
import math






def   lowerCAmelCase_						(					)				->		None:







	'''simple docstring'''


	__magic_name__		:		Dict	   =     input("Enter message: "   )
	__magic_name__		:		Dict	   =     int(input(F'''Enter key [2-{len(_snake_case   ) - 1}]: '''   )   )
	__magic_name__		:		Optional[int]	   =     input("Encryption/Decryption [e/d]: "   )

	if mode.lower().startswith("e"   ):
		__magic_name__		:		Union[str, Any]	   =     encrypt_message(_snake_case      ,   _snake_case   )
	elif mode.lower().startswith("d"   ):
		__magic_name__		:		Dict	   =     decrypt_message(_snake_case      ,   _snake_case   )

	# Append pipe symbol (vertical bar) to identify spaces at the end.
	print(F'''Output:\n{text + "|"}'''   )






def   lowerCAmelCase_						(					_snake_case      :  int      ,   _snake_case      :  str   )				->		str:







	'''simple docstring'''


	__magic_name__		:		Optional[int]	   =     [""] * key
	for col in range(_snake_case   ):
		__magic_name__		:		Union[str, Any]	   =     col
		while pointer < len(_snake_case   ):
			cipher_text[col] += message[pointer]
			pointer += key
	return "".join(_snake_case   )






def   lowerCAmelCase_						(					_snake_case      :  int      ,   _snake_case      :  str   )				->		str:







	'''simple docstring'''


	__magic_name__		:		Tuple	   =     math.ceil(len(_snake_case   ) / key   )
	__magic_name__		:		int	   =     key
	__magic_name__		:		Tuple	   =     (num_cols * num_rows) - len(_snake_case   )
	__magic_name__		:		int	   =     [""] * num_cols
	__magic_name__		:		Dict	   =     0
	__magic_name__		:		Dict	   =     0

	for symbol in message:
		plain_text[col] += symbol
		col += 1

		if (
		    (col == num_cols)
		    or (col == num_cols - 1)
		    and (row >= num_rows - num_shaded_boxes)
		):
			__magic_name__		:		Any	   =     0
			row += 1

	return "".join(_snake_case   )


if __name__ == "__main__":
				import doctest

				doctest.testmod()
				main()


from itertools import zip_longest

import requests
from bsa import BeautifulSoup
from pandas import DataFrame






def   lowerCAmelCase_						(					_snake_case      :  str = "laptop"   )				->		DataFrame:







	'''simple docstring'''


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