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102 lines
3.7 KiB
Python
102 lines
3.7 KiB
Python
from typing import Dict, Union
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from model_data.BaseUtility import Definitions
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from model_data.epc_attributes.attribute_utils import clean_description, remove_punctuation, find_keyword
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class MainFuelAttributes(Definitions):
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FUEL_KEYWORDS = [
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'heat network',
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'mains gas',
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'electricity',
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'oil',
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'biomass',
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'biodiesel',
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# Note: there is als a category called 'bottled LPG', but only 2/50k entries had this
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'lpg',
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'waste combustion',
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'biogas',
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'wood logs',
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'dual fuel mineral wood',
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'gas',
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'anthracite',
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'smokeless coal',
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'house coal',
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'wood chips',
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# We don't treat wood chips and wood pelles as the same.
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# Wood pellets have a higher energy density than wood chips. This is due to their manufacturing process,
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# which compresses the wood and removes most of the moisture, making them more efficient as a fuel
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'wood pellets',
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]
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COMPLEX_FUEL_KEYWORDS = [
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'heat from boilers using biodiesel from any biomass source'
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]
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TARIFF_KEYWORDS = [
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'unspecified tariff'
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# We may come across more later but this is all observed for now
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]
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UNKNOWN_FUEL = "unknown"
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NO_INDIVIDUAL_HEATING_OR_COMMUNITY_NETWORK = [
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'to be used only when there is no heatinghotwater system or data is from a community network',
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'to be used only when there is no heatinghotwater system'
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]
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def __init__(self, description: str):
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self.description: str = remove_punctuation(clean_description(description.lower()))
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self.is_community = 'community' in self.description and 'not community' not in self.description
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self.is_unknown = False
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self.nodata = not description or description in self.DATA_ANOMALY_MATCHES
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if not self.nodata and not any(
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self._keyword_in_description(keywords)
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for keywords in [
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self.FUEL_KEYWORDS,
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self.NO_INDIVIDUAL_HEATING_OR_COMMUNITY_NETWORK,
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self.TARIFF_KEYWORDS,
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self.COMPLEX_FUEL_KEYWORDS
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]
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):
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raise ValueError('Invalid description')
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def _keyword_in_description(self, keywords):
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return any(keyword in self.description for keyword in keywords)
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def process(self) -> Dict[str, Union[str, bool]]:
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if self.nodata:
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result = {
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"fuel_type": self.UNKNOWN_FUEL,
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"tariff_type": None,
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"is_community": False,
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"no_individual_heating_or_community_network": False,
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"complex_fuel_type": None
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}
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return result
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result: Dict[str, Union[str, bool]] = {
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"fuel_type": find_keyword(self.description, self.FUEL_KEYWORDS),
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"tariff_type": find_keyword(self.description, self.TARIFF_KEYWORDS),
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"is_community": self.is_community,
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"no_individual_heating_or_community_network": find_keyword(
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self.description, self.NO_INDIVIDUAL_HEATING_OR_COMMUNITY_NETWORK
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),
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"complex_fuel_type": find_keyword(self.description, self.COMPLEX_FUEL_KEYWORDS),
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}
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# to make this field palettable, if no_individual_heating_or_community_network is populated, we'll
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# just set it to true
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result["no_individual_heating_or_community_network"] = bool(
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result["no_individual_heating_or_community_network"]
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)
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if not result["fuel_type"]:
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result["fuel_type"] = self.UNKNOWN_FUEL
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# We'll do checks on unknown fuel data_types to ensure we don't miss anything
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self.is_unknown = True
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return result
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