junte/Model
1
0
Fork 0
mirror of https://github.com/Hestia-Homes/Model.git synced 2026-07-12 13:29:04 +00:00
Code Issues Projects Releases Packages Wiki Activity Actions

increase timeout of engine dispatcher

Browse source
This commit is contained in:
Khalim Conn-Kowlessar 2025-12-03 22:07:52 +00:00
parent dbf75bf559
commit 0876e948c9
2 changed files with 95 additions and 94 deletions
Show stats Download patch file Download diff file Expand all files Collapse all files

187
etl/customers/peabody/Nov 2025 Consulting Project/data_prep.py
View file

@ -74,125 +74,125 @@ sustainability_data["Floor Area Band"] = sustainability_data["Total Floor Area (
# Roof insulation category # Roof insulation category
# 1) Split roof insulation into > 100mm loft and <= 100mm loft # 1) Split roof insulation into > 100mm loft and <= 100mm loft
sustainability_data["Roof Insulation Category"] = sustainability_data["Roof Insulation"].copy() sustainability_data["Roof Insulation Category"] = sustainability_data["Roof Insulation"].copy()
sustainability_data["Roof Insulation Category"] = np.where( # sustainability_data["Roof Insulation Category"] = np.where(
sustainability_data["Roof Insulation Category"].isin( # sustainability_data["Roof Insulation Category"].isin(
['mm200', 'mm300', 'mm250', 'mm150', 'mm270', 'mm400', 'mm350'], # ['mm200', 'mm300', 'mm250', 'mm150', 'mm270', 'mm400', 'mm350'],
), # ),
"LI > 100mm", # "LI > 100mm",
sustainability_data["Roof Insulation Category"], # sustainability_data["Roof Insulation Category"],
) # )
sustainability_data["Roof Insulation Category"] = np.where( # sustainability_data["Roof Insulation Category"] = np.where(
sustainability_data["Roof Insulation Category"].isin( # sustainability_data["Roof Insulation Category"].isin(
['mm100', 'mm50', 'mm75', 'mm25'], # ['mm100', 'mm50', 'mm75', 'mm25'],
), # ),
"LI <= 100mm", # "LI <= 100mm",
sustainability_data["Roof Insulation Category"], # sustainability_data["Roof Insulation Category"],
) # )
# 2) Group all of the glazed together (e.g. double glazed, secondary glazed, triple glazed) # 2) Group all of the glazed together (e.g. double glazed, secondary glazed, triple glazed)
sustainability_data["Glazing Type"] = sustainability_data["Glazing"].copy() sustainability_data["Glazing Type"] = sustainability_data["Glazing"].copy()
sustainability_data["Glazing Type"] = np.where( # sustainability_data["Glazing Type"] = np.where(
sustainability_data["Glazing Type"].isin( # sustainability_data["Glazing Type"].isin(
['Double 2002 or later', 'Double before 2002', 'Double but age unknown', 'DoubleKnownData'] # ['Double 2002 or later', 'Double before 2002', 'Double but age unknown', 'DoubleKnownData']
), # ),
"Double Glazed", # "Double Glazed",
sustainability_data["Glazing Type"], # sustainability_data["Glazing Type"],
) # )
sustainability_data["Glazing Type"] = np.where( # sustainability_data["Glazing Type"] = np.where(
sustainability_data["Glazing Type"].isin(['Triple', 'TripleKnownData']), # sustainability_data["Glazing Type"].isin(['Triple', 'TripleKnownData']),
"Triple Glazed", # "Triple Glazed",
sustainability_data["Glazing Type"], # sustainability_data["Glazing Type"],
) # )
# 3) Group up boiler efficiency A, B-D, E - G? or someting like this # 3) Group up boiler efficiency A, B-D, E - G? or someting like this
sustainability_data["Boiler Efficiency Group"] = sustainability_data["Boiler Efficiency"].copy() sustainability_data["Boiler Efficiency Group"] = sustainability_data["Boiler Efficiency"].copy()
sustainability_data["Boiler Efficiency Group"] = np.where( # sustainability_data["Boiler Efficiency Group"] = np.where(
sustainability_data["Boiler Efficiency Group"].isin(['B', 'C', 'D']), # sustainability_data["Boiler Efficiency Group"].isin(['B', 'C', 'D']),
"B-D", # "B-D",
