def build_transaction(column_indices, row):
ta = Transaction()
if config.ACCOUNT_NO_COL in column_indices:
ta.set_account_no(
row[column_indices[config.ACCOUNT_NO_COL]].strip())
ta.date = util.parse_date(row[column_indices[config.DATE_COL]])
ta.amount = float(row[column_indices[config.AMOUNT_COL]].replace(
'.', '').replace(',', '.'))
if config.PAYMENT_REASON_COL in column_indices:
ta.payment_reason = re.sub(
r' +', ' ',
row[column_indices[config.PAYMENT_REASON_COL]].strip())
if config.RECIPIENT_COL in column_indices:
ta.recipient = re.sub(
r' +', ' ', row[column_indices[config.RECIPIENT_COL]].strip())
if config.OTHER_ACCOUNT_NO_COL in column_indices:
ta.set_other_account_no(
row[column_indices[config.OTHER_ACCOUNT_NO_COL]].strip())
return ta
def test_aggregate_transactions_by_year(self):
transactions = [
Transaction('123456', datetime(year=2018, month=3, day=5), 120.0,
'reason', 'recipient', config.INCOME_CATEGORY),
Transaction('123456', datetime(year=2018, month=5, day=18), -50.0,
'reason', 'recipient', self.category1),
Transaction('123456', datetime(year=2018, month=8, day=15), -30.0,
'reason', 'recipient', self.category1),
Transaction('123456', datetime(year=2018, month=9, day=3), -100.0,
'reason', 'recipient', self.category2),
Transaction('123456', datetime(year=2019, month=6, day=21), -150.0,
'reason', 'recipient', self.category2),
]
data_provider = DataProvider.load(transactions)
df_all = data_provider.get_all_transactions()
x_axis, category_values = data_provider.aggregate_by_category_as_tuple(
df_all, 'YS', config.CATEGORY_MAIN_COL)
self.assertEqual(2, len(x_axis))
self.assertEqual(3, len(
category_values.keys())) # includes income category
self.assertListEqual([120.0, 0.0],
list(category_values[config.INCOME_CATEGORY]))
self.assertListEqual([80.0, 0.0],
list(category_values[self.category1]))
self.assertListEqual([100.0, 150.0],
list(category_values[self.category2]))
def test_aggregate_different_expenses_by_month(self):
transactions = [
Transaction('123456', datetime(year=2019, month=3, day=1), -20.0,
'reason', 'recipient', self.category1),
Transaction('123456', datetime(year=2019, month=3, day=18), -50.0,
'reason', 'recipient', self.category2),
Transaction('123456', datetime(year=2019, month=4, day=15), -30.0,
'reason', 'recipient', self.category1),
Transaction('123456', datetime(year=2019, month=6, day=5), -100.0,
'reason', 'recipient', self.category2),
Transaction('123456', datetime(year=2019, month=6, day=21), -150.0,
'reason', 'recipient', self.category2),
]
data_provider = DataProvider.load(transactions)
df_all = data_provider.get_all_transactions()
x_axis, category_values = data_provider.aggregate_by_category_as_tuple(
df_all, 'MS', config.CATEGORY_MAIN_COL)
self.assertEqual(4, len(x_axis))
self.assertEqual(3, len(category_values.keys()))
self.assertListEqual([20.0, 30.0, 0.0, 0.0],
list(category_values[self.category1]))
self.assertListEqual([50.0, 0.0, 0.0, 250.0],
list(category_values[self.category2]))
def find_category(self, transaction: Transaction):
"""
Finds a matching category for the given transaction.
If the amount of the transaction is positive, the INCOME category is returned, otherwise the first category with
a matching keyword is used. If no matching keyword could be found the MISC category is used.
:param transaction:
:return: (main_category, sub_category)
"""
category = None
# income
if not transaction.is_expense():
category = self.find_sub_category(transaction,
config.INCOME_CATEGORY)
if category is None:
category = config.INCOME_CATEGORY, self._empty_category
else: # expense
for main_cat in config.categories.keys():
if main_cat is not config.INCOME_CATEGORY:
category = self.find_sub_category(transaction, main_cat)
if category:
break
if category is None:
category = config.MISC_CATEGORY, self._empty_category
return category
def test_aggregate_income_by_month(self):
transactions = [
Transaction('123456', datetime(year=2019, month=3, day=5), 20.0,
'reason', 'recipient', config.INCOME_CATEGORY),
Transaction('123456', datetime(year=2019, month=3, day=18), 50.0,
'reason', 'recipient', config.INCOME_CATEGORY),
Transaction('123456', datetime(year=2019, month=5, day=8), 100.0,
'reason', 'recipient', config.INCOME_CATEGORY),
]
data_provider = DataProvider.load(transactions)
df_all = data_provider.get_all_transactions()
x_axis, category_values = data_provider.aggregate_by_category_as_tuple(
df_all, 'MS', config.CATEGORY_MAIN_COL)
self.assertEqual(3, len(x_axis))
self.assertEqual(3, len(category_values.keys()))
self.assertListEqual([70.0, 0.0, 100.0],
list(category_values[config.INCOME_CATEGORY]))
def test_transaction_without_matching_keyword_expect_misc_category(self):
ta = Transaction('123456', datetime.datetime.now(), -40, 'Shoes', 'Amazon', '')
finder = CategoryFinder()
finder.assign_category([ta])
self.assertEqual(config.MISC_CATEGORY, ta.main_category)
def test_transaction_with_recipient_expect_car_category(self):
ta = Transaction('123456', datetime.datetime.now(), -30, '', 'Aral', '')
finder = CategoryFinder()
finder.assign_category([ta])
self.assertEqual('Car', ta.main_category)
def test_transaction_with_positive_amount_expect_income_category(self):
ta = Transaction('123456', datetime.datetime.now(), 100, 'salary', '', '')
finder = CategoryFinder()
finder.assign_category([ta])
self.assertEqual(config.INCOME_CATEGORY, ta.main_category)