mirror of
https://github.com/Hestia-Homes/Model.git
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adding the summary report extraction class
This commit is contained in:
Khalim Conn-Kowlessar
parent
63521dd1e3
commit
bcbb43ed8f
4 changed files with 315 additions and 62 deletions
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@ -1,6 +1,10 @@
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import os
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import pandas as pd
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import utils.file_data_extraction as file_extraction_tools
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from utils.fullSapParser import FullSapParser
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from utils.OsmosisCondtionReportParser import OsmosisConditionReportParser
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output_template = {
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"Property Address": None,
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@ -9,6 +13,7 @@ output_template = {
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"City/County": None,
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"District/Town": None,
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"Funding Stream": None,
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# "Risk Path": None,
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"Local Authority": None,
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"Trustmark Lodgement ID": None,
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"Certificate Number": None,
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@ -18,11 +23,12 @@ output_template = {
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"Doors UMR": None,
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"Measure Lodgement Date": None,
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"Full Lodgement Date": None,
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"Name": None,
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"Phone": None,
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"Email": None,
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"Secondary Contact Name": None,
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"Secondary Contact Phone": None,
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"Owner - Name": None,
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"Owner - Phone": None,
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"Owner - Email": None,
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"Tenant - Name": None,
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"Tenant - Phone": None,
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"R. Assessor - Name": None,
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"Trustmark Licence Number": None,
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"Retrofit Assessment Date": None,
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"Company Name": None,
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@ -30,7 +36,7 @@ output_template = {
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"Property Type": None,
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"Property Detachment": None,
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"No. of Bedrooms": None,
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"Property Age": None,
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"Property age": None,
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"SAP Rating Pre (from IMA)": None,
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"Pre Heat Transfer": None,
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"Pre Total Floor Area": None,
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@ -44,22 +50,6 @@ output_template = {
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"Number of Eligible Measures Installed": None,
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"Total Cost of Works": None,
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"Annual Fuel Saving (MTP)": None,
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"Work Type ID": None,
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"Measure Category": None,
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"Installer": None,
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"Operative Name": None,
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"Operative Certif. Reference": None,
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"Manufacturer": None,
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"Model": None,
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"Financial Protection Body (IBG)": None,
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"Policy Start Date": None,
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"IBG Policy Reference": None,
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"Warranty Duration": None,
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"Total Invoiced (Including VAT)": None,
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"Installation Date": None,
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"Handover Date": None,
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"Percentage": None,
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"Reference Number": None,
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}
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@ -100,14 +90,19 @@ def handler():
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extractors = {
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"elmhurst epr": file_extraction_tools.ElmhurstEprExtractor,
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"elmhurst summary report": None,
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"osmosis condition report": None,
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"elmhurst summary report": file_extraction_tools.ElmhurstSummaryReportExtractor,
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"osmosis condition report": OsmosisConditionReportParser,
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"elmhurst evidence report": None,
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"full sap xml": FullSapParser,
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}
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extracted = []
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for property_folder in folders:
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coordinator_folder = os.path.join(source_data_path, property_folder, "2. RA Coordinator Info")
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# Check if this folder exists
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if not os.path.exists(coordinator_folder):
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coordinator_folder = os.path.join(source_data_path, property_folder, "1. RA Coordinator Info")
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# Get the contents of the folder
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coordinator_folder_contents = [
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@ -123,10 +118,10 @@ def handler():
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if report_type is None:
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raise ValueError(f"Unknown report type for {filename}")
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file_extractor = extractors.get(report_type)
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file_extractor = extractors[report_type]
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if file_extractor is None:
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continue
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extracted_contents[report_type] = file_extractor(filepath).extract()
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if file_extraction_tools.is_xml(filepath):
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@ -141,24 +136,27 @@ def handler():
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output_row_data = output_template.copy()
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# dict_keys([, , , 'City/County', 'District/Town',
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# 'Local Authority',
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# 'Trustmark Lodgement ID',
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# 'Certificate Number', 'EWI UMR', 'Loft UMR', 'Windows UMR',
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# 'Doors UMR', 'Measure Lodgement Date', 'Full Lodgement Date',
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# 'Name', 'Phone', 'Email', (owner)
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# 'Secondary Contact
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# Name', 'Secondary Contact Phone', 'Trustmark Licence Number', 'Retrofit Assessment Date', 'Company Name',
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# 'Retrofit Designer Name', , 'No. of Bedrooms',
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# ,
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# 'Pre Air Tightness', 'SAP Rating Post (from EPC)', 'Post Heat Transfer', 'Post Total Floor Area',
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# 'Post Heat Demand', 'Post Air Tightness', 'Number of Eligible Measures Installed', 'Total Cost of Works',
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# 'Annual Fuel Saving (MTP)', 'Work Type ID', 'Measure Category', 'Installer', 'Operative Name', 'Operative
