"""simple docstring"""






import pytest

from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.text import TextDatasetReader

from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases



def   a_						(					lowerCamelCase					,			lowerCamelCase       ):
				assert isinstance(lowerCamelCase					,			lowerCamelCase       )
				assert dataset.num_rows == 4
				assert dataset.num_columns == 1
				assert dataset.column_names == ["text"]
				for feature, expected_dtype in expected_features.items():
								assert dataset.features[feature].dtype == expected_dtype



@pytest.mark.parametrize('keep_in_memory'					,			[False, True]       )
def   a_						(					lowerCamelCase					,			lowerCamelCase					,			lowerCamelCase       ):
				UpperCAmelCase__             =							tmp_path / 'cache'
				UpperCAmelCase__             =							{'text': 'string'}
				with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
								UpperCAmelCase__             =							TextDatasetReader(lowerCamelCase					,			cache_dir=lowerCamelCase					,			keep_in_memory=lowerCamelCase       ).read()
				_check_text_dataset(lowerCamelCase					,			lowerCamelCase       )



@pytest.mark.parametrize(
    'features'					,			[
        None,
        {'text': 'string'},
        {'text': 'int32'},
        {'text': 'float32'},
    ]					,			)
def   a_						(					lowerCamelCase					,			lowerCamelCase					,			lowerCamelCase       ):
				UpperCAmelCase__             =							tmp_path / 'cache'
				UpperCAmelCase__             =							{'text': 'string'}
				UpperCAmelCase__             =							features.copy() if features else default_expected_features
				UpperCAmelCase__             =							(
				    Features({feature: Value(lowerCamelCase       ) for feature, dtype in features.items()}       ) if features is not None else None
				)
				UpperCAmelCase__             =							TextDatasetReader(lowerCamelCase					,			features=lowerCamelCase					,			cache_dir=lowerCamelCase       ).read()
				_check_text_dataset(lowerCamelCase					,			lowerCamelCase       )



@pytest.mark.parametrize('split'					,			[None, NamedSplit('train'       ), 'train', 'test']       )
def   a_						(					lowerCamelCase					,			lowerCamelCase					,			lowerCamelCase       ):
				UpperCAmelCase__             =							tmp_path / 'cache'
				UpperCAmelCase__             =							{'text': 'string'}
				UpperCAmelCase__             =							TextDatasetReader(lowerCamelCase					,			cache_dir=lowerCamelCase					,			split=lowerCamelCase       ).read()
				_check_text_dataset(lowerCamelCase					,			lowerCamelCase       )
				assert dataset.split == split if split else "train"



@pytest.mark.parametrize('path_type'					,			[str, list]       )
def   a_						(					lowerCamelCase					,			lowerCamelCase					,			lowerCamelCase       ):
				if issubclass(lowerCamelCase					,			lowerCamelCase       ):
								UpperCAmelCase__             =							text_path
				elif issubclass(lowerCamelCase					,			lowerCamelCase       ):
								UpperCAmelCase__             =							[text_path]
				UpperCAmelCase__             =							tmp_path / 'cache'
				UpperCAmelCase__             =							{'text': 'string'}
				UpperCAmelCase__             =							TextDatasetReader(lowerCamelCase					,			cache_dir=lowerCamelCase       ).read()
				_check_text_dataset(lowerCamelCase					,			lowerCamelCase       )



def   a_						(					lowerCamelCase					,			lowerCamelCase					,			lowerCamelCase=("train",)       ):
				assert isinstance(lowerCamelCase					,			lowerCamelCase       )
				for split in splits:
								UpperCAmelCase__             =							dataset_dict[split]
								assert dataset.num_rows == 4
								assert dataset.num_columns == 1
								assert dataset.column_names == ["text"]
								for feature, expected_dtype in expected_features.items():
												assert dataset.features[feature].dtype == expected_dtype



