def test_normalize(self, normalize_mock, hash_sha_256_mock):
initial_state = {
'f5first': 'FirstName',
'f5last': 'LastName',
'fi': 'FI',
'dobd': '01',
'dobm': '02',
'doby': '2000',
}
user_data = UserData(
f5first=initial_state['f5first'],
f5last=initial_state['f5last'],
fi=initial_state['fi'],
dobd=initial_state['dobd'],
dobm=initial_state['dobm'],
doby=initial_state['doby'],
)
hash_sha_256_mock.side_effect = (lambda field: field + '-sha256'
if field else None)
normalize_mock.side_effect = (lambda _, field: field + '-normal'
if field else None)
actual = user_data.normalize()
expected = {}
for key, value in initial_state.items():
expected[key] = '%s-normal-sha256' % value
self.assertEqual(actual, expected)
def test_normalize_it_normalizes_and_hashes(self):
initial_state = {
'f5first': 'First',
'f5last': 'Last',
'fi': 'A',
'dobd': '01',
'dobm': '02',
'doby': '2000',
'lead_id': 'lead-id-3',
}
user_data = UserData(
f5first=initial_state['f5first'],
f5last=initial_state['f5last'],
fi=initial_state['fi'],
dobd=initial_state['dobd'],
dobm=initial_state['dobm'],
doby=initial_state['doby'],
lead_id=initial_state['lead_id'],
)
actual = user_data.normalize()
expected = {
'f5first':
Normalize.hash_sha_256(initial_state['f5first'].lower()),
'f5last': Normalize.hash_sha_256(initial_state['f5last'].lower()),
'fi': Normalize.hash_sha_256(initial_state['fi'].lower()),
'dobd': Normalize.hash_sha_256(initial_state['dobd']),
'dobm': Normalize.hash_sha_256(initial_state['dobm']),
'doby': Normalize.hash_sha_256(initial_state['doby']),
'lead_id': initial_state['lead_id'],
}
self.assertEqual(actual, expected)
def test_multi_value_normalization_with_empty(self):
user_data = UserData()
user_data.emails = []
user_data.phones = []
user_data.genders = []
user_data.dates_of_birth = []
user_data.last_names = []
user_data.first_names = []
user_data.cities = []
user_data.states = []
user_data.country_codes = []
user_data.zip_codes = []
user_data.external_ids = []
normalized_data = user_data.normalize()
self.assertFalse(normalized_data)
def test_constructor(self):
event_name = 'event_name-0'
event_time = 123
event_source_url = 'event_source_url-2'
opt_out = False
event_id = 'event_id-3'
user_data = UserData(email='*****@*****.**')
custom_data = CustomData(order_id=123)
data_processing_options = ['4' '5']
data_processing_options_country = 6
data_processing_options_state = 7
action_source = ActionSource.APP
event = Event(
event_name=event_name,
event_time=event_time,
event_source_url=event_source_url,
opt_out=opt_out,
event_id=event_id,
user_data=user_data,
custom_data=custom_data,
data_processing_options=data_processing_options,
data_processing_options_country=data_processing_options_country,
data_processing_options_state=data_processing_options_state,
action_source=action_source,
)
expected_params = {
'event_name': event_name,
'event_time': event_time,
'event_source_url': event_source_url,
'opt_out': opt_out,
'event_id': event_id,
'user_data': user_data.normalize(),
'custom_data': custom_data.normalize(),
'data_processing_options': data_processing_options,
'data_processing_options_country': data_processing_options_country,
'data_processing_options_state': data_processing_options_state,
'action_source': action_source.value,
}
self.assertEqual(event.normalize(), expected_params)
def test_normalize_it_normalizes_and_hashes(self):
initial_state = {
'emails': ['*****@*****.**', '*****@*****.**', '*****@*****.**'],
'phones': ['12345678912', '12062072008', '12062072008'],
'genders': [Gender.MALE, Gender.FEMALE, Gender.FEMALE],
'dates_of_birth': ['19900101', '19660202', '19660202'],
'last_names': ['smith', 'brown', 'brown'],
'first_names': ['joe', 'mary', 'mary'],
'cities': ['seattle', 'sanfrancisco', 'sanfrancisco'],
'states': ['ca', 'wa', 'wa'],
'country_codes': ['us', 'ca', 'ca'],
'zip_codes': ['98001', '12345', '12345'],
'external_ids': ['123', '456', '456'],
'f5first': 'First',
'f5last': 'Last',
'fi': 'A',
'dobd': '01',
'dobm': '02',
'doby': '2000',
'lead_id': 'lead-id-3',
}
user_data = UserData(
f5first=initial_state['f5first'],
f5last=initial_state['f5last'],
fi=initial_state['fi'],
dobd=initial_state['dobd'],
dobm=initial_state['dobm'],
doby=initial_state['doby'],
lead_id=initial_state['lead_id'],
)
user_data.emails = initial_state['emails']
user_data.phones = initial_state['phones']
user_data.genders = initial_state['genders']
user_data.dates_of_birth = initial_state['dates_of_birth']
user_data.last_names = initial_state['last_names']
user_data.first_names = initial_state['first_names']
user_data.cities = initial_state['cities']
user_data.states = initial_state['states']
user_data.country_codes = initial_state['country_codes']
user_data.zip_codes = initial_state['zip_codes']
user_data.external_ids = initial_state['external_ids']
actual = user_data.normalize()
expected = {
'em':
self.__hash_list(initial_state['emails'][0:2]),
'ph':
self.__hash_list(initial_state['phones'][0:2]),
'ge':
self.__hash_list(
list(map(lambda g: g.value, initial_state['genders'][0:2]))),
'db':
self.__hash_list(initial_state['dates_of_birth'][0:2]),
'ln':
self.__hash_list(initial_state['last_names'][0:2]),
'fn':
self.__hash_list(initial_state['first_names'][0:2]),
'ct':
self.__hash_list(initial_state['cities'][0:2]),
'st':
self.__hash_list(initial_state['states'][0:2]),
'zp':
self.__hash_list(initial_state['zip_codes'][0:2]),
'country':
self.__hash_list(initial_state['country_codes'][0:2]),
'external_id':
initial_state['external_ids'][0:2],
'f5first':
Normalize.hash_sha_256(initial_state['f5first'].lower()),
'f5last':
Normalize.hash_sha_256(initial_state['f5last'].lower()),
'fi':
Normalize.hash_sha_256(initial_state['fi'].lower()),
'dobd':
Normalize.hash_sha_256(initial_state['dobd']),
'dobm':
Normalize.hash_sha_256(initial_state['dobm']),
'doby':
Normalize.hash_sha_256(initial_state['doby']),
'lead_id':
initial_state['lead_id'],
}
not_equal_items = {
k: actual[k]
for k in actual
if k not in expected or sorted(actual[k]) != sorted(expected[k])
}
self.assertEqual(len(not_equal_items), 0)
self.assertEqual(len(actual), len(expected))