




'''simple docstring'''
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  lowerCamelCase(       SCREAMING_SNAKE_CASE_					,SCREAMING_SNAKE_CASE_    )		->		Tuple:
			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  lowerCamelCase(       SCREAMING_SNAKE_CASE_					,SCREAMING_SNAKE_CASE_					,SCREAMING_SNAKE_CASE_    )		->		List[Any]:
			A_       		=   tmp_path / 'cache'
			A_       		=   {'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
			with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
						A_       		=   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  lowerCamelCase(       SCREAMING_SNAKE_CASE_					,SCREAMING_SNAKE_CASE_					,SCREAMING_SNAKE_CASE_    )		->		str:
			A_       		=   tmp_path / 'cache'
			# CSV file loses col_1 string dtype information: default now is "int64" instead of "string"
			A_       		=   {'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
			A_       		=   features.copy() if features else default_expected_features
			A_       		=   (
			    Features({feature: Value(SCREAMING_SNAKE_CASE_    ) for feature, dtype in features.items()}    ) if features is not None else None
			)
			A_       		=   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  lowerCamelCase(       SCREAMING_SNAKE_CASE_					,SCREAMING_SNAKE_CASE_					,SCREAMING_SNAKE_CASE_    )		->		Any:
			A_       		=   tmp_path / 'cache'
			A_       		=   {'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
			A_       		=   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  lowerCamelCase(       SCREAMING_SNAKE_CASE_					,SCREAMING_SNAKE_CASE_					,SCREAMING_SNAKE_CASE_    )		->		Optional[int]:
			if issubclass(SCREAMING_SNAKE_CASE_					,SCREAMING_SNAKE_CASE_    ):
						A_       		=   csv_path
			elif issubclass(SCREAMING_SNAKE_CASE_					,SCREAMING_SNAKE_CASE_    ):
						A_       		=   [csv_path]
			A_       		=   tmp_path / 'cache'
			A_       		=   {'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
			A_       		=   CsvDatasetReader(SCREAMING_SNAKE_CASE_					,cache_dir=SCREAMING_SNAKE_CASE_    ).read()
			_check_csv_dataset(SCREAMING_SNAKE_CASE_					,SCREAMING_SNAKE_CASE_    )





def  lowerCamelCase(       SCREAMING_SNAKE_CASE_					,SCREAMING_SNAKE_CASE_					,SCREAMING_SNAKE_CASE_=("train",)    )		->		Union[str, Any]:
			assert isinstance(SCREAMING_SNAKE_CASE_					,SCREAMING_SNAKE_CASE_    )
			for split in splits:
						A_       		=   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  lowerCamelCase(       SCREAMING_SNAKE_CASE_					,SCREAMING_SNAKE_CASE_					,SCREAMING_SNAKE_CASE_    )		->		Optional[Any]:
			A_       		=   tmp_path / 'cache'
			A_       		=   {'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
			with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
						A_       		=   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  lowerCamelCase(       SCREAMING_SNAKE_CASE_					,SCREAMING_SNAKE_CASE_					,SCREAMING_SNAKE_CASE_    )		->		str:
			A_       		=   tmp_path / 'cache'
			# CSV file loses col_1 string dtype information: default now is "int64" instead of "string"
			A_       		=   {'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
			A_       		=   features.copy() if features else default_expected_features
			A_       		=   (
			    Features({feature: Value(SCREAMING_SNAKE_CASE_    ) for feature, dtype in features.items()}    ) if features is not None else None
			)
			A_       		=   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  lowerCamelCase(       SCREAMING_SNAKE_CASE_					,SCREAMING_SNAKE_CASE_					,SCREAMING_SNAKE_CASE_    )		->		Optional[int]:
			if split:
						A_       		=   {split: csv_path}
			else:
						A_       		=   {'train': csv_path, 'test': csv_path}
			A_       		=   tmp_path / 'cache'
			A_       		=   {'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
			A_       		=   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  lowerCamelCase(       SCREAMING_SNAKE_CASE_    )		->		Optional[int]:
			with open(SCREAMING_SNAKE_CASE_					,encoding='utf-8'    ) as csvfile:
						yield from csv.reader(SCREAMING_SNAKE_CASE_    )





def  lowerCamelCase(       SCREAMING_SNAKE_CASE_					,SCREAMING_SNAKE_CASE_    )		->		List[str]:
			A_       		=   tmp_path / 'cache'
			A_       		=   os.path.join(SCREAMING_SNAKE_CASE_					,'tmp.csv'    )
			A_       		=   CsvDatasetReader({'train': csv_path}					,cache_dir=SCREAMING_SNAKE_CASE_    ).read()
			CsvDatasetWriter(dataset['train']					,SCREAMING_SNAKE_CASE_					,num_proc=1    ).write()

			A_       		=   iter_csv_file(SCREAMING_SNAKE_CASE_    )
			A_       		=   iter_csv_file(SCREAMING_SNAKE_CASE_    )

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





def  lowerCamelCase(       SCREAMING_SNAKE_CASE_					,SCREAMING_SNAKE_CASE_    )		->		List[str]:
			A_       		=   tmp_path / 'cache'
			A_       		=   os.path.join(SCREAMING_SNAKE_CASE_					,'tmp.csv'    )
			A_       		=   CsvDatasetReader({'train': csv_path}					,cache_dir=SCREAMING_SNAKE_CASE_    ).read()
			CsvDatasetWriter(dataset['train']					,SCREAMING_SNAKE_CASE_					,num_proc=2    ).write()

			A_       		=   iter_csv_file(SCREAMING_SNAKE_CASE_    )
			A_       		=   iter_csv_file(SCREAMING_SNAKE_CASE_    )

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






def  lowerCamelCase(       SCREAMING_SNAKE_CASE_					,SCREAMING_SNAKE_CASE_    )		->		int:
			A_       		=   tmp_path / 'cache'
			A_       		=   os.path.join(SCREAMING_SNAKE_CASE_					,'tmp.csv'    )
			A_       		=   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'''
def  lowerCamelCase(       SCREAMING_SNAKE_CASE_    )		->		list:
			A_       		=   [True for i in range(n + 1    )]
			A_       		=   [i - 1 for i in range(n + 1    )]
			A_       		=   []
			for i in range(2					,n + 1    ):
						if is_prime[i]:
									primes.append(SCREAMING_SNAKE_CASE_    )
						for j in range(0					,len(SCREAMING_SNAKE_CASE_    )    ):
									if i * primes[j] >= n:
												break
									A_       		=   False

									if i % primes[j] == 0:
												A_       		=   totients[i] * primes[j]
												break

									A_       		=   totients[i] * (primes[j] - 1)

			return totients


if __name__ == "__main__":
							import doctest

							doctest.testmod()