@pytest.mark.parametrize('keep_in_memory'					,			[False, True]       )
def   a_						(					lowerCamelCase					,			lowerCamelCase					,			lowerCamelCase       ):
				UpperCAmelCase__             =							tmp_path / 'cache'
				UpperCAmelCase__             =							{'text': 'string'}
				with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
								UpperCAmelCase__             =							TextDatasetReader({'train': text_path}					,			cache_dir=lowerCamelCase					,			keep_in_memory=lowerCamelCase       ).read()
				_check_text_datasetdict(lowerCamelCase					,			lowerCamelCase       )



@pytest.mark.parametrize(
    'features'					,			[
        None,
        {'text': 'string'},
        {'text': 'int32'},
        {'text': 'float32'},
    ]					,			)
def   a_						(					lowerCamelCase					,			lowerCamelCase					,			lowerCamelCase       ):
				UpperCAmelCase__             =							tmp_path / 'cache'
				# CSV file loses col_1 string dtype information: default now is "int64" instead of "string"
				UpperCAmelCase__             =							{'text': 'string'}
				UpperCAmelCase__             =							features.copy() if features else default_expected_features
				UpperCAmelCase__             =							(
				    Features({feature: Value(lowerCamelCase       ) for feature, dtype in features.items()}       ) if features is not None else None
				)
				UpperCAmelCase__             =							TextDatasetReader({'train': text_path}					,			features=lowerCamelCase					,			cache_dir=lowerCamelCase       ).read()
				_check_text_datasetdict(lowerCamelCase					,			lowerCamelCase       )







@pytest.mark.parametrize('split'					,			[None, NamedSplit('train'       ), 'train', 'test']       )
def   a_						(					lowerCamelCase					,			lowerCamelCase					,			lowerCamelCase       ):
				if split:
								UpperCAmelCase__             =							{split: text_path}
				else:
								UpperCAmelCase__             =							'train'
								UpperCAmelCase__             =							{'train': text_path, 'test': text_path}
				UpperCAmelCase__             =							tmp_path / 'cache'
				UpperCAmelCase__             =							{'text': 'string'}
				UpperCAmelCase__             =							TextDatasetReader(lowerCamelCase					,			cache_dir=lowerCamelCase       ).read()
				_check_text_datasetdict(lowerCamelCase					,			lowerCamelCase					,			splits=list(path.keys()       )       )
				assert all(dataset[split].split == split for split in path.keys()       )




"""simple docstring"""






from __future__ import annotations

from collections import namedtuple
from dataclasses import dataclass
@dataclass
class 				snake_case       :




					"""simple docstring"""

					snake_case__				    = 42
					snake_case__				    = None
					snake_case__				    = None






lowerCAmelCase__  :  Union[str, Any]						     =	namedtuple('CoinsDistribResult', 'moves excess')



def   a_						(					lowerCamelCase       ):

				if root is None:
								return 0

				# Validation
				def count_nodes(lowerCamelCase       ) -> int:
								if node is None:
												return 0

								return count_nodes(node.left       ) + count_nodes(node.right       ) + 1

				def count_coins(lowerCamelCase       ) -> int:
								if node is None:
												return 0

								return count_coins(node.left       ) + count_coins(node.right       ) + node.data

				if count_nodes(lowerCamelCase       ) != count_coins(lowerCamelCase       ):
								raise ValueError('The nodes number should be same as the number of coins'       )

				# Main calculation
				def get_distrib(lowerCamelCase       ) -> CoinsDistribResult:

								if node is None:
												return CoinsDistribResult(0					,			1       )

								UpperCAmelCase__      ,	UpperCAmelCase__             =							get_distrib(node.left       )
								UpperCAmelCase__      ,	UpperCAmelCase__             =							get_distrib(node.right       )

								UpperCAmelCase__             =							1 - left_distrib_excess
								UpperCAmelCase__             =							1 - right_distrib_excess

								UpperCAmelCase__             =							(
								    left_distrib_moves
								    + right_distrib_moves
								    + abs(lowerCamelCase       )
								    + abs(lowerCamelCase       )
								)
								UpperCAmelCase__             =							node.data - coins_to_left - coins_to_right

								return CoinsDistribResult(lowerCamelCase					,			lowerCamelCase       )

				return get_distrib(lowerCamelCase       )[0]


if __name__ == "__main__":
						import doctest

						doctest.testmod()



