

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

import requests
from bsa import BeautifulSoup

snake_case_   :   str        =       {
    """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   lowercase_	(    _lowercase       :		Tuple = "dhaka"							,      _lowercase       :		Any = 5	):




					'''simple docstring'''






					UpperCAmelCase			:   Optional[int]      =				min(_lowercase							,      50	)  # Prevent abuse!
					UpperCAmelCase			:   Union[str, Any]      =				{
					    "q": query,
					    "tbm": "isch",
					    "hl": "en",
					    "ijn": "0",
					}

					UpperCAmelCase			:   Any      =				requests.get("https://www.google.com/search"							,      params=_lowercase							,      headers=_lowercase	)
					UpperCAmelCase			:   int      =				BeautifulSoup(html.text							,      "html.parser"	)
					UpperCAmelCase			:   int      =				"".join(
					    re.findall(R"AF_initDataCallback\(([^<]+)\);"							,      str(soup.select("script"	)	)	)	)

					UpperCAmelCase			:   Dict      =				json.dumps(_lowercase	)
					UpperCAmelCase			:   List[Any]      =				json.loads(_lowercase	)

					UpperCAmelCase			:   int      =				re.findall(
					    R"\[\"GRID_STATE0\",null,\[\[1,\[0,\".*?\",(.*),\"All\","							,      _lowercase							,      )
					if not matched_google_image_data:
										return 0

					UpperCAmelCase			:   str      =				re.sub(
					    R"\[\"(https\:\/\/encrypted-tbn0\.gstatic\.com\/images\?.*?)\",\d+,\d+\]"							,      ""							,      str(_lowercase	)							,      )

					UpperCAmelCase			:   List[str]      =				re.findall(
					    R"(?:\'|,),\[\"(https:|http.*?)\",\d+,\d+\]"							,      _lowercase							,      )
					for index, fixed_full_res_image in enumerate(_lowercase	):
										if index >= max_images:
															return index
										UpperCAmelCase			:   Any      =				bytes(_lowercase							,      "ascii"	).decode(
										    "unicode-escape"	)
										UpperCAmelCase			:   Union[str, Any]      =				bytes(_lowercase							,      "ascii"	).decode(
										    "unicode-escape"	)
										UpperCAmelCase			:   List[str]      =				urllib.request.build_opener()
										UpperCAmelCase			:   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",
										    )
										]
										urllib.request.install_opener(_lowercase	)
										UpperCAmelCase			:   Optional[Any]      =				F"""query_{query.replace(' '							,      '_'	)}"""
										if not os.path.exists(_lowercase	):
															os.makedirs(_lowercase	)
										urllib.request.urlretrieve(  # noqa: S310
										    _lowercase							,      F"""{path_name}/original_size_img_{index}.jpg"""	)
					return index


if __name__ == "__main__":
	try:
		snake_case_   :   Tuple        =       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 typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


snake_case_   :   Dict        =       {
    """configuration_mvp""": ["""MVP_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MvpConfig""", """MvpOnnxConfig"""],
    """tokenization_mvp""": ["""MvpTokenizer"""],
}

try:
	if not is_tokenizers_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	snake_case_   :   List[Any]        =       ["""MvpTokenizerFast"""]

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	snake_case_   :   Any        =       [
	    """MVP_PRETRAINED_MODEL_ARCHIVE_LIST""",
	    """MvpForCausalLM""",
	    """MvpForConditionalGeneration""",
	    """MvpForQuestionAnswering""",
	    """MvpForSequenceClassification""",
	    """MvpModel""",
	    """MvpPreTrainedModel""",
	]

if TYPE_CHECKING:
	from .configuration_mvp import MVP_PRETRAINED_CONFIG_ARCHIVE_MAP, MvpConfig, MvpOnnxConfig
	from .tokenization_mvp import MvpTokenizer

	try:
		if not is_tokenizers_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .tokenization_mvp_fast import MvpTokenizerFast

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_mvp import (
		    MVP_PRETRAINED_MODEL_ARCHIVE_LIST,
		    MvpForCausalLM,
		    MvpForConditionalGeneration,
		    MvpForQuestionAnswering,
		    MvpForSequenceClassification,
		    MvpModel,
		    MvpPreTrainedModel,
		)

else:
	import sys

	snake_case_   :   List[str]        =       _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)


