


from itertools import zip_longest

import requests
from bsa import BeautifulSoup
from pandas import DataFrame







def 						lowerCamelCase(   a__ = "laptop"):
    _SCREAMING_SNAKE_CASE			  =f"https://www.amazon.in/laptop/s?k={product}"
    _SCREAMING_SNAKE_CASE			  ={
        'User-Agent': 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36\n        (KHTML, like Gecko)Chrome/44.0.2403.157 Safari/537.36',
        'Accept-Language': 'en-US, en;q=0.5',
    }
    _SCREAMING_SNAKE_CASE			  =BeautifulSoup(requests.get(_lowerCamelCase	,headers=_lowerCamelCase).text)
    # Initialize a Pandas dataframe with the column titles
    _SCREAMING_SNAKE_CASE			  =DataFrame(
        columns=[
            '''Product Title''',
            '''Product Link''',
            '''Current Price of the product''',
            '''Product Rating''',
            '''MRP of the product''',
            '''Discount''',
        ])
    # Loop through each entry and store them in the dataframe
    for item, _ in zip_longest(
        soup.find_all(
            '''div'''	,attrs={'''class''': '''s-result-item''', '''data-component-type''': '''s-search-result'''}	,)	,soup.find_all('''div'''	,attrs={'''class''': '''a-row a-size-base a-color-base'''})	,):
        try:
            _SCREAMING_SNAKE_CASE			  =item.ha.text
            _SCREAMING_SNAKE_CASE			  ='https://www.amazon.in/' + item.ha.a['href']
            _SCREAMING_SNAKE_CASE			  =item.find('''span'''	,attrs={'''class''': '''a-offscreen'''}).text
            try:
                _SCREAMING_SNAKE_CASE			  =item.find('''span'''	,attrs={'''class''': '''a-icon-alt'''}).text
            except AttributeError:
                _SCREAMING_SNAKE_CASE			  ='Not available'
            try:
                _SCREAMING_SNAKE_CASE			  =(
                    '₹'
                    + item.find(
                        '''span'''	,attrs={'''class''': '''a-price a-text-price'''}).text.split('''₹''')[1]
                )
            except AttributeError:
                _SCREAMING_SNAKE_CASE			  =''
            try:
                _SCREAMING_SNAKE_CASE			  =float(
                    (
                        (
                            float(product_mrp.strip('''₹''').replace(''','''	,''''''))
                            - float(product_price.strip('''₹''').replace(''','''	,''''''))
                        )
                        / float(product_mrp.strip('''₹''').replace(''','''	,''''''))
                    )
                    * 100)
            except ValueError:
                _SCREAMING_SNAKE_CASE			  =float('''nan''')
        except AttributeError:
            pass
        _SCREAMING_SNAKE_CASE			  =[
            product_title,
            product_link,
            product_price,
            product_rating,
            product_mrp,
            discount,
        ]
    _SCREAMING_SNAKE_CASE			  =' '
    _SCREAMING_SNAKE_CASE			  =' '
    data_frame.index += 1
    return data_frame


if __name__ == "__main__":
       snake_case_						:			Tuple													=							'''headphones'''
       get_amazon_product_data(product).to_csv(f"""Amazon Product Data for {product}.csv""")



from collections.abc import Generator







def 						lowerCamelCase(   ):
				_SCREAMING_SNAKE_CASE  ,				_SCREAMING_SNAKE_CASE			  =0, 1
				while True:
								_SCREAMING_SNAKE_CASE  ,				_SCREAMING_SNAKE_CASE			  =b, a + b
								yield b







def 						lowerCamelCase(   a__ = 1000):
				_SCREAMING_SNAKE_CASE			  =1
				_SCREAMING_SNAKE_CASE			  =fibonacci_generator()
				while len(str(next(a__))) < n:
								answer += 1
				return answer + 1


if __name__ == "__main__":
							print(solution(int(str(input()).strip())))