mirror of
https://github.com/Hestia-Homes/Model.git
synced 2026-06-08 11:17:27 +00:00
set up test file data
This commit is contained in:
Khalim Conn-Kowlessar
parent
f061f41cfa
commit
a44912defa
1 changed files with 109 additions and 28 deletions
|
|
@ -22,49 +22,130 @@ def app():
|
|||
|
||||
# Birmingham has a Local Authority Code of E08000025
|
||||
|
||||
# ~~~~~~~~~~~~~~~~~~~~
|
||||
# First example
|
||||
# ~~~~~~~~~~~~~~~~~~~~
|
||||
# Let's take an EPC D property
|
||||
example_1_reponse = epc_client.domestic.search(
|
||||
params={
|
||||
"local-authority": "E08000025",
|
||||
"property-type": "house",
|
||||
}
|
||||
},
|
||||
size=1000
|
||||
)
|
||||
example_1_reponse = example_1_reponse["rows"]
|
||||
# Get a property with a cavity wall
|
||||
example_1_reponse_filtered = [
|
||||
x for x in example_1_reponse if
|
||||
"cavity wall, as built, no insulation (assumed)" in x["walls-description"].lower()
|
||||
]
|
||||
example_1_reponse_filtered = [
|
||||
x for x in example_1_reponse_filtered if "pitched, no insulation (assumed)" in x["roof-description"].lower()
|
||||
]
|
||||
print(example_1_reponse_filtered[0]["postcode"])
|
||||
# 21 Penshaw Grove
|
||||
print(example_1_reponse_filtered[0]["address1"])
|
||||
# B13 9NL
|
||||
print(example_1_reponse_filtered[0]["built-form"])
|
||||
# Mid-Terrace
|
||||
print(example_1_reponse_filtered[0]["current-energy-rating"])
|
||||
# 'D'
|
||||
|
||||
g_data = epc_client.domestic.search(params={"energy-band": "g"}, size=n_g)
|
||||
f_data = epc_client.domestic.search(params={"energy-band": "f"}, size=n_f)
|
||||
e_data = epc_client.domestic.search(params={"energy-band": "e"}, size=n_e)
|
||||
d_data = epc_client.domestic.search(params={"energy-band": "d"}, size=n_d)
|
||||
c_data = epc_client.domestic.search(params={"energy-band": "c"}, size=n_c)
|
||||
b_data = epc_client.domestic.search(params={"energy-band": "b"}, size=n_b)
|
||||
a_data = epc_client.domestic.search(params={"energy-band": "a"}, size=n_a)
|
||||
# ~~~~~~~~~~~~~~~~~~~~
|
||||
# Second example
|
||||
# ~~~~~~~~~~~~~~~~~~~~
|
||||
|
||||
# Combine the final data
|
||||
final_data = (
|
||||
g_data["rows"] + f_data["rows"] + e_data["rows"] + d_data["rows"] + c_data["rows"] + b_data["rows"]
|
||||
+ a_data["rows"]
|
||||
# Let's take an EPC E property
|
||||
example_2_reponse = epc_client.domestic.search(
|
||||
params={
|
||||
"local-authority": "E08000025",
|
||||
"property-type": "house",
|
||||
"energy-band": "e"
|
||||
},
|
||||
size=1000
|
||||
)
|
||||
|
||||
# TODO: We also take homes with just a specific type of wall
|
||||
|
||||
final_data = [
|
||||
x for x in final_data if ("cavity wall" in x["walls-description"].lower()) or (
|
||||
"solid brick" in x["walls-description"].lower()
|
||||
) or ("average thermal transmittance" in x["walls-description"].lower())
|
||||
example_2_reponse = example_2_reponse["rows"]
|
||||
# Get a solid wall example
|
||||
example_2_reponse_filtered = [
|
||||
x for x in example_2_reponse if
|
||||
"solid brick, as built, no insulation (assumed)" in x["walls-description"].lower()
|
||||
]
|
||||
# With some existing loft insulation
|
||||
example_2_reponse_filtered = [
|
||||
x for x in example_2_reponse_filtered if "pitched, 100 mm loft insulation" in x["roof-description"].lower()
