




from itertools import zip_longest

import requests
from bsa import BeautifulSoup
from pandas import DataFrame



def       UpperCAmelCase       (     _snake_case = "laptop"							):
							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(_snake_case						, headers=_snake_case							).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__":
		UpperCAmelCase_						="""headphones"""
		get_amazon_product_data(product).to_csv(F'''Amazon Product Data for {product}.csv''')









from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


UpperCAmelCase_						={
    """configuration_jukebox""": [
        """JUKEBOX_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """JukeboxConfig""",
        """JukeboxPriorConfig""",
        """JukeboxVQVAEConfig""",
    ],
    """tokenization_jukebox""": ["""JukeboxTokenizer"""],
}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		UpperCAmelCase_						=[
		    """JUKEBOX_PRETRAINED_MODEL_ARCHIVE_LIST""",
		    """JukeboxModel""",
		    """JukeboxPreTrainedModel""",
		    """JukeboxVQVAE""",
		    """JukeboxPrior""",
		]

if TYPE_CHECKING:
		from .configuration_jukebox import (
		    JUKEBOX_PRETRAINED_CONFIG_ARCHIVE_MAP,
		    JukeboxConfig,
		    JukeboxPriorConfig,
		    JukeboxVQVAEConfig,
		)
		from .tokenization_jukebox import JukeboxTokenizer

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_jukebox import (
				    JUKEBOX_PRETRAINED_MODEL_ARCHIVE_LIST,
				    JukeboxModel,
				    JukeboxPreTrainedModel,
				    JukeboxPrior,
				    JukeboxVQVAE,
				)

else:
		import sys

		UpperCAmelCase_						=_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)



