report formate changes all model

AppCode/AOHandler.py

@@ -71,16 +71,15 @@ class AOHandler:
         self.cursor.callproc('DeleteAOById', [id])
         self.conn.commit()
 
-
-    # CLOSE CONNECTION
-    def close(self):
-        self.cursor.close()
-        self.conn.close()
-
     # report download by year
     def ao_report_download(self, selected_year):
         try:
-                # Call stored proc to fetch year-wise records
+            # AY calculation (2020 -> AY 2020-2021)
+            ay_start = int(selected_year)
+            ay_end = ay_start + 1
+            assessment_year = f"AY {ay_start}-{ay_end}"
+
+            # Fetch AO records
             self.cursor.callproc("GetAOByYear", [selected_year])
 
             rows = []
@@ -90,30 +89,109 @@ class AOHandler:
             if not rows:
                 return None
 
-                df = pd.DataFrame(rows)
+            # Remove id column if exists
+            for row in rows:
+                row.pop("id", None)
 
-                # TRANSPOSE
+            # Mapping DB fields → readable Excel labels
-                df_transposed = df.transpose()
+            field_mapping = {
-                df_transposed.insert(0, 'Field', df_transposed.index)
+                "gross_total_income": "Gross Total Income",
-
+                "disallowance_14a": "Add: Disallowance u/s 14A",
-                # Rename columns: Record 1, 2, 3...
+                "disallowance_37": "Add: Disallowance u/s 37",
-                record_cols = {
+                "deduction_80ia_business": "Less: Deduction u/s 80IA - On Business Income",
-                    i: f"Record {i}"
+                "deduction_80ia_misc": "On Misc Receipts",
-                    for i in df_transposed.columns if isinstance(i, int)
+                "deduction_80ia_other": "On Other",
+                "deduction_sec37_disallowance": "On Sec 37 Disallowance",
+                "deduction_80g": "Less: Deduction u/s 80G",
+                "net_taxable_income": "Net Taxable Income",
+                "tax_30_percent": "Tax @ 30%",
+                "tax_book_profit_18_5": "Tax @ 18.5% on Book Profit",
+                "tax_payable": "Tax Payable",
+                "surcharge_12": "Surcharge @ 12%",
+                "edu_cess_3": "Education Cess @ 3%",
+                "total_tax_payable": "Total Tax Payable",
+                "mat_credit": "Less: MAT Credit Utilized",
+                "interest_234c": "Add: Interest u/s 234C",
+                "total_tax": "Total Tax",
+                "advance_tax": "Advance Tax",
+                "tds": "TDS",
+                "tcs": "TCS",
+                "sat": "SAT",
+                "tax_on_assessment": "Tax on Regular Assessment",
+                "refund": "Refund",
+                "Remarks": "Remarks"
             }
-                df_transposed.rename(columns=record_cols, inplace=True)
-                df_transposed.reset_index(drop=True, inplace=True)
 
-                # Excel Output
+            # Vertical AO structure
+            data = []
+            for key, label in field_mapping.items():
+                value = rows[0].get(key, 0)
+                data.append([label, value])
+
+            df = pd.DataFrame(data, columns=["Particulars", "AO"])
+
+            # Excel output
             output = io.BytesIO()
             with pd.ExcelWriter(output, engine="xlsxwriter") as writer:
-                    df_transposed.to_excel(writer, index=False, sheet_name="AO_Vertical")
+                workbook = writer.book
-                    worksheet = writer.sheets["AO_Vertical"]
+                worksheet = workbook.add_worksheet("AO Report")
-                    worksheet.set_column(0, 0, 30)
+                writer.sheets["AO Report"] = worksheet
+
+                # Formats
+                title_fmt = workbook.add_format({
+                    "bold": True,
+                    "align": "center",
+                    "font_size": 14
+                })
+                header_fmt = workbook.add_format({
+                    "bold": True,
+                    "border": 1,
+                    "align": "center"
+                })
+                text_fmt = workbook.add_format({"border": 1})
+                num_fmt = workbook.add_format({
+                    "border": 1,
+                    "num_format": "#,##0.00"
+                })
+
+                # Company Name
+                worksheet.merge_range(
+                    "A1:B1",
+                    "Laxmi Civil Engineering Services Pvt Ltd",
+                    title_fmt
+                )
+
+                # Assessment Year
+                worksheet.merge_range(
+                    "A2:B2",
+                    f"Assessment Year : {assessment_year}",
+                    workbook.add_format({"bold": True, "align": "center"})
+                )
+
+                # Header
+                worksheet.write_row("A4", ["Particulars", "AO"], header_fmt)
+
+                # Data rows
+                row_no = 4
+                for _, row in df.iterrows():
+                    worksheet.write(row_no, 0, row["Particulars"], text_fmt)
+                    worksheet.write(row_no, 1, row["AO"], num_fmt)
+                    row_no += 1
+
+                # Column width
+                worksheet.set_column("A:A", 45)
+                worksheet.set_column("B:B", 20)
 
