

from itertools import zip_longest

import requests
from bsa import BeautifulSoup
from pandas import DataFrame
def     UpperCAmelCase_       (						_A = "laptop"    ):





     '''simple docstring'''




     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
        (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(_A				,		headers=_A    ).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(''','''				,		''''''    )    )
                        )
                        * 1_00    )
               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__":
       _SCREAMING_SNAKE_CASE					:  str             =      '''headphones'''
       get_amazon_product_data(product).to_csv(F"Amazon Product Data for {product}.csv")





from functools import reduce

_SCREAMING_SNAKE_CASE					:  Any             =      (
    '''73167176531330624919225119674426574742355349194934'''
    '''96983520312774506326239578318016984801869478851843'''
    '''85861560789112949495459501737958331952853208805511'''
    '''12540698747158523863050715693290963295227443043557'''
    '''66896648950445244523161731856403098711121722383113'''
    '''62229893423380308135336276614282806444486645238749'''
    '''30358907296290491560440772390713810515859307960866'''
    '''70172427121883998797908792274921901699720888093776'''
    '''65727333001053367881220235421809751254540594752243'''
    '''52584907711670556013604839586446706324415722155397'''
    '''53697817977846174064955149290862569321978468622482'''
    '''83972241375657056057490261407972968652414535100474'''
    '''82166370484403199890008895243450658541227588666881'''
    '''16427171479924442928230863465674813919123162824586'''
    '''17866458359124566529476545682848912883142607690042'''
    '''24219022671055626321111109370544217506941658960408'''
    '''07198403850962455444362981230987879927244284909188'''
    '''84580156166097919133875499200524063689912560717606'''
    '''05886116467109405077541002256983155200055935729725'''
    '''71636269561882670428252483600823257530420752963450'''
)
def     UpperCAmelCase_       (						_A = N    ):





     '''simple docstring'''




     return max(
         # mypy cannot properly interpret reduce
         int(reduce(lambda _A				,		_A    : str(int(_A    ) * int(_A    )    )				,		n[i : i + 13]    )    )
         for i in range(len(_A    ) - 12    )    )


if __name__ == "__main__":
       print(F"{solution() = }")


