






"""simple docstring"""
import json
import os
import re
import sys
import urllib.request

import requests
from bsa import BeautifulSoup

lowerCamelCase_							      = {
    '''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 							snake_case (  A__ = "dhaka"      ,A__ = 5		):
			UpperCAmelCase_	:					str     	=   min(A__      ,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=A__      ,headers=A__		)
			UpperCAmelCase_	:					List[str]     	=   BeautifulSoup(html.text      ,"html.parser"		)
			UpperCAmelCase_	:					str     	=   "".join(
			    re.findall(r"AF_initDataCallback\(([^<]+)\);"      ,str(soup.select("script"		)		)		)		)

			UpperCAmelCase_	:					Optional[int]     	=   json.dumps(A__		)
			UpperCAmelCase_	:					Any     	=   json.loads(A__		)

			UpperCAmelCase_	:					Optional[int]     	=   re.findall(
			    r"\[\"GRID_STATE0\",null,\[\[1,\[0,\".*?\",(.*),\"All\","      ,A__      ,)
			if not matched_google_image_data:
						return 0

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

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


if __name__ == "__main__":
			try:
						lowerCamelCase_							      = 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"""
import timeit

import numpy as np

import datasets
from datasets.arrow_writer import ArrowWriter
from datasets.features.features import _ArrayXD

def 							snake_case (  A__		):
			def wrapper(*A__      ,**A__		):
						UpperCAmelCase_	:					Union[str, Any]     	=   timeit.default_timer()
						UpperCAmelCase_	:					Union[str, Any]     	=   func(*A__      ,**A__		)
						UpperCAmelCase_	:					Dict     	=   timeit.default_timer() - starttime
						return delta

			UpperCAmelCase_	:					Optional[Any]     	=   func.__name__

			return wrapper

def 							snake_case (  A__      ,A__=1_00      ,A__=None		):
			UpperCAmelCase_	:					str     	=   []
			UpperCAmelCase_	:					List[str]     	=   seq_shapes or {}
			for i in range(A__		):
						UpperCAmelCase_	:					int     	=   {}
						for col_id, (k, v) in enumerate(features.items()		):
									if isinstance(A__      ,_ArrayXD		):
												UpperCAmelCase_	:					Optional[int]     	=   np.random.rand(*v.shape		).astype(v.dtype		)
									elif isinstance(A__      ,datasets.Value		):
												if v.dtype == "string":
															UpperCAmelCase_	:					List[str]     	=   "The small grey turtle was surprisingly fast when challenged."
												else:
															UpperCAmelCase_	:					List[str]     	=   np.random.randint(10      ,size=1		).astype(v.dtype		).item()
									elif isinstance(A__      ,datasets.Sequence		):
												while isinstance(A__      ,datasets.Sequence		):
															UpperCAmelCase_	:					List[str]     	=   v.feature
												UpperCAmelCase_	:					List[Any]     	=   seq_shapes[k]
												UpperCAmelCase_	:					Dict     	=   np.random.rand(*A__		).astype(v.dtype		)
									UpperCAmelCase_	:					Dict     	=   data

						dummy_data.append((i, example)		)

			return dummy_data




def 							snake_case (  A__      ,A__      ,A__=1_00      ,A__=None		):
			UpperCAmelCase_	:					Optional[Any]     	=   generate_examples(A__      ,num_examples=A__      ,seq_shapes=A__		)

			with ArrowWriter(features=A__      ,path=A__		) as writer:
						for key, record in dummy_data:
									UpperCAmelCase_	:					Any     	=   features.encode_example(A__		)
									writer.write(A__		)

						UpperCAmelCase_	,      UpperCAmelCase_	:					Optional[int]     	=   writer.finalize()

			if not num_final_examples == num_examples:
						raise ValueError(
						    F"""Error writing the dataset, wrote {num_final_examples} examples but should have written {num_examples}."""		)

			UpperCAmelCase_	:					List[Any]     	=   datasets.Dataset.from_file(filename=A__      ,info=datasets.DatasetInfo(features=A__		)		)

			return dataset



