Model/model_data/tests/test_land_registry_client.py
2023-06-16 09:36:02 +01:00

49 lines
2.1 KiB
Python

import pandas as pd
from unittest.mock import patch, call
from model_data.LandRegistryClient import LandRegistryClient
class TestLandRegistryClient:
@patch('pandas.read_csv')
@patch('fuzzywuzzy.fuzz.ratio')
def test_read(self, mock_fuzz, mock_read_csv):
# setup mocks
mock_read_csv.return_value = pd.DataFrame([
['1', '815000', '2022-06-28', 'SW6 3JA', 'F', 'N', 'L', 'FLAT', 'GROUND FLOOR', '6 DYMOCK STREET', None,
'LONDON', 'HAMMERSMITH AND FULHAM', 'GREATER LONDON', 'A', 'Y'],
['2', '200', '2023-03-04', 'N16 0EG', 'S', 'N', 'F', '25', None, 'DEFOE ROAD', None, 'LONDON', 'HACKNEY',
'GREATER LONDON', 'B', 'Y'],
['3', '300', '2023-03-05', 'N16 0EG', 'O', 'Y', 'L', '26', None, 'DEFOE ROAD', None, 'LONDON', 'HACKNEY',
'GREATER LONDON', 'A', 'N']
], columns=LandRegistryClient.COLUMN_NAMES)
mock_fuzz.side_effect = [70, 100, 50]
# setup client
addresses = [{
'postcode': 'SW6 3JA', 'address1': 'GROUND FLOOR', 'address2': 'FLAT 6 DYMOCK STREET', 'address3': 'FULHAM',
'address': 'Ground Floor Flat, 6 Dymock Street, Fulham', 'uprn': '34063921'
}]
client = LandRegistryClient(['path_to_data.csv'], addresses)
# call read
result = client.read()
# assertions
mock_read_csv.assert_called_once_with('path_to_data.csv', header=None)
assert mock_fuzz.call_args_list == [
call('GROUND FLOOR FLAT 6 DYMOCK STREET ', 'GROUND FLOOR FLAT 6 DYMOCK STREET FULHAM'),
call('GROUND FLOOR FLAT 6 DYMOCK STREET ', 'GROUND FLOOR FLAT 6 DYMOCK STREET FULHAM')
]
pd.testing.assert_frame_equal(result, pd.DataFrame({
'price': ["815000"],
'date_of_transfer': ['2022-06-28'],
'property_type': ['F'],
'old_new': ['N'],
'duration': ['L'],
'ppd_category_type': ['A'],
'record_status': ['Y'],
'uprn': ['34063921'],
'address': ['Ground Floor Flat, 6 Dymock Street, Fulham']
}))