
import csv
import os

import pytest

from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.csv import CsvDatasetReader, CsvDatasetWriter

from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases




def 				__SCREAMING_SNAKE_CASE  (						SCREAMING_SNAKE_CASE			: Dict       ,				SCREAMING_SNAKE_CASE			: Union[str, Any]     )	->		str:
				assert isinstance(SCREAMING_SNAKE_CASE       ,				SCREAMING_SNAKE_CASE     )
				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




@pytest.mark.parametrize('keep_in_memory'       ,				[False, True]     )
def 				__SCREAMING_SNAKE_CASE  (						SCREAMING_SNAKE_CASE			: Union[str, Any]       ,				SCREAMING_SNAKE_CASE			: int       ,				SCREAMING_SNAKE_CASE			: Union[str, Any]     )	->		Tuple:
				__lowercase								=   tmp_path / 'cache'
				__lowercase								=   {'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
				with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
								__lowercase								=   CsvDatasetReader(SCREAMING_SNAKE_CASE       ,				cache_dir=SCREAMING_SNAKE_CASE       ,				keep_in_memory=SCREAMING_SNAKE_CASE     ).read()
				_check_csv_dataset(SCREAMING_SNAKE_CASE       ,				SCREAMING_SNAKE_CASE     )




@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  (						SCREAMING_SNAKE_CASE			: int       ,				SCREAMING_SNAKE_CASE			: int       ,				SCREAMING_SNAKE_CASE			: Optional[Any]     )	->		List[Any]:
				__lowercase								=   tmp_path / 'cache'
				# CSV file loses col_1 string dtype information: default now is "int64" instead of "string"
				__lowercase								=   {'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
				__lowercase								=   features.copy() if features else default_expected_features
				__lowercase								=   (
				    Features({feature: Value(SCREAMING_SNAKE_CASE     ) for feature, dtype in features.items()}     ) if features is not None else None
				)
				__lowercase								=   CsvDatasetReader(SCREAMING_SNAKE_CASE       ,				features=SCREAMING_SNAKE_CASE       ,				cache_dir=SCREAMING_SNAKE_CASE     ).read()
				_check_csv_dataset(SCREAMING_SNAKE_CASE       ,				SCREAMING_SNAKE_CASE     )




@pytest.mark.parametrize('split'       ,				[None, NamedSplit('train'     ), 'train', 'test']     )
def 				__SCREAMING_SNAKE_CASE  (						SCREAMING_SNAKE_CASE			: Any       ,				SCREAMING_SNAKE_CASE			: int       ,				SCREAMING_SNAKE_CASE			: Union[str, Any]     )	->		int:
				__lowercase								=   tmp_path / 'cache'
				__lowercase								=   {'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
				__lowercase								=   CsvDatasetReader(SCREAMING_SNAKE_CASE       ,				cache_dir=SCREAMING_SNAKE_CASE       ,				split=SCREAMING_SNAKE_CASE     ).read()
				_check_csv_dataset(SCREAMING_SNAKE_CASE       ,				SCREAMING_SNAKE_CASE     )
				assert dataset.split == split if split else "train"




@pytest.mark.parametrize('path_type'       ,				[str, list]     )
def 				__SCREAMING_SNAKE_CASE  (						SCREAMING_SNAKE_CASE			: Union[str, Any]       ,				SCREAMING_SNAKE_CASE			: Dict       ,				SCREAMING_SNAKE_CASE			: Any     )	->		str:
				if issubclass(SCREAMING_SNAKE_CASE       ,				SCREAMING_SNAKE_CASE     ):
								__lowercase								=   csv_path
				elif issubclass(SCREAMING_SNAKE_CASE       ,				SCREAMING_SNAKE_CASE     ):
								__lowercase								=   [csv_path]
				__lowercase								=   tmp_path / 'cache'
				__lowercase								=   {'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
				__lowercase								=   CsvDatasetReader(SCREAMING_SNAKE_CASE       ,				cache_dir=SCREAMING_SNAKE_CASE     ).read()
				_check_csv_dataset(SCREAMING_SNAKE_CASE       ,				SCREAMING_SNAKE_CASE     )




def 				__SCREAMING_SNAKE_CASE  (						SCREAMING_SNAKE_CASE			: Dict       ,				SCREAMING_SNAKE_CASE			: Dict       ,				SCREAMING_SNAKE_CASE			: Optional[Any]=("train",)     )	->		Optional[int]:
				assert isinstance(SCREAMING_SNAKE_CASE       ,				SCREAMING_SNAKE_CASE     )
				for split in splits:
								__lowercase								=   dataset_dict[split]
								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




@pytest.mark.parametrize('keep_in_memory'       ,				[False, True]     )
def 				__SCREAMING_SNAKE_CASE  (						SCREAMING_SNAKE_CASE			: Union[str, Any]       ,				SCREAMING_SNAKE_CASE			: Any       ,				SCREAMING_SNAKE_CASE			: str     )	->		Dict:
				__lowercase								=   tmp_path / 'cache'
				__lowercase								=   {'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
				with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
								__lowercase								=   CsvDatasetReader({'train': csv_path}       ,				cache_dir=SCREAMING_SNAKE_CASE       ,				keep_in_memory=SCREAMING_SNAKE_CASE     ).read()
				_check_csv_datasetdict(SCREAMING_SNAKE_CASE       ,				SCREAMING_SNAKE_CASE     )