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# Certif. Reference', 'Manufacturer', 'Model', 'Financial Protection Body (IBG)', 'Policy Start Date',
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# 'IBG Policy Reference', 'Warranty Duration', 'Total Invoiced (Including VAT)', 'Installation Date',
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# 'Handover Date', 'Percentage', 'Reference Number'])
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# dict_keys([ 'City/County', 'District/Town',
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# 'Local Authority', 'Trustmark Lodgement ID', 'Certificate Number', 'EWI UMR', 'Loft UMR', 'Windows UMR',
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# 'Doors UMR', 'Measure Lodgement Date', 'Full Lodgement Date', 'Owner - Name', 'Owner - Phone',
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# 'Owner - Email', 'Tenant - Name', 'Tenant - Phone',
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# 'Trustmark Licence Number',
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# 'Company Name', 'Retrofit Designer Name',
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# Pre Air Tightness', 'SAP Rating Post (from EPC)', 'Post Heat
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# Transfer', 'Post Total Floor Area', 'Post Heat Demand', 'Post Air Tightness', 'Number of Eligible Measures
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# Installed', 'Total Cost of Works', 'Annual Fuel Saving (MTP)'])
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# Populate the output row data
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if extracted_contents["elmhurst epr"]:
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update_dictionary_with_check(
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output_row_data,
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{
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"Funding Stream": funding_stream,
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"Property Address": property_folder.split(")")[1].strip(),
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"Osm. ID": property_folder.split(")")[0].strip().lstrip("(").strip(),
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}
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)
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if extracted_contents.get("elmhurst epr"):
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total_floor_area = sum(
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[x["Floor Area (m2)"] for x in extracted_contents["elmhurst epr"]["Building Parts"]] +
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# Get the conservatory floor area
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@ -170,33 +168,45 @@ def handler():
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extracted_contents["elmhurst epr"]["Primary Energy Use Intensity (kWh/m2/yr)"] * total_floor_area
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)
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to_insert = {
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"Property Address": property_folder.split(")")[1].strip(),
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"Osm. ID": property_folder.split(")")[0].strip().lstrip("(").strip(),
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epr_to_insert = {
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"Postcode": extracted_contents["elmhurst epr"]["Postcode"],
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"City/County": None,
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"District/Town": None,
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"Funding Stream": funding_stream,
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"Local Authority": None,
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'Property Age': extracted_contents["elmhurst epr"]["Property Age"],
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'SAP Rating Pre (from IMA)': extracted_contents["elmhurst epr"]["Current SAP Rating"],
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'Pre Heat Transfer': pre_heat_transfer,
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'Pre Total Floor Area': total_floor_area,
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'Pre Heat Demand': pre_heat_demand,
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"R. Assessor - Name": extracted_contents["elmhurst epr"]["Assessor Name"],
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"Retrofit Assessment Date": extracted_contents["elmhurst epr"]["Assessment Date"],
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}
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update_dictionary_with_check(
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output_row_data,
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epr_to_insert
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)
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output_row_data["Property Address"] = property_folder.split(")")[1].strip()
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output_row_data["Osm. ID"] = property_folder.split(")")[0].strip().lstrip("(").strip()
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output_row_data["Postcode"] = extracted_contents["elmhurst epr"]["Postcode"]
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output_row_data["City/County"] = ()
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output_row_data["Batch"] = ()
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output_row_data["Funding Stream"] = funding_stream
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output_row_data["Risk Path"] = ()
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if extracted_contents["full sap xml"]:
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to_insert = {
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if extracted_contents.get("full sap xml"):
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xml_to_insert = {
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"Property Type": extracted_contents["full sap xml"]["Property Type"],
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"Property Detachment": extracted_contents["full sap xml"]["Built Form"],
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"Property Age": extracted_contents["full sap xml"]["Age Band"],
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"Property age": extracted_contents["full sap xml"]["Age Band"],
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}
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update_dictionary_with_check(
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output_row_data,
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xml_to_insert
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)
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if extracted_contents.get("osmosis condition report"):
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cr_to_insert = {
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"No. of Bedrooms": extracted_contents["osmosis condition report"]["No. of Bedrooms"],
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# "Risk Path": extracted_contents["osmosis condition report"]["Risk Assessment Pathway"],
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}
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update_dictionary_with_check(
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output_row_data,
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cr_to_insert
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)
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extracted.append(output_row_data)
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extracted_df = pd.DataFrame(extracted)
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@ -5,4 +5,6 @@ openpyxl
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boto3
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usaddress==0.5.11
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fuzzywuzzy==0.18.0
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python-dotenv
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python-dotenv
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python-docx
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pymupdf
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49
utils/OsmosisCondtionReportParser.py
Normal file
49
utils/OsmosisCondtionReportParser.py
Normal file
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@ -0,0 +1,49 @@
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import re
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import boto3
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import PyPDF2
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import fitz
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class OsmosisConditionReportParser:
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def __init__(self, filekey, bucket_name=None):
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self.s3_client = boto3.client('s3')
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self.bucket_name = bucket_name
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self.filekey = filekey
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self.pdf_text = None
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self._read_file()
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def _read_file(self):
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"""
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Reads the XML file either locally or from S3 and parses it using minidom.
