upload client side MH and MH DC model commit

app/models/mh_dc_client_model.py

@@ -13,29 +13,25 @@ class ManholeDomesticChamberClient(db.Model):
     # Basic Fields
     Location = db.Column(db.String(255))
     Node_No = db.Column(db.String(100))
+    MH_TOP_LEVEL = db.Column(db.Float)
+    MH_IL_LEVEL = db.Column(db.Float)
     Depth_of_MH = db.Column(db.Float)
    
-    # Excavation categories 
-    d_0_to_0_75 = db.Column(db.Float)
-    d_1_06_to_1_65 = db.Column(db.Float)
-    d_1_06_to_1_65 = db.Column(db.Float)
-    d_1_66_to_2_15 = db.Column(db.Float)
-    d_2_16_to_2_65 = db.Column(db.Float)
-    d_2_66_to_3_15 = db.Column(db.Float)
-    d_3_16_to_3_65= db.Column(db.Float)
-    d_3_66_to_4_15 = db.Column(db.Float)
-    d_4_16_to_4_65 = db.Column(db.Float)
-    d_4_66_to_5_15 = db.Column(db.Float)
-    d_5_16_to_5_65 = db.Column(db.Float)
  
-    d_5_66_to_6_15 = db.Column(db.Float)
+    # Excavation categories 
-    d_6_16_to_6_65 = db.Column(db.Float)
+    d_0_to_1_5 = db.Column(db.Float)
-    d_6_66_to_7_15 = db.Column(db.Float)
+    d_1_5_to_2_0 = db.Column(db.Float)
-    d_7_16_to_7_65 = db.Column(db.Float)
+    d_2_0_to_2_5 = db.Column(db.Float)
-    d_7_66_to_8_15 = db.Column(db.Float)
+    d_2_5_to_3_0 = db.Column(db.Float)
-    d_8_16_to_8_65 = db.Column(db.Float)
+
-    d_8_66_to_9_15 = db.Column(db.Float)
+    d_3_0_to_3_5 = db.Column(db.Float)
-    d_9_16_to_9_65 = db.Column(db.Float)
+    d_3_5_to_4_0 = db.Column(db.Float)
+    d_4_0_to_4_5= db.Column(db.Float)
+    d_4_5_to_5_0 = db.Column(db.Float)
+
+    d_5_0_to_5_5 = db.Column(db.Float)
+    d_5_5_to_6_0 = db.Column(db.Float)
+    d_6_0_to_6_5 = db.Column(db.Float)
 
     Domestic_Chambers = db.Column(db.Float)
 

app/models/mh_ex_client_model.py

@@ -14,25 +14,32 @@ class ManholeExcavationClient(db.Model):
     Location = db.Column(db.String(255))
     MH_NO = db.Column(db.String(100))
     GL_m = db.Column(db.Float)
-
+    MH_Invert_Level = db.Column(db.Float)
-
+    MH_Top_Level = db.Column(db.Float)
-   
+    Ex_Level = db.Column(db.Float)
-    Upto_IL_Depth = db.Column(db.Float)
     Cutting_Depth = db.Column(db.Float)
+    MH_Depth = db.Column(db.Float)
     ID_of_MH_m = db.Column(db.Float)
-    Ex_Dia_of_Manhole = db.Column(db.Float)
+
+    Dia_of_MH_Cutting = db.Column(db.Float)
     Area_of_Manhole = db.Column(db.Float)
    
     # Excavation categories
+    Marshi_Muddy_Slushy_0_to_1_5 = db.Column(db.Float)
+    Marshi_Muddy_Slushy_1_5_to_3_0 = db.Column(db.Float)
+    Marshi_Muddy_Slushy_3_0_to_4_5 = db.Column(db.Float)
+
     Soft_Murum_0_to_1_5 = db.Column(db.Float)
     Soft_Murum_1_5_to_3_0 = db.Column(db.Float)
     Soft_Murum_3_0_to_4_5 = db.Column(db.Float)
 
     Hard_Murum_0_to_1_5 = db.Column(db.Float)
     Hard_Murum_1_5_to_3_0 = db.Column(db.Float)
+    Hard_Murum_3_0_to_4_5 = db.Column(db.Float)
 
     Soft_Rock_0_to_1_5 = db.Column(db.Float)
     Soft_Rock_1_5_to_3_0 = db.Column(db.Float)
+    Soft_Murum_3_0_to_4_5 = db.Column(db.Float)
 
