




from unittest import TestCase

from datasets import Sequence, Value
from datasets.arrow_dataset import Dataset

class        lowercase      (    __UpperCAmelCase):







				def 					a_  (							self   :					List[str]       ):



					"""simple docstring"""

					return [
					    {"col_1": 3, "col_2": "a"},
					    {"col_1": 2, "col_2": "b"},
					    {"col_1": 1, "col_2": "c"},
					    {"col_1": 0, "col_2": "d"},
					]







				def 					a_  (							self   :					Dict       ):



					"""simple docstring"""

					A_  :				Optional[Any]	   =		{'''col_1''': [3, 2, 1, 0], '''col_2''': ['''a''', '''b''', '''c''', '''d''']}
					return Dataset.from_dict(_lowerCamelCase       )







				def 					a_  (							self   :					Optional[Any]       ):



					"""simple docstring"""

					A_  :				str	   =		self._create_example_records()
					A_  :				str	   =		Dataset.from_list(_lowerCamelCase       )
					self.assertListEqual(dset.column_names      ,     ['''col_1''', '''col_2''']       )
					for i, r in enumerate(_lowerCamelCase       ):
						self.assertDictEqual(_lowerCamelCase      ,     example_records[i]       )







				def 					a_  (							self   :					Any       ):



					"""simple docstring"""

					A_  :				Any	   =		self._create_example_records()
					A_  :				Optional[Any]	   =		Dataset.from_list(_lowerCamelCase       )
					A_  :				Tuple	   =		Dataset.from_dict({k: [r[k] for r in example_records] for k in example_records[0]}       )
					self.assertEqual(dset.info      ,     dset_from_dict.info       )







				def 					a_  (							self   :					Optional[Any]       ):  # checks what happens with missing columns



					"""simple docstring"""

					A_  :				Optional[int]	   =		[{'''col_1''': 1}, {'''col_2''': '''x'''}]
					A_  :				Dict	   =		Dataset.from_list(_lowerCamelCase       )
					self.assertDictEqual(dset[0]      ,     {'''col_1''': 1}       )
					self.assertDictEqual(dset[1]      ,     {'''col_1''': None}       )  # NB: first record is used for columns







				def 					a_  (							self   :					Optional[Any]       ):  # checks if the type can be inferred from the second record



					"""simple docstring"""

					A_  :				str	   =		[{'''col_1''': []}, {'''col_1''': [1, 2]}]
					A_  :				Optional[Any]	   =		Dataset.from_list(_lowerCamelCase       )
					self.assertEqual(dset.info.features['''col_1''']      ,     Sequence(Value('''int64'''       )       )       )







				def 					a_  (							self   :					Tuple       ):



					"""simple docstring"""

					A_  :				Tuple	   =		Dataset.from_list([]       )
					self.assertEqual(len(_lowerCamelCase       )      ,     0       )
					self.assertListEqual(dset.column_names      ,     []       )











"""simple docstring"""

from queue import PriorityQueue
from typing import Any

import numpy as np

def 		lowercase_      (		_UpperCAmelCase  ,      _UpperCAmelCase  ,      _UpperCAmelCase  ,      _UpperCAmelCase  ,      _UpperCAmelCase  ,      _UpperCAmelCase  ,      _UpperCAmelCase  ,      _UpperCAmelCase  ,      _UpperCAmelCase  ,      ):




	"""simple docstring"""






	for nxt, d in graph[v]:
		if nxt in visited_forward:
			continue
		A_  :				Tuple	   =		cst_fwd.get(_UpperCAmelCase  ,      np.inf	)
		A_  :				Any	   =		cst_fwd[v] + d
		if new_cost_f < old_cost_f:
			queue.put((new_cost_f, nxt)	)
			A_  :				Tuple	   =		new_cost_f
			A_  :				Dict	   =		v
		if nxt in visited_backward:
			if cst_fwd[v] + d + cst_bwd[nxt] < shortest_distance:
				A_  :				Optional[Any]	   =		cst_fwd[v] + d + cst_bwd[nxt]
	return shortest_distance

def 		lowercase_      (		_UpperCAmelCase  ,      _UpperCAmelCase  ,      _UpperCAmelCase  ,      _UpperCAmelCase	):




	"""simple docstring"""






	A_  :				Tuple	   =		-1

	A_  :				Any	   =		set()
	A_  :				Tuple	   =		set()
	A_  :				Optional[int]	   =		{source: 0}
	A_  :				Dict	   =		{destination: 0}
	A_  :				Any	   =		{source: None}
	A_  :				Optional[Any]	   =		{destination: None}
	A_  :				PriorityQueue[Any]	   =		PriorityQueue()
	A_  :				PriorityQueue[Any]	   =		PriorityQueue()

	A_  :				Union[str, Any]	   =		np.inf

	queue_forward.put((0, source)	)
	queue_backward.put((0, destination)	)

	if source == destination:
		return 0

	while not queue_forward.empty() and not queue_backward.empty():
		A_   , A_  :				Union[str, Any]	   =		queue_forward.get()
		visited_forward.add(_UpperCAmelCase	)

		A_   , A_  :				Optional[int]	   =		queue_backward.get()
		visited_backward.add(_UpperCAmelCase	)

		A_  :				Any	   =		pass_and_relaxation(
		    _UpperCAmelCase  ,      _UpperCAmelCase  ,      _UpperCAmelCase  ,      _UpperCAmelCase  ,      _UpperCAmelCase  ,      _UpperCAmelCase  ,      _UpperCAmelCase  ,      _UpperCAmelCase  ,      _UpperCAmelCase  ,      )

		A_  :				Dict	   =		pass_and_relaxation(
		    _UpperCAmelCase  ,      _UpperCAmelCase  ,      _UpperCAmelCase  ,      _UpperCAmelCase  ,      _UpperCAmelCase  ,      _UpperCAmelCase  ,      _UpperCAmelCase  ,      _UpperCAmelCase  ,      _UpperCAmelCase  ,      )

		if cst_fwd[v_fwd] + cst_bwd[v_bwd] >= shortest_distance:
			break

	if shortest_distance != np.inf:
		A_  :				Optional[Any]	   =		shortest_distance
	return shortest_path_distance


_lowerCamelCase  :			Optional[Any]        =       {
    'B': [['C', 1]],
    'C': [['D', 1]],
    'D': [['F', 1]],
    'E': [['B', 1], ['G', 2]],
    'F': [],
    'G': [['F', 1]],
}
_lowerCamelCase  :			Any        =       {
    'B': [['E', 1]],
    'C': [['B', 1]],
    'D': [['C', 1]],
    'F': [['D', 1], ['G', 1]],
    'E': [[None, np.inf]],
    'G': [['E', 2]],
}

if __name__ == "__main__":
		import doctest

		doctest.testmod()