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Raises:
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ValueError: If the file cannot be found, read, or parsed.
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"""
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chunk_size = 10
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try:
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if self.bucket_name:
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# Read from S3
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raise NotImplementedError("Imeplement me")
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else:
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with fitz.open(self.filekey) as pdf:
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text = ""
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for page in pdf:
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text += page.get_text()
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# Parse the XML content using minidom
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self.pdf_text = text
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except FileNotFoundError:
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raise ValueError(f"Local file not found: {self.filekey}")
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except Exception as e:
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raise ValueError(f"An error occurred while reading or parsing the XML: {e}")
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def extract(self):
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return {
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"No. of Bedrooms": int(re.search(r"No\. of Bedrooms \(Total\)\s*(\d+)", self.pdf_text).group(1)),
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"Risk Assessment Pathway": re.search(r"Risk\s*Assessment\s*Pathway\s*([A-Z])", self.pdf_text).group(1)
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}
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@ -100,8 +100,8 @@ def is_xml(filename):
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class ElmhurstEprExtractor:
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"""
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A utility class for extracting specific data from Elmhurst Energy Performance Reports (EPR).
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"""
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A utility class for extracting specific data from Elmhurst Energy Performance Reports (EPR).
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"""
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def __init__(self, file_path):
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self.file_path = file_path
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@ -388,6 +388,7 @@ class ElmhurstEprExtractor:
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text = "".join(page.extract_text() for page in reader.pages)
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data["Assessor Name"] = re.search(r"Created by:\s*(.*?)\n", text).group(1).strip()
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data["Assessment Date"] = re.search(r"\nAssessment Date\s*(.*?)\n", text).group(1).strip()
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# Extracting individual components
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address_match = re.search(r"ENERGY REPORT\nDwelling Address\s*(.*?)\s*\nReference", text, re.DOTALL)
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@ -467,3 +468,194 @@ class ElmhurstEprExtractor:
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data["Water Heating Code"] = water_heating_code_match.group(1).strip()
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return data
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class ElmhurstSummaryReportExtractor:
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"""
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A utility class for extracting specific data from Elmhurst Energy Performance Reports (EPR).
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"""
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def __init__(self, file_path):
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self.file_path = file_path
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def extract(self):
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"""
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Extracts specific data from the provided PDF file.
