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63 lines
1.5 KiB
Python
63 lines
1.5 KiB
Python
import pandas as pd
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from utils.s3 import read_excel_from_s3
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from utils.s3 import save_csv_to_s3
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PORTFOLIO_ID = 75
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USER_ID = 8
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def app():
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asset_list = [
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{
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"address": "19 Emily Gardens",
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"postcode": "B16 0ED",
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},
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{
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"address": "Flat 6 41 Bradford Street",
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"postcode": "B5 6HX",
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},
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{
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"address": "197 FIELD LANE",
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"postcode": "B32 4HL",
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},
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{
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"address": "FLAT 4 108 SUMMER ROAD",
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"postcode": "B23 6DY",
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},
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{
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"address": "1, St. Benedicts Road",
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"postcode": "B10 9DP",
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},
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{
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"address": "29 COOKSEY LANE",
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"postcode": "B44 9QL",
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},
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{
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"address": "40 TRITTIFORD ROAD",
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"postcode": "B13 0HG",
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}
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]
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asset_list = pd.DataFrame(asset_list)
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# Store the asset list in s3
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filename = f"{USER_ID}/{PORTFOLIO_ID}/pilot.csv"
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save_csv_to_s3(
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dataframe=asset_list,
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bucket_name="retrofit-plan-inputs-dev",
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file_name=filename
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)
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# EPC C portoflio
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body = {
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"portfolio_id": str(PORTFOLIO_ID),
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"housing_type": "Private",
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"goal": "Increase EPC",
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"goal_value": "B",
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"trigger_file_path": filename,
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"already_installed_file_path": "",
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"patches_file_path": "",
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"non_invasive_recommendations_file_path": "",
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"budget": None,
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}
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print(body)
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