



"""simple docstring"""






def 			_lowercase				(  __snake_case					,__snake_case					,__snake_case	)						->   int:

			def update_area_of_max_square(__snake_case					,__snake_case	) -> int:
						# BASE CASE
						if row >= rows or col >= cols:
									return 0

						__lowerCAmelCase      :  Tuple												=       update_area_of_max_square(__snake_case					,col + 1	)
						__lowerCAmelCase      :  Union[str, Any]												=       update_area_of_max_square(row + 1					,col + 1	)
						__lowerCAmelCase      :  Union[str, Any]												=       update_area_of_max_square(row + 1					,__snake_case	)

						if mat[row][col]:
									__lowerCAmelCase      :  Optional[int]												=       1 + min([right, diagonal, down]	)
									__lowerCAmelCase      :  Optional[Any]												=       max(largest_square_area[0]					,__snake_case	)
									return sub_problem_sol
						else:
									return 0

			__lowerCAmelCase      :  Union[str, Any]												=       [0]
			update_area_of_max_square(0					,0	)
			return largest_square_area[0]


def 			_lowercase				(  __snake_case					,__snake_case					,__snake_case	)						->   int:

			def update_area_of_max_square_using_dp_array(
			    __snake_case					,__snake_case					,__snake_case	) -> int:
						if row >= rows or col >= cols:
									return 0
						if dp_array[row][col] != -1:
									return dp_array[row][col]

						__lowerCAmelCase      :  Optional[Any]												=       update_area_of_max_square_using_dp_array(__snake_case					,col + 1					,__snake_case	)
						__lowerCAmelCase      :  Dict												=       update_area_of_max_square_using_dp_array(row + 1					,col + 1					,__snake_case	)
						__lowerCAmelCase      :  Optional[Any]												=       update_area_of_max_square_using_dp_array(row + 1					,__snake_case					,__snake_case	)

						if mat[row][col]:
									__lowerCAmelCase      :  int												=       1 + min([right, diagonal, down]	)
									__lowerCAmelCase      :  Union[str, Any]												=       max(largest_square_area[0]					,__snake_case	)
									__lowerCAmelCase      :  Tuple												=       sub_problem_sol
									return sub_problem_sol
						else:
									return 0

			__lowerCAmelCase      :  Optional[Any]												=       [0]
			__lowerCAmelCase      :  Union[str, Any]												=       [[-1] * cols for _ in range(__snake_case	)]
			update_area_of_max_square_using_dp_array(0					,0					,__snake_case	)

			return largest_square_area[0]


def 			_lowercase				(  __snake_case					,__snake_case					,__snake_case	)						->   int:
			__lowerCAmelCase      :  Union[str, Any]												=       [[0] * (cols + 1) for _ in range(rows + 1	)]
			__lowerCAmelCase      :  Optional[int]												=       0
			for row in range(rows - 1					,-1					,-1	):
						for col in range(cols - 1					,-1					,-1	):
									__lowerCAmelCase      :  str												=       dp_array[row][col + 1]
									__lowerCAmelCase      :  int												=       dp_array[row + 1][col + 1]
									__lowerCAmelCase      :  Union[str, Any]												=       dp_array[row + 1][col]

									if mat[row][col] == 1:
												__lowerCAmelCase      :  Dict												=       1 + min(__snake_case					,__snake_case					,__snake_case	)
												__lowerCAmelCase      :  Optional[Any]												=       max(dp_array[row][col]					,__snake_case	)
									else:
												__lowerCAmelCase      :  int												=       0

			return largest_square_area


def 			_lowercase				(  __snake_case					,__snake_case					,__snake_case	)						->   int:
			__lowerCAmelCase      :  Union[str, Any]												=       [0] * (cols + 1)
			__lowerCAmelCase      :  Dict												=       [0] * (cols + 1)
			__lowerCAmelCase      :  Dict												=       0
			for row in range(rows - 1					,-1					,-1	):
						for col in range(cols - 1					,-1					,-1	):
									__lowerCAmelCase      :  Optional[int]												=       current_row[col + 1]
									__lowerCAmelCase      :  int												=       next_row[col + 1]
									__lowerCAmelCase      :  List[str]												=       next_row[col]

									if mat[row][col] == 1:
												__lowerCAmelCase      :  str												=       1 + min(__snake_case					,__snake_case					,__snake_case	)
												__lowerCAmelCase      :  Optional[Any]												=       max(current_row[col]					,__snake_case	)
									else:
												__lowerCAmelCase      :  Union[str, Any]												=       0
						__lowerCAmelCase      :  Optional[int]												=       current_row

			return largest_square_area


if __name__ == "__main__":
	import doctest

	doctest.testmod()
	print(largest_square_area_in_matrix_bottom_up(2, 2, [[1, 1], [1, 1]]))




"""simple docstring"""






from itertools import zip_longest

import requests
from bsa import BeautifulSoup
from pandas import DataFrame


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


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