     Hard_Rock_0_to_1_5 = db.Column(db.Float)
     Hard_Rock_1_5_to_3_0 = db.Column(db.Float)
@@ -41,18 +48,24 @@ class ManholeExcavationClient(db.Model):
     Hard_Rock_6_0_to_7_5 = db.Column(db.Float)
 
     # Totals
+    Marshi_Muddy_Slushy_0_to_1_5_total = db.Column(db.Float)
+    Marshi_Muddy_Slushy_1_5_to_3_0_total = db.Column(db.Float)
+    Marshi_Muddy_Slushy_3_0_to_4_5_total = db.Column(db.Float)
+
     Soft_Murum_0_to_1_5_total = db.Column(db.Float)
     Soft_Murum_1_5_to_3_0_total = db.Column(db.Float)
     Soft_Murum_3_0_to_4_5_total = db.Column(db.Float)
 
     Hard_Murum_0_to_1_5_total = db.Column(db.Float)
-    Hard_Murum_1_5_and_above_total = db.Column(db.Float)
+    Hard_Murum_1_5_to_3_0_total = db.Column(db.Float)
+    Hard_Murum_3_0_to_4_5_total = db.Column(db.Float)
 
     Soft_Rock_0_to_1_5_total = db.Column(db.Float)
-    Soft_Rock_1_5_and_above_total = db.Column(db.Float)
+    Soft_Rock_1_5_to_3_0_total = db.Column(db.Float)
+    Soft_Rock_3_0_to_4_5_total = db.Column(db.Float)
 
     Hard_Rock_0_to_1_5_total = db.Column(db.Float)
-    Hard_Rock_1_5_and_above_total = db.Column(db.Float)
+    Hard_Rock_1_5_to_3_0_total = db.Column(db.Float)
     Hard_Rock_3_0_to_4_5_total = db.Column(db.Float)
     Hard_Rock_4_5_to_6_0_total = db.Column(db.Float)
     Hard_Rock_6_0_to_7_5_total = db.Column(db.Float)

app/routes/generate_comparison_report.py

@@ -1,15 +1,18 @@
 from flask import Blueprint, render_template, request, send_file, flash
-from app.models.subcontractor_model import Subcontractor
 
+from app.models.subcontractor_model import Subcontractor
 from app.models.trench_excavation_model import TrenchExcavation
 from app.models.tr_ex_client_model import TrenchExcavationClient
+from app.models.manhole_excavation_model import ManholeExcavation
+from app.models.mh_ex_client_model import ManholeExcavationClient
+
 from app import db
 
 import pandas as pd
 import io
 
-generate_report_bp = Blueprint("generate_report", __name__, url_prefix="/report")
 
+generate_report_bp = Blueprint("generate_report", __name__, url_prefix="/report")
 
 
 @generate_report_bp.route("/comparison_report", methods=["GET", "POST"])
@@ -21,21 +24,26 @@ def comparison_report():
 
         if not subcontractor_id:
             flash("Please select a subcontractor.", "danger")
-            return render_template("generate_comparison_report.html", subcontractors=subcontractors)
+            return render_template(
+                "generate_comparison_report.html",
+                subcontractors=subcontractors
+            )
 
         subcontractor = Subcontractor.query.get_or_404(subcontractor_id)
 
-        # Fetch data
+        contractor_tr_ex = TrenchExcavation.query.filter_by(
-        contractor_rows = TrenchExcavation.query.filter_by(subcontractor_id=subcontractor_id).all()
+            subcontractor_id=subcontractor_id
-        client_rows = TrenchExcavationClient.query.filter_by(subcontractor_id=subcontractor_id).all()
+        ).all()
 
+        client_tr_ex = TrenchExcavationClient.query.filter_by(
+            subcontractor_id=subcontractor_id
+        ).all()
 
+        combined_rows_tr_ex = []
 
-        diff_rows = []
+        for row1, row2 in zip(client_tr_ex, contractor_tr_ex):
-
+            # -------- Tr.Ex CLIENT TOTAL ----------
-        for row1, row2 in zip(client_rows, contractor_rows):
+            client_total = (
-
-            total1 = (
                 (row1.Marshi_Muddy_Slushy_0_to_1_5_total or 0) +
                 (row1.Marshi_Muddy_Slushy_1_5_to_3_0_total or 0) +
                 (row1.Marshi_Muddy_Slushy_3_0_to_4_5_total or 0) +
@@ -55,7 +63,8 @@ def comparison_report():
                 (row1.Hard_Rock_6_0_to_7_5_total or 0)
             )
 
