






from itertools import zip_longest

import requests
from bsa import BeautifulSoup
from pandas import DataFrame

def   snake_case (UpperCAmelCase__ = "laptop"  )	->    DataFrame:
  UpperCamelCase_: Dict   				=    F'''https://www.amazon.in/laptop/s?k={product}'''
  UpperCamelCase_: Union[str, Any]   				=    {
      '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',
  }
  UpperCamelCase_: str   				=    BeautifulSoup(requests.get(UpperCAmelCase__     ,   headers=UpperCAmelCase__  ).text  )
  # Initialize a Pandas dataframe with the column titles
  UpperCamelCase_: List[Any]   				=    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:
      UpperCamelCase_: Tuple   				=    item.ha.text
      UpperCamelCase_: Optional[int]   				=    'https://www.amazon.in/' + item.ha.a['href']
      UpperCamelCase_: Dict   				=    item.find('span'     ,   attrs={'class': 'a-offscreen'}  ).text
      try:
        UpperCamelCase_: str   				=    item.find('span'     ,   attrs={'class': 'a-icon-alt'}  ).text
      except AttributeError:
        UpperCamelCase_: Union[str, Any]   				=    'Not available'
      try:
        UpperCamelCase_: Dict   				=    (
            '₹'
            + item.find(
                'span'     ,   attrs={'class': 'a-price a-text-price'}  ).text.split('₹'  )[1]
        )
      except AttributeError:
        UpperCamelCase_: Any   				=    ''
      try:
        UpperCamelCase_: Optional[Any]   				=    float(
            (
                (
                    float(product_mrp.strip('₹'  ).replace(','     ,   ''  )  )
                    - float(product_price.strip('₹'  ).replace(','     ,   ''  )  )
                )
                / float(product_mrp.strip('₹'  ).replace(','     ,   ''  )  )
            )
            * 1_0_0  )
      except ValueError:
        UpperCamelCase_: Dict   				=    float('nan'  )
    except AttributeError:
      pass
    UpperCamelCase_: Any   				=    [
        product_title,
        product_link,
        product_price,
        product_rating,
        product_mrp,
        discount,
    ]
  UpperCamelCase_: Optional[int]   				=    ' '
  UpperCamelCase_: int   				=    ' '
  data_frame.index += 1
  return data_frame


if __name__ == "__main__":
   A_		:		str		     =			'headphones'
   get_amazon_product_data(product).to_csv(F'''Amazon Product Data for {product}.csv''')







from abc import ABC, abstractmethod
from argparse import ArgumentParser




class     _lowerCAmelCase(	UpperCAmelCase_ ):





       """simple docstring"""







       @staticmethod
       @abstractmethod
       def       _a   ( _lowerCamelCase							):
         raise NotImplementedError()





       @abstractmethod
       def       _a   ( self							):
         raise NotImplementedError()