





"""simple docstring"""
import asyncio
import os
import shutil
import subprocess
import sys
import tempfile
import unittest
from distutils.util import strtobool
from functools import partial
from pathlib import Path
from typing import List, Union
from unittest import mock

import torch

from ..state import AcceleratorState, PartialState
from ..utils import (
    gather,
    is_bnb_available,
    is_comet_ml_available,
    is_datasets_available,
    is_deepspeed_available,
    is_mps_available,
    is_safetensors_available,
    is_tensorboard_available,
    is_torch_version,
    is_tpu_available,
    is_transformers_available,
    is_wandb_available,
    is_xpu_available,
)



def        lowerCAmelCase_(   lowercase_     :							Any						,   lowercase_     :							Union[str, Any]=False							)	->       Dict:
				try:
								_lowerCamelCase        =				os.environ[key]
				except KeyError:
								# KEY isn't set, default to `default`.
								_lowerCamelCase        =				default
				else:
								# KEY is set, convert it to True or False.
								try:
												_lowerCamelCase        =				strtobool(lowercase_							)
								except ValueError:
												# More values are supported, but let's keep the message simple.
												raise ValueError(F"""If set, {key} must be yes or no."""							)
				return _value


__SCREAMING_SNAKE_CASE  :						int    							=      parse_flag_from_env('''RUN_SLOW''', default=False)



def        lowerCAmelCase_(   lowercase_     :							str							)	->       Union[str, Any]:
				return unittest.skip('''Test was skipped'''							)(lowercase_							)



def        lowerCAmelCase_(   lowercase_     :							Union[str, Any]							)	->       Tuple:
				return unittest.skipUnless(_run_slow_tests						,   '''test is slow'''							)(lowercase_							)



def        lowerCAmelCase_(   lowercase_     :							Dict							)	->       Optional[int]:
				return unittest.skipUnless(not torch.cuda.is_available()						,   '''test requires only a CPU'''							)(lowercase_							)



def        lowerCAmelCase_(   lowercase_     :							Optional[int]							)	->       Optional[int]:
				return unittest.skipUnless(torch.cuda.is_available()						,   '''test requires a GPU'''							)(lowercase_							)



def        lowerCAmelCase_(   lowercase_     :							Tuple							)	->       int:
				return unittest.skipUnless(is_xpu_available()						,   '''test requires a XPU'''							)(lowercase_							)



def        lowerCAmelCase_(   lowercase_     :							List[Any]							)	->       List[str]:
				return unittest.skipUnless(is_mps_available()						,   '''test requires a `mps` backend support in `torch`'''							)(lowercase_							)



def        lowerCAmelCase_(   lowercase_     :							Optional[int]							)	->       str:
				return unittest.skipUnless(
				    is_transformers_available() and is_datasets_available()						,   '''test requires the Hugging Face suite'''							)(lowercase_							)



def        lowerCAmelCase_(   lowercase_     :							Union[str, Any]							)	->       Dict:
				return unittest.skipUnless(is_bnb_available()						,   '''test requires the bitsandbytes library'''							)(lowercase_							)



def        lowerCAmelCase_(   lowercase_     :							Any							)	->       List[str]:
				return unittest.skipUnless(is_tpu_available()						,   '''test requires TPU'''							)(lowercase_							)



def        lowerCAmelCase_(   lowercase_     :							List[str]							)	->       Dict:
				return unittest.skipUnless(torch.cuda.device_count() == 1						,   '''test requires a GPU'''							)(lowercase_							)



def        lowerCAmelCase_(   lowercase_     :							List[Any]							)	->       List[Any]:
				return unittest.skipUnless(torch.xpu.device_count() == 1						,   '''test requires a XPU'''							)(lowercase_							)



def        lowerCAmelCase_(   lowercase_     :							Optional[int]							)	->       Optional[Any]:
				return unittest.skipUnless(torch.cuda.device_count() > 1						,   '''test requires multiple GPUs'''							)(lowercase_							)



def        lowerCAmelCase_(   lowercase_     :							Any							)	->       Tuple:
				return unittest.skipUnless(torch.xpu.device_count() > 1						,   '''test requires multiple XPUs'''							)(lowercase_							)



def        lowerCAmelCase_(   lowercase_     :							Optional[Any]							)	->       List[Any]:
				return unittest.skipUnless(is_safetensors_available()						,   '''test requires safetensors'''							)(lowercase_							)



def        lowerCAmelCase_(   lowercase_     :							str							)	->       List[Any]:
				return unittest.skipUnless(is_deepspeed_available()						,   '''test requires DeepSpeed'''							)(lowercase_							)



