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Model/etl/epc/tests/test_epcrecord.py
Khalim Conn-Kowlessar 1b15f66f48 removing online dependency from tests
2025-05-15 17:12:19 +01:00

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import pickle
import pytest
from etl.epc.Record import EPCRecord
from etl.epc.settings import DATA_ANOMALY_MATCHES
import random
class TestEpcRecord:
@pytest.fixture()
def cleaning_data(self):
with open("recommendations/tests/test_data/cleaning_data.pkl", "rb") as f:
data = pickle.load(f)
return data
@pytest.fixture()
def epc_records_1(self):
epc_records_1 = {
'original_epc': {
'low-energy-fixed-light-count': '', 'address': '139 School Road, Hall Green',
'uprn-source': 'Energy Assessor', 'floor-height': '2.6', 'heating-cost-potential': '1138',
'unheated-corridor-length': '', 'hot-water-cost-potential': '175',
'construction-age-band': 'England and Wales: 1900-1929', 'potential-energy-rating': 'B',
'mainheat-energy-eff': 'Good', 'windows-env-eff': 'Average', 'lighting-energy-eff': 'Very Good',
'environment-impact-potential': '82', 'glazed-type': 'double glazing, unknown install date',
'heating-cost-current': '2711', 'address3': '',
'mainheatcont-description': 'Programmer, TRVs and bypass',
'sheating-energy-eff': 'N/A', 'property-type': 'House', 'local-authority-label': 'Birmingham',
'fixed-lighting-outlets-count': '11', 'energy-tariff': 'Single', 'mechanical-ventilation': 'natural',
'hot-water-cost-current': '310', 'county': '', 'postcode': 'B28 8JF', 'solar-water-heating-flag': 'N',
'constituency': 'E14000562', 'co2-emissions-potential': '2.0', 'number-heated-rooms': '4',
'floor-description': 'Suspended, no insulation (assumed)', 'energy-consumption-potential': '107',
'local-authority': 'E08000025', 'built-form': 'Semi-Detached', 'number-open-fireplaces': '0',
'windows-description': 'Fully double glazed', 'glazed-area': 'Normal', 'inspection-date': '2023-07-05',
'mains-gas-flag': 'Y', 'co2-emiss-curr-per-floor-area': '65', 'address1': '139 School Road',
'heat-loss-corridor': '', 'flat-storey-count': '', 'constituency-label': 'Birmingham, Hall Green',
'roof-energy-eff': 'Average', 'total-floor-area': '103.0', 'building-reference-number': '10004697322',
'environment-impact-current': '43', 'co2-emissions-current': '6.7',
'roof-description': 'Pitched, 100 mm loft insulation', 'floor-energy-eff': 'N/A',
'number-habitable-rooms': '4', 'address2': 'Hall Green', 'hot-water-env-eff': 'Good',
'posttown': 'BIRMINGHAM', 'mainheatc-energy-eff': 'Average', 'main-fuel': 'mains gas (not community)',
'lighting-env-eff': 'Very Good', 'windows-energy-eff': 'Average', 'floor-env-eff': 'N/A',
'sheating-env-eff': 'N/A', 'lighting-description': 'Low energy lighting in 82% of fixed outlets',
'roof-env-eff': 'Average', 'walls-energy-eff': 'Very Poor', 'photo-supply': '0.0',
'lighting-cost-potential': '182', 'mainheat-env-eff': 'Good', 'multi-glaze-proportion': '100',
'main-heating-controls': '', 'lodgement-datetime': '2023-07-13 08:23:07', 'flat-top-storey': '',
'current-energy-rating': 'E', 'secondheat-description': 'None', 'walls-env-eff': 'Very Poor',
'transaction-type': 'rental', 'uprn': '100070505235', 'current-energy-efficiency': '51',
'energy-consumption-current': '366', 'mainheat-description': 'Boiler and radiators, mains gas',
'lighting-cost-current': '182', 'lodgement-date': '2023-07-13', 'extension-count': '0',
'mainheatc-env-eff': 'Average',
'lmk-key': 'c1d137711da433fb3cced74b1a6848da8bbc1159d076455d26d7b4668982601e',
'wind-turbine-count': '0',
'tenure': 'Rented (social)', 'floor-level': '', 'potential-energy-efficiency': '84',
'hot-water-energy-eff': 'Good', 'low-energy-lighting': '82',
'walls-description': 'Solid brick, as built, no insulation (assumed)',
'hotwater-description': 'From main system'}, 'full_sap_epc': {}, 'old_data': []
}
return epc_records_1
def test_clean_mechanical_ventilation(self, cleaning_data, epc_records_1):
