added new scripts

etl/jjc_invoice.py

@@ -0,0 +1,55 @@
+from etl.scraper.scraper import SharePointScraper, SharePointInstaller, WEEK_COMMENCING
+from pprint import pformat
+from etl.pdfReader.pdfReaderToText import pdfReaderToText
+from etl.surveyedData.surveryedData import surveyedDataProcessor
+import pandas as pd
+
+
+
+
+def main():
+    data = {
+         "Address": [],
+         "Surveyor's Name": [],
+         "Type of Work": [],
+         "Price": []
+    }
+
+    south_coast_scraper = SharePointScraper(SharePointInstaller.SOUTH_COAST_INSULATION)
+    file_paths = south_coast_scraper.download_file_for_each_address()
+    list_of_surveys = []
+    for eachAddress in file_paths:
+            for address, files in eachAddress.items():
+                list_of_surveys.append(surveyedDataProcessor(address, files))
+
+
+    for survey in list_of_surveys:
+        if survey.pre_site_note:
+            if survey.pre_site_note.property_description.main_property.wall.insulation.lower() == 'as built' \
+                and survey.pre_site_note.property_description.main_property.wall.construction.lower() == "cavity wall":
+                if survey.csr:
+                    data["Price"].append(500)
+                    data["Type of Work"].append("REMIDIAL CWI ONLY")
+                else:
+                    data["Price"].append(1000)
+                    data["Type of Work"].append("CAVITY ONLY")
+            else:
+                # Solar
+                data["Price"].append(1608)
+                data["Type of Work"].append("SOLAR")
+
+            data["Address"].append(survey.address)
+            data["Surveyor's Name"].append(survey.pre_site_note.assessor_information.name)
+
+    df = pd.DataFrame(data)
+
+    # Save to an Excel file
+    df.to_excel("survey_data.xlsx", index=False)
+
+    print(f"WEEK COMMENCING {WEEK_COMMENCING}")
+    print("Excel file 'survey_data.xlsx' created successfully!")
+    print(pformat(data))
+
+
+if __name__ == "__main__":
+    main()

etl/sgec_invoice.py

@@ -0,0 +1,55 @@
+from etl.scraper.scraper import SharePointScraper, SharePointInstaller, WEEK_COMMENCING
+from pprint import pformat
+from etl.pdfReader.pdfReaderToText import pdfReaderToText
+from etl.surveyedData.surveryedData import surveyedDataProcessor
+import pandas as pd
+
+
+
+
+def main():
+    data = {
+         "Address": [],
+         "Surveyor's Name": [],
+         "Type of Work": [],
+         "Price": []
+    }
+
+    south_coast_scraper = SharePointScraper(SharePointInstaller.SOUTH_COAST_INSULATION)
+    file_paths = south_coast_scraper.download_file_for_each_address()
+    list_of_surveys = []
+    for eachAddress in file_paths:
+            for address, files in eachAddress.items():
+                list_of_surveys.append(surveyedDataProcessor(address, files))
+
+
+    for survey in list_of_surveys:
+        if survey.pre_site_note:
+            if survey.pre_site_note.property_description.main_property.wall.insulation.lower() == 'as built' \
+                and survey.pre_site_note.property_description.main_property.wall.construction.lower() == "cavity wall":
+                if survey.csr:
+                    data["Price"].append(500)
+                    data["Type of Work"].append("REMIDIAL CWI ONLY")
+                else:
+                    data["Price"].append(1000)
+                    data["Type of Work"].append("CAVITY ONLY")
+            else:
+                # Solar
+                data["Price"].append(1608)
+                data["Type of Work"].append("SOLAR")
+
+            data["Address"].append(survey.address)
+            data["Surveyor's Name"].append(survey.pre_site_note.assessor_information.name)
+
+    df = pd.DataFrame(data)
+
+    # Save to an Excel file
+    df.to_excel("survey_data.xlsx", index=False)
+
+    print(f"WEEK COMMENCING {WEEK_COMMENCING}")
+    print("Excel file 'survey_data.xlsx' created successfully!")
+    print(pformat(data))
+
+
+if __name__ == "__main__":
+    main()