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Data includes:
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- Current SAP rating
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- Fuel Bill
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- Address
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"""
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# Expected keys:
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# dict_keys(['Total Number of Doors', 'Number of Insulated
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# Doors', 'Number of Light Fittings', 'Number of LEL Fittings', 'Number of fittings needing LEL', 'Windows',
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# 'Primary Heating', 'Secondary Heating', 'Building Parts', 'Roof Details', 'Wall Details', 'Conservatory',
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# 'Water Heating Code'])
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data = {
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}
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with (open(self.file_path, "rb") as file):
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reader = PyPDF2.PdfReader(file)
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text = ""
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for page in reader.pages:
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text += page.extract_text()
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# Match and extract
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name_match = re.search(r"Name:\s*([A-Za-z\s]+)\s*Title:\s*([A-Za-z\.]+)", text)
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if not name_match:
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raise ValueError("Couldn't extract surveyor name")
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data["Assessor Name"] = name_match.group(2).strip() + " " + name_match.group(1).strip()
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data["Assessment Date"] = re.search(r"Inspection Date:\s*(.*?)\n", text).group(1).strip()
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# Address and postcode
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postcode = re.search(r"Postcode:\s*(.*?)\nRegion:", text)
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region = re.search(r"Region:\s*(.*?)\nHouse Name:", text)
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house_name = re.search(r"House Name:\s*(.*?)\nHouse No:", text)
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house_no = re.search(r"House No:\s*(.*?)\nStreet:", text)
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street = re.search(r"Street:\s*(.*?)\nLocality:", text)
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locality = re.search(r"Locality:\s*(.*?)\nTown:", text)
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town = re.search(r"Town:\s*(.*?)\nCounty:", text)
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county = re.search(r"County:\s*(.*?)\nProperty Tenure:", text)
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# Clean extracted values and remove any prefixes
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address_parts = [
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house_no.group(1).strip() if house_no else "",
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house_name.group(1).strip() if house_name else "",
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street.group(1).strip() if street else "",
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locality.group(1).strip() if locality else "",
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town.group(1).strip() if town else "",
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county.group(1).strip() if county else "",
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region.group(1).strip() if region else "",
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postcode.group(1).strip() if postcode else ""
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]
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# Join non-empty parts with a comma
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data["Address"] = ", ".join([part for part in address_parts if part])
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data["Postcode"] = postcode.group(1).strip()
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# Extract Current SAP rating
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sap_match = re.search(r"Current SAP rating:\s*([A-Z] \d+)", text)
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if not sap_match:
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raise ValueError("Could not extract SAP rating")
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data["Current SAP Rating"] = sap_match.group(1).split(" ")[1]
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# We don't have primary energy in the summary report
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data['Primary Energy Use Intensity (kWh/m2/yr)'] = None
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# Number of storeys
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storeys_match = re.search(r"Number of Storeys:\s*(\d+)", text)
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if not storeys_match:
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raise ValueError("Could not extract number of storeys")
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data["Number of Storeys"] = int(storeys_match.group(1))
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# Extract Fuel Bill
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fuel_bill_match = re.search(r"Fuel Bill:\s*£(\d+)", text)
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if not fuel_bill_match:
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raise ValueError("Could not extract fuel bill")
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data["Fuel Bill"] = f"£{fuel_bill_match.group(1)}"
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# Extract Total Number of Doors
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total_doors_match = re.search(r"Total Number of Doors\s*(\d+)", text)
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if not total_doors_match:
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raise ValueError("Could not extract total number of doors")
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data["Total Number of Doors"] = int(total_doors_match.group(1))
