


from __future__ import annotations

from sys import maxsize
from typing import Generic, TypeVar

SCREAMING_SNAKE_CASE :   Tuple							      =				TypeVar("T")



def        UpperCamelCase_(   lowerCamelCase_				)					->		int:
    return (position - 1) // 2



def        UpperCamelCase_(   lowerCamelCase_				)					->		int:
    return (2 * position) + 1



def        UpperCamelCase_(   lowerCamelCase_				)					->		int:
    return (2 * position) + 2






class _lowerCamelCase(		Generic[T]     ):
       def __init__(      self) ->     None:




           """simple docstring"""

           _lowercase :							list[tuple[T, int]]   	=	[]
           _lowercase :							dict[T, int]   	=	{}
           _lowercase :							int   	=	0
       def __len__(      self) ->     int:




           """simple docstring"""

           return self.elements
       def __repr__(      self) ->     str:




           """simple docstring"""

           return str(self.heap)
       def     UpperCamelCase  (      self) ->     bool:




           """simple docstring"""

           return self.elements == 0
       def     UpperCamelCase  (      self,   lowerCamelCase,   lowerCamelCase) ->     None:




           """simple docstring"""

           self.heap.append((elem, weight))
           _lowercase :							str   	=	self.elements
           self.elements += 1
           self._bubble_up(lowerCamelCase)
       def     UpperCamelCase  (      self) ->     T:




           """simple docstring"""

           if self.elements > 1:
               self._swap_nodes(0,   self.elements - 1)
           _lowercase	,       _lowercase :							Any   	=	self.heap.pop()
           del self.position_map[elem]
           self.elements -= 1
           if self.elements > 0:
               _lowercase	,       _lowercase :							int   	=	self.heap[0]
               self._bubble_down(lowerCamelCase)
           return elem
       def     UpperCamelCase  (      self,   lowerCamelCase,   lowerCamelCase) ->     None:




           """simple docstring"""

           _lowercase :							List[Any]   	=	self.position_map[elem]
           _lowercase :							Tuple   	=	(elem, weight)
           if position > 0:
               _lowercase :							Union[str, Any]   	=	get_parent_position(lowerCamelCase)
               _lowercase	,       _lowercase :							int   	=	self.heap[parent_position]
               if parent_weight > weight:
                   self._bubble_up(lowerCamelCase)
               else:
                   self._bubble_down(lowerCamelCase)
           else:
               self._bubble_down(lowerCamelCase)
       def     UpperCamelCase  (      self,   lowerCamelCase) ->     None:




           """simple docstring"""

           _lowercase :							Union[str, Any]   	=	self.position_map[elem]
           if curr_pos == 0:
               return None
           _lowercase :							str   	=	get_parent_position(lowerCamelCase)
           _lowercase	,       _lowercase :							Dict   	=	self.heap[curr_pos]
           _lowercase	,       _lowercase :							List[Any]   	=	self.heap[parent_position]
           if parent_weight > weight:
               self._swap_nodes(lowerCamelCase,   lowerCamelCase)
               return self._bubble_up(lowerCamelCase)
           return None
       def     UpperCamelCase  (      self,   lowerCamelCase) ->     None:




           """simple docstring"""

           _lowercase :							Tuple   	=	self.position_map[elem]
           _lowercase	,       _lowercase :							Union[str, Any]   	=	self.heap[curr_pos]
           _lowercase :							Dict   	=	get_child_left_position(lowerCamelCase)
           _lowercase :							Tuple   	=	get_child_right_position(lowerCamelCase)
           if child_left_position < self.elements and child_right_position < self.elements:
               _lowercase	,       _lowercase :							Any   	=	self.heap[child_left_position]
               _lowercase	,       _lowercase :							List[str]   	=	self.heap[child_right_position]
               if child_right_weight < child_left_weight and child_right_weight < weight:
                   self._swap_nodes(lowerCamelCase,   lowerCamelCase)
                   return self._bubble_down(lowerCamelCase)
           if child_left_position < self.elements:
               _lowercase	,       _lowercase :							List[str]   	=	self.heap[child_left_position]
               if child_left_weight < weight:
                   self._swap_nodes(lowerCamelCase,   lowerCamelCase)
                   return self._bubble_down(lowerCamelCase)
           else:
               return None
           if child_right_position < self.elements:
               _lowercase	,       _lowercase :							Tuple   	=	self.heap[child_right_position]
               if child_right_weight < weight:
                   self._swap_nodes(lowerCamelCase,   lowerCamelCase)
                   return self._bubble_down(lowerCamelCase)
           return None




       def     UpperCamelCase  (      self,   lowerCamelCase,   lowerCamelCase) ->     None:




