def test_data_calls_connection_get(self, mock):
datatable = Datatable('ZACKS/FC')
Data.page(datatable, params={'ticker': ['AAPL', 'MSFT'],
'per_end_date': {'gte': '2015-01-01'},
'qopts': {'columns': ['ticker', 'per_end_date']}})
expected = call('get', 'datatables/ZACKS/FC',
params={'ticker[]': ['AAPL', 'MSFT'],
'per_end_date.gte': '2015-01-01',
'qopts.columns[]': ['ticker', 'per_end_date']})
self.assertEqual(mock.call_args, expected)
def test_data_calls_connection_post(self, mock):
RequestType.USE_GET_REQUEST = False
datatable = Datatable('ZACKS/FC')
Data.page(datatable, params={'ticker': ['AAPL', 'MSFT'],
'per_end_date': {'gte': '2015-01-01'},
'qopts': {'columns': ['ticker', 'per_end_date']}})
expected = call('post', 'datatables/ZACKS/FC',
json={'ticker': ['AAPL', 'MSFT'],
'per_end_date.gte': '2015-01-01',
'qopts.columns': ['ticker', 'per_end_date']})
self.assertEqual(mock.call_args, expected)
def test_to_numpy_returns_numpy_object(self, request_method):
if request_method == 'POST':
RequestType.USE_GET_REQUEST = False
datatable = Datatable('ZACKS/FC')
results = Data.page(datatable, params={})
data = results.to_numpy()
self.assertIsInstance(data, numpy.core.records.recarray)
def test_to_numpy_returns_numpy_object(self):
results = Data.all(params={
'database_code': 'NSE',
'dataset_code': 'OIL'
})
data = results.to_numpy()
self.assertIsInstance(data, numpy.core.records.recarray)
def test_pandas_dataframe_index_is_none(self, request_method):
if request_method == 'POST':
RequestType.USE_GET_REQUEST = False
datatable = Datatable('ZACKS/FC')
results = Data.page(datatable, params={})
df = results.to_pandas()
self.assertEqual(df.index.name, 'None')
def test_pandas_dataframe_index_is_none(self, request_method):
if request_method == 'POST':
RequestType.USE_GET_REQUEST = False
datatable = Datatable('ZACKS/FC')
results = Data.page(datatable, params={})
df = results.to_pandas()
self.assertEqual(df.index.name, 'None')
def test_data_to_list(self):
list_data = Data.all(
params={'database_code': 'NSE', 'dataset_code': 'OIL'}).to_list()
self.assertItemsEqual(list_data[0], self.expected_list_values[0])
self.assertItemsEqual(list_data[1], self.expected_list_values[1])
self.assertItemsEqual(list_data[2], self.expected_list_values[2])
self.assertItemsEqual(list_data[3], self.expected_list_values[3])
def test_to_pandas_returns_pandas_dataframe_object(self, request_method):
if request_method == 'POST':
RequestType.USE_GET_REQUEST = False
datatable = Datatable('ZACKS/FC')
results = Data.page(datatable, params={})
df = results.to_pandas()
self.assertIsInstance(df, pandas.core.frame.DataFrame)
def test_values_and_meta_exist(self, request_method):
if request_method == 'POST':
RequestType.USE_GET_REQUEST = False
datatable = Datatable('ZACKS/FC')
results = Data.page(datatable, params={})
self.assertIsNotNone(results.values)
self.assertIsNotNone(results.meta)
def test_to_csv_returns_expected_csv(self):
results = Data.all(
params={'database_code': 'NSE', 'dataset_code': 'OIL'})
data = results.to_csv()
expected = "Date,column.1,column.2,column.3\n2015-07-11,444.3,10,3\n" + \
"2015-07-13,433.3,4,3\n2015-07-14,437.5,3,3\n2015-07-15,440.0,2,3\n"
self.assertEqual(data, expected)
def test_values_and_meta_exist(self):
results = Data.all(params={
'database_code': 'NSE',
'dataset_code': 'OIL'
})
self.assertIsNotNone(results.values)
self.assertIsNotNone(results.meta)
def test_column_names_match(self):
results = Data.all(params={
'database_code': 'NSE',
'dataset_code': 'OIL'
})
six.assertCountEqual(self, results.column_names,
['Date', 'column.1', 'column.2', 'column.3'])
def test_to_numpy_returns_numpy_object(self, request_method):
if request_method == 'POST':
RequestType.USE_GET_REQUEST = False
datatable = Datatable('ZACKS/FC')
