import pandas as pd
from openpyxl import load_workbook
from openpyxl.styles import PatternFill
from openpyxl.utils import range_boundaries

# Load MomentsPay_Bank_new.xlsx
moments_pay_bank_df = pd.read_excel('SrikaraPaytm06-06.xlsx')

# Load Transaction details as on 14.12.2023
transaction_details_df = pd.read_excel('SrikaraintegratedHIS.xlsx')

# Convert relevant columns to a common data type (string)
transaction_details_df['Paid Amount'] = transaction_details_df['Amount'].astype(str).replace(r'\.0$', '', regex=True)
#transaction_details_df['Umr No'] = transaction_details_df['Umr No'].astype(str).replace(r'\.0$', '', regex=True)

#moments_pay_bank_df['hospital_id'] = moments_pay_bank_df['uhid'].astype(str).replace('\.0$', '', regex=True).replace(r"UHID", '', regex=True)
moments_pay_bank_df['total_amount'] = moments_pay_bank_df['Amount'].astype(str).replace('\.0$', '', regex=True)

transaction_details_df = transaction_details_df[transaction_details_df['MomentsPay Matched']=="NO"]

transaction_details_df = transaction_details_df[transaction_details_df['Payment Mode Name']=="UPI"]

# Specify the mapping between fields excluding 'processing_id' and 'transaction_id'
field_mapping = {'Paid Amount' : 'total_amount'}

# Remove duplicates from moments_pay_bank_df based on 'transaction_id'
moments_pay_bank_df_dedup = moments_pay_bank_df.drop_duplicates(subset=['total_amount'], keep='first')

# Merge dataframes on the specified fields

merged_df = pd.merge(transaction_details_df, moments_pay_bank_df_dedup[list(field_mapping.values())],
                     left_on=list(field_mapping.keys()),
                     right_on=list(field_mapping.values()),
                     how='left')
unmerged_df = pd.merge(transaction_details_df, moments_pay_bank_df_dedup[list(field_mapping.values())],
                       left_on=list(field_mapping.keys()),
                       right_on=list(field_mapping.values()),
                       how='outer', indicator=True)
print(merged_df.columns)
equal_records = merged_df[~merged_df['total_amount'].isnull()]
equal_records.insert(0, 'S.No.', range(1, len(equal_records) + 1))
equal_records['momentpay matched'] = 'YES'
print(equal_records)
unequal_records = unmerged_df[unmerged_df['_merge'] == 'left_only']
unequal_records.insert(0, 'S.No.', range(1, len(unequal_records) + 1))
unequal_records['momentpay matched'] = 'NO'
print(unequal_records)
# Function to create or overwrite an Excel sheet
def create_or_overwrite_sheet(sheet_name, data):
    with pd.ExcelWriter('Srikara-HISBANK06-06.xlsx', mode='a', engine='openpyxl', if_sheet_exists='replace') as writer:
        data.to_excel(writer, sheet_name=sheet_name, index=False)

# Generate sheet names
sheet_name_matched = 'M-HISBankUpi-Matched'
sheet_name_unmatched = 'M-HISBankUpi-Unmatched'
create_or_overwrite_sheet(sheet_name_matched, equal_records)
create_or_overwrite_sheet(sheet_name_unmatched, unequal_records)

wb = load_workbook('Srikara-HISBANK06-06.xlsx')
Summary_Sheet = wb['Summary']

settled_date = moments_pay_bank_df['Settled_Date'].mode()[0]
#Summary_Sheet['A10'] = settled_date
print(settled_date)
# Update summary sheet with total transaction details
num_rows = len(transaction_details_df)
Summary_Sheet['K10'] = num_rows

total_amount = transaction_details_df['Paid Amount'].astype(float).sum()
Summary_Sheet['L10'] = f"₹{total_amount:,.2f}"

# Update summary sheet with matched transaction details
HIS_Matched_df = pd.read_excel('Srikara-HISBANK06-06.xlsx', sheet_name='M-HISBankUpi-Matched')
num_rows = len(HIS_Matched_df)
Summary_Sheet['M10'] = num_rows

total_amount = HIS_Matched_df['Paid Amount'].astype(float).sum()
Summary_Sheet['N10'] = f"₹{total_amount:,.2f}"

# Update summary sheet with unmatched transaction details
HIS_UnMatched_df = pd.read_excel('Srikara-HISBANK06-06.xlsx', sheet_name='M-HISBankUpi-Unmatched')
num_rows = len(HIS_UnMatched_df)
Summary_Sheet['O10'] = num_rows

total_amount = HIS_UnMatched_df['Paid Amount'].astype(float).sum()
Summary_Sheet['P10'] = f"₹{total_amount:,.2f}"

# Define the color for the header
header_fill = PatternFill(fgColor='1274bd', fill_type='solid')

for sheet_name in ['M-HISBankUpi-Matched', 'M-HISBankUpi-Unmatched']:
    worksheet = wb[sheet_name]

    
     # Apply style to the header row
    for row in worksheet.iter_rows(min_row=1, max_row=1):
        for cell in row:
            cell.fill = header_fill

# Save the workbook
wb.save('Srikara-HISBANK06-06.xlsx')