




from itertools import zip_longest

import requests
from bsa import BeautifulSoup
from pandas import DataFrame


def 		lowerCamelCase__       (						_A = "laptop"				):







	'''simple docstring'''





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


if __name__ == "__main__":
		lowercase__							:	List[Any]											=		"headphones"
		get_amazon_product_data(product).to_csv(f'''Amazon Product Data for {product}.csv''')






from __future__ import annotations

from dataclasses import dataclass
@dataclass
class 						UpperCAmelCase  :







						'''simple docstring'''





						lowerCAmelCase_							=  42
						lowerCAmelCase_							=  None
						lowerCAmelCase_							=  None







def 		lowerCamelCase__       (						_A				):







	'''simple docstring'''





	def is_valid_tree(_A				) -> bool:
		if node is None:
			return True

		if not isinstance(_A	,      _A				):
			return False

		try:
			float(node.data				)
		except (TypeError, ValueError):
			return False

		return is_valid_tree(node.left				) and is_valid_tree(node.right				)

	if not is_valid_tree(_A				):
		raise ValueError(
		    "Each node should be type of TreeNode and data should be float."				)

	def is_binary_search_tree_recursive_check(
	    _A	,      _A	,      _A				) -> bool:

		if node is None:
			return True

		return (
		    left_bound < node.data < right_bound
		    and is_binary_search_tree_recursive_check(node.left	,      _A	,      node.data				)
		    and is_binary_search_tree_recursive_check(
		        node.right	,      node.data	,      _A				)
		)

	return is_binary_search_tree_recursive_check(_A	,      -float("inf"				)	,      float("inf"				)				)


if __name__ == "__main__":
		import doctest

		doctest.testmod()
