def test_data_creation_from_base_row(self, mock_read_csv):
"""Confirm creation of a CountyMortgageData object from a CSV row."""
f = StringIO(self.data_header + self.data_row)
reader = csv.DictReader(f)
mock_read_csv.return_value = reader
load_values()
self.assertEqual(CountyMortgageData.objects.count(), 1)
county = CountyMortgageData.objects.first()
fields = reader.fieldnames
fields.pop(fields.index('fips')) # test string separately
fields.pop(fields.index('open')) # 'open' is stored as 'total'
fields.pop(fields.index('date')) # date must be parsed before testing
self.assertEqual(county.fips, self.data_row_dict.get('fips'))
open_value = int(self.data_row_dict.get('open'))
self.assertEqual(county.total, open_value)
target_date = parser.parse(self.data_row_dict['date']).date()
self.assertEqual(county.date, target_date)
for field in fields: # remaining fields can be tested in a loop
self.assertEqual(getattr(county, field),
int(self.data_row_dict.get(field)))
# test computed values
self.assertEqual(county.epoch, int(target_date.strftime('%s')) * 1000)
self.assertEqual(
county.percent_90,
int(self.data_row_dict.get('ninety')) * 1.0 / open_value)
self.assertEqual(county.percent_30_60,
(int(self.data_row_dict.get('thirty')) +
int(self.data_row_dict.get('sixty'))) * 1.0 /
open_value)
def test_load_values(self, mock_read_in):
mock_read_in.return_value = [{
'thirty': '4', 'month': '1', 'current': '262', 'sixty': '1',
'ninety': '0', 'date': '01/01/2008', 'open': '270', 'other': '3',
'fips': '12081'}]
load_values()
self.assertEqual(mock_read_in.call_count, 1)
self.assertEqual(CountyMortgageData.objects.count(), 1)
def test_load_values(self, mock_read_in):
mock_read_in.return_value = [{
'thirty': '4', 'month': '1', 'current': '262', 'sixty': '1',
'ninety': '0', 'date': '01/01/2008', 'open': '270', 'other': '3',
'fips': '12081'}]
load_values()
self.assertEqual(mock_read_in.call_count, 1)
self.assertEqual(CountyMortgageData.objects.count(), 1)
def test_load_values_return_fips(self, mock_read_in):
mock_read_in.return_value = [{
'thirty': '4', 'month': '1', 'current': '262', 'sixty': '1',
'ninety': '0', 'date': '01/01/2008', 'open': '270', 'other': '3',
'fips': '12081'}]
fips_list = load_values(return_fips=True)
self.assertEqual(mock_read_in.call_count, 1)
self.assertEqual(fips_list, ['12081'])
def test_load_values_return_fips(self, mock_read_in):
mock_read_in.return_value = [{
'thirty': '4', 'month': '1', 'current': '262', 'sixty': '1',
'ninety': '0', 'date': '01/01/2008', 'open': '270', 'other': '3',
'fips': '12081'}]
fips_list = load_values(return_fips=True)
self.assertEqual(mock_read_in.call_count, 1)
self.assertEqual(fips_list, ['12081'])
def test_data_creation_from_base_row(
self, mock_read_csv):
"""
Confirm that loading a single row of real base data creates
a CountyMortgageData object with the base row's values,
and that the object's calculated API values are correct.
"""
f = StringIO.StringIO(self.data_header + self.data_row)
reader = unicodecsv.DictReader(f)
mock_read_csv.return_value = reader
load_values()
self.assertEqual(CountyMortgageData.objects.count(), 1)
county = CountyMortgageData.objects.first()
fields = reader.fieldnames
fields.pop(fields.index('fips')) # test string separately
fields.pop(fields.index('open')) # 'open' is stored as 'total'
fields.pop(fields.index('date')) # date must be parsed before testing
self.assertEqual(county.fips, self.data_row_dict.get('fips'))
open_value = int(self.data_row_dict.get('open'))
self.assertEqual(county.total, open_value)
target_date = parser.parse(self.data_row_dict['date']).date()
self.assertEqual(county.date, target_date)
for field in fields: # remaining fields can be tested in a loop
self.assertEqual(
getattr(county, field), int(self.data_row_dict.get(field)))
# test computed values
self.assertEqual(
county.epoch,
int(target_date.strftime('%s')) * 1000)
self.assertEqual(
county.percent_90,
int(self.data_row_dict.get('ninety')) * 1.0 / open_value)
self.assertEqual(
county.percent_30_60,
(int(self.data_row_dict.get('thirty')) +
int(self.data_row_dict.get('sixty'))) * 1.0 / open_value)
