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.wiki_aapl = {'dataset': DatasetFactory.build(
database_code='WIKI', dataset_code='AAPL')}
unit_test.wiki_msft = {'dataset': DatasetFactory.build(
database_code='WIKI', dataset_code='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('WIKI/AAPL', unit_test.wiki_aapl['dataset'])
unit_test.wiki_obj = Dataset('WIKI/MSFT', unit_test.wiki_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.wiki_aapl,
unit_test.wiki_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/WIKI/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/WIKI/MSFT/data'),
body=json.dumps(unit_test.dataset_data))
def setUpClass(cls):
httpretty.enable()
dataset_data = {'dataset_data': DatasetDataFactory.build()}
httpretty.register_uri(
httpretty.GET,
re.compile('https://www.quandl.com/api/v3/datasets*'),
body=json.dumps(dataset_data))
cls.expected_raw_data = [{
'date': datetime.date(2015, 7, 11),
'column1': 444.3,
'column2': 10,
'column3': 3
}, {
'date': datetime.date(2015, 7, 13),
'column1': 433.3,
'column2': 4,
'column3': 3
}, {
'date': datetime.date(2015, 7, 14),
'column1': 437.5,
'column2': 3,
'column3': 3
}, {
'date': datetime.date(2015, 7, 15),
'column1': 440.0,
'column2': 2,
'column3': 3
}]
cls.expected_list_values = [[datetime.date(2015, 7, 11), 444.3, 10, 3],
[datetime.date(2015, 7, 13), 433.3, 4, 3],
[datetime.date(2015, 7, 14), 437.5, 3, 3],
[datetime.date(2015, 7, 15), 440.0, 2, 3]]
def test_exception_raised_if_column_and_data_row_mistmatch(self):
dataset_data = {
'dataset_data': DatasetDataFactory.build(column_names=['blah'])}
httpretty.register_uri(httpretty.GET,
re.compile(
'https://www.quandl.com/api/v3/datasets*'),
body=json.dumps(dataset_data))
self.assertRaises(InvalidDataError, lambda: Data.all())
def test_exception_raised_if_column_and_data_row_mistmatch(self):
dataset_data = {
'dataset_data': DatasetDataFactory.build(column_names=['blah'])
}
httpretty.register_uri(
httpretty.GET,
re.compile('https://www.quandl.com/api/v3/datasets*'),
body=json.dumps(dataset_data))
self.assertRaises(InvalidDataError, lambda: Data.all())
def setUpClass(cls):
httpretty.enable()
dataset_data = {'dataset_data': DatasetDataFactory.build()}
httpretty.register_uri(httpretty.GET,
re.compile(
'https://www.quandl.com/api/v3/datasets*'),
body=json.dumps(dataset_data))
cls.expected_raw_data = [{'date': datetime.date(2015, 7, 11), 'column1': 444.3,
'column2': 10, 'column3': 3},
{'date': datetime.date(2015, 7, 13), 'column1': 433.3,
'column2': 4, 'column3': 3},
{'date': datetime.date(2015, 7, 14), 'column1': 437.5,
'column2': 3, 'column3': 3},
{'date': datetime.date(2015, 7, 15), 'column1': 440.0,
'column2': 2, 'column3': 3}]
cls.expected_list_values = [[datetime.date(2015, 7, 11), 444.3, 10, 3],
[datetime.date(2015, 7, 13), 433.3, 4, 3],
[datetime.date(2015, 7, 14), 437.5, 3, 3],
[datetime.date(2015, 7, 15), 440.0, 2, 3]]
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))