-            total2 = (
+            # -------- SUBCONTRACTOR TOTAL ----------
+            contractor_total = (
                 (row2.Soft_Murum_0_to_1_5_total or 0) +
                 (row2.Soft_Murum_1_5_to_3_0_total or 0) +
                 (row2.Soft_Murum_3_0_to_4_5_total or 0) +
@@ -69,54 +78,132 @@ def comparison_report():
                 (row2.Hard_Rock_6_0_to_7_5_total or 0)
             )
 
-            diff = total1 - total2
+            diff = client_total - contractor_total
 
-            # ---- store for excel ----
+            # -------- COMBINED ROW ----------
-            diff_rows.append({
+            row_data = {
                 "Location": row1.Location,
-                "Node No": row1.MH_NO,
+                "MH No": row1.MH_NO,
-                "Client Sum": round(total1, 2),
+            }
-                "Subcontractor Sum": round(total2, 2),
-                "Diff": round(diff, 2)
-            })
 
-            # optional console print
+            # Client columns
+            for col, val in row1.__dict__.items():
+                if col.startswith("_") or col in ["id", "created_at", "subcontractor_id"]:
+                    continue
+                row_data[f"Client_{col}"] = val
+
+            row_data["Client_Total"] = round(client_total, 2)
+
+            # Subcontractor columns
+            for col, val in row2.__dict__.items():
+                if col.startswith("_") or col in ["id", "created_at", "subcontractor_id"]:
+                    continue
+                row_data[f"Sub_{col}"] = val
+
+            row_data["Sub_Total"] = round(contractor_total, 2)
+            row_data["Diff"] = round(diff, 2)
+
+            combined_rows_tr_ex.append(row_data)
+
+            # Console log
             print(
-                f"Location : {row1.Location} | "
+                f"{row1.Location} | {row1.MH_NO} | "
-                f"MH_NO : {row1.MH_NO} | "
+                f"Client={client_total} | Sub={contractor_total} | Diff={diff}"
-                f"Client : {total1} | "
-                f"Sub : {total2} | "
-                f"Diff : {diff}"
             )
 
+        # -------- Tr.Ex model ----------
+        df_tr_ex = pd.DataFrame(combined_rows_tr_ex)
+
+        # manhole ex
+        # contractor_mh_ex = ManholeExcavation.query.filter_by(
+        #     subcontractor_id=subcontractor_id
+        # ).all()
+
+        # client_mh_ex = ManholeExcavationClient.query.filter_by(
+        #     subcontractor_id=subcontractor_id
+        # ).all()
+
+        # combined_rows_mh_ex = []
+
+        # for row1, row2 in zip(client_mh_ex, contractor_mh_ex):
+        #     # -------- Tr.Ex CLIENT TOTAL ----------
+        #     client_total = (
+        #         (row1.Marshi_Muddy_Slushy_0_to_1_5_total or 0) +
+        #         (row1.Marshi_Muddy_Slushy_1_5_to_3_0_total or 0) +
+        #         (row1.Marshi_Muddy_Slushy_3_0_to_4_5_total or 0) +
+        #         (row1.Soft_Murum_0_to_1_5_total or 0) +
+        #         (row1.Soft_Murum_1_5_to_3_0_total or 0) +
+        #         (row1.Soft_Murum_3_0_to_4_5_total or 0) +
+        #         (row1.Hard_Murum_0_to_1_5_total or 0) +
+        #         (row1.Hard_Murum_1_5_to_3_0_total or 0) +
+        #         (row1.Hard_Murum_3_0_to_4_5_total or 0) +
+        #         (row1.Soft_Rock_0_to_1_5_total or 0) +
+        #         (row1.Soft_Rock_1_5_to_3_0_total or 0) +
+        #         (row1.Soft_Rock_3_0_to_4_5_total or 0) +
+        #         (row1.Hard_Rock_0_to_1_5_total or 0) +
+        #         (row1.Hard_Rock_1_5_to_3_0_total or 0) +
+        #         (row1.Hard_Rock_3_0_to_4_5_total or 0) +
+        #         (row1.Hard_Rock_4_5_to_6_0_total or 0) +
+        #         (row1.Hard_Rock_6_0_to_7_5_total or 0)
+        #     )
+
+        #     # -------- SUBCONTRACTOR TOTAL ----------
+        #     contractor_total = (
+        #         (row2.Soft_Murum_0_to_1_5_total or 0) +
+        #         (row2.Soft_Murum_1_5_to_3_0_total or 0) +
+        #         (row2.Soft_Murum_3_0_to_4_5_total or 0) +
+        #         (row2.Hard_Murum_0_to_1_5_total or 0) +
+        #         (row2.Hard_Murum_1_5_and_above_total or 0) +
+        #         (row2.Soft_Rock_0_to_1_5_total or 0) +
+        #         (row2.Soft_Rock_1_5_and_above_total or 0) +
+        #         (row2.Hard_Rock_0_to_1_5_total or 0) +
+        #         (row2.Hard_Rock_1_5_and_above_total or 0) +
+        #         (row2.Hard_Rock_4_5_to_6_0_total or 0) +
+        #         (row2.Hard_Rock_6_0_to_7_5_total or 0)
+        #     )
+
+        #     diff = client_total - contractor_total
+
+        #     # -------- COMBINED ROW ----------
+        #     row_data = {
+        #         "Location": row1.Location,
+        #         "MH No": row1.MH_NO,
+        #     }
+
+        #     # Client columns
+        #     for col, val in row1.__dict__.items():
+        #         if col.startswith("_") or col in ["id", "created_at", "subcontractor_id"]:
+        #             continue
+        #         row_data[f"Client_{col}"] = val
+
+        #     row_data["Client_Total"] = round(client_total, 2)
+
+        #     # Subcontractor columns
+        #     for col, val in row2.__dict__.items():
+        #         if col.startswith("_") or col in ["id", "created_at", "subcontractor_id"]:
+        #             continue
+        #         row_data[f"Sub_{col}"] = val
+
+        #     row_data["Sub_Total"] = round(contractor_total, 2)
+        #     row_data["Diff"] = round(diff, 2)
+
+        #     combined_rows_tr_ex.append(row_data)
+
+        #     # Console log
+        #     print(
+        #         f"{row1.Location} | {row1.MH_NO} | "
+        #         f"Client={client_total} | Sub={contractor_total} | Diff={diff}"
+        #     )
 
