# 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