





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_		(					lowerCAmelCase:		Union[str, Any]			,							lowerCAmelCase:		Union[str, Any] )->						Any:
  assert isinstance(__UpperCamelCase			,							__UpperCamelCase )
  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_		(					lowerCAmelCase:		List[str]			,							lowerCAmelCase:		List[str]			,							lowerCAmelCase:		Union[str, Any] )->						int:
  _snake_case      : Optional[int]														=		tmp_path / 'cache'
  _snake_case      : int														=		{'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
  with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
    _snake_case      : int														=		CsvDatasetReader(__UpperCamelCase			,							cache_dir=__UpperCamelCase			,							keep_in_memory=__UpperCamelCase ).read()
  _check_csv_dataset(__UpperCamelCase			,							__UpperCamelCase )


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


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


@pytest.mark.parametrize('path_type'			,							[str, list] )
def 			lowerCamelCase_		(					lowerCAmelCase:		str			,							lowerCAmelCase:		str			,							lowerCAmelCase:		List[Any] )->						List[Any]:
  if issubclass(__UpperCamelCase			,							__UpperCamelCase ):
    _snake_case      : Tuple														=		csv_path
  elif issubclass(__UpperCamelCase			,							__UpperCamelCase ):
    _snake_case      : Union[str, Any]														=		[csv_path]
  _snake_case      : List[Any]														=		tmp_path / 'cache'
  _snake_case      : Union[str, Any]														=		{'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
  _snake_case      : List[Any]														=		CsvDatasetReader(__UpperCamelCase			,							cache_dir=__UpperCamelCase ).read()
  _check_csv_dataset(__UpperCamelCase			,							__UpperCamelCase )


def 			lowerCamelCase_		(					lowerCAmelCase:		List[str]			,							lowerCAmelCase:		List[Any]			,							lowerCAmelCase:		int=("train",) )->						int:
  assert isinstance(__UpperCamelCase			,							__UpperCamelCase )
  for split in splits:
    _snake_case      : str														=		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_		(					lowerCAmelCase:		List[Any]			,							lowerCAmelCase:		List[str]			,							lowerCAmelCase:		Optional[int] )->						Optional[Any]:
  _snake_case      : Any														=		tmp_path / 'cache'
  _snake_case      : Any														=		{'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
  with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
    _snake_case      : Optional[Any]														=		CsvDatasetReader({'train': csv_path}			,							cache_dir=__UpperCamelCase			,							keep_in_memory=__UpperCamelCase ).read()
  _check_csv_datasetdict(__UpperCamelCase			,							__UpperCamelCase )


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


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


def 			lowerCamelCase_		(					lowerCAmelCase:		Union[str, Any] )->						Optional[int]:
  with open(__UpperCamelCase			,							encoding='utf-8' ) as csvfile:
    yield from csv.reader(__UpperCamelCase )


def 			lowerCamelCase_		(					lowerCAmelCase:		List[str]			,							lowerCAmelCase:		List[Any] )->						str:
  _snake_case      : Dict														=		tmp_path / 'cache'
  _snake_case      : Optional[int]														=		os.path.join(__UpperCamelCase			,							'tmp.csv' )
  _snake_case      : Optional[int]														=		CsvDatasetReader({'train': csv_path}			,							cache_dir=__UpperCamelCase ).read()
  CsvDatasetWriter(dataset['train']			,							__UpperCamelCase			,							num_proc=1 ).write()

  _snake_case      : Optional[int]														=		iter_csv_file(__UpperCamelCase )
  _snake_case      : Any														=		iter_csv_file(__UpperCamelCase )

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


def 			lowerCamelCase_		(					lowerCAmelCase:		Union[str, Any]			,							lowerCAmelCase:		List[Any] )->						str:
  _snake_case      : int														=		tmp_path / 'cache'
  _snake_case      : Dict														=		os.path.join(__UpperCamelCase			,							'tmp.csv' )
  _snake_case      : Any														=		CsvDatasetReader({'train': csv_path}			,							cache_dir=__UpperCamelCase ).read()
  CsvDatasetWriter(dataset['train']			,							__UpperCamelCase			,							num_proc=2 ).write()

  _snake_case      : Dict														=		iter_csv_file(__UpperCamelCase )
  _snake_case      : int														=		iter_csv_file(__UpperCamelCase )

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







def 			lowerCamelCase_		(					lowerCAmelCase:		Union[str, Any]			,							lowerCAmelCase:		Union[str, Any] )->						List[Any]:
  _snake_case      : Optional[int]														=		tmp_path / 'cache'
  _snake_case      : List[Any]														=		os.path.join(__UpperCamelCase			,							'tmp.csv' )
  _snake_case      : Dict														=		CsvDatasetReader({'train': csv_path}			,							cache_dir=__UpperCamelCase ).read()
  with pytest.raises(__UpperCamelCase ):
    CsvDatasetWriter(dataset['train']			,							__UpperCamelCase			,							num_proc=0 )






"""simple docstring"""


def     _lowerCamelCase(__UpperCamelCase = 4000000       )				-> int:
	_lowerCAmelCase								=1
	_lowerCAmelCase								=2
	_lowerCAmelCase								=0
	while j <= n:
		if j % 2 == 0:
			total += j
		_lowerCAmelCase						,							_lowerCAmelCase								=j, i + j

	return total


if __name__ == "__main__":
			print(F"""{solution() = }""")



