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handling coal community heating fuel
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00694a200d
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3 changed files with 11 additions and 4 deletions
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@ -22,7 +22,6 @@ from recommendations.recommendation_utils import (
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)
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)
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from backend.ml_models.AnnualBillSavings import AnnualBillSavings
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from backend.ml_models.AnnualBillSavings import AnnualBillSavings
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from backend.app.utils import sap_to_epc
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from backend.app.utils import sap_to_epc
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from backend.Funding import Funding
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import backend.app.assumptions as assumptions
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import backend.app.assumptions as assumptions
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ENVIRONMENT = os.environ.get("ENVIRONMENT", "dev")
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ENVIRONMENT = os.environ.get("ENVIRONMENT", "dev")
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@ -340,7 +339,6 @@ class Property:
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recommendation_record=recommendation_record,
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recommendation_record=recommendation_record,
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recommendations=property_representative_recommendations,
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recommendations=property_representative_recommendations,
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primary_recommendation_id=self.id,
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primary_recommendation_id=self.id,
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non_invasive_recommendations=self.non_invasive_recommendations,
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)
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)
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return scoring_dict
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return scoring_dict
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@ -1243,7 +1241,8 @@ class Property:
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"heat network": "Natural Gas (Community Scheme)",
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"heat network": "Natural Gas (Community Scheme)",
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"lpg": 'LPG',
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"lpg": 'LPG',
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"biodiesel": "Smokeless Fuel",
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"biodiesel": "Smokeless Fuel",
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"b30d": "B30K Biofuel"
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"b30d": "B30K Biofuel",
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"coal": "Coal",
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}
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}
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self.heating_energy_source = list({
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self.heating_energy_source = list({
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@ -15,7 +15,6 @@ from sqlmodel import Session
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from etl.epc.Record import EPCRecord
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from etl.epc.Record import EPCRecord
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from sqlalchemy.exc import IntegrityError, OperationalError
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from sqlalchemy.exc import IntegrityError, OperationalError
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from sqlalchemy.orm import sessionmaker
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from starlette.responses import Response
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from starlette.responses import Response
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from backend.app.BatterySapScorer import BatterySAPScorer
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from backend.app.BatterySapScorer import BatterySAPScorer
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@ -0,0 +1,9 @@
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"""
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For the Peabody project, there were a number of subtasks that failed due to issues, with the most
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prominent being errors with the property address and ID data.
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This script will fetch those failed subtasks, get the associated properties and delete the properties
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from the database so that the subtasks can be restarted cleanly.
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Additionally, we wil find the problematic records and remove them
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"""
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