
"""simple docstring"""





import json
import os
import re
import sys
import urllib.request

import requests
from bsa import BeautifulSoup

_a :    List[Any]														=		{
    """User-Agent""": """Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36"""
    """ (KHTML, like Gecko) Chrome/70.0.3538.102 Safari/537.36 Edge/18.19582"""
}



def 				lowerCamelCase__		(      __snake_case = "dhaka",					__snake_case = 5     )							->		int:


					"""simple docstring"""





					_UpperCamelCase										=  min(__snake_case,					50     )  # Prevent abuse!
					_UpperCamelCase										=  {
					    '''q''': query,
					    '''tbm''': '''isch''',
					    '''hl''': '''en''',
					    '''ijn''': '''0''',
					}

					_UpperCamelCase										=  requests.get('''https://www.google.com/search''',					params=__snake_case,					headers=__snake_case     )
					_UpperCamelCase										=  BeautifulSoup(html.text,					'''html.parser'''     )
					_UpperCamelCase										=  ''''''.join(
					    re.findall(r'''AF_initDataCallback\(([^<]+)\);''',					str(soup.select('''script'''     )     )     )     )

					_UpperCamelCase										=  json.dumps(__snake_case     )
					_UpperCamelCase										=  json.loads(__snake_case     )

					_UpperCamelCase										=  re.findall(
					    r'''\[\"GRID_STATE0\",null,\[\[1,\[0,\".*?\",(.*),\"All\",''',					__snake_case,					)
					if not matched_google_image_data:
										return 0

					_UpperCamelCase										=  re.sub(
					    r'''\[\"(https\:\/\/encrypted-tbn0\.gstatic\.com\/images\?.*?)\",\d+,\d+\]''',					'''''',					str(__snake_case     ),					)

					_UpperCamelCase										=  re.findall(
					    r'''(?:\'|,),\[\"(https:|http.*?)\",\d+,\d+\]''',					__snake_case,					)
					for index, fixed_full_res_image in enumerate(__snake_case     ):
										if index >= max_images:
															return index
										_UpperCamelCase										=  bytes(__snake_case,					'''ascii'''     ).decode(
										    '''unicode-escape'''     )
										_UpperCamelCase										=  bytes(__snake_case,					'''ascii'''     ).decode(
										    '''unicode-escape'''     )
										_UpperCamelCase										=  urllib.request.build_opener()
										_UpperCamelCase										=  [
										    (
										        '''User-Agent''',
										        '''Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36'''
										        ''' (KHTML, like Gecko) Chrome/70.0.3538.102 Safari/537.36 Edge/18.19582''',
										    )
										]
										urllib.request.install_opener(__snake_case     )
										_UpperCamelCase										=  F'''query_{query.replace(" ",					"_"     )}'''
										if not os.path.exists(__snake_case     ):
															os.makedirs(__snake_case     )
										urllib.request.urlretrieve(  # noqa: S310
										    __snake_case,					F'''{path_name}/original_size_img_{index}.jpg'''     )
					return index


if __name__ == "__main__":
				try:
								_a :    Optional[int]														=		download_images_from_google_query(sys.argv[1])
								print(F"""{image_count} images were downloaded to disk.""")
				except IndexError:
								print("""Please provide a search term.""")
								raise








"""simple docstring"""





from ...utils import is_torch_available, is_transformers_available


if is_transformers_available() and is_torch_available():
				from .pipeline_vq_diffusion import LearnedClassifierFreeSamplingEmbeddings, VQDiffusionPipeline