 
-        # Convert to DataFrame
-        df_contractor = pd.DataFrame([r.__dict__ for r in contractor_rows])
-        df_client = pd.DataFrame([r.__dict__ for r in client_rows])
-        df_diff = pd.DataFrame(diff_rows, columns=["Location", "Node No", "Client Sum", "Subcontractor Sum", "Diff"])
 
 
-        # Drop unwanted columns
-        drop_cols = ["id", "subcontractor_id", "created_at", "_sa_instance_state", "Remarks"]
-        df_contractor.drop(columns=drop_cols, errors="ignore", inplace=True)
-        df_client.drop(columns=drop_cols, errors="ignore", inplace=True)
 
-        # Convert to numeric
-        df_contractor = df_contractor.apply(pd.to_numeric, errors="coerce").fillna(0)
-        df_client = df_client.apply(pd.to_numeric, errors="coerce").fillna(0)
-
-        
-        # EXPORT EXCEL
         output = io.BytesIO()
         file_name = f"{subcontractor.subcontractor_name}_Comparison_Report.xlsx"
 
         with pd.ExcelWriter(output, engine="xlsxwriter") as writer:
-            df_contractor.to_excel(writer, index=False, sheet_name="Contractor_Data")
+            df_tr_ex.to_excel(writer, index=False, sheet_name="Tr.Ex")
-            df_client.to_excel(writer, index=False, sheet_name="Client_Data")
-            df_diff.to_excel(writer, index=False, sheet_name="Diff")
-            
-           
 
         output.seek(0)
 
@@ -127,7 +214,7 @@ def comparison_report():
             mimetype="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
         )
 
-    return render_template("generate_comparison_report.html", subcontractors=subcontractors)
+    return render_template(
-
+        "generate_comparison_report.html",
-
+        subcontractors=subcontractors
-
+    )

app/services/file_service.py

@@ -6,8 +6,11 @@ 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.models.tr_ex_client_model import TrenchExcavationClient
 from app.models.mh_ex_client_model import ManholeExcavationClient
+from app.models.mh_dc_client_model import ManholeDomesticChamberClient
+
 
 from app.utils.file_utils import ensure_upload_folder
 
@@ -56,14 +59,17 @@ class FileService:
             if file_type == "manhole_domestic_chamber":
                 return self.process_manhole_domestic_chamber(df, subcontractor_id)
             
-            # Trench Excavation save (client)
+            # Tr Ex save (client)
             if file_type =="tr_ex_client":
                 return self.client_trench_excavation(df, subcontractor_id)
 
-            # Manhole Excavation save (client)
+            # Mh Ex save (client)
-            # if file_type =="mh_ex_client":
+            if file_type =="mh_ex_client":
-            #     return self.client_manhole_excavation(df, subcontractor_id)
+                return self.client_manhole_excavation(df, subcontractor_id)
 
+             # Mh and Dc  save (client)
+            if file_type == "mh_dc_client":
+                return self.client_manhole_domestic_chamber(df, subcontractor_id)
 
             return True, "File uploaded successfully."
 