           """simple docstring"""

           _lowercase :							int   	=	self.heap[nodea_pos][0]
           _lowercase :							Any   	=	self.heap[nodea_pos][0]
           _lowercase	,       _lowercase :							str   	=	(
               self.heap[nodea_pos],
               self.heap[nodea_pos],
           )
           _lowercase :							Optional[Any]   	=	nodea_pos
           _lowercase :							Optional[Any]   	=	nodea_pos






class _lowerCamelCase(		Generic[T]     ):
       def __init__(      self) ->     None:




           """simple docstring"""

           _lowercase :							dict[T, dict[T, int]]   	=	{}
           _lowercase :							int   	=	0
       def __repr__(      self) ->     str:




           """simple docstring"""

           return str(self.connections)
       def __len__(      self) ->     int:




           """simple docstring"""

           return self.nodes
       def     UpperCamelCase  (      self,   lowerCamelCase) ->     None:




           """simple docstring"""

           if node not in self.connections:
               _lowercase :							List[str]   	=	{}
               self.nodes += 1




       def     UpperCamelCase  (      self,   lowerCamelCase,   lowerCamelCase,   lowerCamelCase) ->     None:




           """simple docstring"""

           self.add_node(lowerCamelCase)
           self.add_node(lowerCamelCase)
           _lowercase :							Any   	=	weight
           _lowercase :							str   	=	weight



def        UpperCamelCase_(   lowerCamelCase_							,				)					->		tuple[dict[T, int], dict[T, T | None]]:
    _lowercase :							dict[T, int]   	=	{node: maxsize for node in graph.connections}
    _lowercase :							dict[T, T | None]   	=	{node: None for node in graph.connections}

    _lowercase :							MinPriorityQueue[T]   	=	MinPriorityQueue()
    for node, weight in dist.items():
        priority_queue.push(lowerCamelCase_							,				lowerCamelCase_				)

    if priority_queue.is_empty():
        return dist, parent

    # initialization
    _lowercase :							int   	=	priority_queue.extract_min()
    _lowercase :							str   	=	0
    for neighbour in graph.connections[node]:
        if dist[neighbour] > dist[node] + graph.connections[node][neighbour]:
            _lowercase :							str   	=	dist[node] + graph.connections[node][neighbour]
            priority_queue.update_key(lowerCamelCase_							,				dist[neighbour]				)
            _lowercase :							str   	=	node

    # running prim's algorithm
    while not priority_queue.is_empty():
        _lowercase :							Tuple   	=	priority_queue.extract_min()
        for neighbour in graph.connections[node]:
            if dist[neighbour] > dist[node] + graph.connections[node][neighbour]:
                _lowercase :							str   	=	dist[node] + graph.connections[node][neighbour]
                priority_queue.update_key(lowerCamelCase_							,				dist[neighbour]				)
                _lowercase :							List[Any]   	=	node
    return dist, parent






import os

import pytest
import yaml

from datasets.features.features import Features, Value
from datasets.info import DatasetInfo, DatasetInfosDict



@pytest.mark.parametrize(
    'files'							,				[
        ['full:README.md', 'dataset_infos.json'],
        ['empty:README.md', 'dataset_infos.json'],
        ['dataset_infos.json'],
        ['full:README.md'],
    ]							,				)
def        UpperCamelCase_(   lowerCamelCase_							,				lowerCamelCase_				)					->		List[str]:
    _lowercase :							Any   	=	tmp_path_factory.mktemp('dset_infos_dir'				)
    if "full:README.md" in files:
        with open(dataset_infos_dir / 'README.md'							,				'w'				) as f:
            f.write('---\ndataset_info:\n  dataset_size: 42\n---'				)
    if "empty:README.md" in files:
        with open(dataset_infos_dir / 'README.md'							,				'w'				) as f:
            f.write(''				)
    # we want to support dataset_infos.json for backward compatibility
    if "dataset_infos.json" in files:
        with open(dataset_infos_dir / 'dataset_infos.json'							,				'w'				) as f:
            f.write('{"default": {"dataset_size": 42}}'				)
    _lowercase :							Any   	=	DatasetInfosDict.from_directory(lowerCamelCase_				)
    assert dataset_infos
    assert dataset_infos["default"].dataset_size == 42



