Mdified comparison route and roundoff values checking also.

AppCode/FileHandler.py

@@ -0,0 +1,14 @@
+import os
+
+
+class FileHandler:
+
+    UPLOAD_FOLDER = 'uploads'
+    RESULT_FILE = 'unmatched_result.xlsx'
+
+    @staticmethod
+    def check_or_create_folder_exists():
+       
+       if not os.path.exists(FileHandler.UPLOAD_FOLDER):
+            os.makedirs(FileHandler.UPLOAD_FOLDER)
+

AppCode/ServerPort.py

@@ -0,0 +1,5 @@
+
+# Server config.
+class CompGSTServer:
+    host='0.0.0.0'
+    port=5001

AppCode/compare_excel.py

@@ -0,0 +1,74 @@
+import pandas as pd
+
+class Comparison:
+
+    @staticmethod
+    def normalize_value(val):
+        """Normalize non-numeric values (date, string)."""
+        if pd.isna(val):
+            return ""
+
+        # Normalize dates
+        if isinstance(val, pd.Timestamp):
+            return val.date().isoformat()
+
+        # Normalize strings
+        return str(val).strip().upper().replace(" ", "")
+
+    @staticmethod
+    def round_amount(val, decimals=0):
+        """Round numeric values safely for comparison."""
+        if pd.isna(val):
+            return ""
+        try:
+            return round(float(val), decimals)
+        except Exception:
+            return val
+
+    @staticmethod
+    def find_unmatched_rows(sheet1_df, sheet2_df):
+        # Clean column names
+        sheet1_df.columns = sheet1_df.columns.str.strip()
+        sheet2_df.columns = sheet2_df.columns.str.strip()
+
+        comparison_columns = [
+            'Date',
+            'GSTIN/UIN',
+            'Voucher Ref. No.',
+            'Total Tax',
+            'Total Amount'
+        ]
+
+        amount_columns = ['Total Tax', 'Total Amount']
+
+        # Validate required columns
+        for col in comparison_columns:
+            if col not in sheet1_df.columns or col not in sheet2_df.columns:
+                raise ValueError(f"Missing column '{col}' in one of the sheets.")
+
+        # Normalize values
+        for col in comparison_columns:
+            if col in amount_columns:
+                sheet1_df[col] = sheet1_df[col].apply(
+                    lambda x: Comparison.round_amount(x, 0)
+                )
+                sheet2_df[col] = sheet2_df[col].apply(
+                    lambda x: Comparison.round_amount(x, 0)
+                )
+            else:
+                sheet1_df[col] = sheet1_df[col].apply(Comparison.normalize_value)
+                sheet2_df[col] = sheet2_df[col].apply(Comparison.normalize_value)
+
+        # Create comparison keys
+        sheet1_keys = sheet1_df[comparison_columns].apply(tuple, axis=1)
+        sheet2_keys = sheet2_df[comparison_columns].apply(tuple, axis=1)
+
+        # Find unmatched rows
+        unmatched_sheet1 = sheet1_df[~sheet1_keys.isin(sheet2_keys)].copy()
+        unmatched_sheet2 = sheet2_df[~sheet2_keys.isin(sheet1_keys)].copy()
+
+        # Add source column
+        unmatched_sheet1["Source"] = "Portal"
+        unmatched_sheet2["Source"] = "Tally"
+
+        return unmatched_sheet1, unmatched_sheet2

app.py

@@ -1,42 +1,56 @@
 from flask import Flask, render_template, request, send_file
 import pandas as pd
-from compare_gst_excel import find_unmatched_rows
 import os
 from werkzeug.utils import secure_filename
+from AppCode.FileHandler import FileHandler
+from AppCode.ServerPort import CompGSTServer
+from AppCode.compare_excel import Comparison
 
 app = Flask(__name__)
-UPLOAD_FOLDER = 'uploads'
-RESULT_FILE = 'unmatched_result.xlsx'
 
-if not os.path.exists(UPLOAD_FOLDER):
-    os.makedirs(UPLOAD_FOLDER)
+# check file Folder valid
+FileHandler.check_or_create_folder_exists()
 
+# upload page show 
 @app.route('/')
 def index():
     return render_template('upload.html')
 
