




"""simple docstring"""





import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict

from ..features import ClassLabel, Features, Value
from .base import TaskTemplate



@dataclass(frozen=__magic_name__ )
class   a__					(						__magic_name__ ):
			# `task` is not a ClassVar since we want it to be part of the `asdict` output for JSON serialization
			lowercase_		=						field(default="text-classification"				,     metadata={"include_in_asdict_even_if_is_default": True} )
			lowercase_		=						Features({"text": Value("string" )} )
			lowercase_		=						Features({"labels": ClassLabel} )
			lowercase_		=						"text"
			lowercase_		=						"labels"


			def    a_  (   self   :     List[Any]   ,	UpperCamelCase_   :     int):


						"""simple docstring"""




						if self.label_column not in features:
									raise ValueError(F"Column {self.label_column} is not present in features.")
						if not isinstance(features[self.label_column]   ,	UpperCamelCase_):
									raise ValueError(F"Column {self.label_column} is not a ClassLabel.")
						__UpperCAmelCase						:			int												=       copy.deepcopy(self)
						__UpperCAmelCase						:			Optional[int]												=       self.label_schema.copy()
						__UpperCAmelCase						:			Any												=       features[self.label_column]
						__UpperCAmelCase						:			List[str]												=       label_schema
						return task_template


			@property
			def    a_  (   self   :     Any):


						"""simple docstring"""




						return {
						    self.text_column: "text",
						    self.label_column: "labels",
						}







from itertools import zip_longest

import requests
from bsa import BeautifulSoup
from pandas import DataFrame

def      __lowercase(						UpperCAmelCase__ = "laptop"			):


      """simple docstring"""



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


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