





'''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 						__lowerCamelCase			(	UpperCAmelCase_					,				UpperCAmelCase_							)   ->List[Any]:
	assert isinstance(UpperCAmelCase_					,				UpperCAmelCase_							)
	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 						__lowerCamelCase			(	UpperCAmelCase_					,				UpperCAmelCase_					,				UpperCAmelCase_							)   ->Union[str, Any]:
	snake_case__	       =   tmp_path / 'cache'
	snake_case__	       =   {'text': 'string'}
	with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
		snake_case__	       =   TextDatasetReader(UpperCAmelCase_					,				cache_dir=UpperCAmelCase_					,				keep_in_memory=UpperCAmelCase_							).read()
	_check_text_dataset(UpperCAmelCase_					,				UpperCAmelCase_							)




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




@pytest.mark.parametrize('split'					,				[None, NamedSplit('train'							), 'train', 'test']							)
def 						__lowerCamelCase			(	UpperCAmelCase_					,				UpperCAmelCase_					,				UpperCAmelCase_							)   ->List[str]:
	snake_case__	       =   tmp_path / 'cache'
	snake_case__	       =   {'text': 'string'}
	snake_case__	       =   TextDatasetReader(UpperCAmelCase_					,				cache_dir=UpperCAmelCase_					,				split=UpperCAmelCase_							).read()
	_check_text_dataset(UpperCAmelCase_					,				UpperCAmelCase_							)
	assert dataset.split == split if split else "train"




@pytest.mark.parametrize('path_type'					,				[str, list]							)
def 						__lowerCamelCase			(	UpperCAmelCase_					,				UpperCAmelCase_					,				UpperCAmelCase_							)   ->Tuple:
	if issubclass(UpperCAmelCase_					,				UpperCAmelCase_							):
		snake_case__	       =   text_path
	elif issubclass(UpperCAmelCase_					,				UpperCAmelCase_							):
		snake_case__	       =   [text_path]
	snake_case__	       =   tmp_path / 'cache'
	snake_case__	       =   {'text': 'string'}
	snake_case__	       =   TextDatasetReader(UpperCAmelCase_					,				cache_dir=UpperCAmelCase_							).read()
	_check_text_dataset(UpperCAmelCase_					,				UpperCAmelCase_							)




def 						__lowerCamelCase			(	UpperCAmelCase_					,				UpperCAmelCase_					,				UpperCAmelCase_=("train",)							)   ->Union[str, Any]:
	assert isinstance(UpperCAmelCase_					,				UpperCAmelCase_							)
	for split in splits:
		snake_case__	       =   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 						__lowerCamelCase			(	UpperCAmelCase_					,				UpperCAmelCase_					,				UpperCAmelCase_							)   ->Union[str, Any]:
	snake_case__	       =   tmp_path / 'cache'
	snake_case__	       =   {'text': 'string'}
	with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
		snake_case__	       =   TextDatasetReader({'train': text_path}					,				cache_dir=UpperCAmelCase_					,				keep_in_memory=UpperCAmelCase_							).read()
	_check_text_datasetdict(UpperCAmelCase_					,				UpperCAmelCase_							)




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







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










'''simple docstring'''




a__					:			Optional[Any]          =     '''Alexander Joslin'''

import operator as op

from .stack import Stack




def 						__lowerCamelCase			(	UpperCAmelCase_							)   ->int:
	snake_case__	       =   {'*': op.mul, '/': op.truediv, '+': op.add, '-': op.sub}

	snake_case__	       =   Stack()
	snake_case__	       =   Stack()

	for i in equation:
		if i.isdigit():
			# RULE 1
			operand_stack.push(int(UpperCAmelCase_							)							)
		elif i in operators:
			# RULE 2
			operator_stack.push(UpperCAmelCase_							)
		elif i == ")":
			# RULE 4
			snake_case__	       =   operator_stack.peek()
			operator_stack.pop()
			snake_case__	       =   operand_stack.peek()
			operand_stack.pop()
			snake_case__	       =   operand_stack.peek()
			operand_stack.pop()

			snake_case__	       =   operators[opr](UpperCAmelCase_					,				UpperCAmelCase_							)
			operand_stack.push(UpperCAmelCase_							)

    # RULE 5
	return operand_stack.peek()


if __name__ == "__main__":
			a__					:			Any          =     '''(5 + ((4 * 2) * (2 + 3)))'''
			# answer = 45
			print(f"""{equation} = {dijkstras_two_stack_algorithm(equation)}""")



