

from __future__ import annotations

from enum import Enum, unique
from typing import TypeVar

# Create a generic variable that can be 'Enum', or any subclass.
UpperCamelCase__					: Dict								=      TypeVar("T", bound="Enum")



@unique
class  __snake_case					(      lowerCAmelCase__    ):
  __lowerCAmelCase       :		int  	=					80
  __lowerCAmelCase       :		Tuple  	=					70
  __lowerCAmelCase       :		Tuple  	=					60
  __lowerCAmelCase       :		Any  	=					50
  __lowerCAmelCase       :		int  	=					40
  __lowerCAmelCase       :		str  	=					30
  __lowerCAmelCase       :		int  	=					20
  __lowerCAmelCase       :		int  	=					10






@unique
class  __snake_case					(      lowerCAmelCase__    ):
  __lowerCAmelCase       :		List[str]  	=					24
  __lowerCAmelCase       :		Tuple  	=					21
  __lowerCAmelCase       :		List[str]  	=					18
  __lowerCAmelCase       :		Optional[Any]  	=					15
  __lowerCAmelCase       :		str  	=					12
  __lowerCAmelCase       :		int  	=					9
  __lowerCAmelCase       :		Any  	=					6
  __lowerCAmelCase       :		str  	=					3
  __lowerCAmelCase       :		Any  	=					2
  __lowerCAmelCase       :		Union[str, Any]  	=					1
  __lowerCAmelCase       :		Tuple  	=					-1
  __lowerCAmelCase       :		Union[str, Any]  	=					-2
  __lowerCAmelCase       :		Dict  	=					-3
  __lowerCAmelCase       :		Optional[int]  	=					-6
  __lowerCAmelCase       :		Dict  	=					-9
  __lowerCAmelCase       :		Optional[Any]  	=					-12
  __lowerCAmelCase       :		str  	=					-15
  __lowerCAmelCase       :		Tuple  	=					-18
  __lowerCAmelCase       :		List[Any]  	=					-21
  __lowerCAmelCase       :		str  	=					-24

  @classmethod
  def   lowerCAmelCase__       (   cls):
      return {unit.name: unit.value for unit in cls if unit.value > 0}


  @classmethod
  def   lowerCAmelCase__       (   cls):
      return {unit.name: unit.value for unit in cls if unit.value < 0}






def    _UpperCAmelCase    (					_SCREAMING_SNAKE_CASE   :						float    ):





    """simple docstring"""


    SCREAMING_SNAKE_CASE_													=  SIUnit.get_positive() if value > 0 else SIUnit.get_negative()
    for name_prefix, value_prefix in prefixes.items():
        SCREAMING_SNAKE_CASE_													=  value / (10**value_prefix)
        if numerical_part > 1:
            return f"""{numerical_part!s} {name_prefix}"""
    return str(_SCREAMING_SNAKE_CASE    )


def    _UpperCAmelCase    (					_SCREAMING_SNAKE_CASE   :						float    ):





    """simple docstring"""


    for prefix in BinaryUnit:
        SCREAMING_SNAKE_CASE_													=  value / (2**prefix.value)
        if numerical_part > 1:
            return f"""{numerical_part!s} {prefix.name}"""
    return str(_SCREAMING_SNAKE_CASE    )


if __name__ == "__main__":
       import doctest

       doctest.testmod()





# A Bipartite Graph is a graph whose vertices can be divided into two independent sets,
# U and V such that every edge (u, v) either connects a vertex from U to V or a vertex
# from V to U. In other words, for every edge (u, v), either u belongs to U and v to V,
# or u belongs to V and v to U. We can also say that there is no edge that connects
# vertices of same set.
from queue import Queue


def    _UpperCAmelCase    (					_SCREAMING_SNAKE_CASE   :						List[str]    ):





    """simple docstring"""


    SCREAMING_SNAKE_CASE_													=  Queue()
    SCREAMING_SNAKE_CASE_													=  [False] * len(_SCREAMING_SNAKE_CASE    )
    SCREAMING_SNAKE_CASE_													=  [-1] * len(_SCREAMING_SNAKE_CASE    )

    def bfs():
        while not queue.empty():
            SCREAMING_SNAKE_CASE_													=  queue.get()
            SCREAMING_SNAKE_CASE_													=  True

            for neighbour in graph[u]:
                if neighbour == u:
                    return False

                if color[neighbour] == -1:
                    SCREAMING_SNAKE_CASE_													=  1 - color[u]
                    queue.put(_SCREAMING_SNAKE_CASE    )

                elif color[neighbour] == color[u]:
                    return False

        return True

    for i in range(len(_SCREAMING_SNAKE_CASE    )    ):
        if not visited[i]:
            queue.put(_SCREAMING_SNAKE_CASE    )
            SCREAMING_SNAKE_CASE_													=  0
            if bfs() is False:
                return False

    return True


if __name__ == "__main__":
       # Adjacency List of graph
       print(check_bipartite({0: [1, 3], 1: [0, 2], 2: [1, 3], 3: [0, 2]}))


