


"""simple docstring"""


from functools import reduce

_snake_case        =				(
    "73167176531330624919225119674426574742355349194934"
    "96983520312774506326239578318016984801869478851843"
    "85861560789112949495459501737958331952853208805511"
    "12540698747158523863050715693290963295227443043557"
    "66896648950445244523161731856403098711121722383113"
    "62229893423380308135336276614282806444486645238749"
    "30358907296290491560440772390713810515859307960866"
    "70172427121883998797908792274921901699720888093776"
    "65727333001053367881220235421809751254540594752243"
    "52584907711670556013604839586446706324415722155397"
    "53697817977846174064955149290862569321978468622482"
    "83972241375657056057490261407972968652414535100474"
    "82166370484403199890008895243450658541227588666881"
    "16427171479924442928230863465674813919123162824586"
    "17866458359124566529476545682848912883142607690042"
    "24219022671055626321111109370544217506941658960408"
    "07198403850962455444362981230987879927244284909188"
    "84580156166097919133875499200524063689912560717606"
    "05886116467109405077541002256983155200055935729725"
    "71636269561882670428252483600823257530420752963450"
)



def 	snake_case    (					_a:  Any = N				)->		int:
      '''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() = }""")











"""simple docstring"""







from itertools import zip_longest

import requests
from bsa import BeautifulSoup
from pandas import DataFrame


def      UpperCamelCase       ( _A = "laptop" )     ->       DataFrame:
				lowercase    :      List[str]       = F"""https://www.amazon.in/laptop/s?k={product}"""
				lowercase    :      str       = {
				    """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""",
				}
				lowercase    :      str       = BeautifulSoup(requests.get(_A  ,				headers=_A ).text )
				# Initialize a Pandas dataframe with the column titles
				lowercase    :      Optional[Any]       = 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:
												lowercase    :      str       = item.ha.text
												lowercase    :      Tuple       = """https://www.amazon.in/""" + item.ha.a["""href"""]
												lowercase    :      Tuple       = item.find("""span"""  ,				attrs={"""class""": """a-offscreen"""} ).text
												try:
																lowercase    :      Any       = item.find("""span"""  ,				attrs={"""class""": """a-icon-alt"""} ).text
												except AttributeError:
																lowercase    :      Tuple       = """Not available"""
												try:
																lowercase    :      Any       = (
																    """₹"""
																    + item.find(
																        """span"""  ,				attrs={"""class""": """a-price a-text-price"""} ).text.split("""₹""" )[1]
																)
												except AttributeError:
																lowercase    :      Any       = """"""
												try:
																lowercase    :      List[str]       = float(
																    (
																        (
																            float(product_mrp.strip("""₹""" ).replace(""","""  ,				"""""" ) )
																            - float(product_price.strip("""₹""" ).replace(""","""  ,				"""""" ) )
																        )
																        / float(product_mrp.strip("""₹""" ).replace(""","""  ,				"""""" ) )
																    )
																    * 100 )
												except ValueError:
																lowercase    :      Tuple       = float("""nan""" )
								except AttributeError:
												pass
								lowercase    :      Union[str, Any]       = [
								    product_title,
								    product_link,
								    product_price,
								    product_rating,
								    product_mrp,
								    discount,
								]
				lowercase    :      Tuple       = """ """
				lowercase    :      List[str]       = """ """
				data_frame.index += 1
				return data_frame


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