results = Data.page(datatable, params={})
data = results.to_numpy()
self.assertIsInstance(data, numpy.core.records.recarray)
def test_raw_data_is_zip_of_column_names_and_data(self):
results = Data.all(
params={'database_code': 'NSE', 'dataset_code': 'OIL'})
self.assertItemsEqual(results[0].__get_raw_data__(), self.expected_list_values[0])
self.assertItemsEqual(results[1].__get_raw_data__(), self.expected_list_values[1])
self.assertItemsEqual(results[2].__get_raw_data__(), self.expected_list_values[2])
self.assertItemsEqual(results[3].__get_raw_data__(), self.expected_list_values[3])
def test_to_pandas_returns_pandas_dataframe_object(self, request_method):
if request_method == 'POST':
RequestType.USE_GET_REQUEST = False
datatable = Datatable('ZACKS/FC')
results = Data.page(datatable, params={})
df = results.to_pandas()
self.assertIsInstance(df, pandas.core.frame.DataFrame)
def test_values_and_meta_exist(self, request_method):
if request_method == 'POST':
RequestType.USE_GET_REQUEST = False
datatable = Datatable('ZACKS/FC')
results = Data.page(datatable, params={})
self.assertIsNotNone(results.values)
self.assertIsNotNone(results.meta)
def test_to_pandas_returns_pandas_dataframe_object(self):
results = Data.all(params={
'database_code': 'NSE',
'dataset_code': 'OIL'
})
df = results.to_pandas()
self.assertIsInstance(df, pandas.core.frame.DataFrame)
def test_pandas_dataframe_date_field_is_datetime(self):
datatable = Datatable('ZACKS/FC')
results = Data.page(datatable, params={})
df = results.to_pandas()
self.assertIsInstance(df['per_end_date'][0], pandas.datetime)
self.assertIsInstance(df['per_end_date'][1], pandas.datetime)
self.assertIsInstance(df['per_end_date'][2], pandas.datetime)
self.assertIsInstance(df['per_end_date'][3], pandas.datetime)
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_pandas_dataframe_date_field_is_datetime(self):
datatable = Datatable('ZACKS/FC')
results = Data.page(datatable, params={})
df = results.to_pandas()
self.assertIsInstance(df['per_end_date'][0], pandas.datetime)
self.assertIsInstance(df['per_end_date'][1], pandas.datetime)
self.assertIsInstance(df['per_end_date'][2], pandas.datetime)
self.assertIsInstance(df['per_end_date'][3], pandas.datetime)
def test_data_returned_are_data_objects(self):
results = Data.all(params={
'database_code': 'NSE',
'dataset_code': 'OIL'
})
self.assertEqual(len(results), 4)
for result in results:
self.assertIsInstance(result, Data)
def test_pandas_dataframe_index_is_datetime(self):
results = Data.all(params={
'database_code': 'NSE',
'dataset_code': 'OIL'
})
df = results.to_pandas()
self.assertEqual(df.index.name, 'Date')
self.assertIsInstance(df.index, pandas.DatetimeIndex)
def test_to_csv_returns_expected_csv(self):
results = Data.all(params={
'database_code': 'NSE',
'dataset_code': 'OIL'
})
data = results.to_csv()
expected = "Date,column.1,column.2,column.3\n2015-07-11,444.3,10,3\n" + \
"2015-07-13,433.3,4,3\n2015-07-14,437.5,3,3\n2015-07-15,440.0,2,3\n"
self.assertEqual(data, expected)
def test_data_to_list(self):
list_data = Data.all(params={
'database_code': 'NSE',
'dataset_code': 'OIL'
}).to_list()
six.assertCountEqual(self, list_data[0], self.expected_list_values[0])
six.assertCountEqual(self, list_data[1], self.expected_list_values[1])
six.assertCountEqual(self, list_data[2], self.expected_list_values[2])
six.assertCountEqual(self, list_data[3], self.expected_list_values[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_to_csv_returns_expected_csv(self):
datatable = Datatable('ZACKS/FC')
results = Data.page(datatable, params={})
data = results.to_csv()
expected = "None,per_end_date,ticker,tot_oper_exp\n" + \
"0,2015-07-11,AAPL,456.9\n" + \
"1,2015-07-13,433.3,\n" + \
"2,2015-07-14,AAPL,419.1\n" + \
