


'''simple docstring'''


from itertools import zip_longest

import requests
from bsa import BeautifulSoup
from pandas import DataFrame






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






from __future__ import annotations

import numpy as np





def 					__lowerCamelCase	( UpperCamelCase__      ):







							'''simple docstring'''






							snake_case_				,    snake_case_							=    np.shape(UpperCamelCase__      )
							if rows != columns:
														snake_case_							=    (
														    '\'table\' has to be of square shaped array but got a '
														    F'''{rows}x{columns} array:\n{table}'''
														)
														raise ValueError(UpperCamelCase__      )

							snake_case_							=    np.zeros((rows, columns)      )
							snake_case_							=    np.zeros((rows, columns)      )
							for i in range(UpperCamelCase__      ):
														for j in range(UpperCamelCase__      ):
																					snake_case_							=    sum(lower[i][k] * upper[k][j] for k in range(UpperCamelCase__      )      )
																					if upper[j][j] == 0:
																												raise ArithmeticError('No LU decomposition exists'      )
																					snake_case_							=    (table[i][j] - total) / upper[j][j]
														snake_case_							=    1
														for j in range(UpperCamelCase__   ,							UpperCamelCase__      ):
																					snake_case_							=    sum(lower[i][k] * upper[k][j] for k in range(UpperCamelCase__      )      )
																					snake_case_							=    table[i][j] - total
							return lower, upper


if __name__ == "__main__":
					import doctest

					doctest.testmod()