def        lowerCAmelCase_(   lowercase_     :							str							)	->       int:
				return unittest.skipUnless(is_torch_version('''>='''						,   '''1.12.0'''							)						,   '''test requires torch version >= 1.12.0'''							)(lowercase_							)



def        lowerCAmelCase_(   lowercase_     :							List[Any]=None						,   lowercase_     :							List[Any]=None							)	->       List[Any]:
				if test_case is None:
								return partial(lowercase_						,   version=lowercase_							)
				return unittest.skipUnless(is_torch_version('''>='''						,   lowercase_							)						,   F"""test requires torch version >= {version}"""							)(lowercase_							)



def        lowerCAmelCase_(   lowercase_     :							Any							)	->       Optional[int]:
				return unittest.skipUnless(is_tensorboard_available()						,   '''test requires Tensorboard'''							)(lowercase_							)



def        lowerCAmelCase_(   lowercase_     :							List[str]							)	->       str:
				return unittest.skipUnless(is_wandb_available()						,   '''test requires wandb'''							)(lowercase_							)



def        lowerCAmelCase_(   lowercase_     :							Tuple							)	->       List[Any]:
				return unittest.skipUnless(is_comet_ml_available()						,   '''test requires comet_ml'''							)(lowercase_							)


__SCREAMING_SNAKE_CASE  :						Optional[Any]    							=      (
    any([is_wandb_available(), is_tensorboard_available()]) and not is_comet_ml_available()
)



def        lowerCAmelCase_(   lowercase_     :							Optional[int]							)	->       Tuple:
				return unittest.skipUnless(
				    _atleast_one_tracker_available						,   '''test requires at least one tracker to be available and for `comet_ml` to not be installed'''						,   )(lowercase_							)


class 							lowerCamelCase_(   unittest.TestCase    ):





					'''simple docstring'''



					lowercase__   :       Union[str, Any]										= True

					@classmethod
					def 			snake_case__      (    cls   ):
									_lowerCamelCase        =				tempfile.mkdtemp()

					@classmethod
					def 			snake_case__      (    cls   ):
									if os.path.exists(cls.tmpdir   ):
													shutil.rmtree(cls.tmpdir   )





					def 			snake_case__      (    self   ):
									if self.clear_on_setup:
													for path in Path(self.tmpdir   ).glob('''**/*'''   ):
																	if path.is_file():
																					path.unlink()
																	elif path.is_dir():
																					shutil.rmtree(lowerCamelCase__   )


class 							lowerCamelCase_(   unittest.TestCase    ):





					'''simple docstring'''



					def 			snake_case__      (    self   ):
									super().tearDown()
									# Reset the state of the AcceleratorState singleton.
									AcceleratorState._reset_state()
									PartialState._reset_state()


class 							lowerCamelCase_(   unittest.TestCase    ):





					'''simple docstring'''



					def 			snake_case__      (    self				,       lowerCamelCase__   ):
									_lowerCamelCase        =				mocks if isinstance(lowerCamelCase__				,       (tuple, list)   ) else [mocks]
									for m in self.mocks:
													m.start()
													self.addCleanup(m.stop   )



def        lowerCAmelCase_(   lowercase_     :							Optional[int]							)	->       Any:
				_lowerCamelCase        =				AcceleratorState()
				_lowerCamelCase        =				tensor[None].clone().to(state.device							)
				_lowerCamelCase        =				gather(lowercase_							).cpu()
				_lowerCamelCase        =				tensor[0].cpu()
				for i in range(tensors.shape[0]							):
								if not torch.equal(tensors[i]						,   lowercase_							):
												return False
				return True


class 							lowerCamelCase_:





					'''simple docstring'''



					def __init__(    self				,       lowerCamelCase__				,       lowerCamelCase__				,       lowerCamelCase__   ):
									_lowerCamelCase        =				returncode
									_lowerCamelCase        =				stdout
									_lowerCamelCase        =				stderr



async def        lowerCAmelCase_(   lowercase_     :							Union[str, Any]						,   lowercase_     :							int							)	->       Optional[int]:
				while True:
								_lowerCamelCase        =				await stream.readline()
								if line:
												callback(lowercase_							)
								else:
												break



async def        lowerCAmelCase_(   lowercase_     :							List[Any]						,   lowercase_     :							Union[str, Any]=None						,   lowercase_     :							Tuple=None						,   lowercase_     :							List[str]=None						,   lowercase_     :							Union[str, Any]=False						,   lowercase_     :							Union[str, Any]=False							)	->       _RunOutput:
				if echo:
								print('''\nRunning: '''						,   ''' '''.join(lowercase_							)							)

