




import timeit

import numpy as np

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




def  SCREAMING_SNAKE_CASE     (	__UpperCamelCase      :						Tuple				)  ->							Tuple:
    def wrapper(*__UpperCamelCase      :						int	,					**__UpperCamelCase      :						Optional[Any]				):
        UpperCAmelCase_										=					timeit.default_timer()
        UpperCAmelCase_										=					func(*__UpperCamelCase	,					**__UpperCamelCase				)
        UpperCAmelCase_										=					timeit.default_timer() - starttime
        return delta

    UpperCAmelCase_										=					func.__name__

    return wrapper




def  SCREAMING_SNAKE_CASE     (	__UpperCamelCase      :						dict	,					__UpperCamelCase      :						List[str]=100	,					__UpperCamelCase      :						List[Any]=None				)  ->							Union[str, Any]:
    UpperCAmelCase_										=					[]
    UpperCAmelCase_										=					seq_shapes or {}
    for i in range(__UpperCamelCase				):
        UpperCAmelCase_										=					{}
        for col_id, (k, v) in enumerate(features.items()				):
            if isinstance(__UpperCamelCase	,					_ArrayXD				):
                UpperCAmelCase_										=					np.random.rand(*v.shape				).astype(v.dtype				)
            elif isinstance(__UpperCamelCase	,					datasets.Value				):
                if v.dtype == "string":
                    UpperCAmelCase_										=					'''The small grey turtle was surprisingly fast when challenged.'''
                else:
                    UpperCAmelCase_										=					np.random.randint(10	,					size=1				).astype(v.dtype				).item()
            elif isinstance(__UpperCamelCase	,					datasets.Sequence				):
                while isinstance(__UpperCamelCase	,					datasets.Sequence				):
                    UpperCAmelCase_										=					v.feature
                UpperCAmelCase_										=					seq_shapes[k]
                UpperCAmelCase_										=					np.random.rand(*__UpperCamelCase				).astype(v.dtype				)
            UpperCAmelCase_										=					data

        dummy_data.append((i, example)				)

    return dummy_data




def  SCREAMING_SNAKE_CASE     (	__UpperCamelCase      :						List[str]	,					__UpperCamelCase      :						Optional[int]	,					__UpperCamelCase      :						List[Any]=100	,					__UpperCamelCase      :						str=None				)  ->							Union[str, Any]:
    UpperCAmelCase_										=					generate_examples(__UpperCamelCase	,					num_examples=__UpperCamelCase	,					seq_shapes=__UpperCamelCase				)

    with ArrowWriter(features=__UpperCamelCase	,					path=__UpperCamelCase				) as writer:
        for key, record in dummy_data:
            UpperCAmelCase_										=					features.encode_example(__UpperCamelCase				)
            writer.write(__UpperCamelCase				)

        UpperCAmelCase_			,							UpperCAmelCase_										=					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}.'				)

    UpperCAmelCase_										=					datasets.Dataset.from_file(filename=__UpperCamelCase	,					info=datasets.DatasetInfo(features=__UpperCamelCase				)				)

    return dataset











from __future__ import annotations

import os
from collections.abc import Mapping

_lowerCamelCase      			=						tuple[int, int]



class       a					:

     '''simple docstring'''





     def __init__(     self       :      str ,   __snake_case       :      set[int] ,   __snake_case       :      Mapping[EdgeT, int]    ):
         UpperCAmelCase_										=					vertices
         UpperCAmelCase_										=					{
             (min(__snake_case    ), max(__snake_case    )): weight for edge, weight in edges.items()
         }
     def   lowerCamelCase_       (     self       :      Any ,   __snake_case       :      EdgeT ,   __snake_case       :      int    ):
         self.vertices.add(edge[0]    )
         self.vertices.add(edge[1]    )
         UpperCAmelCase_										=					weight




     def   lowerCamelCase_       (     self       :      Union[str, Any]    ):
         UpperCAmelCase_										=					Graph({min(self.vertices    )} ,   {}    )
         UpperCAmelCase_										=					42
         UpperCAmelCase_										=					42
         UpperCAmelCase_										=					42
         UpperCAmelCase_										=					42

         while len(subgraph.vertices    ) < len(self.vertices    ):
             UpperCAmelCase_										=					max(self.edges.values()    ) + 1
             for edge, weight in self.edges.items():
                 if (edge[0] in subgraph.vertices) ^ (edge[1] in subgraph.vertices):
                     if weight < min_weight:
                         UpperCAmelCase_										=					edge
                         UpperCAmelCase_										=					weight

             subgraph.add_edge(__snake_case ,   __snake_case    )

         return subgraph




def  SCREAMING_SNAKE_CASE     (	__UpperCamelCase      :						str = "p107_network.txt"				)  ->							int:
    UpperCAmelCase_										=					os.path.abspath(os.path.dirname(__UpperCamelCase				)				)
    UpperCAmelCase_										=					os.path.join(__UpperCamelCase	,					__UpperCamelCase				)
    UpperCAmelCase_										=					{}
    UpperCAmelCase_										=					42
    UpperCAmelCase_										=					42
    UpperCAmelCase_										=					42

    with open(__UpperCamelCase				) as f:
        UpperCAmelCase_										=					f.read().strip().split('''\n'''				)

    UpperCAmelCase_										=					[line.split(''','''				) for line in data]

    for edgea in range(1	,					len(__UpperCamelCase				)				):
        for edgea in range(__UpperCamelCase				):
            if adjaceny_matrix[edgea][edgea] != "-":
                UpperCAmelCase_										=					int(adjaceny_matrix[edgea][edgea]				)

    UpperCAmelCase_										=					Graph(set(range(len(__UpperCamelCase				)				)				)	,					__UpperCamelCase				)

    UpperCAmelCase_										=					graph.prims_algorithm()

    UpperCAmelCase_										=					sum(graph.edges.values()				)
    UpperCAmelCase_										=					sum(subgraph.edges.values()				)

    return initial_total - optimal_total


if __name__ == "__main__":
 print(F"{solution() = }")