|
||||
]
|
||||
|
||||
# TODO: For the moment, don't use park homes
|
||||
final_csv_data = pd.DataFrame(
|
||||
[{"address": x["address"], "postcode": x["postcode"], "Notes": None} for x
|
||||
in final_data if
|
||||
x["property-type"] not in ["Park home"]]
|
||||
)
|
||||
print(example_2_reponse_filtered[0]["postcode"])
|
||||
# B13 9BY
|
||||
print(example_2_reponse_filtered[0]["address1"])
|
||||
# 2 Bloomfield Road
|
||||
print(example_2_reponse_filtered[0]["built-form"])
|
||||
# Semi-Detached
|
||||
print(example_2_reponse_filtered[0]["current-energy-rating"])
|
||||
# E
|
||||
|
||||
final_csv_data = pd.concat([starting_csv, final_csv_data]).reset_index(drop=True)
|
||||
# ~~~~~~~~~~~~~~~~~~~~
|
||||
# Third example
|
||||
# ~~~~~~~~~~~~~~~~~~~~
|
||||
example_3_reponse = epc_client.domestic.search(
|
||||
params={
|
||||
"local-authority": "E08000025",
|
||||
"property-type": "house",
|
||||
"energy-band": "f"
|
||||
},
|
||||
size=1000
|
||||
)
|
||||
example_3_reponse = example_3_reponse["rows"]
|
||||
print(example_3_reponse[2]["walls-description"])
|
||||
print(example_3_reponse[2]["floor-description"])
|
||||
print(example_3_reponse[3]["roof-description"])
|
||||
print(example_3_reponse[3]["postcode"])
|
||||
# B32 3DG
|
||||
print(example_3_reponse[3]["address1"])
|
||||
# 18 Parkside
|
||||
print(example_3_reponse[3]["built-form"])
|
||||
# End-Terrace
|
||||
|
||||
# ~~~~~~~~~~~~~~~~~~~~
|
||||
# Final example
|
||||
# ~~~~~~~~~~~~~~~~~~~~
|
||||
# Let's take a flat that is a D
|
||||
example_4_reponse = epc_client.domestic.search(
|
||||
params={
|
||||
"local-authority": "E08000025",
|
||||
"property-type": "flat",
|
||||
"energy-band": "d"
|
||||
},
|
||||
size=1000
|
||||
)
|
||||
example_4_reponse = example_4_reponse["rows"]
|
||||
|
||||
example_4_reponse_filtered = [
|
||||
x for x in example_4_reponse if
|
||||
"cavity wall, as built, no insulation (assumed)" in x["walls-description"].lower()
|
||||
]
|
||||
print(example_4_reponse_filtered[0]["postcode"])
|
||||
# B14 6PU
|
||||
print(example_4_reponse_filtered[0]["address1"])
|
||||
# Flat 3
|
||||
|
||||
print(example_4_reponse_filtered[0]["floor-description"])
|
||||
print(example_4_reponse_filtered[0]["property-type"])
|
||||
# Flat
|
||||
|
||||
test_file = pd.DataFrame(
|
||||
[
|
||||
{"address": "21 Penshaw Grove", "postcode": "B13 9NL", "Notes": None},
|
||||
{"address": "2 Bloomfield Road", "postcode": "B13 9BY", "Notes": None},
|
||||
{"address": "18 Parkside", "postcode": "B32 3DG", "Notes": None},
|
||||
{"address": "Flat 3", "postcode": "B14 6PU", "Notes": None},
|
||||
]
|
||||
)
|
||||
|
||||
# Store the data in s3
|
||||
filename = f"{USER_ID}/{PORTFOLIO_ID}/test_inputs.csv"
|
||||
save_csv_to_s3(
|
||||
dataframe=final_csv_data,
|
||||
dataframe=test_file,
|
||||
bucket_name="retrofit-plan-inputs-dev",
|
||||
file_name=filename
|
||||
)
|
||||
|
|
@ -73,7 +154,7 @@ def app():
|
|||
"portfolio_id": str(PORTFOLIO_ID),
|
||||
"housing_type": "Social",
|
||||
"goal": "Increase EPC",
|
||||
"goal_value": "B",
|
||||
"goal_value": "C",
|
||||
"trigger_file_path": filename
|
||||
}
|
||||
print(body)
|
||||
|
|
|
|||
Loading…
Add table
Reference in a new issue