






'''simple docstring'''



from itertools import zip_longest

import requests
from bsa import BeautifulSoup
from pandas import DataFrame



def  __UpperCAmelCase						(					SCREAMING_SNAKE_CASE__:						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\n        (KHTML, like Gecko)Chrome/44.0.2403.157 Safari/537.36',
       'Accept-Language': 'en-US, en;q=0.5',
   }
   __a					  =     BeautifulSoup(requests.get(SCREAMING_SNAKE_CASE__,       headers=SCREAMING_SNAKE_CASE__     ).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(',',       ''     )     )
                )
                * 100     )
         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__":
 __UpperCamelCase   :							str         =   """headphones"""
 get_amazon_product_data(product).to_csv(f"""Amazon Product Data for {product}.csv""")







'''simple docstring'''



__UpperCamelCase   :							List[Any]         =   """ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/"""



def  __UpperCAmelCase						(					SCREAMING_SNAKE_CASE__:						bytes     )	->      bytes:

   """simple docstring"""
   # Make sure the supplied data is a bytes-like object
   if not isinstance(SCREAMING_SNAKE_CASE__,       SCREAMING_SNAKE_CASE__     ):
      __a					  =     f"""a bytes-like object is required, not '{data.__class__.__name__}'"""
      raise TypeError(SCREAMING_SNAKE_CASE__     )

   __a					  =     ''.join(bin(SCREAMING_SNAKE_CASE__     )[2:].zfill(8     ) for byte in data     )

   __a					  =     len(SCREAMING_SNAKE_CASE__     ) % 6 != 0

   if padding_needed:
      # The padding that will be added later
      __a					  =     b'=' * ((6 - len(SCREAMING_SNAKE_CASE__     ) % 6) // 2)

      # Append binary_stream with arbitrary binary digits (0's by default) to make its
      # length a multiple of 6.
      binary_stream += "0" * (6 - len(SCREAMING_SNAKE_CASE__     ) % 6)
   else:
      __a					  =     b''

   # Encode every 6 binary digits to their corresponding Base64 character
   return (
       "".join(
           B64_CHARSET[int(binary_stream[index : index + 6],       2     )]
           for index in range(0,       len(SCREAMING_SNAKE_CASE__     ),       6     )     ).encode()
       + padding
   )



def  __UpperCAmelCase						(					SCREAMING_SNAKE_CASE__:						str     )	->      bytes:

   """simple docstring"""
   # Make sure encoded_data is either a string or a bytes-like object
   if not isinstance(SCREAMING_SNAKE_CASE__,       SCREAMING_SNAKE_CASE__     ) and not isinstance(SCREAMING_SNAKE_CASE__,       SCREAMING_SNAKE_CASE__     ):
      __a					  =     (
          'argument should be a bytes-like object or ASCII string, '
          f"""not '{encoded_data.__class__.__name__}'"""
      )
      raise TypeError(SCREAMING_SNAKE_CASE__     )

   # In case encoded_data is a bytes-like object, make sure it contains only
   # ASCII characters so we convert it to a string object
   if isinstance(SCREAMING_SNAKE_CASE__,       SCREAMING_SNAKE_CASE__     ):
      try:
         __a					  =     encoded_data.decode('utf-8'     )
      except UnicodeDecodeError:
         raise ValueError('base64 encoded data should only contain ASCII characters'     )

   __a					  =     encoded_data.count('='     )

   # Check if the encoded string contains non base64 characters
   if padding:
      assert all(
          char in B64_CHARSET for char in encoded_data[:-padding]     ), "Invalid base64 character(s) found."
   else:
      assert all(
          char in B64_CHARSET for char in encoded_data     ), "Invalid base64 character(s) found."

   # Check the padding
   assert len(SCREAMING_SNAKE_CASE__     ) % 4 == 0 and padding < 3, "Incorrect padding"

   if padding:
      # Remove padding if there is one
      __a					  =     encoded_data[:-padding]

      __a					  =     ''.join(
          bin(B64_CHARSET.index(SCREAMING_SNAKE_CASE__     )     )[2:].zfill(6     ) for char in encoded_data     )[: -padding * 2]
   else:
      __a					  =     ''.join(
          bin(B64_CHARSET.index(SCREAMING_SNAKE_CASE__     )     )[2:].zfill(6     ) for char in encoded_data     )

   __a					  =     [
       int(binary_stream[index : index + 8],       2     )
       for index in range(0,       len(SCREAMING_SNAKE_CASE__     ),       8     )
   ]

   return bytes(SCREAMING_SNAKE_CASE__     )


if __name__ == "__main__":
 import doctest

 doctest.testmod()