create Mh.Ex model and MH & DC model and upload commit

app/services/file_service.py

@@ -1,11 +1,12 @@
-# app/services/file_service.py
-
 import os
 import pandas as pd
 from werkzeug.utils import secure_filename
 from app.config import Config
 from app import db
 from app.models.trench_excavation_model import TrenchExcavation
+from app.models.manhole_excavation_model import ManholeExcavation
+from app.models.manhole_domestic_chamber_model import ManholeDomesticChamber
+
 from app.utils.file_utils import ensure_upload_folder
 
 
@@ -41,8 +42,18 @@ class FileService:
             print(df.head())
             print("=============================\n")
 
+            # Trench Excavation save 
             if file_type == "trench_excavation":
                 return self.process_trench_excavation(df, subcontractor_id)
+            
+            # Manhole Excavation save
+            if file_type == "manhole_excavation":
+                return self.process_manhole_excavation(df, subcontractor_id)
+            
+            # Manhole and Domestic Chamber Construction save
+            if file_type == "manhole_domestic_chamber":
+                return self.process_manhole_excavation(df, subcontractor_id)
+
 
             return True, "File uploaded successfully."
 
@@ -51,7 +62,7 @@ class FileService:
 
 
 
-    #   CLEAN & SAVE TRENCH EXCAVATION DATA
+    #   Trench Excavation save method (TrenchExcavation model)
     def process_trench_excavation(self, df, subcontractor_id):
 
         # Clean column names (strip whitespace)
@@ -101,3 +112,114 @@ class FileService:
         except Exception as e:
             db.session.rollback()
             return False, f"Trench Excavation Save Failed: {e}"
+        
+
+    #   Manhole Excavation save method (ManholeExcavation model)
+    def process_manhole_excavation(self, df, subcontractor_id):
+
+        # Clean column names (strip whitespace)
+        df.columns = [str(c).strip() for c in df.columns]
+
+        # If the sheet has merged cells -> forward fill Location
+        if "Location" in df.columns:
+            df["Location"] = df["Location"].ffill()
+
+        # REMOVE empty rows
+        df = df.dropna(how="all")
+
+        # Identify missing location rows before insert
+        missing_loc = df[df["Location"].isna() | (df["Location"].astype(str).str.strip() == "")]
+        if not missing_loc.empty:
+            return False, f"Error: Some rows have empty Location. Rows: {missing_loc.index.tolist()}"
+
+        saved_count = 0
+
+        try:
+            for index, row in df.iterrows():
+
+                record_data = {}
+
+                # Insert only fields that exist in model
+                for col in df.columns:
+                    if hasattr(ManholeExcavation, col):
+                        value = row[col]
+
+                        # Normalize empty values
+                        if pd.isna(value) or str(value).strip() in ["", "-", "—", "nan", "NaN"]:
+                            value = None
+
+                        record_data[col] = value
+
+                record = ManholeExcavation(
+                    subcontractor_id=subcontractor_id,
+                    **record_data
+                )
+
+                db.session.add(record)
+                saved_count += 1
+
+            db.session.commit()
+            return True, f"Manhole Excavation data saved successfully. Total rows: {saved_count}"
+
+        except Exception as e:
+            db.session.rollback()
+            return False, f"Manhole Excavation Save Failed: {e}"
+
+
+    #   Manhole and Domestic Chamber Construction save method (ManholeDomesticChamber  model)
+    def process_manhole_excavation(self, df, subcontractor_id):
+
+        # Clean column names (strip whitespace)
+        df.columns = [str(c).strip() for c in df.columns]
+
+        # If the sheet has merged cells -> forward fill Location
+        if "Location" in df.columns:
+            df["Location"] = df["Location"].ffill()
+
+        # REMOVE empty rows
+        df = df.dropna(how="all")
+
+        # Identify missing location rows before insert
+        missing_loc = df[df["Location"].isna() | (df["Location"].astype(str).str.strip() == "")]
+        if not missing_loc.empty:
+            return False, f"Error: Some rows have empty Location. Rows: {missing_loc.index.tolist()}"
+
+        saved_count = 0
+
+        try:
+            for index, row in df.iterrows():
+
+                record_data = {}
+
+                # Insert only fields that exist in model
+                for col in df.columns:
+                    if hasattr(ManholeDomesticChamber, col):
+                        value = row[col]
+
+                        # Normalize empty values
+                        if pd.isna(value) or str(value).strip() in ["", "-", "—", "nan", "NaN"]:
+                            value = None
+
+                        record_data[col] = value
+
+                record = ManholeDomesticChamber(
+                    subcontractor_id=subcontractor_id,
+                    **record_data
+                )
+
+                db.session.add(record)
+                saved_count += 1
+
+            db.session.commit()
+            return True, f"Manhole Domestic Chamber Construction data saved successfully. Total rows: {saved_count}"
+
+        except Exception as e:
+            db.session.rollback()
+            return False, f"Manhole Domestic Chamber Construction Save Failed: {e}"
+        
+
+
+
+
+
+