'''simple docstring'''





from typing import Callable, Optional

from .. import Features
from ..packaged_modules.generator.generator import Generator
from .abc import AbstractDatasetInputStream




class 		SCREAMING_SNAKE_CASE     (					SCREAMING_SNAKE_CASE	):







				'''simple docstring'''





				def __init__(						self					:						List[Any]       ,		lowercase__					:						Callable       ,		lowercase__					:						Optional[Features] = None       ,		lowercase__					:						str = None       ,		lowercase__					:						bool = False       ,		lowercase__					:						bool = False       ,		lowercase__					:						Optional[dict] = None       ,		lowercase__					:						Optional[int] = None       ,		**lowercase__					:						List[Any]       ,		)							->Optional[Any]:


										'''simple docstring'''




										super().__init__(
										    features=lowercase__       ,		cache_dir=lowercase__       ,		keep_in_memory=lowercase__       ,		streaming=lowercase__       ,		num_proc=lowercase__       ,		**lowercase__       ,		)
										_UpperCamelCase			:			List[Any]   			=						Generator(
										    cache_dir=lowercase__       ,		features=lowercase__       ,		generator=lowercase__       ,		gen_kwargs=lowercase__       ,		**lowercase__       ,		)







				def  snake_case__				(						self					:						Tuple					)							->Dict:


										'''simple docstring'''




										if self.streaming:
																_UpperCamelCase			:			List[Any]   			=						self.builder.as_streaming_dataset(split="train"					)
										# Build regular (map-style) dataset
										else:
																_UpperCamelCase			:			Optional[Any]   			=						None
																_UpperCamelCase			:			Union[str, Any]   			=						None
																_UpperCamelCase			:			Any   			=						None
																_UpperCamelCase			:			List[Any]   			=						None

																self.builder.download_and_prepare(
																    download_config=lowercase__       ,		download_mode=lowercase__       ,		verification_mode=lowercase__       ,		base_path=lowercase__       ,		num_proc=self.num_proc       ,		)
																_UpperCamelCase			:			int   			=						self.builder.as_dataset(
																    split="train"       ,		verification_mode=lowercase__       ,		in_memory=self.keep_in_memory					)
										return dataset



'''simple docstring'''





import random




class 		SCREAMING_SNAKE_CASE     :







				'''simple docstring'''





				@staticmethod
				def  snake_case__				(						lowercase__					:						str					)							->tuple[list[int], list[int]]:


										'''simple docstring'''




										_UpperCamelCase			:			List[str]   			=						[ord(lowercase__					) for i in text]
										_UpperCamelCase			:			Dict   			=						[]
										_UpperCamelCase			:			Optional[int]   			=						[]
										for i in plain:
																_UpperCamelCase			:			Tuple   			=						random.randint(1       ,		300					)
																_UpperCamelCase			:			Any   			=						(i + k) * k
																cipher.append(lowercase__					)
																key.append(lowercase__					)
										return cipher, key







				@staticmethod
				def  snake_case__				(						lowercase__					:						list[int]       ,		lowercase__					:						list[int]					)							->str:


										'''simple docstring'''




										_UpperCamelCase			:			int   			=						[]
										for i in range(len(lowercase__					)					):
																_UpperCamelCase			:			List[Any]   			=						int((cipher[i] - (key[i]) ** 2) / key[i]					)
																plain.append(chr(lowercase__					)					)
										return "".join(lowercase__					)


if __name__ == "__main__":
			lowerCAmelCase_	,	lowerCAmelCase_	:		Optional[int]			=     Onepad().encrypt("""Hello""")
			print(c, k)
			print(Onepad().decrypt(c, k))


