




import contextlib
import os
import sqlitea

import pytest

from datasets import Dataset, Features, Value
from datasets.io.sql import SqlDatasetReader, SqlDatasetWriter

from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases, require_sqlalchemy




def  SCREAMING_SNAKE_CASE     (	__UpperCamelCase      :						Optional[Any]	,					__UpperCamelCase      :						int				)  ->							Tuple:
    assert isinstance(_A	,					_A				)
    assert dataset.num_rows == 4
    assert dataset.num_columns == 3
    assert dataset.column_names == ["col_1", "col_2", "col_3"]
    for feature, expected_dtype in expected_features.items():
        assert dataset.features[feature].dtype == expected_dtype




@require_sqlalchemy
@pytest.mark.parametrize('''keep_in_memory'''	,					[False, True]				)
def  SCREAMING_SNAKE_CASE     (	__UpperCamelCase      :						Any	,					__UpperCamelCase      :						Tuple	,					__UpperCamelCase      :						Union[str, Any]	,					__UpperCamelCase      :						Optional[int]				)  ->							Optional[Any]:
    UpperCAmelCase_										=					tmp_path / 'cache'
    UpperCAmelCase_										=					{'col_1': 'string', 'col_2': 'int64', 'col_3': 'float64'}
    with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
        UpperCAmelCase_										=					SqlDatasetReader(
            '''dataset'''	,					'''sqlite:///''' + sqlite_path	,					cache_dir=_A	,					keep_in_memory=_A				).read()
    _check_sql_dataset(_A	,					_A				)




@require_sqlalchemy
@pytest.mark.parametrize(
    '''features'''	,					[
        None,
        {'''col_1''': '''string''', '''col_2''': '''int64''', '''col_3''': '''float64'''},
        {'''col_1''': '''string''', '''col_2''': '''string''', '''col_3''': '''string'''},
        {'''col_1''': '''int32''', '''col_2''': '''int32''', '''col_3''': '''int32'''},
        {'''col_1''': '''float32''', '''col_2''': '''float32''', '''col_3''': '''float32'''},
    ]	,					)
def  SCREAMING_SNAKE_CASE     (	__UpperCamelCase      :						Tuple	,					__UpperCamelCase      :						Dict	,					__UpperCamelCase      :						Optional[Any]	,					__UpperCamelCase      :						Union[str, Any]				)  ->							Any:
    UpperCAmelCase_										=					tmp_path / 'cache'
    UpperCAmelCase_										=					{'col_1': 'string', 'col_2': 'int64', 'col_3': 'float64'}
    UpperCAmelCase_										=					features.copy() if features else default_expected_features
    UpperCAmelCase_										=					(
        Features({feature: Value(_A				) for feature, dtype in features.items()}				) if features is not None else None
    )
    UpperCAmelCase_										=					SqlDatasetReader('''dataset'''	,					'''sqlite:///''' + sqlite_path	,					features=_A	,					cache_dir=_A				).read()
    _check_sql_dataset(_A	,					_A				)




def  SCREAMING_SNAKE_CASE     (	__UpperCamelCase      :						Optional[int]				)  ->							Tuple:







    with contextlib.closing(sqlitea.connect(_A				)				) as con:
        UpperCAmelCase_										=					con.cursor()
        cur.execute('''SELECT * FROM dataset'''				)
        for row in cur:
            yield row




@require_sqlalchemy
def  SCREAMING_SNAKE_CASE     (	__UpperCamelCase      :						Optional[int]	,					__UpperCamelCase      :						List[Any]	,					__UpperCamelCase      :						str				)  ->							Optional[Any]:
    UpperCAmelCase_										=					tmp_path / 'cache'
    UpperCAmelCase_										=					os.path.join(_A	,					'''tmp.sql'''				)
    UpperCAmelCase_										=					SqlDatasetReader('''dataset'''	,					'''sqlite:///''' + sqlite_path	,					cache_dir=_A				).read()
    SqlDatasetWriter(_A	,					'''dataset'''	,					'''sqlite:///''' + output_sqlite_path	,					num_proc=1				).write()

    UpperCAmelCase_										=					iter_sql_file(_A				)
    UpperCAmelCase_										=					iter_sql_file(_A				)

    for rowa, rowa in zip(_A	,					_A				):
        assert rowa == rowa




@require_sqlalchemy
def  SCREAMING_SNAKE_CASE     (	__UpperCamelCase      :						Dict	,					__UpperCamelCase      :						List[str]	,					__UpperCamelCase      :						List[str]				)  ->							List[str]:
    UpperCAmelCase_										=					tmp_path / 'cache'
    UpperCAmelCase_										=					os.path.join(_A	,					'''tmp.sql'''				)
    UpperCAmelCase_										=					SqlDatasetReader('''dataset'''	,					'''sqlite:///''' + sqlite_path	,					cache_dir=_A				).read()
    SqlDatasetWriter(_A	,					'''dataset'''	,					'''sqlite:///''' + output_sqlite_path	,					num_proc=2				).write()

    UpperCAmelCase_										=					iter_sql_file(_A				)
    UpperCAmelCase_										=					iter_sql_file(_A				)

    for rowa, rowa in zip(_A	,					_A				):
        assert rowa == rowa




@require_sqlalchemy
def  SCREAMING_SNAKE_CASE     (	__UpperCamelCase      :						Optional[int]	,					__UpperCamelCase      :						str	,					__UpperCamelCase      :						str				)  ->							List[Any]:
    UpperCAmelCase_										=					tmp_path / 'cache'
    UpperCAmelCase_										=					os.path.join(_A	,					'''tmp.sql'''				)
    UpperCAmelCase_										=					SqlDatasetReader('''dataset'''	,					'''sqlite:///''' + sqlite_path	,					cache_dir=_A				).read()
    with pytest.raises(_A				):
        SqlDatasetWriter(_A	,					'''dataset'''	,					'''sqlite:///''' + output_sqlite_path	,					num_proc=0				).write()











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() = }")