             output.seek(0)
             return output
 
         except mysql.connector.Error as e:
-                print("MySQL Error:", e)
+            print("MySQL Error →", e)
             return None
+
+
+
+    # CLOSE CONNECTION
+    def close(self):
+        self.cursor.close()
+        self.conn.close()

AppCode/CITHandler.py

@@ -4,7 +4,6 @@ import pandas as pd
 import io
 
 
-
 class CITHandler:
 
     def __init__(self):
@@ -51,8 +50,6 @@ class CITHandler:
         self.cursor.callproc("InsertCIT", values)
         self.conn.commit()
 
-
-  
     # UPDATE CIT RECORD
     def update_cit(self, id, data):
         columns = [
@@ -69,22 +66,19 @@ class CITHandler:
         self.cursor.callproc("UpdateCITById", values)
         self.conn.commit()
 
-
-
     # DELETE CIT RECORD
     def delete_cit(self, id):
         self.cursor.callproc("DeleteCITById", [id])
         self.conn.commit()
-
+    # 
-    # CLOSE CONNECTION
-    def close(self):
-        self.cursor.close()
-        self.conn.close()
-
-
     def cit_report_download(self, selected_year):
         try:
-                # Call stored procedure
+            # AY calculation (2020 -> AY 2020-2021)
+            ay_start = int(selected_year)
+            ay_end = ay_start + 1
+            assessment_year = f"AY {ay_start}-{ay_end}"
+
+            # Fetch CIT records
             self.cursor.callproc("GetCITByYear", [selected_year])
 
             rows = []
@@ -94,28 +88,108 @@ class CITHandler:
             if not rows:
                 return None
 
-                df = pd.DataFrame(rows)
+            # Remove id column if exists
+            for row in rows:
+                row.pop("id", None)
+
+            # Mapping DB fields → readable Excel labels
+            field_mapping = {
+                "gross_total_income": "Gross Total Income",
+                "disallowance_14a": "Add: Disallowance u/s 14A",
+                "disallowance_37": "Add: Disallowance u/s 37",
+                "deduction_80ia_business": "Less: Deduction u/s 80IA - On Business Income",
+                "deduction_80ia_misc": "On Misc Receipts",
+                "deduction_80ia_other": "On Other",
+                "deduction_sec37_disallowance": "On Sec 37 Disallowance",
+                "deduction_80g": "Less: Deduction u/s 80G",
+                "net_taxable_income": "Net Taxable Income",
+                "tax_30_percent": "Tax @ 30%",
+                "tax_book_profit_18_5": "Tax @ 18.5% on Book Profit",
+                "tax_payable": "Tax Payable",
+                "surcharge_12": "Surcharge @ 12%",
+                "edu_cess_3": "Education Cess @ 3%",
+                "total_tax_payable": "Total Tax Payable",
+                "mat_credit": "Less: MAT Credit Utilized",
+                "interest_234c": "Add: Interest u/s 234C",
+                "total_tax": "Total Tax",
+                "advance_tax": "Advance Tax",
+                "tds": "TDS",
+                "tcs": "TCS",
+                "sat": "SAT",
+                "tax_on_assessment": "Tax on Regular Assessment",
+                "refund": "Refund",
+                "Remarks": "Remarks"
+            }
+
+            # Vertical CIT structure (single record per year)
+            data = []
+            for key, label in field_mapping.items():
+                value = rows[0].get(key, 0)
+                data.append([label, value])
+
+            df = pd.DataFrame(data, columns=["Particulars", "CIT"])
 