# We have an epc with Natural ventilation - the resulting epc should also have natural ventulation
record = EPCRecord(cleaning_data=cleaning_data)
record.prepared_epc = {
"mechanical-ventilation": "natural"
}
record._clean_ventilation()
assert record.prepared_epc["mechanical-ventilation"] == "natural"
record2 = EPCRecord(cleaning_data=cleaning_data)
record2.prepared_epc = {
"mechanical-ventilation": ""
}
record2._clean_ventilation()
assert record2.prepared_epc["mechanical-ventilation"] is None
record3 = EPCRecord(cleaning_data=cleaning_data)
record3.prepared_epc = {
"mechanical-ventilation": None
}
record3._clean_ventilation()
assert record3.prepared_epc["mechanical-ventilation"] is None
record4 = EPCRecord(cleaning_data=cleaning_data)
record4.prepared_epc = {
"mechanical-ventilation": "INVALID"
}
record4._clean_ventilation()
assert record4.prepared_epc["mechanical-ventilation"] is None
def test_clean_energy_valid_values(self, cleaning_data, epc_records_1):
record = EPCRecord(cleaning_data=cleaning_data)
record.prepared_epc = {
"energy-consumption-current": "200",
"co2-emissions-current": "5.5"
}
record._clean_energy()
assert record.prepared_epc["energy-consumption-current"] == 200.0
assert record.prepared_epc["co2-emissions-current"] == 5.5
def test_clean_energy_empty_values(self, cleaning_data):
# We cannot have invalid values so this should raise an exception
record = EPCRecord(cleaning_data=cleaning_data)
record.prepared_epc = {
"energy-consumption-current": "",
"co2-emissions-current": ""
}
with pytest.raises(ValueError):
record._clean_energy()
def test_clean_built_form_valid_remap(self, cleaning_data, epc_records_1):
record = EPCRecord(cleaning_data=cleaning_data)
# Assuming "Semi" should be remapped to "Semi-Detached"
record.prepared_epc = {
"built-form": "Semi-Detached",
"property-type": "Flat" # Assuming this affects the remapping
}
record._clean_built_form()
assert record.prepared_epc["built-form"] == "Semi-Detached"
def test_clean_built_form_anomaly(self, cleaning_data, epc_records_1):
record = EPCRecord(cleaning_data=cleaning_data)
record.prepared_epc = {
"built-form": "",
"property-type": "Flat"
}
record._clean_built_form()
assert record.prepared_epc["built-form"] == "End-Terrace"
def test_clean_floor_area_valid(self, cleaning_data):
record = EPCRecord(cleaning_data=cleaning_data)
record.prepared_epc = {
"total-floor-area": "120.5"
}
record._clean_floor_area()
assert record.prepared_epc["total-floor-area"] == 120.5
def test_clean_floor_area_empty(self, cleaning_data):
record = EPCRecord(cleaning_data=cleaning_data)
record.prepared_epc = {
"total-floor-area": ""
}
# We have no known case of missing floor area
with pytest.raises(ValueError):
record._clean_floor_area()
def test_clean_heat_loss_corridor_valid(self, cleaning_data):
record = EPCRecord(cleaning_data=cleaning_data)
record.prepared_epc = {
"heat-loss-corridor": "unheated corridor",
"unheated-corridor-length": ""
}
record._clean_heat_loss_corridor()
assert record.prepared_epc["heat-loss-corridor"] == "unheated corridor"
record = EPCRecord(cleaning_data=cleaning_data)
record.prepared_epc = {
"heat-loss-corridor": "unheated corridor",
"unheated-corridor-length": None
}
record._clean_heat_loss_corridor()
assert record.prepared_epc["heat-loss-corridor"] == "unheated corridor"
assert record.prepared_epc["unheated-corridor-length"] is None
def test_clean_heat_loss_corridor_anomaly(self, cleaning_data):
record = EPCRecord(cleaning_data=cleaning_data)
# Assuming "InvalidCorridor" is an anomaly
record.prepared_epc = {
"heat-loss-corridor": "InvalidCorridor",
"unheated-corridor-length": ""
}
record._clean_heat_loss_corridor()
assert record.prepared_epc["heat-loss-corridor"] == "no corridor"
def test_clean_mains_gas_valid(self, cleaning_data):
record = EPCRecord(cleaning_data=cleaning_data)
record.prepared_epc = {
"mains-gas-flag": "Y"
}