"3,2015-07-15,476.5,\n"
self.assertEqual(data, expected)
def test_to_csv_returns_expected_csv(self):
datatable = Datatable('ZACKS/FC')
results = Data.page(datatable, params={})
data = results.to_csv()
expected = "None,per_end_date,ticker,tot_oper_exp\n" + \
"0,2015-07-11,AAPL,456.9\n" + \
"1,2015-07-13,433.3,\n" + \
"2,2015-07-14,AAPL,419.1\n" + \
"3,2015-07-15,476.5,\n"
self.assertEqual(data, expected)
def test_pandas_dataframe_date_field_is_datetime(self, request_method):
if request_method == 'POST':
RequestType.USE_GET_REQUEST = False
datatable = Datatable('ZACKS/FC')
results = Data.page(datatable, params={})
df = results.to_pandas()
self.assertIsInstance(df['per_end_date'][0], pandas.datetime)
self.assertIsInstance(df['per_end_date'][1], pandas.datetime)
self.assertIsInstance(df['per_end_date'][2], pandas.datetime)
self.assertIsInstance(df['per_end_date'][3], pandas.datetime)
def test_pandas_dataframe_date_field_is_datetime(self, request_method):
if request_method == 'POST':
RequestType.USE_GET_REQUEST = False
datatable = Datatable('ZACKS/FC')
results = Data.page(datatable, params={})
df = results.to_pandas()
self.assertIsInstance(df['per_end_date'][0], pandas.datetime)
self.assertIsInstance(df['per_end_date'][1], pandas.datetime)
self.assertIsInstance(df['per_end_date'][2], pandas.datetime)
self.assertIsInstance(df['per_end_date'][3], pandas.datetime)
def setUpClass(cls):
cls.expected_column_names = [
six.u('Date'),
six.u('column.1'),
six.u('column.2'),
six.u('column.3')
]
cls.data_object = Data(
['2015-07-15', 440.0, 2, 3],
meta={'column_names': cls.expected_column_names})
def test_data_calls_connection_get(self, mock):
datatable = Datatable('ZACKS/FC')
Data.page(datatable,
params={
'ticker': ['AAPL', 'MSFT'],
'per_end_date': {
'gte': '2015-01-01'
},
'qopts': {
'columns': ['ticker', 'per_end_date']
}
})
expected = call('get',
'datatables/ZACKS/FC',
params={
'ticker[]': ['AAPL', 'MSFT'],
'per_end_date.gte': '2015-01-01',
'qopts.columns[]': ['ticker', 'per_end_date']
})
self.assertEqual(mock.call_args, expected)
def test_to_csv_returns_expected_csv(self, request_method):
if request_method == 'POST':
RequestType.USE_GET_REQUEST = False
datatable = Datatable('ZACKS/FC')
results = Data.page(datatable, params={})
data = results.to_csv()
expected = "None,per_end_date,ticker,tot_oper_exp\n" + \
"0,2015-07-11,AAPL,456.9\n" + \
"1,2015-07-13,433.3,\n" + \
"2,2015-07-14,AAPL,419.1\n" + \
"3,2015-07-15,476.5,\n"
self.assertEqual(data, expected)
def test_data_calls_connection_post(self, mock):
RequestType.USE_GET_REQUEST = False
datatable = Datatable('ZACKS/FC')
Data.page(datatable,
params={
'ticker': ['AAPL', 'MSFT'],
'per_end_date': {
'gte': '2015-01-01'
},
'qopts': {
'columns': ['ticker', 'per_end_date']
}
})
expected = call('post',
'datatables/ZACKS/FC',
json={
'ticker': ['AAPL', 'MSFT'],
'per_end_date.gte': '2015-01-01',
'qopts.columns': ['ticker', 'per_end_date']
})
self.assertEqual(mock.call_args, expected)
def test_to_csv_returns_expected_csv(self, request_method):
if request_method == 'POST':
RequestType.USE_GET_REQUEST = False
datatable = Datatable('ZACKS/FC')
results = Data.page(datatable, params={})
data = results.to_csv()
expected = "None,per_end_date,ticker,tot_oper_exp\n" + \
"0,2015-07-11,AAPL,456.9\n" + \
"1,2015-07-13,433.3,\n" + \
"2,2015-07-14,AAPL,419.1\n" + \
"3,2015-07-15,476.5,\n"
self.assertEqual(data, expected)
def test_raw_data_is_zip_of_column_names_and_data(self):
results = Data.all(params={
'database_code': 'NSE',
'dataset_code': 'OIL'
})
six.assertCountEqual(self, results[0].__get_raw_data__(),
self.expected_list_values[0])
six.assertCountEqual(self, results[1].__get_raw_data__(),
self.expected_list_values[1])
six.assertCountEqual(self, results[2].__get_raw_data__(),
