

'''simple docstring'''

import json
import os
from dataclasses import dataclass

import numpy as np
import pyarrow as pa

import datasets
from utils import get_duration


lowerCAmelCase_						   =			1_0_0_0_0_0_0_0_0_0_0_0
lowerCAmelCase_						   =			1_0_0_0_0

lowerCAmelCase_   ,	lowerCAmelCase_						   =			os.path.split(__file__)
lowerCAmelCase_						   =			os.path.join(RESULTS_BASEPATH, "results", RESULTS_FILENAME.replace(".py", ".json"))

def     lowerCamelCase__       ( A					,   A							)			->		datasets.Dataset:
	snake_case							 =				pa.Table.from_pydict({'col': [0] * chunk_size}							)
	snake_case							 =				pa.concat_tables([table] * (num_examples // chunk_size)							)
	return datasets.Dataset(A					,   fingerprint='table_100B'							)







@dataclass
class lowerCamelCase      :
				snake_case_           =   42
				snake_case_           =   42
				snake_case_           =   42
				snake_case_           =   42

				def 				_lowerCamelCase						(					self   )						->       Any:
					snake_case							 =				np.random.default_rng(self.seed   )
					snake_case							 =				rng.integers(low=self.low,	high=self.high,	size=self.size   ).tolist()

				def __iter__(					self   )						->       Any:
					return iter(self._sampled_values   )






				def __len__(					self   )						->       str:
					return self.size

@get_duration
def     lowerCamelCase__       ( A							)			->		List[Any]:
	snake_case							 =				dataset[0]

@get_duration
def     lowerCamelCase__       ( A							)			->		int:
	snake_case							 =				dataset[-1]

@get_duration
def     lowerCamelCase__       ( A							)			->		Dict:
	snake_case							 =				dataset[range(len(A							) // 2					,   len(A							) // 2 + 1_0_2_4							)]

@get_duration
def     lowerCamelCase__       ( A							)			->		Optional[Any]:
	snake_case							 =				dataset[RandIter(0					,   len(A							)					,   1_0_2_4					,   seed=4_2							)]

def     lowerCamelCase__       ( )			->		Optional[int]:
	snake_case							 =				{'num examples': SPEED_TEST_N_EXAMPLES}
	snake_case							 =				(get_first_row, get_last_row, get_batch_of_aaaa_rows, get_batch_of_aaaa_random_rows)
	print('generating dataset'							)
	snake_case							 =				generate_100B_dataset(num_examples=A					,   chunk_size=A							)
	print('Functions'							)
	for func in functions:
		print(func.__name__							)
		snake_case							 =				func(A							)

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


if __name__ == "__main__":  # useful to run the profiler
						benchmark_table_100B()








'''simple docstring'''

import os

import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent

lowerCAmelCase_						   =			{"UserAgent": UserAgent().random}
lowerCAmelCase_						   =			"https://www.mywaifulist.moe/random"

def     __magic_name__       ( A					,   A							)			->		None:
	snake_case							 =				requests.get(A					,   headers=A							)
	with open(A					,   'wb'							) as file:
		file.write(image.content							)

def     __magic_name__       ( )			->		tuple[str, str, str]:
	snake_case							 =				BeautifulSoup(requests.get(A					,   headers=A							).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(A							)							)
	snake_case							 =				title.strip().replace(' '					,   '_'							)
	snake_case							 =				F'''{image_title}{image_extension}'''
	save_image(A					,   A							)
	return (title, description, image_title)


if __name__ == "__main__":
						lowerCAmelCase_   ,	lowerCAmelCase_   ,	lowerCAmelCase_						   =			random_anime_character()
						print(f"{title}\n\n{desc}\n\nImage saved : {image_title}")