@pytest.mark.parametrize(
    'dataset_info'							,				[
        DatasetInfo(),
        DatasetInfo(
            description='foo'							,				features=Features({'a': Value('int32'				)}				)							,				builder_name='builder'							,				config_name='config'							,				version='1.0.0'							,				splits=[{'name': 'train'}]							,				download_size=42							,				),
    ]							,				)
def        UpperCamelCase_(   lowerCamelCase_							,				lowerCamelCase_				)					->		Optional[int]:
    _lowercase :							Union[str, Any]   	=	str(lowerCamelCase_				)
    dataset_info.write_to_directory(lowerCamelCase_				)
    _lowercase :							List[str]   	=	DatasetInfo.from_directory(lowerCamelCase_				)
    assert dataset_info == reloaded
    assert os.path.exists(os.path.join(lowerCamelCase_							,				'dataset_info.json'				)				)



def        UpperCamelCase_(   )					->		int:
    _lowercase :							Tuple   	=	DatasetInfo(
        description='foo'							,				citation='bar'							,				homepage='https://foo.bar'							,				license='CC0'							,				features=Features({'a': Value('int32'				)}				)							,				post_processed={}							,				supervised_keys=()							,				task_templates=[]							,				builder_name='builder'							,				config_name='config'							,				version='1.0.0'							,				splits=[{'name': 'train', 'num_examples': 42}]							,				download_checksums={}							,				download_size=1337							,				post_processing_size=442							,				dataset_size=1234							,				size_in_bytes=1337 + 442 + 1234							,				)
    _lowercase :							Optional[int]   	=	dataset_info._to_yaml_dict()
    assert sorted(lowerCamelCase_				) == sorted(DatasetInfo._INCLUDED_INFO_IN_YAML				)
    for key in DatasetInfo._INCLUDED_INFO_IN_YAML:
        assert key in dataset_info_yaml_dict
        assert isinstance(dataset_info_yaml_dict[key]							,				(list, dict, int, str)				)
    _lowercase :							str   	=	yaml.safe_dump(lowerCamelCase_				)
    _lowercase :							str   	=	yaml.safe_load(lowerCamelCase_				)
    assert dataset_info_yaml_dict == reloaded



def        UpperCamelCase_(   )					->		int:
    _lowercase :							Tuple   	=	DatasetInfo()
    _lowercase :							Tuple   	=	dataset_info._to_yaml_dict()
    assert dataset_info_yaml_dict == {}



@pytest.mark.parametrize(
    'dataset_infos_dict'							,				[
        DatasetInfosDict(),
        DatasetInfosDict({'default': DatasetInfo()}				),
        DatasetInfosDict({'my_config_name': DatasetInfo()}				),
        DatasetInfosDict(
            {
                'default': DatasetInfo(
                    description='foo'							,				features=Features({'a': Value('int32'				)}				)							,				builder_name='builder'							,				config_name='config'							,				version='1.0.0'							,				splits=[{'name': 'train'}]							,				download_size=42							,				)
            }				),
        DatasetInfosDict(
            {
                'v1': DatasetInfo(dataset_size=42				),
                'v2': DatasetInfo(dataset_size=1337				),
            }				),
    ]							,				)
def        UpperCamelCase_(   lowerCamelCase_							,				lowerCamelCase_				)					->		Dict:
    _lowercase :							Tuple   	=	str(lowerCamelCase_				)
    dataset_infos_dict.write_to_directory(lowerCamelCase_				)
    _lowercase :							Tuple   	=	DatasetInfosDict.from_directory(lowerCamelCase_				)

    # the config_name of the dataset_infos_dict take over the attribute
    for config_name, dataset_info in dataset_infos_dict.items():
        _lowercase :							Any   	=	config_name
        # the yaml representation doesn't include fields like description or citation
        # so we just test that we can recover what we can from the yaml
        _lowercase :							str   	=	DatasetInfo._from_yaml_dict(dataset_info._to_yaml_dict()				)
    assert dataset_infos_dict == reloaded

    if dataset_infos_dict:
        assert os.path.exists(os.path.join(lowerCamelCase_							,				'README.md'				)				)