				_lowerCamelCase        =				await asyncio.create_subprocess_exec(
				    cmd[0]						,   *cmd[1:]						,   stdin=lowercase_						,   stdout=asyncio.subprocess.PIPE						,   stderr=asyncio.subprocess.PIPE						,   env=lowercase_						,   )

				# note: there is a warning for a possible deadlock when using `wait` with huge amounts of data in the pipe
				# https://docs.python.org/3/library/asyncio-subprocess.html#asyncio.asyncio.subprocess.Process.wait
				#
				# If it starts hanging, will need to switch to the following code. The problem is that no data
				# will be seen until it's done and if it hangs for example there will be no debug info.
				# out, err = await p.communicate()
				# return _RunOutput(p.returncode, out, err)

				_lowerCamelCase        =				[]
				_lowerCamelCase        =				[]

				def tee(lowercase_     :							int						,   lowercase_     :							List[Any]						,   lowercase_     :							Dict						,   lowercase_     :							List[str]=""							):
								_lowerCamelCase        =				line.decode('''utf-8'''							).rstrip()
								sink.append(lowercase_							)
								if not quiet:
												print(lowercase_						,   lowercase_						,   file=lowercase_							)

    # XXX: the timeout doesn't seem to make any difference here
				await asyncio.wait(
				    [
				        asyncio.create_task(_read_stream(p.stdout						,   lambda lowercase_							: tee(lowercase_						,   lowercase_						,   sys.stdout						,   label='''stdout:'''							)							)							),
				        asyncio.create_task(_read_stream(p.stderr						,   lambda lowercase_							: tee(lowercase_						,   lowercase_						,   sys.stderr						,   label='''stderr:'''							)							)							),
				    ]						,   timeout=lowercase_						,   )
				return _RunOutput(await p.wait()						,   lowercase_						,   lowercase_							)



def        lowerCAmelCase_(   lowercase_     :							Union[str, Any]						,   lowercase_     :							Optional[Any]=None						,   lowercase_     :							Any=None						,   lowercase_     :							Any=1_80						,   lowercase_     :							Optional[int]=False						,   lowercase_     :							Optional[Any]=True							)	->       _RunOutput:
				_lowerCamelCase        =				asyncio.get_event_loop()
				_lowerCamelCase        =				loop.run_until_complete(
				    _stream_subprocess(lowercase_						,   env=lowercase_						,   stdin=lowercase_						,   timeout=lowercase_						,   quiet=lowercase_						,   echo=lowercase_							)							)

				_lowerCamelCase        =				''' '''.join(lowercase_							)
				if result.returncode > 0:
								_lowerCamelCase        =				'''\n'''.join(result.stderr							)
								raise RuntimeError(
								    F"""'{cmd_str}' failed with returncode {result.returncode}\n\n"""
								    F"""The combined stderr from workers follows:\n{stderr}"""							)

				return result


class 							lowerCamelCase_(   A__    ):





					'''simple docstring'''



					pass



def        lowerCAmelCase_(   lowercase_     :							List[str]						,   lowercase_     :							Dict=False							)	->       Optional[int]:
				try:
								_lowerCamelCase        =				subprocess.check_output(lowercase_						,   stderr=subprocess.STDOUT							)
								if return_stdout:
												if hasattr(lowercase_						,   '''decode'''							):
																_lowerCamelCase        =				output.decode('''utf-8'''							)
												return output
				except subprocess.CalledProcessError as e:
								raise SubprocessCallException(
								    F"""Command `{" ".join(lowercase_							)}` failed with the following error:\n\n{e.output.decode()}"""							) from e





"""simple docstring"""
from itertools import zip_longest

import requests
from bsa import BeautifulSoup
from pandas import DataFrame



def        lowerCAmelCase_(   lowercase_     :							str = "laptop"							)	->       DataFrame:
				_lowerCamelCase        =				F"""https://www.amazon.in/laptop/s?k={product}"""
				_lowerCamelCase        =				{
				    '''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''',
				}
				_lowerCamelCase        =				BeautifulSoup(requests.get(lowercase_						,   headers=lowercase_							).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(''','''						,   ''''''							)							)
																    )
																    * 1_00							)
												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__":
			__SCREAMING_SNAKE_CASE  :						Optional[int]    							=      '''headphones'''
			get_amazon_product_data(product).to_csv(F"""Amazon Product Data for {product}.csv""")