record._clean_mains_gas()
assert record.prepared_epc["mains-gas-flag"] is True
def test_clean_mains_gas_anomaly(self, cleaning_data):
record = EPCRecord(cleaning_data=cleaning_data)
record.prepared_epc = {
"mains-gas-flag": "InvalidValue"
}
# It should always be Y or N or an anomally value
with pytest.raises(KeyError):
record._clean_mains_gas()
record = EPCRecord(cleaning_data=cleaning_data)
record.prepared_epc = {
"mains-gas-flag": random.choice(list(DATA_ANOMALY_MATCHES))
}
record._clean_mains_gas()
assert record.prepared_epc["mains-gas-flag"] is None
def test_clean_solar_hot_water_valid(self, cleaning_data):
record = EPCRecord(cleaning_data=cleaning_data)
record.prepared_epc = {
"solar-water-heating-flag": "Y"
}
record._clean_solar_hot_water()
assert record.prepared_epc["solar-water-heating-flag"] == "Y"
assert record.solar_water_heating_flag_bool is True
def test_clean_solar_hot_water_empty(self, cleaning_data):
record = EPCRecord(cleaning_data=cleaning_data)
record.prepared_epc = {
"solar-water-heating-flag": ""
}
record._clean_solar_hot_water()
assert record.prepared_epc["solar-water-heating-flag"] == "N"
assert record.solar_water_heating_flag_bool is False
def test_clean_number_lighting_outlets_valid(self, cleaning_data, epc_records_1):
record = EPCRecord(cleaning_data=cleaning_data, epc_records=epc_records_1)
record.prepared_epc = {
"fixed-lighting-outlets-count": "5"
}
record._clean_number_lighting_outlets()
assert record.prepared_epc["fixed-lighting-outlets-count"] == 5.0
def test_clean_number_lighting_outlets_empty(self, cleaning_data, epc_records_1):
record = EPCRecord(cleaning_data=cleaning_data)
record.run_mode = "newdata"
record.prepared_epc = {
"fixed-lighting-outlets-count": "",
"property-type": "Flat",
"built-form": "Semi-Detached",
"construction-age-band": "England and Wales: 1900-1929",
"local-authority": "E08000025",
"number-habitable-rooms": "4",
"number-heated-rooms": "4",
}
record.old_data = []
record.full_sap_epc = []
record._clean_number_lighting_outlets()
assert record.prepared_epc["fixed-lighting-outlets-count"] == 10
def test_clean_count_variables(self, cleaning_data):
record = EPCRecord(cleaning_data=cleaning_data)
record.prepared_epc = {
"number-open-fireplaces": "1",
"extension-count": None,
"flat-storey-count": "",
"number-habitable-rooms": "INVALID!",
}
record._clean_count_variables()
assert record.prepared_epc["number-open-fireplaces"] == 1.0
assert record.prepared_epc["extension-count"] == 0
assert record.prepared_epc["flat-storey-count"] is None
assert record.prepared_epc["number-habitable-rooms"] is None
def test_clean_floor_level(self, cleaning_data):
record = EPCRecord(cleaning_data=cleaning_data)
record.prepared_epc = {
"floor-level": "1",
}
record._clean_floor_level()
assert record.prepared_epc["floor-level"] == 1.0
record = EPCRecord(cleaning_data=cleaning_data)
record.prepared_epc = {
"floor-level": "",
}
record._clean_floor_level()
assert record.prepared_epc["floor-level"] is None
record = EPCRecord(cleaning_data=cleaning_data)
record.prepared_epc = {
"floor-level": None,
}
record._clean_floor_level()
assert record.prepared_epc["floor-level"] is None
def test_clean_solar_hot_water(self, cleaning_data):
record = EPCRecord(cleaning_data=cleaning_data)
record.prepared_epc = {
"solar-water-heating-flag": "Y",
}
record._clean_solar_hot_water()
assert record.prepared_epc["solar-water-heating-flag"] == "Y"
assert record.solar_water_heating_flag_bool is True
record = EPCRecord(cleaning_data=cleaning_data)
record.prepared_epc = {
"solar-water-heating-flag": "N",
}
record._clean_solar_hot_water()
assert record.prepared_epc["solar-water-heating-flag"] == "N"
assert record.solar_water_heating_flag_bool is False
record = EPCRecord(cleaning_data=cleaning_data)
record.prepared_epc = {
"solar-water-heating-flag": "",
}
record._clean_solar_hot_water()
assert record.prepared_epc["solar-water-heating-flag"] == "N"
