






from itertools import zip_longest

import requests
from bsa import BeautifulSoup
from pandas import DataFrame



def 			_SCREAMING_SNAKE_CASE						( __lowercase   :			str = "laptop"    )						->      DataFrame:





    """simple docstring"""

    __A         =	f"https://www.amazon.in/laptop/s?k={product}"
    __A         =	{
        """User-Agent""": """Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36
        (KHTML, like Gecko)Chrome/44.0.2403.157 Safari/537.36""",
        """Accept-Language""": """en-US, en;q=0.5""",
    }
    __A         =	BeautifulSoup(requests.get(__lowercase			,				headers=__lowercase    ).text    )
    # Initialize a Pandas dataframe with the column titles
    __A         =	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:
            __A         =	item.ha.text
            __A         =	"""https://www.amazon.in/""" + item.ha.a["""href"""]
            __A         =	item.find("""span"""			,				attrs={"""class""": """a-offscreen"""}    ).text
            try:
                __A         =	item.find("""span"""			,				attrs={"""class""": """a-icon-alt"""}    ).text
            except AttributeError:
                __A         =	"""Not available"""
            try:
                __A         =	(
                    """₹"""
                    + item.find(
                        """span"""			,				attrs={"""class""": """a-price a-text-price"""}    ).text.split("""₹"""    )[1]
                )
            except AttributeError:
                __A         =	""""""
            try:
                __A         =	float(
                    (
                        (
                            float(product_mrp.strip("""₹"""    ).replace(""","""			,				""""""    )    )
                            - float(product_price.strip("""₹"""    ).replace(""","""			,				""""""    )    )
                        )
                        / float(product_mrp.strip("""₹"""    ).replace(""","""			,				""""""    )    )
                    )
                    * 1_0_0    )
            except ValueError:
                __A         =	float("""nan"""    )
        except AttributeError:
            pass
        __A         =	[
            product_title,
            product_link,
            product_price,
            product_rating,
            product_mrp,
            discount,
        ]
    __A         =	""" """
    __A         =	""" """
    data_frame.index += 1
    return data_frame


if __name__ == "__main__":
  __a      :       int				  =   "headphones"
  get_amazon_product_data(product).to_csv(f"""Amazon Product Data for {product}.csv""")












from collections.abc import Sequence



def 			_SCREAMING_SNAKE_CASE						( __lowercase   :			Sequence[float]			,				__lowercase   :			float    )						->      float:





    """simple docstring"""

    return sum(c * (x**i) for i, c in enumerate(__lowercase    )    )



def 			_SCREAMING_SNAKE_CASE						( __lowercase   :			Sequence[float]			,				__lowercase   :			float    )						->      float:





    """simple docstring"""

    __A         =	0.0
    for coeff in reversed(__lowercase    ):
        __A         =	result * x + coeff
    return result


if __name__ == "__main__":
  __a      :       Dict				  =   (0.0, 0.0, 5.0, 9.3, 7.0)
  __a      :       Optional[Any]				  =   1_0.0
  print(evaluate_poly(poly, x))
  print(horner(poly, x))




