import timeit

import numpy as np

import datasets
from datasets.arrow_writer import ArrowWriter
from datasets.features.features import _ArrayXD







def     _a				(      lowercase__  :			Optional[int] ):







     '''simple docstring'''


     def wrapper(*lowercase__  :			str     ,  **lowercase__  :			List[str] ):
          SCREAMING_SNAKE_CASE__				:				Optional[int]			=		timeit.default_timer()
          SCREAMING_SNAKE_CASE__				:				Tuple			=		func(*lowercase__     ,  **lowercase__ )
          SCREAMING_SNAKE_CASE__				:				Union[str, Any]			=		timeit.default_timer() - starttime
          return delta

     SCREAMING_SNAKE_CASE__				:				List[str]			=		func.__name__

     return wrapper







def     _a				(      lowercase__  :			dict     ,  lowercase__  :			List[str]=1_00     ,  lowercase__  :			List[str]=None ):







     '''simple docstring'''


     SCREAMING_SNAKE_CASE__				:				Optional[Any]			=		[]
     SCREAMING_SNAKE_CASE__				:				Optional[int]			=		seq_shapes or {}
     for i in range(lowercase__ ):
          SCREAMING_SNAKE_CASE__				:				str			=		{}
          for col_id, (k, v) in enumerate(features.items() ):
               if isinstance(lowercase__     ,  _ArrayXD ):
                    SCREAMING_SNAKE_CASE__				:				Optional[Any]			=		np.random.rand(*v.shape ).astype(v.dtype )
               elif isinstance(lowercase__     ,  datasets.Value ):
                    if v.dtype == "string":
                         SCREAMING_SNAKE_CASE__				:				int			=		'The small grey turtle was surprisingly fast when challenged.'
                    else:
                         SCREAMING_SNAKE_CASE__				:				Tuple			=		np.random.randint(10     ,  size=1 ).astype(v.dtype ).item()
               elif isinstance(lowercase__     ,  datasets.Sequence ):
                    while isinstance(lowercase__     ,  datasets.Sequence ):
                         SCREAMING_SNAKE_CASE__				:				Union[str, Any]			=		v.feature
                    SCREAMING_SNAKE_CASE__				:				Any			=		seq_shapes[k]
                    SCREAMING_SNAKE_CASE__				:				Tuple			=		np.random.rand(*lowercase__ ).astype(v.dtype )
               SCREAMING_SNAKE_CASE__				:				Optional[Any]			=		data

          dummy_data.append((i, example) )

     return dummy_data







def     _a				(      lowercase__  :			int     ,  lowercase__  :			Optional[int]     ,  lowercase__  :			Optional[Any]=1_00     ,  lowercase__  :			List[str]=None ):







     '''simple docstring'''


     SCREAMING_SNAKE_CASE__				:				Optional[int]			=		generate_examples(lowercase__     ,  num_examples=lowercase__     ,  seq_shapes=lowercase__ )

     with ArrowWriter(features=lowercase__     ,  path=lowercase__ ) as writer:
          for key, record in dummy_data:
               SCREAMING_SNAKE_CASE__				:				List[str]			=		features.encode_example(lowercase__ )
               writer.write(lowercase__ )

          SCREAMING_SNAKE_CASE__			,							SCREAMING_SNAKE_CASE__				:				int			=		writer.finalize()

     if not num_final_examples == num_examples:
          raise ValueError(
              f'''Error writing the dataset, wrote {num_final_examples} examples but should have written {num_examples}.''' )

     SCREAMING_SNAKE_CASE__				:				Optional[int]			=		datasets.Dataset.from_file(filename=lowercase__     ,  info=datasets.DatasetInfo(features=lowercase__ ) )

     return dataset




import heapq as hq
import math
from collections.abc import Iterator

class       snake_case					:




  def __init__(      self     :	str     , a_     :	str				)->       Any:




       """simple docstring"""
       SCREAMING_SNAKE_CASE__				:				List[str]			=		str(id_				)
       SCREAMING_SNAKE_CASE__				:				Any			=		None
       SCREAMING_SNAKE_CASE__				:				Optional[Any]			=		None
       SCREAMING_SNAKE_CASE__				:				Any			=		[]
       SCREAMING_SNAKE_CASE__				:				Union[str, Any]			=		{}  # {vertex:distance}




  def __lt__(      self     :	int     , a_     :	Tuple				)->       Union[str, Any]:




       """simple docstring"""
       return self.key < other.key




  def __repr__(      self     :	Any				)->       Dict:




       """simple docstring"""
       return self.id




  def 	__lowercase(      self     :	Optional[Any]     , a_     :	int				)->       List[str]:




       """simple docstring"""
       self.neighbors.append(a_				)




  def 	__lowercase(      self     :	int     , a_     :	int     , a_     :	Optional[Any]				)->       Any:




       """simple docstring"""
       SCREAMING_SNAKE_CASE__				:				Tuple			=		weight







def     _a				(      lowercase__  :			Optional[Any]     ,  lowercase__  :			Union[str, Any]     ,  lowercase__  :			Tuple     ,  lowercase__  :			Dict ):







     '''simple docstring'''


     graph[a - 1].add_neighbor(graph[b - 1] )
     graph[b - 1].add_neighbor(graph[a - 1] )
     # add the edges:
     graph[a - 1].add_edge(graph[b - 1]     ,  lowercase__ )
     graph[b - 1].add_edge(graph[a - 1]     ,  lowercase__ )







def     _a				(      lowercase__  :			list     ,  lowercase__  :			Vertex ):







     '''simple docstring'''


     SCREAMING_SNAKE_CASE__				:				Any			=		[]
     for u in graph:
          SCREAMING_SNAKE_CASE__				:				Dict			=		math.inf
          SCREAMING_SNAKE_CASE__				:				str			=		None
     SCREAMING_SNAKE_CASE__				:				List[str]			=		0
     SCREAMING_SNAKE_CASE__				:				int			=		graph[:]
     while q:
          SCREAMING_SNAKE_CASE__				:				Optional[Any]			=		min(lowercase__ )
          q.remove(lowercase__ )
          for v in u.neighbors:
               if (v in q) and (u.edges[v.id] < v.key):
                    SCREAMING_SNAKE_CASE__				:				int			=		u
                    SCREAMING_SNAKE_CASE__				:				Any			=		u.edges[v.id]
     for i in range(1     ,  len(lowercase__ ) ):
          a.append((int(graph[i].id ) + 1, int(graph[i].pi.id ) + 1) )
     return a







def     _a				(      lowercase__  :			list     ,  lowercase__  :			Vertex ):







     '''simple docstring'''


     for u in graph:
          SCREAMING_SNAKE_CASE__				:				List[str]			=		math.inf
          SCREAMING_SNAKE_CASE__				:				int			=		None
     SCREAMING_SNAKE_CASE__				:				Optional[Any]			=		0

     SCREAMING_SNAKE_CASE__				:				Tuple			=		list(lowercase__ )
     hq.heapify(lowercase__ )

     while h:
          SCREAMING_SNAKE_CASE__				:				Optional[int]			=		hq.heappop(lowercase__ )
          for v in u.neighbors:
               if (v in h) and (u.edges[v.id] < v.key):
                    SCREAMING_SNAKE_CASE__				:				List[str]			=		u
                    SCREAMING_SNAKE_CASE__				:				Dict			=		u.edges[v.id]
                    hq.heapify(lowercase__ )

     for i in range(1     ,  len(lowercase__ ) ):
          yield (int(graph[i].id ) + 1, int(graph[i].pi.id ) + 1)







def     _a				(      ):







     '''simple docstring'''




if __name__ == "__main__":
      import doctest

      doctest.testmod()