             # Excel output
             output = io.BytesIO()
             with pd.ExcelWriter(output, engine="xlsxwriter") as writer:
+                workbook = writer.book
+                worksheet = workbook.add_worksheet("CIT Report")
+                writer.sheets["CIT Report"] = worksheet
 
-                    for i, (_, row) in enumerate(df.iterrows(), start=1):
+                # Formats
-                        # Convert row to vertical format
+                title_fmt = workbook.add_format({
-                        vertical_df = pd.DataFrame(row).reset_index()
+                    "bold": True,
-                        vertical_df.columns = ['Field', 'Value']
+                    "align": "center",
+                    "font_size": 14
+                })
+                header_fmt = workbook.add_format({
+                    "bold": True,
+                    "border": 1,
+                    "align": "center"
+                })
+                text_fmt = workbook.add_format({"border": 1})
+                num_fmt = workbook.add_format({
+                    "border": 1,
+                    "num_format": "#,##0.00"
+                })
 
-                        start_row = (i - 1) * (len(vertical_df) + 3)  # gap between blocks
+                # Company Name
-                        vertical_df.to_excel(
+                worksheet.merge_range(
-                            writer,
+                    "A1:B1",
-                            sheet_name='CIT_Report',
+                    "Laxmi Civil Engineering Services Pvt Ltd",
-                            index=False,
+                    title_fmt
-                            startrow=start_row
                 )
 
+                # Assessment Year
+                worksheet.merge_range(
+                    "A2:B2",
+                    f"Assessment Year : {assessment_year}",
+                    workbook.add_format({"bold": True, "align": "center"})
+                )
+
+                # Header
+                worksheet.write_row("A4", ["Particulars", "CIT"], header_fmt)
+
+                # Data rows
+                row_no = 4
+                for _, row in df.iterrows():
+                    worksheet.write(row_no, 0, row["Particulars"], text_fmt)
+                    worksheet.write(row_no, 1, row["CIT"], num_fmt)
+                    row_no += 1
+
+                # Column widths
+                worksheet.set_column("A:A", 45)
+                worksheet.set_column("B:B", 20)
+
             output.seek(0)
             return output
 
         except mysql.connector.Error as e:
-                print("MySQL Error:", e)
+            print("MySQL Error →", e)
             return None
+
+
+ # CLOSE CONNECTION
+    def close(self):
+        self.cursor.close()
+        self.conn.close()

AppCode/ITATHandler.py

@@ -65,10 +65,14 @@ class ITATHandler:
         self.conn.commit()
 
 
-   
     def itat_report_download(self, selected_year):
         try:
-                # Call stored procedure
+            # AY calculation (2020 -> AY 2020-2021)
+            ay_start = int(selected_year)
+            ay_end = ay_start + 1
+            assessment_year = f"AY {ay_start}-{ay_end}"
+
+            # Fetch ITAT data
             self.cursor.callproc("GetITATByYear", [selected_year])
             rows = []
             for result in self.cursor.stored_results():
@@ -77,20 +81,107 @@ class ITATHandler:
             if not rows:
                 return None
 