assert record.solar_water_heating_flag_bool is False
record = EPCRecord(cleaning_data=cleaning_data)
record.prepared_epc = {
"solar-water-heating-flag": None,
}
record._clean_solar_hot_water()
assert record.prepared_epc["solar-water-heating-flag"] == "N"
assert record.solar_water_heating_flag_bool is False
def test_year_built(self, cleaning_data):
# This test handles a specific test case
# Mock the property object
epc_records = {
"original_epc": {
'low-energy-fixed-light-count': '', 'address': '19 Waterloo Road, Shoeburyness',
'uprn-source': 'Energy Assessor', 'floor-height': '2.65', 'heating-cost-potential': '436',
'unheated-corridor-length': '', 'hot-water-cost-potential': '100',
'construction-age-band': 'England and Wales: 1900-1929', 'potential-energy-rating': 'B',
'mainheat-energy-eff': 'Good', 'windows-env-eff': 'Good', 'lighting-energy-eff': 'Very Good',
'environment-impact-potential': '89', 'glazed-type': 'double glazing installed during or after 2002',
'heating-cost-current': '888', 'address3': '',
'mainheatcont-description': 'Programmer and room thermostat',
'sheating-energy-eff': 'N/A', 'report-type': '100', 'property-type': 'House',
'local-authority-label': 'Southend-on-Sea', 'fixed-lighting-outlets-count': '9',
'energy-tariff': 'Single',
'mechanical-ventilation': 'natural', 'hot-water-cost-current': '386', 'county': '',
'postcode': 'SS3 9EQ',
'solar-water-heating-flag': 'N', 'constituency': 'E14001501', 'co2-emissions-potential': '0.7',
'number-heated-rooms': '4', 'floor-description': 'Suspended, no insulation (assumed)',
'energy-consumption-potential': '49', 'local-authority': 'E06000033', 'built-form': 'Mid-Terrace',
'number-open-fireplaces': '0', 'windows-description': 'Fully double glazed', 'glazed-area': 'Normal',
'inspection-date': '2025-03-17', 'mains-gas-flag': 'Y', 'co2-emiss-curr-per-floor-area': '58',
'address1': '19 Waterloo Road', 'heat-loss-corridor': '', 'flat-storey-count': '',
'constituency-label': '',
'roof-energy-eff': 'Average', 'total-floor-area': '78.0', 'building-reference-number': '10007286268',
'environment-impact-current': '48', 'co2-emissions-current': '4.5',
'roof-description': 'Pitched, 100 mm loft insulation', 'floor-energy-eff': 'N/A',
'number-habitable-rooms': '4', 'address2': 'Shoeburyness', 'hot-water-env-eff': 'Average',
'posttown': 'SOUTHEND-ON-SEA', 'mainheatc-energy-eff': 'Average',
'main-fuel': 'mains gas (not community)',
'lighting-env-eff': 'Very Good', 'windows-energy-eff': 'Good', 'floor-env-eff': 'N/A',
'sheating-env-eff': 'N/A', 'lighting-description': 'Low energy lighting in 78% of fixed outlets',
'roof-env-eff': 'Average', 'walls-energy-eff': 'Very Poor', 'photo-supply': '0.0',
'lighting-cost-potential': '101', 'mainheat-env-eff': 'Good', 'multi-glaze-proportion': '100',
'main-heating-controls': '', 'lodgement-datetime': '2025-03-25 16:59:15', 'flat-top-storey': '',
'current-energy-rating': 'D', 'secondheat-description': 'None', 'walls-env-eff': 'Very Poor',
'transaction-type': 'marketed sale', 'uprn': 100090702270, 'current-energy-efficiency': '56',
'energy-consumption-current': '329', 'mainheat-description': 'Boiler and radiators, mains gas',
'lighting-cost-current': '101', 'lodgement-date': '2025-03-25', 'extension-count': '1',
'mainheatc-env-eff': 'Average',
'lmk-key': 'ff00a1e150063f7bbcac1644be57fdcf05b6c9c60053f80c5d218bf2863fea93',
'wind-turbine-count': '0',
'tenure': 'Owner-occupied', 'floor-level': '', 'potential-energy-efficiency': '89',
'hot-water-energy-eff': 'Average', 'low-energy-lighting': '78',
'walls-description': 'Solid brick, as built, no insulation (assumed)',
'hotwater-description': 'From main system'
},
"full_sap_epc": {},
"old_data": []
}
prepared_epc = EPCRecord(
epc_records=epc_records,
run_mode="newdata",
cleaning_data=cleaning_data
)
assert prepared_epc.get("year_built") == 1900
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