_test.dataset_data = {'dataset_data': DatasetDataFactory.build()}
# mock out calls with column_index query param
# NOTE: this will always return 'column.1' as the column name
single_col_data = DatasetDataFactory.build(
column_names=[six.u('Date'), six.u('column.1')],
data=[['2015-07-11', 444.3], ['2015-07-13', 433.3],
['2015-07-14', 437.5], ['2015-07-15', 440.0]])
unit_test.single_dataset_data = {'dataset_data': single_col_data}
dataset_data = DatasetDataFactory.build()
d_values = dataset_data.pop('data')
d_metadata = dataset_data
unit_test.data_list_obj = DataList(Data, d_values, d_metadata)
unit_test.nse_oil = {
'dataset': DatasetFactory.build(database_code='NSE',
dataset_code='OIL')
}
unit_test.goog_aapl = {
'dataset':
DatasetFactory.build(database_code='GOOG', dataset_code='NASDAQ_AAPL')
}
unit_test.goog_msft = {
'dataset':
DatasetFactory.build(database_code='GOOG',
dataset_code='NASDAQ_MSFT',
newest_available_date='2015-07-30',
oldest_available_date='2013-01-01')
}
unit_test.single_col = {
'dataset':
DatasetFactory.build(database_code='SINGLE',
dataset_code='COLUMN',
newest_available_date='2015-07-30',
oldest_available_date='2013-01-01')
}
unit_test.oil_obj = Dataset('NSE/OIL', unit_test.nse_oil['dataset'])
unit_test.aapl_obj = Dataset('GOOG/AAPL', unit_test.goog_aapl['dataset'])
unit_test.goog_obj = Dataset('GOOG/MSFT', unit_test.goog_msft['dataset'])
unit_test.single_col_obj = Dataset('SINGLE/COLUMN',
unit_test.single_col['dataset'])
httpretty.register_uri(
httpretty.GET,
re.compile('https://www.quandl.com/api/v3/datasets/.*/metadata'),
responses=[
httpretty.Response(body=json.dumps(dataset)) for dataset in
[unit_test.nse_oil, unit_test.goog_aapl, unit_test.goog_msft]
])
# mock our query param column_index request
httpretty.register_uri(
httpretty.GET,
"https://www.quandl.com/api/v3/datasets/SINGLE/COLUMN/data",
body=json.dumps(unit_test.single_dataset_data))
httpretty.register_uri(
httpretty.GET,
"https://www.quandl.com/api/v3/datasets/GOOG/NASDAQ_AAPL/data",
body=json.dumps(unit_test.dataset_data))
httpretty.register_uri(
httpretty.GET,
re.compile('https://www.quandl.com/api/v3/datasets/NSE/OIL/data'),
body=json.dumps(unit_test.dataset_data))
httpretty.register_uri(
httpretty.GET,
re.compile(
'https://www.quandl.com/api/v3/datasets/GOOG/NASDAQ_MSFT/data'),
body=json.dumps(unit_test.dataset_data))
def test_datasets_has_more_results(self):
results = Dataset.all()
self.assertFalse(results.has_more_results())
def test_values_exist(self):
results = Dataset.all()
self.assertIsInstance(results.values, list)
self.assertIsInstance(results.values[0], Dataset)
def test_datasets_return_dataset_objects(self):
results = Dataset.all()
self.assertEqual(len(results), 3)
for result in results:
self.assertIsInstance(result, Dataset)
def test_dataset_calls_connection(self, mock):
d = Dataset('NSE/OIL')
d.data_fields()
expected = call('get', 'datasets/NSE/OIL/metadata', params={})
self.assertEqual(mock.call_args, expected)
def test_dataset_attributes_are_datetime_objects(self):
dataset = Dataset('NSE/OIL')
self.assertIsInstance(dataset.refreshed_at, datetime.datetime)
self.assertIsInstance(dataset.newest_available_date, datetime.date)
def test_dataset_returns_dataset_object(self):
dataset = Dataset('NSE/OIL')
self.assertIsInstance(dataset, Dataset)
self.assertEqual(dataset.dataset_code, 'OIL')
def test_dataset_calls_connection(self, mock):
d = Dataset('NSE/OIL')
d.data_fields()
expected = call('get', 'datasets/NSE/OIL/metadata', params={})
self.assertEqual(mock.call_args, expected)
def test_to_list_returns_list(self):
results = Dataset.all()
data = results.to_list()
self.assertIsInstance(data, list)
self.assertIsInstance(data[0], list)
def test_meta_attributes_can_be_accessed(self):
results = Dataset.all()
self.assertEqual(results.meta['current_page'], 1)
self.assertEqual(results.current_page, 1)
def test_to_list_returns_list(self):
results = Dataset.all()
data = results.to_list()
self.assertIsInstance(data, list)
self.assertIsInstance(data[0], list)
def test_dataset_column_names_match_expected(self):
dataset = Dataset('NSE/OIL')
six.assertCountEqual(self,
dataset.column_names, ['Date', 'column.1', 'column.2', 'column.3'])
def test_datasets_calls_connection(self, mock):
Dataset.all()
expected = call('get', 'datasets', params={})
self.assertEqual(mock.call_args, expected)
def test_datasets_calls_connection(self, mock):
Dataset.all()
expected = call('get', 'datasets', params={})
self.assertEqual(mock.call_args, expected)
def test_datasets_return_dataset_objects(self):
results = Dataset.all()
self.assertEqual(len(results), 3)
for result in results:
self.assertIsInstance(result, Dataset)
def test_datasets_has_more_results(self):
results = Dataset.all()
self.assertFalse(results.has_more_results())
def test_dataset_column_names_match_expected(self):
dataset = Dataset('NSE/OIL')
self.assertItemsEqual(dataset.column_names,
['Date', 'column.1', 'column.2', 'column.3'])
