
from itertools import zip_longest

import requests
from bsa import BeautifulSoup
from pandas import DataFrame



def 		lowercase_    (     A__ = "laptop"	)							->							DataFrame:
    """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__":
   _A						      =				"headphones"
   get_amazon_product_data(product).to_csv(f"Amazon Product Data for {product}.csv")



import os

# Precomputes a list of the 100 first triangular numbers
_A						      =				[int(0.5 * n * (n + 1)) for n in range(1, 1_01)]



def 		lowercase_    (     )							->							Tuple:
    """simple docstring"""

    snake_case				  =      os.path.dirname(os.path.realpath(A__	)	)
    snake_case				  =      os.path.join(A__				,	"words.txt"	)

    snake_case				  =      ""
    with open(A__	) as f:
        snake_case				  =      f.readline()

    snake_case				  =      [word.strip("\""	) for word in words.strip("\r\n"	).split(","	)]
    snake_case				  =      [
        word
        for word in [sum(ord(A__	) - 64 for x in word	) for word in words]
        if word in TRIANGULAR_NUMBERS
    ]
    return len(A__	)


if __name__ == "__main__":
   print(solution())