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# Extract Number of Insulated Doors
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insulated_doors_match = re.search(r"Number of Insulated Doors\s*(\d+)", text)
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if not insulated_doors_match:
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raise ValueError("Could not extract number of insulated doors")
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data["Number of Insulated Doors"] = int(insulated_doors_match.group(1))
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windows_section = re.search(r"Windows\s*(.*?)\s*Draught Proofing", text, re.DOTALL)
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windows_text = windows_section.group(1)
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window_data = extract_window_age_description(windows_text)
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data.update(window_data)
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# Extract heating system
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# Extract Primary Heating Data
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# Extract Primary Heating Section
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primary_heating_section1 = re.search(r"Main\s*Heating1\s*(.*?)\s*Main\s*Heating2", text, re.DOTALL)
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primary_heating_section2 = re.search(r"Main\s*Heating1\s*(.*?)\s*Water\s*Heating", text, re.DOTALL)
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primary_heating_section = primary_heating_section1 if primary_heating_section1 else primary_heating_section2
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primary_text = primary_heating_section.group(1)
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data["Existing Primary Heating System"] = re.search(r"Main Heating Code\s*(.*?)\n", primary_text).group(
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1).strip()
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data["Existing Primary Heating PCDF Reference"] = re.search(
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r"PCDF boiler Reference\s*(\d+)", primary_text
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).group(1)
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data["Existing Primary Heating Controls"] = re.search(
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r"Main Heating Controls\s*(.*?)\n", primary_text
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).group(1).strip()
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data["Existing Primary Heating % of Heat"] = int(
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re.search(r"Percentage of Heat\s*(\d+)\s*%", primary_text).group(1)
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)
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# Extract Secondary Heating Section
|
||||
secondary_heating_section = re.search(r"Main\s*Heating2\s*(.*?)\s*Water\s*Heating", text, re.DOTALL)
|
||||
|
||||
if secondary_heating_section is None:
|
||||
data["Existing Secondary Heating System"] = ""
|
||||
data["Existing Secondary Heating PCDF Reference"] = ""
|
||||
data["Existing Secondary Heating Controls"] = ""
|
||||
data["Existing Secondary Heating % of Heat"] = 0
|
||||
|
||||
else:
|
||||
secondary_text = secondary_heating_section.group(1)
|
||||
|
||||
main_heating_code_match_secondary = re.search(
|
||||
r"Main Heating Code\s*(.*?)(?=\n|Percentage of Heat)", secondary_text
|
||||
)
|
||||
data["Existing Secondary Heating System"] = main_heating_code_match_secondary.group(1).strip()
|
||||
data["Existing Secondary Heating PCDF Reference"] = re.search(r"PCDF boiler Reference\s*(\d+)",
|
||||
secondary_text).group(1)
|
||||
second_heating_controls_match = re.search(r"Main Heating Controls\s*(.*?)\n", secondary_text)
|
||||
data["Existing Secondary Heating Controls"] = (
|
||||
second_heating_controls_match.group(1).strip() if second_heating_controls_match else ""
|
||||
)
|
||||
data["Existing Secondary Heating % of Heat"] = int(
|
||||
re.search(r"Percentage of Heat\s*(\d+)\s*%", secondary_text).group(1)
|
||||
)
|
||||
|
||||
# Extract Secondary Heating and Water Heating Codes
|
||||
secondary_heating_code_match = re.search(r"Secondary Heating Code\s*(.*?)\n", text)
|
||||
water_heating_code_match = re.search(r"Water Heating Code\s*(.*?)\n", text)
|
||||
|
||||
if data["Existing Secondary Heating System"] == "":
|
||||
data["Secondary Heating Code"] = ""
|
||||
else:
|
||||
data["Secondary Heating Code"] = secondary_heating_code_match.group(
|
||||
1).strip() if secondary_heating_code_match else ""
|
||||
|
||||
data["Water Heating Code"] = water_heating_code_match.group(1).strip()
|
||||
|
||||
dimensions = extract_building_parts_summary(text)
|
||||
data.update(dimensions)
|
||||
|
||||
data["Number of Light Fittings"] = int(re.search(r"Total number of light fittings\s*(\d+)", text).group(1))
|
||||
data["Number of LEL Fittings"] = int(re.search(r"Total number of L.E.L. fittings\s*(\d+)", text).group(1))
|
||||
data["Number of fittings needing LEL"] = data["Number of Light Fittings"] - data["Number of LEL Fittings"]
|
||||
|
||||
extracted_roof_data = extract_roof_details_summary(text)
|
||||
main_roof_data = [roof for roof in extracted_roof_data if "Main" in roof["Building Part"]][0]
|
||||
data["Main Roof Type"] = main_roof_data["Roof Type"]
|
||||
data["Main Roof Insulation"] = main_roof_data["Roof Insulation"]
|
||||
data["Main Roof Insulation Thickness"] = main_roof_data["Roof Insulation Thickness"]
|
||||
|
||||
walls_data = extract_wall_details_summary(text)
|
||||
# Get the main building wall data
|
||||
main_building_walls = [wall for wall in walls_data if "Main" in wall["Building Part"]][0]
|
||||
data["Main Wall Type"] = main_building_walls["Wall Type"]
|
||||
data["Main Wall Insulation"] = main_building_walls["Wall Insulation"]
|
||||
data["Main Wall Dry-lining"] = main_building_walls["Wall Dry-lining"]
|
||||
data["Main Wall Thickness"] = main_building_walls["Wall Thickness (mm)"]
|
||||
data["Main Building Alternative Wall Type"] = main_building_walls["Alternative Wall Type"]
|
||||
data["Main Building Alternative Wall Insulation"] = main_building_walls["Alternative Wall Insulation"]
|
||||
data["Main Building Alternative Wall Dry-lining"] = main_building_walls["Alternative Wall Dry-lining"]
|
||||
data["Main Building Alternative Wall Thickness"] = main_building_walls["Alternative Wall Thickness (mm)"]
|
||||
|
||||
return data
|
||||
|
|
|
|||
Loading…
Add table
Reference in a new issue