





from typing import Any





class 				a			:






				def __init__(  self			, _lowerCAmelCase					):

										"""simple docstring"""




										__SCREAMING_SNAKE_CASE:				Optional[Any]           =   data
										__SCREAMING_SNAKE_CASE:				Dict           =   None





class 				a			:






				def __init__(  self					):

										"""simple docstring"""




										__SCREAMING_SNAKE_CASE:				str           =   None






				def 			snake_case_    (  self					):

										"""simple docstring"""




										__SCREAMING_SNAKE_CASE:				List[str]           =   self.head
										while temp is not None:
																print(temp.data			, end=''' '''					)
																__SCREAMING_SNAKE_CASE:				Optional[int]           =   temp.next
										print()






				def 			snake_case_    (  self			, _lowerCAmelCase					):

										"""simple docstring"""




										__SCREAMING_SNAKE_CASE:				Union[str, Any]           =   Node(_lowerCAmelCase					)
										__SCREAMING_SNAKE_CASE:				str           =   self.head
										__SCREAMING_SNAKE_CASE:				Any           =   new_node






				def 			snake_case_    (  self			, _lowerCAmelCase			, _lowerCAmelCase					):

										"""simple docstring"""




										if node_data_a == node_data_a:
																return
										else:
																__SCREAMING_SNAKE_CASE:				str           =   self.head
																while node_a is not None and node_a.data != node_data_a:
																						__SCREAMING_SNAKE_CASE:				Optional[Any]           =   node_a.next

																__SCREAMING_SNAKE_CASE:				Optional[Any]           =   self.head
																while node_a is not None and node_a.data != node_data_a:
																						__SCREAMING_SNAKE_CASE:				int           =   node_a.next

																if node_a is None or node_a is None:
																						return

																__SCREAMING_SNAKE_CASE       ,__SCREAMING_SNAKE_CASE:				Union[str, Any]           =   node_a.data, node_a.data


if __name__ == "__main__":
							lowerCAmelCase							:       Union[str, Any]					 =	LinkedList()
							for i in range(5, 0, -1):
														ll.push(i)

							ll.print_list()

							ll.swap_nodes(1, 4)
							print("""After swapping""")
							ll.print_list()










from typing import Callable, Optional

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





class 				a			(      __lowercase			):






				def __init__(  self			, _lowerCAmelCase			, _lowerCAmelCase = None			, _lowerCAmelCase = None			, _lowerCAmelCase = False			, _lowerCAmelCase = False			, _lowerCAmelCase = None			, _lowerCAmelCase = None			, **_lowerCAmelCase			, ):

										"""simple docstring"""




										super().__init__(
										    features=_lowerCAmelCase			, cache_dir=_lowerCAmelCase			, keep_in_memory=_lowerCAmelCase			, streaming=_lowerCAmelCase			, num_proc=_lowerCAmelCase			, **_lowerCAmelCase			, )
										__SCREAMING_SNAKE_CASE:				Any           =   Generator(
										    cache_dir=_lowerCAmelCase			, features=_lowerCAmelCase			, generator=_lowerCAmelCase			, gen_kwargs=_lowerCAmelCase			, **_lowerCAmelCase			, )






				def 			snake_case_    (  self					):

										"""simple docstring"""




										if self.streaming:
																__SCREAMING_SNAKE_CASE:				List[str]           =   self.builder.as_streaming_dataset(split='''train'''					)
										# Build regular (map-style) dataset
										else:
																__SCREAMING_SNAKE_CASE:				str           =   None
																__SCREAMING_SNAKE_CASE:				List[Any]           =   None
																__SCREAMING_SNAKE_CASE:				Tuple           =   None
																__SCREAMING_SNAKE_CASE:				Optional[Any]           =   None

																self.builder.download_and_prepare(
																    download_config=_lowerCAmelCase			, download_mode=_lowerCAmelCase			, verification_mode=_lowerCAmelCase			, base_path=_lowerCAmelCase			, num_proc=self.num_proc			, )
																__SCREAMING_SNAKE_CASE:				List[str]           =   self.builder.as_dataset(
																    split='''train'''			, verification_mode=_lowerCAmelCase			, in_memory=self.keep_in_memory					)
										return dataset



