




'''simple docstring'''





import os

import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent

UpperCamelCase_		:    Any									=		{'''UserAgent''': UserAgent().random}
UpperCamelCase_		:    List[str]									=		'''https://www.mywaifulist.moe/random'''





def 			__a			(     _UpperCamelCase:					str      ,		_UpperCamelCase:					str					)		->				None:

     """simple docstring"""




     _snake_case							=   requests.get(_UpperCamelCase      ,		headers=_UpperCamelCase					)
     with open(_UpperCamelCase      ,		"wb"					) as file:
          file.write(image.content					)





def 			__a			(     )		->				tuple[str, str, str]:

     """simple docstring"""




     _snake_case							=   BeautifulSoup(requests.get(_UpperCamelCase      ,		headers=_UpperCamelCase					).text      ,		"html.parser"					)
     _snake_case							=   soup.find("meta"      ,		attrs={"property": "og:title"}					).attrs["content"]
     _snake_case							=   soup.find("meta"      ,		attrs={"property": "og:image"}					).attrs["content"]
     _snake_case							=   soup.find("p"      ,		id="description"					).get_text()
     _snake_case							,      _snake_case							=   os.path.splitext(os.path.basename(_UpperCamelCase					)					)
     _snake_case							=   title.strip().replace(" "      ,		"_"					)
     _snake_case							=   F"""{image_title}{image_extension}"""
     save_image(_UpperCamelCase      ,		_UpperCamelCase					)
     return (title, description, image_title)


if __name__ == "__main__":
   UpperCamelCase_		:    Dict									=		random_anime_character()
   print(F'{title}\n\n{desc}\n\nImage saved : {image_title}')








'''simple docstring'''





import json
import os
import tempfile

import datasets
from utils import generate_example_dataset, get_duration


UpperCamelCase_		:    List[str]									=		500000

UpperCamelCase_			,			UpperCamelCase_		:    Dict									=		os.path.split(__file__)
UpperCamelCase_		:    int									=		os.path.join(RESULTS_BASEPATH, '''results''', RESULTS_FILENAME.replace('''.py''', '''.json'''))





@get_duration
def 			__a			(     _UpperCamelCase:					datasets.Dataset					)		->				List[Any]:

     """simple docstring"""




     _snake_case							=   dataset.select(range(0      ,		len(_UpperCamelCase					)      ,		2					)					)





@get_duration
def 			__a			(     _UpperCamelCase:					datasets.Dataset					)		->				List[Any]:

     """simple docstring"""




     _snake_case							=   dataset.sort("numbers"					)





@get_duration
def 			__a			(     _UpperCamelCase:					datasets.Dataset					)		->				List[Any]:

     """simple docstring"""




     _snake_case							=   dataset.shuffle()





@get_duration
def 			__a			(     _UpperCamelCase:					datasets.Dataset					)		->				Any:

     """simple docstring"""




     _snake_case							=   dataset.train_test_split(0.1					)





@get_duration
def 			__a			(     _UpperCamelCase:					datasets.Dataset      ,		_UpperCamelCase:					int=10					)		->				List[str]:

     """simple docstring"""




     for shard_id in range(_UpperCamelCase					):
          _snake_case							=   dataset.shard(_UpperCamelCase      ,		_UpperCamelCase					)





def 			__a			(     )		->				int:

     """simple docstring"""




     _snake_case							=   {"num examples": SPEED_TEST_N_EXAMPLES}
     _snake_case							=   (select, sort, shuffle, train_test_split, shard)
     with tempfile.TemporaryDirectory() as tmp_dir:
          print("generating dataset"					)
          _snake_case							=   datasets.Features({"text": datasets.Value("string"					), "numbers": datasets.Value("float32"					)}					)
          _snake_case							=   generate_example_dataset(
              os.path.join(_UpperCamelCase      ,		"dataset.arrow"					)      ,		_UpperCamelCase      ,		num_examples=_UpperCamelCase					)
          print("Functions"					)
          for func in functions:
               print(func.__name__					)
               _snake_case							=   func(_UpperCamelCase					)

     with open(_UpperCamelCase      ,		"wb"					) as f:
          f.write(json.dumps(_UpperCamelCase					).encode("utf-8"					)					)


if __name__ == "__main__":  # useful to run the profiler
   benchmark_indices_mapping()