self.expected_list_values[2])
six.assertCountEqual(self, results[3].__get_raw_data__(),
self.expected_list_values[3])
def setUpClass(cls):
cls.expected_column_names = [
six.u('per_end_date'),
six.u('ticker'),
six.u('tot_oper_exp')
]
cls.expected_column_types = [
six.u('Date'), six.u('String'),
six.u('String')
]
cls.data_object = Data(
['2015-07-11', 'AAPL', 440.0],
meta={
'columns': cls.expected_column_names,
'column_types': cls.expected_column_types
})
def test_values_and_meta_exist(self):
datatable = Datatable('ZACKS/FC')
results = Data.page(datatable, params={})
self.assertIsNotNone(results.values)
self.assertIsNotNone(results.meta)
def test_to_numpy_returns_numpy_object(self):
results = Data.all(
params={'database_code': 'NSE', 'dataset_code': 'OIL'})
data = results.to_numpy()
self.assertIsInstance(data, numpy.core.records.recarray)
def test_to_numpy_returns_numpy_object(self):
datatable = Datatable('ZACKS/FC')
results = Data.page(datatable, params={})
data = results.to_numpy()
self.assertIsInstance(data, numpy.core.records.recarray)
def test_to_pandas_returns_pandas_dataframe_object(self):
datatable = Datatable('ZACKS/FC')
results = Data.page(datatable, params={})
df = results.to_pandas()
self.assertIsInstance(df, pandas.core.frame.DataFrame)
def test_pandas_dataframe_index_is_none(self):
datatable = Datatable('ZACKS/FC')
results = Data.page(datatable, params={})
df = results.to_pandas()
self.assertEqual(df.index.name, 'None')
def test_data_returned_are_data_objects(self):
results = Data.all(
params={'database_code': 'NSE', 'dataset_code': 'OIL'})
self.assertEqual(len(results), 4)
for result in results:
self.assertIsInstance(result, Data)
def test_data_calls_connection(self, mock):
Data.all(params={'database_code': 'NSE', 'dataset_code': 'OIL'})
expected = call('get', 'datasets/NSE/OIL/data', params={})
self.assertEqual(mock.call_args, expected)
def test_values_and_meta_exist(self):
results = Data.all(
params={'database_code': 'NSE', 'dataset_code': 'OIL'})
self.assertIsNotNone(results.values)
self.assertIsNotNone(results.meta)
def test_to_pandas_returns_pandas_dataframe_object(self):
datatable = Datatable('ZACKS/FC')
results = Data.page(datatable, params={})
df = results.to_pandas()
self.assertIsInstance(df, pandas.core.frame.DataFrame)
def test_values_and_meta_exist(self):
datatable = Datatable('ZACKS/FC')
results = Data.page(datatable, params={})
self.assertIsNotNone(results.values)
self.assertIsNotNone(results.meta)
def test_column_names_match(self):
results = Data.all(
params={'database_code': 'NSE', 'dataset_code': 'OIL'})
self.assertItemsEqual(
results.column_names, ['Date', 'column.1', 'column.2', 'column.3'])
def test_pandas_dataframe_index_is_none(self):
datatable = Datatable('ZACKS/FC')
results = Data.page(datatable, params={})
df = results.to_pandas()
self.assertEqual(df.index.name, 'None')
def test_to_pandas_returns_pandas_dataframe_object(self):
results = Data.all(
params={'database_code': 'NSE', 'dataset_code': 'OIL'})
df = results.to_pandas()
self.assertIsInstance(df, pandas.core.frame.DataFrame)
def test_to_numpy_returns_numpy_object(self):
datatable = Datatable('ZACKS/FC')
results = Data.page(datatable, params={})
data = results.to_numpy()
self.assertIsInstance(data, numpy.core.records.recarray)
def test_data_calls_connection(self, mock):
Data.all(params={'database_code': 'NSE', 'dataset_code': 'OIL'})
expected = call('get', 'datasets/NSE/OIL/data', params={})
self.assertEqual(mock.call_args, expected)
def test_pandas_dataframe_index_is_datetime(self):
results = Data.all(
params={'database_code': 'NSE', 'dataset_code': 'OIL'})
df = results.to_pandas()
self.assertEqual(df.index.name, 'Date')
self.assertIsInstance(df.index, pandas.DatetimeIndex)