-                df = pd.DataFrame(rows)
+            # Remove id column if exists
+            for row in rows:
+                row.pop("id", None)
+
+            # Mapping DB fields → readable Excel labels
+            field_mapping = {
+                "gross_total_income": "Gross Total Income",
+                "disallowance_14a": "Add: Disallowance u/s 14A",
+                "disallowance_37": "Add: Disallowance u/s 37",
+                "deduction_80ia_business": "Less: Deduction u/s 80IA - On Business Income",
+                "deduction_80ia_misc": "On Misc Receipts",
+                "deduction_80ia_other": "On Other",
+                "deduction_sec37_disallowance": "On Sec 37 Disallowance",
+                "deduction_80g": "Less: Deduction u/s 80G",
+                "net_taxable_income": "Net Taxable Income",
+                "tax_30_percent": "Tax @ 30%",
+                "tax_book_profit_18_5": "Tax @ 18.5% on Book Profit",
+                "tax_payable": "Tax Payable",
+                "surcharge_12": "Surcharge @ 12%",
+                "edu_cess_3": "Education Cess @ 3%",
+                "total_tax_payable": "Total Tax Payable",
+                "mat_credit": "Less: MAT Credit Utilized",
+                "interest_234c": "Add: Interest u/s 234C",
+                "total_tax": "Total Tax",
+                "advance_tax": "Advance Tax",
+                "tds": "TDS",
+                "tcs": "TCS",
+                "sat": "SAT",
+                "tax_on_assessment": "Tax on Regular Assessment",
+                "refund": "Refund",
+                "Remarks": "Remarks"
+            }
+
+            # Vertical ITAT structure
+            data = []
+            for key, label in field_mapping.items():
+                value = rows[0].get(key, 0)
+                data.append([label, value])
+
+            df = pd.DataFrame(data, columns=["Particulars", "ITAT"])
 
             # Excel output
             output = io.BytesIO()
             with pd.ExcelWriter(output, engine="xlsxwriter") as writer:
-                    df.T.to_excel(writer, header=False, sheet_name="ITAT_Report")
+                workbook = writer.book
+                worksheet = workbook.add_worksheet("ITAT Report")
+                writer.sheets["ITAT Report"] = worksheet
+
+                # Formats
+                title_fmt = workbook.add_format({
+                    "bold": True,
+                    "align": "center",
+                    "font_size": 14
+                })
+                header_fmt = workbook.add_format({
+                    "bold": True,
+                    "border": 1,
+                    "align": "center"
+                })
+                text_fmt = workbook.add_format({"border": 1})
+                num_fmt = workbook.add_format({
+                    "border": 1,
+                    "num_format": "#,##0.00"
+                })
+
+                # Company Name
+                worksheet.merge_range(
+                    "A1:B1",
+                    "Laxmi Civil Engineering Services Pvt Ltd",
+                    title_fmt
+                )
+
+                # Assessment Year
+                worksheet.merge_range(
+                    "A2:B2",
+                    f"Assessment Year : {assessment_year}",
+                    workbook.add_format({"bold": True, "align": "center"})
+                )
+
+                # Header
+                worksheet.write_row("A4", ["Particulars", "ITAT"], header_fmt)
+
+                # Data rows
+                row_no = 4
+                for _, row in df.iterrows():
+                    worksheet.write(row_no, 0, row["Particulars"], text_fmt)
+                    worksheet.write(row_no, 1, row["ITAT"], num_fmt)
+                    row_no += 1
+
+                # Column widths
+                worksheet.set_column("A:A", 45)
+                worksheet.set_column("B:B", 20)
 
             output.seek(0)
             return output
 
         except mysql.connector.Error as e:
-                print("MySQL Error:", e)
+            print("MySQL Error →", e)
             return None
 
+
  # CLOSE CONNECTION
     def close(self):
         self.cursor.close()

AppCode/ITRHandler.py

@@ -81,7 +81,7 @@ class ITRHandler:
         self.conn.commit()
 
 
-    # report download by year  
+    # # report download by year  
     def itr_report_download(self, selected_year):
         try:
             # Call stored procedure
@@ -93,27 +93,90 @@ class ITRHandler:
 
             if not rows:
                 return None
+            for row in rows:
+                row.pop('id', None)
 