sustainability_data["Boiler Efficiency Group"], # sustainability_data["Boiler Efficiency Group"],
) # )
sustainability_data["Boiler Efficiency Group"] = np.where( # sustainability_data["Boiler Efficiency Group"] = np.where(
sustainability_data["Boiler Efficiency Group"].isin(['E', 'F', 'G']), # sustainability_data["Boiler Efficiency Group"].isin(['E', 'F', 'G']),
"E-G", # "E-G",
sustainability_data["Boiler Efficiency Group"], # sustainability_data["Boiler Efficiency Group"],
) # )
# 4) Group up main fuel into gas, electric, oil, other? # 4) Group up main fuel into gas, electric, oil, other?
sustainability_data["Main Fuel Group"] = sustainability_data["Main Fuel"].copy() sustainability_data["Main Fuel Group"] = sustainability_data["Main Fuel"].copy()
sustainability_data["Main Fuel Group"] = np.where( # sustainability_data["Main Fuel Group"] = np.where(
sustainability_data["Main Fuel Group"].isin( # sustainability_data["Main Fuel Group"].isin(
["SmokelessCoal", "BiomassCommunity", "B30DCommunity"] # ["SmokelessCoal", "BiomassCommunity", "B30DCommunity"]
), # ),
"Other Fuel", # "Other Fuel",
sustainability_data["Main Fuel Group"], # sustainability_data["Main Fuel Group"],
) # )
# 5) Wall Construction - group up Sandstone and Granite into one category # 5) Wall Construction - group up Sandstone and Granite into one category
sustainability_data["Wall Construction"] = np.where( # sustainability_data["Wall Construction"] = np.where(
sustainability_data["Wall Construction"].isin(["Sandstone", "Granite"]), # sustainability_data["Wall Construction"].isin(["Sandstone", "Granite"]),
"Sandstone/Granite", # "Sandstone/Granite",
sustainability_data["Wall Construction"] # sustainability_data["Wall Construction"]
) # )
sustainability_data["Wall Construction"] = np.where( # sustainability_data["Wall Construction"] = np.where(
sustainability_data["Wall Construction"].isin(["Timber Frame", "System", "Solid Brick"]), # sustainability_data["Wall Construction"].isin(["Timber Frame", "System"]),
"Solid", # "Timber/System",
sustainability_data["Wall Construction"] # sustainability_data["Wall Construction"]
) # )
# 6) Reduce or remove floor construction # 6) Reduce or remove floor construction
sustainability_data["Floor Construction"] = np.where( # sustainability_data["Floor Construction"] = np.where(
sustainability_data["Floor Construction"].isin(["SuspendedTimber", "SuspendedNotTimber"]), # sustainability_data["Floor Construction"].isin(["SuspendedTimber", "SuspendedNotTimber"]),
"Suspended Floor", # "Suspended Floor",
sustainability_data["Floor Construction"] # sustainability_data["Floor Construction"]
) # )
# 7) Reduce wall insulation # 7) Reduce wall insulation
sustainability_data["Wall Insulation"] = np.where( # sustainability_data["Wall Insulation"] = np.where(
sustainability_data["Wall Insulation"].isin( # sustainability_data["Wall Insulation"].isin(
["FilledCavityPlusInternal", "FilledCavityPlusExternal", "FilledCavity", "External", "Internal"] # ["FilledCavityPlusInternal", "FilledCavityPlusExternal", "FilledCavity", "External", "Internal"]
), # ),
"Insulated", # "Insulated",
sustainability_data["Wall Insulation"] # sustainability_data["Wall Insulation"]
) # )
# 8) Fill floor insulation # 8) Fill floor insulation
sustainability_data["Floor Insulation"] = sustainability_data["Floor Insulation"].fillna("Unknown") sustainability_data["Floor Insulation"] = sustainability_data["Floor Insulation"].fillna("Unknown")
# 9) Reduce Age bands # 9) Reduce Age bands
sustainability_data["Construction Years"] = np.where( # sustainability_data["Construction Years"] = np.where(
sustainability_data["Construction Years"].isin(["2003-2006", "2007-2011", "2012 onwards"]), # sustainability_data["Construction Years"].isin(["2003-2006", "2007-2011", "2012 onwards"]),
"2003 onwards", # "2003 onwards",
