






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__							(      _a  :					str		,  _a  :					List[str]	):





 '''simple docstring'''







 assert isinstance(A_		,  A_	)
 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__							(      _a  :					Dict		,  _a  :					Tuple		,  _a  :					str	):





 '''simple docstring'''







 snake_case__  :    Dict							       =tmp_path / """cache"""
 snake_case__  :    Optional[int]							       ={"""text""": """string"""}
 with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
  snake_case__  :    List[Any]							       =TextDatasetReader(A_		,  cache_dir=A_		,  keep_in_memory=A_	).read()
 _check_text_dataset(A_		,  A_	)







@pytest.mark.parametrize(
    """features"""		,  [
        None,
        {"""text""": """string"""},
        {"""text""": """int32"""},
        {"""text""": """float32"""},
    ]		,  )
def 			A__							(      _a  :					List[Any]		,  _a  :					Optional[Any]		,  _a  :					Optional[Any]	):





 '''simple docstring'''







 snake_case__  :    Optional[Any]							       =tmp_path / """cache"""
 snake_case__  :    Optional[int]							       ={"""text""": """string"""}
 snake_case__  :    Dict							       =features.copy() if features else default_expected_features
 snake_case__  :    Optional[int]							       =(
     Features({feature: Value(A_	) for feature, dtype in features.items()}	) if features is not None else None
 )
 snake_case__  :    str							       =TextDatasetReader(A_		,  features=A_		,  cache_dir=A_	).read()
 _check_text_dataset(A_		,  A_	)







@pytest.mark.parametrize("""split"""		,  [None, NamedSplit("""train"""	), """train""", """test"""]	)
def 			A__							(      _a  :					List[str]		,  _a  :					Any		,  _a  :					List[str]	):





 '''simple docstring'''







 snake_case__  :    List[Any]							       =tmp_path / """cache"""
 snake_case__  :    Union[str, Any]							       ={"""text""": """string"""}
 snake_case__  :    List[Any]							       =TextDatasetReader(A_		,  cache_dir=A_		,  split=A_	).read()
 _check_text_dataset(A_		,  A_	)
 assert dataset.split == split if split else "train"







@pytest.mark.parametrize("""path_type"""		,  [str, list]	)
def 			A__							(      _a  :					str		,  _a  :					Tuple		,  _a  :					Tuple	):





 '''simple docstring'''







 if issubclass(A_		,  A_	):
  snake_case__  :    str							       =text_path
 elif issubclass(A_		,  A_	):
  snake_case__  :    str							       =[text_path]
 snake_case__  :    Dict							       =tmp_path / """cache"""
 snake_case__  :    Optional[int]							       ={"""text""": """string"""}
 snake_case__  :    Any							       =TextDatasetReader(A_		,  cache_dir=A_	).read()
 _check_text_dataset(A_		,  A_	)







def 			A__							(      _a  :					Any		,  _a  :					int		,  _a  :					Tuple=("train",)	):





 '''simple docstring'''







 assert isinstance(A_		,  A_	)
 for split in splits:
  snake_case__  :    Optional[Any]							       =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__							(      _a  :					int		,  _a  :					int		,  _a  :					Optional[int]	):





 '''simple docstring'''







 snake_case__  :    str							       =tmp_path / """cache"""
 snake_case__  :    str							       ={"""text""": """string"""}
 with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
  snake_case__  :    Dict							       =TextDatasetReader({"""train""": text_path}		,  cache_dir=A_		,  keep_in_memory=A_	).read()
 _check_text_datasetdict(A_		,  A_	)







@pytest.mark.parametrize(
    """features"""		,  [
        None,
        {"""text""": """string"""},
        {"""text""": """int32"""},
        {"""text""": """float32"""},
    ]		,  )
def 			A__							(      _a  :					Optional[Any]		,  _a  :					List[str]		,  _a  :					Optional[int]	):





 '''simple docstring'''







 snake_case__  :    Tuple							       =tmp_path / """cache"""
 # CSV file loses col_1 string dtype information: default now is "int64" instead of "string"
 snake_case__  :    Any							       ={"""text""": """string"""}
 snake_case__  :    Union[str, Any]							       =features.copy() if features else default_expected_features
 snake_case__  :    Any							       =(
     Features({feature: Value(A_	) for feature, dtype in features.items()}	) if features is not None else None
 )
 snake_case__  :    Any							       =TextDatasetReader({"""train""": text_path}		,  features=A_		,  cache_dir=A_	).read()
 _check_text_datasetdict(A_		,  A_	)







@pytest.mark.parametrize("""split"""		,  [None, NamedSplit("""train"""	), """train""", """test"""]	)
def 			A__							(      _a  :					Tuple		,  _a  :					Union[str, Any]		,  _a  :					str	):





 '''simple docstring'''







 if split:
  snake_case__  :    str							       ={split: text_path}
 else:
  snake_case__  :    List[Any]							       ="""train"""
  snake_case__  :    Dict							       ={"""train""": text_path, """test""": text_path}
 snake_case__  :    Union[str, Any]							       =tmp_path / """cache"""
 snake_case__  :    str							       ={"""text""": """string"""}
 snake_case__  :    List[Any]							       =TextDatasetReader(A_		,  cache_dir=A_	).read()
 _check_text_datasetdict(A_		,  A_		,  splits=list(path.keys()	)	)
 assert all(dataset[split].split == split for split in path.keys()	)













class  _lowercase   :
      def __init__(     self				,			a   ):
       snake_case__  :    Optional[int]							       =size
       snake_case__  :    List[Any]							       =[0] * size
       snake_case__  :    List[Any]							       =[0] * size
      @staticmethod
      def 						lowercase__					(     a   ):
       return index | (index + 1)
      @staticmethod
      def 						lowercase__					(     a   ):
       return (index & (index + 1)) - 1
      def 						lowercase__					(     self				,			a				,			a   ):
       snake_case__  :    Optional[Any]							       =value
       while index < self.size:
        snake_case__  :    str							       =self.get_prev(a   ) + 1
        if current_left_border == index:
         snake_case__  :    Dict							       =value
        else:
         snake_case__  :    str							       =max(a				,			a				,			a   )
        snake_case__  :    Dict							       =self.get_next(a   )



      def 						lowercase__					(     self				,			a				,			a   ):
       right -= 1  # Because of right is exclusive
       snake_case__  :    Union[str, Any]							       =0
       while left <= right:
        snake_case__  :    List[str]							       =self.get_prev(a   )
        if left <= current_left:
         snake_case__  :    Optional[Any]							       =max(a				,			self.tree[right]   )
         snake_case__  :    Optional[Any]							       =current_left
        else:
         snake_case__  :    Tuple							       =max(a				,			self.arr[right]   )
         right -= 1
       return result


if __name__ == "__main__":
       import doctest

       doctest.testmod()