+# camparison route
 @app.route('/upload', methods=['POST'])
 def upload_file():
-    file = request.files['excel_file']
+    file = request.files.get('excel_file')
     if not file:
         return "No file uploaded.", 400
 
     filename = secure_filename(file.filename)
-    filepath = os.path.join(UPLOAD_FOLDER, filename)
+    filepath = os.path.join(FileHandler.UPLOAD_FOLDER, filename)
     file.save(filepath)
 
     try:
-        # Read Excel with header in row 8 (0-indexed), so header=7
-        df1 = pd.read_excel(filepath, sheet_name=0, header=7)
-        df2 = pd.read_excel(filepath, sheet_name=1, header=7)
+        # Read first two sheets
+        df1 = pd.read_excel(filepath, sheet_name=0, header=0)
+        df2 = pd.read_excel(filepath, sheet_name=1, header=0)
 
-        unmatched = find_unmatched_rows(df1, df2)
-        unmatched.to_excel(RESULT_FILE, index=False)
+        # Get unmatched rows separately
+        unmatched_sheet1, unmatched_sheet2 = Comparison.find_unmatched_rows(df1, df2)
 
-        return send_file(RESULT_FILE, as_attachment=True)
+        # Write result into two Excel sheets
+        with pd.ExcelWriter(FileHandler.RESULT_FILE, engine="openpyxl") as writer:
+            unmatched_sheet1.to_excel(
+                writer, sheet_name="Not In Tally", index=False
+            )
+            unmatched_sheet2.to_excel(
+                writer, sheet_name="Not In Portal", index=False
+            )
+
+        return send_file(FileHandler.RESULT_FILE, as_attachment=True)
 
     except Exception as e:
         return f"Error processing file: {e}", 500
 
+# run
 if __name__ == '__main__':
-    app.run(host='0.0.0.0', port=5000,debug=True)
+    app.run(host=CompGSTServer.host, port=CompGSTServer.port, debug=True)
+
+

compare_gst_excel.py

@@ -1,64 +0,0 @@
-# import pandas as pd
-
-# def normalize_row(row):
-#     return tuple(
-#         str(cell).strip().replace(".0", "") if isinstance(cell, float) and cell.is_integer() else str(cell).strip()
-#         for cell in row
-#     )
-
-# def find_unmatched_rows(sheet1_df, sheet2_df):
-#     # Ensure column names are clean
-#     sheet1_df.columns = sheet1_df.columns.str.strip()
-#     sheet2_df.columns = sheet2_df.columns.str.strip()
-
-#     # Normalize rows for comparison
-#     sheet1_normalized = sheet1_df.apply(normalize_row, axis=1)
-#     sheet2_normalized = sheet2_df.apply(normalize_row, axis=1)
-
-#     # Find unmatched rows
-#     unmatched_in_sheet1 = sheet1_df[~sheet1_normalized.isin(sheet2_normalized)]
-#     unmatched_in_sheet2 = sheet2_df[~sheet2_normalized.isin(sheet1_normalized)]
-
-#     # Mark source
-#     unmatched_in_sheet1["Source"] = "Sheet1"
-#     unmatched_in_sheet2["Source"] = "Sheet2"
-
-#     # Combine
-#     unmatched_combined = pd.concat([unmatched_in_sheet1, unmatched_in_sheet2], ignore_index=True)
-#     return unmatched_combined
-import pandas as pd
-
-def normalize_row(row):
-    return tuple(
-        str(cell).strip().replace(".0", "") if isinstance(cell, float) and cell.is_integer() else str(cell).strip()
-        for cell in row
-    )
-
-def find_unmatched_rows(sheet1_df, sheet2_df):
-    # Clean column names
-    sheet1_df.columns = sheet1_df.columns.str.strip()
-    sheet2_df.columns = sheet2_df.columns.str.strip()
-
-    # Choose the comparison columns
-    comparison_columns = ['Date', 'GSTIN/UIN']
-
-    # Ensure required columns exist
-    for col in comparison_columns:
-        if col not in sheet1_df.columns or col not in sheet2_df.columns:
-            raise ValueError(f"Missing column '{col}' in one of the sheets.")
-
-    # Create keys for comparison
-    sheet1_keys = sheet1_df[comparison_columns].apply(normalize_row, axis=1)
-    sheet2_keys = sheet2_df[comparison_columns].apply(normalize_row, axis=1)
-
-    # Find unmatched rows
-    unmatched_in_sheet1 = sheet1_df[~sheet1_keys.isin(sheet2_keys)].copy()
-    unmatched_in_sheet2 = sheet2_df[~sheet2_keys.isin(sheet1_keys)].copy()
-
-    # Mark source
-    unmatched_in_sheet1["Source"] = "Sheet1"
-    unmatched_in_sheet2["Source"] = "Sheet2"
-
-    # Combine
-    unmatched_combined = pd.concat([unmatched_in_sheet1, unmatched_in_sheet2], ignore_index=True)
-    return unmatched_combined