sustainability_data["Construction Years"], # sustainability_data["Construction Years"],
) # )
sustainability_data["Construction Years"] = np.where( # sustainability_data["Construction Years"] = np.where(
sustainability_data["Construction Years"].isin(["Before 1900", "1900-1929"]), # sustainability_data["Construction Years"].isin(["Before 1900", "1900-1929"]),
"Before 1929", # "Before 1929",
sustainability_data["Construction Years"], # sustainability_data["Construction Years"],
) # )
sustainability_data["Construction Years"] = np.where( # sustainability_data["Construction Years"] = np.where(
sustainability_data["Construction Years"].isin(["1983-1990", "1991-1995"]), # sustainability_data["Construction Years"].isin(["1983-1990", "1991-1995"]),
"1983-1995", # "1983-1995",
sustainability_data["Construction Years"], # sustainability_data["Construction Years"],
) # )
sustainability_data["Construction Years"] = np.where( # sustainability_data["Construction Years"] = np.where(
sustainability_data["Construction Years"].isin(["1950-1966", "1967-1975", "1976-1982"]), # sustainability_data["Construction Years"].isin(["1950-1966", "1967-1975", "1976-1982"]),
"1950-1982", # "1950-1982",
sustainability_data["Construction Years"], # sustainability_data["Construction Years"],
) # )
# Roof # Roof
sustainability_data["Roof Construction"] = np.where( # sustainability_data["Roof Construction"] = np.where(
sustainability_data["Roof Construction"].isin( # sustainability_data["Roof Construction"].isin(
["PitchedNormalLoftAccess", "PitchedThatched", "PitchedNormalNoLoftAccess", "PitchedWithSlopingCeiling"] # ["PitchedNormalLoftAccess", "PitchedThatched", "PitchedNormalNoLoftAccess", "PitchedWithSlopingCeiling"]
), # ),
"Pitched Roof", # "Pitched Roof",
sustainability_data["Roof Construction"] # sustainability_data["Roof Construction"]
) # )
archetype_variables = [ archetype_variables = [
"Type", "Attachment", "Construction Years", "Wall Construction", "Wall Insulation", "Type", "Attachment", "Construction Years", "Wall Construction", "Wall Insulation",
@ -210,7 +210,7 @@ archetypes = sustainability_data[archetype_variables + ["UPRN"]].dropna().groupb
archetypes["Cumulative Count"] = archetypes["Count"].cumsum() archetypes["Cumulative Count"] = archetypes["Count"].cumsum()
archetypes["Cumulative Proportion"] = archetypes["Cumulative Count"] / archetypes["Count"].sum() archetypes["Cumulative Proportion"] = archetypes["Cumulative Count"] / archetypes["Count"].sum()
archetypes_95 = archetypes[archetypes["Cumulative Proportion"] <= 0.97] archetypes_95 = archetypes.copy()
archetypes_95["Archetypes_95_reference"] = archetypes_95.index + 1 archetypes_95["Archetypes_95_reference"] = archetypes_95.index + 1
archetypes_95["Archetypes_95_reference"] = "Archetype_Sample_" + archetypes_95["Archetypes_95_reference"].astype(str) archetypes_95["Archetypes_95_reference"] = "Archetype_Sample_" + archetypes_95["Archetypes_95_reference"].astype(str)
@ -290,6 +290,7 @@ modelling_sample["domna_full_address"] = modelling_sample.apply(lambda x: make_f
# Save this CSV as input # Save this CSV as input
modelling_sample.to_excel( modelling_sample.to_excel(
"/Users/khalimconn-kowlessar/Documents/hestia/Customers/Peabody/Nov 2025 Consulting Project/modelling_sample.xlsx", "/Users/khalimconn-kowlessar/Documents/hestia/Customers/Peabody/Nov 2025 Consulting Project/modelling_sample.xlsx",
sheet_name="Standardised Asset List"
) )
# Save the archetype definitions # Save the archetype definitions
archetypes_95.to_excel( archetypes_95.to_excel(

2
serverless.yml
View file

@ -48,7 +48,7 @@ functions:
fastapi-backend: fastapi-backend:
handler: backend.app.main.handler handler: backend.app.main.handler
timeout: 60 timeout: 600
memorySize: 512 memorySize: 512
role: FastApiLambdaRole role: FastApiLambdaRole
events: events: