UpperCAmelCase_			    =							{
    '''A''': ['''B''', '''C''', '''E'''],
    '''B''': ['''A''', '''D''', '''E'''],
    '''C''': ['''A''', '''F''', '''G'''],
    '''D''': ['''B'''],
    '''E''': ['''A''', '''B''', '''D'''],
    '''F''': ['''C'''],
    '''G''': ['''C'''],
}




def       lowerCAmelCase_     (		lowercase:							dict  ,					lowercase:							Optional[Any]  ,					lowercase:							List[Any]		)    ->				list[str]:







 '''simple docstring'''
 _UpperCamelCase:     Dict							= set()
 # keep track of all the paths to be checked
 _UpperCamelCase:     Tuple							= [[start]]

 # return path if start is goal
 if start == goal:
  return [start]

 # keeps looping until all possible paths have been checked
 while queue:
  # pop the first path from the queue
  _UpperCamelCase:     str							= queue.pop(0		)
  # get the last node from the path
  _UpperCamelCase:     Optional[Any]							= path[-1]
  if node not in explored:
   _UpperCamelCase:     str							= graph[node]
   # go through all neighbour nodes, construct a new path and
   # push it into the queue
   for neighbour in neighbours:
    _UpperCamelCase:     Dict							= list(lowercase		)
    new_path.append(lowercase		)
    queue.append(lowercase		)
    # return path if neighbour is goal
    if neighbour == goal:
     return new_path

            # mark node as explored
   explored.add(lowercase		)

    # in case there's no path between the 2 nodes
 return []




def       lowerCAmelCase_     (		lowercase:							dict  ,					lowercase:							Union[str, Any]  ,					lowercase:							List[str]		)    ->				int:







 '''simple docstring'''
 if not graph or start not in graph or target not in graph:
  return -1
 if start == target:
  return 0
 _UpperCamelCase:     Tuple							= [start]
 _UpperCamelCase:     Tuple							= set(lowercase		)
 # Keep tab on distances from `start` node.
 _UpperCamelCase:     Optional[int]							= {start: 0, target: -1}
 while queue:
  _UpperCamelCase:     Any							= queue.pop(0		)
  if node == target:
   _UpperCamelCase:     Any							= (
       dist[node] if dist[target] == -1 else min(dist[target]  ,					dist[node]		)
   )
  for adjacent in graph[node]:
   if adjacent not in visited:
    visited.add(lowercase		)
    queue.append(lowercase		)
    _UpperCamelCase:     Optional[int]							= dist[node] + 1
 return dist[target]


if __name__ == "__main__":
  print(bfs_shortest_path(demo_graph, '''G''', '''D'''))  # returns ['G', 'C', 'A', 'B', 'D']
  print(bfs_shortest_path_distance(demo_graph, '''G''', '''D'''))  # returns 4
import pytest

from datasets.splits import SplitDict, SplitInfo
from datasets.utils.py_utils import asdict




@pytest.mark.parametrize(
    '''split_dict'''  ,					[
        SplitDict(),
        SplitDict({'''train''': SplitInfo(name='''train'''  ,					num_bytes=1_337  ,					num_examples=42  ,					dataset_name='''my_dataset'''		)}		),
        SplitDict({'''train''': SplitInfo(name='''train'''  ,					num_bytes=1_337  ,					num_examples=42		)}		),
        SplitDict({'''train''': SplitInfo()}		),
    ]  ,					)
def       lowerCAmelCase_     (		lowercase:							SplitDict		)    ->				List[str]:







 '''simple docstring'''
 _UpperCamelCase:     List[str]							= split_dict._to_yaml_list()
 assert len(lowercase		) == len(lowercase		)
 _UpperCamelCase:     Tuple							= SplitDict._from_yaml_list(lowercase		)
 for split_name, split_info in split_dict.items():
  # dataset_name field is deprecated, and is therefore not part of the YAML dump
  _UpperCamelCase:     Optional[Any]							= None
  # the split name of split_dict takes over the name of the split info object
  _UpperCamelCase:     Any							= split_name
 assert split_dict == reloaded





@pytest.mark.parametrize(
    '''split_info'''  ,					[SplitInfo(), SplitInfo(dataset_name=lowercase		), SplitInfo(dataset_name='''my_dataset'''		)]		)
def       lowerCAmelCase_     (		lowercase:							str		)    ->				Tuple:







 '''simple docstring'''
 # For backward compatibility, we need asdict(split_dict) to return split info dictrionaries with the "dataset_name"
 # field even if it's deprecated. This way old versionso of `datasets` can still reload dataset_infos.json files
 _UpperCamelCase:     Optional[Any]							= asdict(SplitDict({'''train''': split_info}		)		)
 assert "dataset_name" in split_dict_asdict["train"]
 assert split_dict_asdict["train"]["dataset_name"] == split_info.dataset_name