def EatEasy_excel_extract(url_input):

    import requests
    import json
    import pandas as pd
    from bs4 import BeautifulSoup
    from urllib.parse import urlparse
    import math
    from io import BytesIO

    payload1 = {'restId': '17902'}
    files = []

    headers2 = {
        'Content-Type': 'application/x-www-form-urlencoded',
        'Cookie': 'eateasy-ae-website=lai3mvcb9hd99nnivbt0pn68ibfjsd6g'
    }
    headers = {
        'Content-Type': 'application/x-www-form-urlencoded',
    }

    # url_input = input("Enter the restaurant URL: ")

    parsed_url = urlparse(url_input)
    restaurant_code = parsed_url.path.strip('/').split('/')[-1]

    url = "https://www.eateasy.ae/dubai/food/getFilteredMenus"
    data = {
        "restCode": restaurant_code
    }

    response = requests.post(url, data=data)

    menu_items_list = []
    category_name_list = []
    j = 0

    if response.status_code == 200:
        soup = BeautifulSoup(response.text, 'html.parser')
        menu_item_boxes = soup.find_all('div', class_='menu-item-box')  # Find all divs with class 'menu-item-box'

        for i, item_box in enumerate(menu_item_boxes):  # Iterate over each menu item box
            img = item_box.find('img')  # Find the img tag within the div
            if img:  # Check if img tag exists
                image_url = img.get('data-image')  # Get the value of 'data-image' attribute
            else:
                image_url = None  # If image URL is not found

            menu_item_details = item_box.find('div', class_='menu-item-details')  # Find menu-item-details div
            if menu_item_details:
                type_ = menu_item_details.find('p', class_='type').text.strip()
                name = menu_item_details.find('h5', class_='menu-food-title').text.strip()
                description = menu_item_details.find('p', itemprop='description').text.strip()
                price = menu_item_details.find('div', class_='menu-item-price').text.strip()
            else:
                # If menu-item-details not found, set defaults
                type_ = ""
                name = ""
                description = ""
                price = ""

            menu_list_options = item_box.find('a', class_='menu-list-options')  # Find the menu-list-options anchor tag
            if menu_list_options:
                value = menu_list_options.get('value')  # Get the value attribute
            else:
                value = None

            if type_ not in category_name_list:
                category_name_list.append(type_)
                j = j+1
                Category_position = j

            else:
                Category_position = j

            menu_item = {
                "Category": type_,
                "Category_position": Category_position,
                "Item_name": name,
                "Item_position": i, 
                "Image": image_url,
                "description": description,
                "price": price,
                "id": value,
            }

            menu_items_list.append(menu_item)  # Append menu item before the request
            if value is not None:
                option_url = f"https://www.eateasy.ae/dubai/order/add_to_cart_v1/{value}/1/"
                option_response = requests.post(option_url, headers=headers2, data=payload1)
                if option_response.status_code == 200:
                    try:
                        json_data = json.loads(option_response.text)
                        extracted_data = []

                        if 'arrResult' in json_data and 'arrFoodChoice' in json_data['arrResult']:
                            for choice in json_data['arrResult']['arrFoodChoice']:
                                extracted_data.append({
                                    'Option_group_name': choice['choice_name'],
                                    'Option_name': choice['name'],
                                    'Extra_price': choice['price'],
                                    'Min': choice.get('mandatory', 0),
                                    'Max': choice.get('max_choice', 1)
                                })

                        grouped_data = {}
                        for choice in extracted_data:
                            group_name = choice['Option_group_name']
                            if group_name not in grouped_data:
                                grouped_data[group_name] = {
                                    'Option_group_name': group_name,
                                    'Min': choice['Min'],
                                    'Max': max(choice['Max'], '1'),
                                }
                            
                            num_options = sum(key.startswith('Option ') for key in grouped_data[group_name])
                            option_index = num_options + 1  # Index for the new option
                            grouped_data[group_name][f"Option {option_index} Name"] = choice['Option_name']
                            grouped_data[group_name][f"Option {option_index} Price"] = choice['Extra_price']
                            
                        for group_data in grouped_data.values():
                            menu_items_list.append(group_data)

                    except json.JSONDecodeError:
                        print("JSON decoding error. Response content may not be in valid JSON format.")
                else:
                    print(f"Failed to get data for item with value {value}. Status code: {option_response.status_code}")

        df = pd.DataFrame(menu_items_list)

        # Ensure 'Max' column exists before renaming or shifting
        if 'Max' in df.columns:
            max_column_index = df.columns.get_loc('Max')
            for i in range(max_column_index + 1, len(df.columns)):
                df.rename(columns={df.columns[i]: ''}, inplace=True)

            option_group_name_index = df.columns.get_loc('Option_group_name')
            for i in range(option_group_name_index, len(df.columns)):
                df.iloc[:, i] = df.iloc[:, i].shift(-1)

        df_cleaned = df.dropna(how='all')

        output = BytesIO()
        with pd.ExcelWriter(output, engine='openpyxl') as writer:
            df_cleaned.to_excel(writer, index=False, sheet_name='Menu')
        output.seek(0)

        return output, f"{restaurant_code}_menu.xlsx"
        # excel_file = f"{restaurant_code}_menu.xlsx"
        # df.to_excel(excel_file, index=False)
        # print(f"Menu items saved to {excel_file}")

    else:
        print(f"Failed to get menu items. Status code: {response.status_code}")
        
    return True