-                # Convert SQL rows to DataFrame
+            # Mapping DB fields → Excel labels (NO underscores)
-                df = pd.DataFrame(rows)
+            field_mapping = {
-                # Transpose
+                "gross_total_income": "Gross Total Income",
-                df_transposed = df.transpose()
+                "disallowance_14a": "Add: Disallowance u/s 14A",
-                df_transposed.insert(0, 'Field', df_transposed.index)
+                "disallowance_37": "Add: Disallowance u/s 37",
-
+                "deduction_80ia_business": "Less: Deduction u/s 80IA - On Business Income",
-                record_cols = {
+                "deduction_80ia_misc": "On Misc Receipts",
-                    i: f"Record {i}"
+                "deduction_80ia_other": "On Other",
-                    for i in df_transposed.columns if isinstance(i, int)
+                "deduction_sec37_disallowance": "On Sec 37 Disallowance",
+                "deduction_80g": "Less: Deduction u/s 80G",
+                "net_taxable_income": "Net Taxable Income",
+                "tax_30_percent": "Tax @ 30%",
+                "tax_book_profit_18_5": "Tax @ 18.5% on Book Profit",
+                "tax_payable": "Tax Payable",
+                "surcharge_12": "Surcharge @ 12%",
+                "edu_cess_3": "Education Cess @ 3%",
+                "total_tax_payable": "Total Tax Payable",
+                "mat_credit": "Less: MAT Credit Utilized",
+                "interest_234c": "Add: Interest u/s 234C",
+                "total_tax": "Total Tax",
+                "advance_tax": "Advance Tax",
+                "tds": "TDS",
+                "tcs": "TCS",
+                "sat": "SAT",
+                "tax_on_assessment": "Tax on Regular Assessment",
+                "refund": "Refund"
             }
 
-                df_transposed.rename(columns=record_cols, inplace=True)
+            # Convert to vertical structure
-                df_transposed.reset_index(drop=True, inplace=True)
+            data = []
+            for key, label in field_mapping.items():
+                value = rows[0].get(key, 0)
+                data.append([label, value])
 
-                # Save to Excel in memory
+            df = pd.DataFrame(data, columns=["Particulars", "ITR"])
+
+            # Excel output
             output = io.BytesIO()
-                with pd.ExcelWriter(output, engine='xlsxwriter') as writer:
+            with pd.ExcelWriter(output, engine="xlsxwriter") as writer:
-                    df_transposed.to_excel(writer, index=False, sheet_name='ITR_Vertical')
+                workbook = writer.book
-                    worksheet = writer.sheets['ITR_Vertical']
+                worksheet = workbook.add_worksheet("ITR Report")
-                    worksheet.set_column(0, 0, 30)
+                writer.sheets["ITR Report"] = worksheet
+
+                # Formats
+                title_fmt = workbook.add_format({
+                    "bold": True, "align": "center", "valign": "vcenter",
+                    "font_size": 14
+                })
+                header_fmt = workbook.add_format({
+                    "bold": True, "border": 1, "align": "center"
+                })
+                cell_fmt = workbook.add_format({"border": 1})
+                num_fmt = workbook.add_format({"border": 1, "num_format": "#,##0.00"})
+
+                # Company name
+                worksheet.merge_range("A1:B1", "Laxmi Civil Engineering Services Pvt Ltd", title_fmt)
+
+                ay_start = int(selected_year)
+                ay_end = ay_start + 1
+                assessment_year = f"AY {ay_start}-{ay_end}"
+
+                # Assessment Year
+                worksheet.merge_range(
+                    "A2:B2",
+                    f"Assessment Year : {assessment_year}",
+                    workbook.add_format({"align": "center", "bold": True})
+                )
+
+                # Headers
+                worksheet.write_row("A4", ["Particulars", "ITR"], header_fmt)
+
+                # Data rows
+                row_no = 4
+                for _, row in df.iterrows():
+                    worksheet.write(row_no, 0, row["Particulars"], cell_fmt)
+                    worksheet.write(row_no, 1, row["ITR"], num_fmt)
+                    row_no += 1
+
+                # Column widths
+                worksheet.set_column("A:A", 45)
+                worksheet.set_column("B:B", 20)
 
             output.seek(0)
             return output