

from itertools import zip_longest

import requests
from bsa import BeautifulSoup
from pandas import DataFrame





def 					__lowerCamelCase	( UpperCamelCase__ = "laptop"      ):







							'''simple docstring'''






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


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







import argparse
import os
from io import BytesIO
from pathlib import Path

import requests
from clip_retrieval.clip_client import ClipClient
from PIL import Image
from tqdm import tqdm





def 					__lowerCamelCase	( UpperCamelCase__   ,							UpperCamelCase__   ,							UpperCamelCase__      ):







							'''simple docstring'''






							snake_case_							=    1.5
							snake_case_							=    int(factor * num_class_images      )
							snake_case_							=    ClipClient(
							    url='https://knn.laion.ai/knn-service'   ,							indice_name='laion_400m'   ,							num_images=UpperCamelCase__   ,							aesthetic_weight=0.1      )

							os.makedirs(F'''{class_data_dir}/images'''   ,							exist_ok=UpperCamelCase__      )
							if len(list(Path(F'''{class_data_dir}/images'''      ).iterdir()      )      ) >= num_class_images:
														return

							while True:
														snake_case_							=    client.query(text=UpperCamelCase__      )
														if len(UpperCamelCase__      ) >= factor * num_class_images or num_images > 1E4:
																					break
														else:
																					snake_case_							=    int(factor * num_images      )
																					snake_case_							=    ClipClient(
																					    url='https://knn.laion.ai/knn-service'   ,							indice_name='laion_400m'   ,							num_images=UpperCamelCase__   ,							aesthetic_weight=0.1   ,							)

							snake_case_							=    0
							snake_case_							=    0
							snake_case_							=    tqdm(desc='downloading real regularization images'   ,							total=UpperCamelCase__      )

							with open(F'''{class_data_dir}/caption.txt'''   ,							'w'      ) as fa, open(F'''{class_data_dir}/urls.txt'''   ,							'w'      ) as fa, open(
							    F'''{class_data_dir}/images.txt'''   ,							'w'      ) as fa:
														while total < num_class_images:
																					snake_case_							=    class_images[count]
																					count += 1
																					try:
																												snake_case_							=    requests.get(images['url']      )
																												if img.status_code == 200:
																																			snake_case_							=    Image.open(BytesIO(img.content      )      )
																																			with open(F'''{class_data_dir}/images/{total}.jpg'''   ,							'wb'      ) as f:
																																										f.write(img.content      )
																																			fa.write(images['caption'] + '\n'      )
																																			fa.write(images['url'] + '\n'      )
																																			fa.write(F'''{class_data_dir}/images/{total}.jpg''' + '\n'      )
																																			total += 1
																																			pbar.update(1      )
																												else:
																																			continue
																					except Exception:
																												continue
							return





def 					__lowerCamelCase	( ):







							'''simple docstring'''






							snake_case_							=    argparse.ArgumentParser(''   ,							add_help=UpperCamelCase__      )
							parser.add_argument('--class_prompt'   ,							help='text prompt to retrieve images'   ,							required=UpperCamelCase__   ,							type=UpperCamelCase__      )
							parser.add_argument('--class_data_dir'   ,							help='path to save images'   ,							required=UpperCamelCase__   ,							type=UpperCamelCase__      )
							parser.add_argument('--num_class_images'   ,							help='number of images to download'   ,							default=200   ,							type=UpperCamelCase__      )
							return parser.parse_args()


if __name__ == "__main__":
					_UpperCAmelCase		:   Optional[int]										=       parse_args()
					retrieve(args.class_prompt, args.class_data_dir, args.num_class_images)




