






"""simple docstring"""







from itertools import zip_longest

import requests
from bsa import BeautifulSoup
from pandas import DataFrame

def _a			(		_snake_case = "laptop"							):







						"""simple docstring"""






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


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











"""simple docstring"""







from pathlib import Path
from typing import List

from transformers import is_torch_available, is_vision_available
from transformers.testing_utils import get_tests_dir, is_tool_test
from transformers.tools.agent_types import AGENT_TYPE_MAPPING, AgentAudio, AgentImage, AgentText


if is_torch_available():
  import torch

if is_vision_available():
  from PIL import Image


_UpperCamelCase					      =  ["""text""", """image""", """audio"""]

def _a			(		_snake_case							):







      """simple docstring"""






      UpperCAmelCase          =	[]

      for input_type in input_types:
            if input_type == "text":
                  inputs.append("""Text input"""							)
            elif input_type == "image":
                  inputs.append(
                      Image.open(Path(get_tests_dir("""fixtures/tests_samples/COCO"""							)							) / """000000039769.png"""							).resize((512, 512)							)							)
            elif input_type == "audio":
                  inputs.append(torch.ones(3000							)							)
            elif isinstance(_snake_case				,	_snake_case							):
                  inputs.append(create_inputs(_snake_case							)							)
            else:
                  raise ValueError(F'''Invalid type requested: {input_type}'''							)

      return inputs

def _a			(		_snake_case							):







      """simple docstring"""






      UpperCAmelCase          =	[]

      for output in outputs:
            if isinstance(_snake_case				,	(str, AgentText)							):
                  output_types.append("""text"""							)
            elif isinstance(_snake_case				,	(Image.Image, AgentImage)							):
                  output_types.append("""image"""							)
            elif isinstance(_snake_case				,	(torch.Tensor, AgentAudio)							):
                  output_types.append("""audio"""							)
            else:
                  raise ValueError(F'''Invalid output: {output}'''							)

      return output_types







@is_tool_test
class  lowerCamelCase__ :






    def     _UpperCamelCase							(			self ):
          self.assertTrue(hasattr(self.tool     ,"""inputs""" ) )
          self.assertTrue(hasattr(self.tool     ,"""outputs""" ) )

          UpperCAmelCase          =	self.tool.inputs
          for _input in inputs:
                if isinstance(_input     ,A ):
                      for __input in _input:
                            self.assertTrue(__input in authorized_types )
                else:
                      self.assertTrue(_input in authorized_types )

          UpperCAmelCase          =	self.tool.outputs
          for _output in outputs:
                self.assertTrue(_output in authorized_types )






    def     _UpperCamelCase							(			self ):
          UpperCAmelCase          =	create_inputs(self.tool.inputs )
          UpperCAmelCase          =	self.tool(*A )

          # There is a single output
          if len(self.tool.outputs ) == 1:
                UpperCAmelCase          =	[outputs]

          self.assertListEqual(output_types(A )     ,self.tool.outputs )






    def     _UpperCamelCase							(			self ):
          self.assertTrue(hasattr(self.tool     ,"""description""" ) )
          self.assertTrue(hasattr(self.tool     ,"""default_checkpoint""" ) )
          self.assertTrue(self.tool.description.startswith("""This is a tool that""" ) )






    def     _UpperCamelCase							(			self ):
          UpperCAmelCase          =	create_inputs(self.tool.inputs )
          UpperCAmelCase          =	self.tool(*A )

          if not isinstance(A     ,A ):
                UpperCAmelCase          =	[outputs]

          self.assertEqual(len(A )     ,len(self.tool.outputs ) )

          for output, output_type in zip(A     ,self.tool.outputs ):
                UpperCAmelCase          =	AGENT_TYPE_MAPPING[output_type]
                self.assertTrue(isinstance(A     ,A ) )






    def     _UpperCamelCase							(			self ):
          UpperCAmelCase          =	create_inputs(self.tool.inputs )

          UpperCAmelCase          =	[]

          for _input, input_type in zip(A     ,self.tool.inputs ):
                if isinstance(A     ,A ):
                      _inputs.append([AGENT_TYPE_MAPPING[_input_type](_input ) for _input_type in input_type] )
                else:
                      _inputs.append(AGENT_TYPE_MAPPING[input_type](_input ) )

        # Should not raise an error
          UpperCAmelCase          =	self.tool(*A )

          if not isinstance(A     ,A ):
                UpperCAmelCase          =	[outputs]

          self.assertEqual(len(A )     ,len(self.tool.outputs ) )



