#!/usr/bin/env python3 import json import os import re import openpyxl from openpyxl.utils import get_column_letter from zipfile import ZipFile, ZIP_DEFLATED def update_excel_variables(excel_path): """ Update the Variables sheet in the Excel file with values from config.json and hide forecast sheets that aren't in the calculated years array Args: excel_path (str): Path to the Excel file to update Returns: bool: True if successful, False otherwise """ # Define paths script_dir = os.path.dirname(os.path.abspath(__file__)) config_path = os.path.join(script_dir, 'config.json') try: # Load config.json with open(config_path, 'r') as f: config = json.load(f) user_data = config.get('user_data', {}) # Load Excel workbook print(f"Opening Excel file: {excel_path}") wb = openpyxl.load_workbook(excel_path) # Try to access the Variables sheet try: # First try by name sheet = wb['Variables'] except KeyError: # If not found by name, try to access the last sheet sheet_names = wb.sheetnames if sheet_names: print(f"Variables sheet not found by name. Using last sheet: {sheet_names[-1]}") sheet = wb[sheet_names[-1]] else: print("No sheets found in the workbook") return False # Map config variables to Excel cells based on the provided mapping cell_mappings = { 'B2': user_data.get('store_name', ''), 'B31': user_data.get('starting_date', ''), 'B32': user_data.get('duration', 36), 'B37': user_data.get('open_days_per_month', 0), # Convenience store type 'H37': user_data.get('convenience_store_type', {}).get('stores_number', 0), 'C37': user_data.get('convenience_store_type', {}).get('monthly_transactions', 0), # Convert boolean to 1/0 for has_digital_screens 'I37': 1 if user_data.get('convenience_store_type', {}).get('has_digital_screens', False) else 0, 'J37': user_data.get('convenience_store_type', {}).get('screen_count', 0), 'K37': user_data.get('convenience_store_type', {}).get('screen_percentage', 0), # Convert boolean to 1/0 for has_in_store_radio 'M37': 1 if user_data.get('convenience_store_type', {}).get('has_in_store_radio', False) else 0, 'N37': user_data.get('convenience_store_type', {}).get('radio_percentage', 0), # Minimarket store type 'H38': user_data.get('minimarket_store_type', {}).get('stores_number', 0), 'C38': user_data.get('minimarket_store_type', {}).get('monthly_transactions', 0), # Convert boolean to 1/0 for has_digital_screens 'I38': 1 if user_data.get('minimarket_store_type', {}).get('has_digital_screens', False) else 0, 'J38': user_data.get('minimarket_store_type', {}).get('screen_count', 0), 'K38': user_data.get('minimarket_store_type', {}).get('screen_percentage', 0), # Convert boolean to 1/0 for has_in_store_radio 'M38': 1 if user_data.get('minimarket_store_type', {}).get('has_in_store_radio', False) else 0, 'N38': user_data.get('minimarket_store_type', {}).get('radio_percentage', 0), # Supermarket store type 'H39': user_data.get('supermarket_store_type', {}).get('stores_number', 0), 'C39': user_data.get('supermarket_store_type', {}).get('monthly_transactions', 0), # Convert boolean to 1/0 for has_digital_screens 'I39': 1 if user_data.get('supermarket_store_type', {}).get('has_digital_screens', False) else 0, 'J39': user_data.get('supermarket_store_type', {}).get('screen_count', 0), 'K39': user_data.get('supermarket_store_type', {}).get('screen_percentage', 0), # Convert boolean to 1/0 for has_in_store_radio 'M39': 1 if user_data.get('supermarket_store_type', {}).get('has_in_store_radio', False) else 0, 'N39': user_data.get('supermarket_store_type', {}).get('radio_percentage', 0), # Hypermarket store type 'H40': user_data.get('hypermarket_store_type', {}).get('stores_number', 0), 'C40': user_data.get('hypermarket_store_type', {}).get('monthly_transactions', 0), # Convert boolean to 1/0 for has_digital_screens 'I40': 1 if user_data.get('hypermarket_store_type', {}).get('has_digital_screens', False) else 0, 'J40': user_data.get('hypermarket_store_type', {}).get('screen_count', 0), 'K40': user_data.get('hypermarket_store_type', {}).get('screen_percentage', 0), # Convert boolean to 1/0 for has_in_store_radio 'M40': 1 if user_data.get('hypermarket_store_type', {}).get('has_in_store_radio', False) else 0, 'N40': user_data.get('hypermarket_store_type', {}).get('radio_percentage', 0), # On-site channels 'B43': user_data.get('website_visitors', 0), 'B44': user_data.get('app_users', 0), 'B45': user_data.get('loyalty_users', 0), # Off-site channels 'B49': user_data.get('facebook_followers', 0), 'B50': user_data.get('instagram_followers', 0), 'B51': user_data.get('google_views', 0), 'B52': user_data.get('email_subscribers', 0), 'B53': user_data.get('sms_users', 0), 'B54': user_data.get('whatsapp_contacts', 0) } # Update the cells for cell_ref, value in cell_mappings.items(): try: # Force the value to be set, even if the cell is protected or has data validation cell = sheet[cell_ref] cell.value = value print(f"Updated {cell_ref} with value: {value}") except Exception as e: print(f"Error updating cell {cell_ref}: {e}") # Save the workbook with variables updated print("Saving workbook with updated variables...") wb.save(excel_path) # Get the calculated years array from config starting_date = user_data.get('starting_date', '') duration = user_data.get('duration', 36) calculated_years = [] # Import datetime at the module level to avoid scope issues import datetime from dateutil.relativedelta import relativedelta # Calculate years array based on starting_date and duration try: # Try to parse the date, supporting both dd/mm/yyyy and dd.mm.yyyy formats if starting_date: if '/' in str(starting_date): day, month, year = map(int, str(starting_date).split('/')) elif '.' in str(starting_date): day, month, year = map(int, str(starting_date).split('.')) elif '-' in str(starting_date): # Handle ISO format (yyyy-mm-dd) date_parts = str(starting_date).split('-') if len(date_parts) == 3: year, month, day = map(int, date_parts) else: # Default to current date if format is not recognized current_date = datetime.datetime.now() year, month, day = current_date.year, current_date.month, current_date.day elif isinstance(starting_date, datetime.datetime): day, month, year = starting_date.day, starting_date.month, starting_date.year else: # Default to current date if format is not recognized current_date = datetime.datetime.now() year, month, day = current_date.year, current_date.month, current_date.day # Create datetime object for starting date start_date = datetime.datetime(year, month, day) # Calculate end date (starting date + duration months - 1 day) end_date = start_date + relativedelta(months=duration-1) # Create a set of years (to avoid duplicates) years_set = set() # Add starting year years_set.add(start_date.year) # Add ending year years_set.add(end_date.year) # If there are years in between, add those too for y in range(start_date.year + 1, end_date.year): years_set.add(y) # Convert set to sorted list calculated_years = sorted(list(years_set)) print(f"Calculated years for sheet visibility: {calculated_years}") else: # Default to current year if no starting date calculated_years = [datetime.datetime.now().year] except Exception as e: print(f"Error calculating years for sheet visibility: {e}") calculated_years = [datetime.datetime.now().year] # Update sheet names - replace {store_name} with actual store name store_name = user_data.get('store_name', '') if store_name: # Dictionary to store old sheet name to new sheet name mappings sheet_name_mapping = {} # Make a copy of the sheet names to avoid modifying during iteration sheet_names = wb.sheetnames.copy() for sheet_name in sheet_names: if '{store_name}' in sheet_name: new_sheet_name = sheet_name.replace('{store_name}', store_name) # Get the sheet by its old name sheet = wb[sheet_name] # Set the new title sheet.title = new_sheet_name # Store the mapping sheet_name_mapping[sheet_name] = new_sheet_name print(f"Renamed sheet '{sheet_name}' to '{new_sheet_name}'") # Check if this is a forecast sheet and if its year is in the calculated years # Forecast sheets have names like "2025 – Forecast {store_name}" if "Forecast" in new_sheet_name: # Extract the year from the sheet name try: sheet_year = int(new_sheet_name.split()[0]) # Hide the sheet if its year is not in the calculated years if sheet_year not in calculated_years: sheet.sheet_state = 'hidden' print(f"Hiding sheet '{new_sheet_name}' as year {sheet_year} is not in calculated years {calculated_years}") except Exception as e: print(f"Error extracting year from sheet name '{new_sheet_name}': {e}") # Save the workbook with renamed and hidden sheets wb.save(excel_path) # Use direct XML modification to replace all instances of {store_name} in formulas print("Using direct XML modification to update all formulas...") update_excel_with_direct_xml(excel_path, store_name) print(f"Excel file updated successfully: {excel_path}") return True except Exception as e: print(f"Error updating Excel file: {e}") return False def update_excel_with_direct_xml(excel_path, store_name): """ Update all references to {store_name} in the Excel file by directly modifying XML Args: excel_path: Path to the Excel file store_name: The store name to replace {store_name} with Returns: bool: True if successful, False otherwise """ try: print(f"Using direct XML modification to replace '{{store_name}}' with '{store_name}'...") # Create a temporary file for modification temp_dir = os.path.dirname(os.path.abspath(excel_path)) temp_file = os.path.join(temp_dir, f"_temp_{os.path.basename(excel_path)}") # Make a copy of the original file import shutil shutil.copy2(excel_path, temp_file) # Count of replacements total_replacements = 0 # Process the Excel file - use a safer approach # First read all files from the zip files_data = {} with ZipFile(excel_path, 'r') as zip_ref: for item in zip_ref.infolist(): files_data[item.filename] = (zip_ref.read(item.filename), item) # Modify the content for filename, (content, item) in files_data.items(): # Only modify XML files that might contain formulas or text if filename.endswith('.xml') or filename.endswith('.rels'): # Skip sheet8.xml which is the Variables sheet (based on common Excel structure) if 'sheet8.xml' in filename: print(f"Skipping Variables sheet: {filename}") continue # Convert to string for text replacement try: text_content = content.decode('utf-8') # Check if this file contains our placeholder if '{store_name}' in text_content: # Count occurrences before replacement occurrences = text_content.count('{store_name}') total_replacements += occurrences # Replace all instances of {store_name} with the actual store name modified_content = text_content.replace('{store_name}', store_name) # Convert back to bytes files_data[filename] = (modified_content.encode('utf-8'), item) print(f"Replaced {occurrences} instances of '{{store_name}}' in {filename}") except UnicodeDecodeError: # Not a text file, leave as is pass # Write the modified zip file with ZipFile(temp_file, 'w', ZIP_DEFLATED) as zip_out: for filename, (content, item) in files_data.items(): zip_out.writestr(filename, content) # Replace the original file with the modified one shutil.move(temp_file, excel_path) print(f"Total replacements: {total_replacements}") return True except Exception as e: print(f"Error updating Excel file with direct XML modification: {e}") import traceback traceback.print_exc() return False if __name__ == "__main__": # For testing purposes import sys if len(sys.argv) > 1: excel_path = sys.argv[1] update_excel_variables(excel_path) else: print("Please provide the path to the Excel file as an argument")