
from __future__ import annotations

import string
from itertools import cycle, product
from pathlib import Path

__magic_name__            =  (
    string.ascii_letters + string.digits + string.punctuation + string.whitespace
)
__magic_name__            =  [ord(letter) for letter in string.ascii_lowercase]
__magic_name__            =  {ord(char) for char in VALID_CHARS}

__magic_name__            =  ["the", "be", "to", "of", "and", "in", "that", "have"]





def 	SCREAMING_SNAKE_CASE__    (      __lowerCAmelCase    ,		__lowerCAmelCase							):
    snake_case__						=				""
    snake_case__						=				42
    snake_case__						=				42
    snake_case__						=				42

    for keychar, cipherchar in zip(cycle(__lowerCAmelCase							)    ,		__lowerCAmelCase							):
        snake_case__						=				cipherchar ^ keychar
        if decodedchar not in VALID_INTS:
            return None
        decoded += chr(__lowerCAmelCase							)

    return decoded





def 	SCREAMING_SNAKE_CASE__    (      __lowerCAmelCase							):
    snake_case__						=				[]
    for key in product(__lowerCAmelCase    ,		repeat=3							):
        snake_case__						=				try_key(__lowerCAmelCase    ,		__lowerCAmelCase							)
        if encoded is not None:
            possibles.append(__lowerCAmelCase							)
    return possibles





def 	SCREAMING_SNAKE_CASE__    (      __lowerCAmelCase    ,		__lowerCAmelCase							):
    return [possible for possible in possibles if common_word in possible.lower()]





def 	SCREAMING_SNAKE_CASE__    (      __lowerCAmelCase = "p059_cipher.txt"							):
    snake_case__						=				42
    snake_case__						=				42
    snake_case__						=				42
    snake_case__						=				42
    snake_case__						=				Path(__lowerCAmelCase							).parent.joinpath(__lowerCAmelCase							).read_text(encoding="utf-8"							)

    snake_case__						=				[int(__lowerCAmelCase							) for number in data.strip().split(","							)]

    snake_case__						=				filter_valid_chars(__lowerCAmelCase							)
    for common_word in COMMON_WORDS:
        snake_case__						=				filter_common_word(__lowerCAmelCase    ,		__lowerCAmelCase							)
        if len(__lowerCAmelCase							) == 1:
            break

    snake_case__						=				possibles[0]
    return sum(ord(__lowerCAmelCase							) for char in decoded_text							)


if __name__ == "__main__":
     print(F'''{solution() = }''')





from itertools import zip_longest

import requests
from bsa import BeautifulSoup
from pandas import DataFrame





def 	SCREAMING_SNAKE_CASE__    (      __lowerCAmelCase = "laptop"							):
    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(__lowerCAmelCase    ,		headers=__lowerCAmelCase							).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__":
     __magic_name__            =  '''headphones'''
     get_amazon_product_data(product).to_csv(F'''Amazon Product Data for {product}.csv''')



