def testColumnNames(self):
table = Table('census', self.schema).data(self.df)
self.assertEqual(len(table.column_names()), 22)
view = table.find({}, {'Information':True, 'State':True})
self.assertEqual(view.column_names(), ['Information', 'State'])
view2 = view.find({}, {'State':True})
self.assertEqual(view2.column_names(), ['State'])
class TestAttributeImplicitSieve(unittest.TestCase):
def setUp(self):
self.df = pd.read_csv(RSC_DIR+'/census.csv')
with open(RSC_DIR+'/schema_census') as f:
schema = json.loads(f.read())
self.schema = OrderedDict(attributes = schema['attributes'], index = schema['index'])
self.table = Table('census', self.schema).data(self.df)
def tearDown(self):
names.clear()
def testDomain(self):
s = AttributeImplicitSieve(self.table, [])
self.assertSetEqual(s.domain , set(self.table.column_names()))
def testProjection(self):
s = AttributeImplicitSieve(self.table, [])
self.assertEqual(s.projection , {})
s.index = ['Information', 'State']
self.assertEqual(s.projection , {u'Information': True, u'State': True})
