






from __future__ import annotations

from collections.abc import Iterable, Iterator
from dataclasses import dataclass

A_       :Tuple       =						(3, 9, -11, 0, 7, 5, 1, -1)
A_       :Optional[int]       =						(4, 6, 2, 0, 8, 10, 3, -2)




@dataclass
class 				__A     :





				"""simple docstring"""







				UpperCamelCase__ :      int
				UpperCamelCase__ :      Node | None




class 				__A     :





				"""simple docstring"""







				def __init__( self							,  lowerCamelCase__    ):




									"""simple docstring"""

									__UpperCamelCase      :					Node | None       		=None
									for i in sorted(lowerCamelCase__							,  reverse=lowerCamelCase__    ):
														__UpperCamelCase      :					Dict       		=Node(lowerCamelCase__							,  self.head    )


				def __iter__( self    ):




									"""simple docstring"""

									__UpperCamelCase      :					List[Any]       		=self.head
									while node:
														yield node.data
														__UpperCamelCase      :					Tuple       		=node.next_node


				def __len__( self    ):




									"""simple docstring"""

									return sum(1 for _ in self    )







				def __str__( self    ):




									"""simple docstring"""

									return " -> ".join([str(lowerCamelCase__    ) for node in self]    )






def 							A     (       a_							,a_					)     ->						SortedLinkedList:
					return SortedLinkedList(list(a_					) + list(a_					)					)


if __name__ == "__main__":
							import doctest

							doctest.testmod()
							A_       :Optional[int]       =						SortedLinkedList
							print(merge_lists(SSL(test_data_odd), SSL(test_data_even)))





'''simple docstring'''

a_  :				str						= """
# Transformers installation
! pip install transformers datasets
# To install from source instead of the last release, comment the command above and uncomment the following one.
# ! pip install git+https://github.com/huggingface/transformers.git
"""

a_  :				Any						= [{"""type""": """code""", """content""": INSTALL_CONTENT}]
a_  :				int						= {
    """{processor_class}""": """FakeProcessorClass""",
    """{model_class}""": """FakeModelClass""",
    """{object_class}""": """FakeObjectClass""",
}