@@ -212,7 +218,7 @@ class FileService:
 
 
     # ---------------------- client ---------------------------------- 
-    # Trench Excavation save method (TrenchExcavationClient model)
+    # Tr Ex save method (TrenchExcavationClient model)
     def client_trench_excavation(self, df, subcontractor_id):
         df.columns = [str(c).strip() for c in df.columns]
         # If the sheet has merged cells -> forward fill Location
@@ -256,49 +262,96 @@ class FileService:
             return False, f"Clinnt Tr Ex Save Failed: {e}"
         
 
-    #   Manhole Excavation save method (ManholeExcavationClient model)
+    #   Mh Ex save method (ManholeExcavationClient model)
-    # def client_manhole_excavation(self, df, subcontractor_id):
+    def client_manhole_excavation(self, df, subcontractor_id):
-    #     # Clean column names (strip whitespace)
+        # Clean column names (strip whitespace)
-    #     df.columns = [str(c).strip() for c in df.columns]
+        df.columns = [str(c).strip() for c in df.columns]
-    #     # If the sheet has merged cells -> forward fill Location
+        # If the sheet has merged cells -> forward fill Location
-    #     if "Location" in df.columns:
+        if "Location" in df.columns:
-    #         df["Location"] = df["Location"].ffill()
+            df["Location"] = df["Location"].ffill()
 
-    #     # REMOVE empty rows
+        # REMOVE empty rows
-    #     df = df.dropna(how="all")
+        df = df.dropna(how="all")
-    #     # Identify missing location rows before insert
+        # Identify missing location rows before insert
-    #     missing_loc = df[df["Location"].isna() | (df["Location"].astype(str).str.strip() == "")]
+        missing_loc = df[df["Location"].isna() | (df["Location"].astype(str).str.strip() == "")]
-    #     if not missing_loc.empty:
+        if not missing_loc.empty:
-    #         return False, f"Error: Some rows have empty Location. Rows: {missing_loc.index.tolist()}"
+            return False, f"Error: Some rows have empty Location. Rows: {missing_loc.index.tolist()}"
 
-    #     saved_count = 0
+        saved_count = 0
 
-    #     try:
+        try:
-    #         for index, row in df.iterrows():
+            for index, row in df.iterrows():
-    #             record_data = {}
+                record_data = {}
-    #             # Insert only fields that exist in model
+                # Insert only fields that exist in model
-    #             for col in df.columns:
+                for col in df.columns:
-    #                 if hasattr(ManholeExcavationClient, col):
+                    if hasattr(ManholeExcavationClient, col):
-    #                     value = row[col]
+                        value = row[col]
 
-    #                     # Normalize empty values
+                        # Normalize empty values
-    #                     if pd.isna(value) or str(value).strip() in ["", "-", "—", "nan", "NaN"]:
+                        if pd.isna(value) or str(value).strip() in ["", "-", "—", "nan", "NaN"]:
-    #                         value = None
+                            value = None
 
-    #                     record_data[col] = value
+                        record_data[col] = value
 
-    #             record = ManholeExcavationClient(
+                record = ManholeExcavationClient(
-    #                 subcontractor_id=subcontractor_id,
+                    subcontractor_id=subcontractor_id,
-    #                 **record_data
+                    **record_data
-    #             )
+                )
 
-    #             db.session.add(record)
+                db.session.add(record)
-    #             saved_count += 1
+                saved_count += 1
 
-    #         db.session.commit()
+            db.session.commit()
-    #         return True, f" Client Mh Ex. data saved successfully. Total rows: {saved_count}"
+            return True, f" Client Mh Ex. data saved successfully. Total rows: {saved_count}"
 
-    #     except Exception as e:
+        except Exception as e:
-    #         db.session.rollback()
+            db.session.rollback()
-    #         return False, f"Client Mh Ex. Save Failed: {e}"
+            return False, f"Client Mh Ex. Save Failed: {e}"
+
+
+    #   Mh and Dc save method (ManholeDomesticChamberClient  model)
+    def client_manhole_domestic_chamber(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(ManholeDomesticChamberClient, 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 = ManholeDomesticChamberClient(
+                    subcontractor_id=subcontractor_id,
+                    **record_data
+                )
+
+                db.session.add(record)
+                saved_count += 1
+
+            db.session.commit()
+            return True, f"Mh and Dc data saved successfully. Total rows: {saved_count}"
+
+        except Exception as e:
+            db.session.rollback()
+            return False, f"Mh and Dc data Save Failed: {e}"