@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  (						SCREAMING_SNAKE_CASE			: List[Any]       ,				SCREAMING_SNAKE_CASE			: Union[str, Any]       ,				SCREAMING_SNAKE_CASE			: Tuple     )	->		Any:
				__lowercase								=   tmp_path / 'cache'
				# CSV file loses col_1 string dtype information: default now is "int64" instead of "string"
				__lowercase								=   {'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
				__lowercase								=   features.copy() if features else default_expected_features
				__lowercase								=   (
				    Features({feature: Value(SCREAMING_SNAKE_CASE     ) for feature, dtype in features.items()}     ) if features is not None else None
				)
				__lowercase								=   CsvDatasetReader({'train': csv_path}       ,				features=SCREAMING_SNAKE_CASE       ,				cache_dir=SCREAMING_SNAKE_CASE     ).read()
				_check_csv_datasetdict(SCREAMING_SNAKE_CASE       ,				SCREAMING_SNAKE_CASE     )




@pytest.mark.parametrize('split'       ,				[None, NamedSplit('train'     ), 'train', 'test']     )
def 				__SCREAMING_SNAKE_CASE  (						SCREAMING_SNAKE_CASE			: Tuple       ,				SCREAMING_SNAKE_CASE			: List[Any]       ,				SCREAMING_SNAKE_CASE			: Union[str, Any]     )	->		Any:
				if split:
								__lowercase								=   {split: csv_path}
				else:
								__lowercase								=   {'train': csv_path, 'test': csv_path}
				__lowercase								=   tmp_path / 'cache'
				__lowercase								=   {'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
				__lowercase								=   CsvDatasetReader(SCREAMING_SNAKE_CASE       ,				cache_dir=SCREAMING_SNAKE_CASE     ).read()
				_check_csv_datasetdict(SCREAMING_SNAKE_CASE       ,				SCREAMING_SNAKE_CASE       ,				splits=list(path.keys()     )     )
				assert all(dataset[split].split == split for split in path.keys()     )




def 				__SCREAMING_SNAKE_CASE  (						SCREAMING_SNAKE_CASE			: Any     )	->		str:
				with open(SCREAMING_SNAKE_CASE       ,				encoding='utf-8'     ) as csvfile:
								yield from csv.reader(SCREAMING_SNAKE_CASE     )




def 				__SCREAMING_SNAKE_CASE  (						SCREAMING_SNAKE_CASE			: str       ,				SCREAMING_SNAKE_CASE			: Optional[Any]     )	->		Any:
				__lowercase								=   tmp_path / 'cache'
				__lowercase								=   os.path.join(SCREAMING_SNAKE_CASE       ,				'tmp.csv'     )
				__lowercase								=   CsvDatasetReader({'train': csv_path}       ,				cache_dir=SCREAMING_SNAKE_CASE     ).read()
				CsvDatasetWriter(dataset['train']       ,				SCREAMING_SNAKE_CASE       ,				num_proc=1     ).write()

				__lowercase								=   iter_csv_file(SCREAMING_SNAKE_CASE     )
				__lowercase								=   iter_csv_file(SCREAMING_SNAKE_CASE     )

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




def 				__SCREAMING_SNAKE_CASE  (						SCREAMING_SNAKE_CASE			: Any       ,				SCREAMING_SNAKE_CASE			: List[Any]     )	->		Tuple:
				__lowercase								=   tmp_path / 'cache'
				__lowercase								=   os.path.join(SCREAMING_SNAKE_CASE       ,				'tmp.csv'     )
				__lowercase								=   CsvDatasetReader({'train': csv_path}       ,				cache_dir=SCREAMING_SNAKE_CASE     ).read()
				CsvDatasetWriter(dataset['train']       ,				SCREAMING_SNAKE_CASE       ,				num_proc=2     ).write()

				__lowercase								=   iter_csv_file(SCREAMING_SNAKE_CASE     )
				__lowercase								=   iter_csv_file(SCREAMING_SNAKE_CASE     )

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




def 				__SCREAMING_SNAKE_CASE  (						SCREAMING_SNAKE_CASE			: Tuple       ,				SCREAMING_SNAKE_CASE			: List[Any]     )	->		List[Any]:
				__lowercase								=   tmp_path / 'cache'
				__lowercase								=   os.path.join(SCREAMING_SNAKE_CASE       ,				'tmp.csv'     )
				__lowercase								=   CsvDatasetReader({'train': csv_path}       ,				cache_dir=SCREAMING_SNAKE_CASE     ).read()
				with pytest.raises(SCREAMING_SNAKE_CASE     ):
								CsvDatasetWriter(dataset['train']       ,				SCREAMING_SNAKE_CASE       ,				num_proc=0     )








'''simple docstring'''

from .balanced_parentheses import balanced_parentheses
from .stack import Stack

def      __magic_name__							(			A				)      ->		int:
	return {"+": 1, "-": 1, "*": 2, "/": 2, "^": 3}.get(A       , -1				)

def      __magic_name__							(			A				)      ->		str:
	if not balanced_parentheses(A				):
		raise ValueError('Mismatched parentheses'				)
	snake_case							=					Stack()
	snake_case							=					[]
	for char in expression_str:
		if char.isalpha() or char.isdigit():
			postfix.append(A				)
		elif char == "(":
			stack.push(A				)
		elif char == ")":
			while not stack.is_empty() and stack.peek() != "(":
				postfix.append(stack.pop()				)
			stack.pop()
		else:
			while not stack.is_empty() and precedence(A				) <= precedence(stack.peek()				):
				postfix.append(stack.pop()				)
			stack.push(A				)
	while not stack.is_empty():
		postfix.append(stack.pop()				)
	return " ".join(A				)


if __name__ == "__main__":
						from doctest import testmod

						testmod()
						lowerCAmelCase_     =      "a+b*(c^d-e)^(f+g*h)-i"

						print("Infix to Postfix Notation demonstration:\n")
						print("Infix notation: " + expression)
						print("Postfix notation: " + infix_to_postfix(expression))





