import sys
import turtle



def A__  (			lowercase:     Optional[Any],		lowercase:     int					)				->		Tuple:
    return (pa[0] + pa[0]) / 2, (pa[1] + pa[1]) / 2



def A__  (			lowercase:     int,		lowercase:     int,		lowercase:     Optional[Any],		lowercase:     Dict,		)				->		Union[str, Any]:
    my_pen.up()
    my_pen.goto(vertexa[0],		vertexa[1]					)
    my_pen.down()
    my_pen.goto(vertexa[0],		vertexa[1]					)
    my_pen.goto(vertexa[0],		vertexa[1]					)
    my_pen.goto(vertexa[0],		vertexa[1]					)

    if depth == 0:
        return

    triangle(_lowercase,		get_mid(_lowercase,		_lowercase					),		get_mid(_lowercase,		_lowercase					),		depth - 1					)
    triangle(_lowercase,		get_mid(_lowercase,		_lowercase					),		get_mid(_lowercase,		_lowercase					),		depth - 1					)
    triangle(_lowercase,		get_mid(_lowercase,		_lowercase					),		get_mid(_lowercase,		_lowercase					),		depth - 1					)


if __name__ == "__main__":
    if len(sys.argv) != 2:
        raise ValueError(
            '''Correct format for using this script: '''
            '''python fractals.py <int:depth_for_fractal>'''
        )
    _lowercase							:      int      							=turtle.Turtle()
    my_pen.ht()
    my_pen.speed(5)
    my_pen.pencolor('''red''')

    _lowercase							:      int      							=[(-1_7_5, -1_2_5), (0, 1_7_5), (1_7_5, -1_2_5)]  # vertices of triangle
    triangle(vertices[0], vertices[1], vertices[2], int(sys.argv[1]))







import io
import json

import fsspec
import pytest

from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.json import JsonDatasetReader, JsonDatasetWriter

from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases



def A__  (			lowercase:     int,		lowercase:     str					)				->		Dict:
       assert isinstance(lowercase,		lowercase					)
       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 A__  (			lowercase:     Dict,		lowercase:     Tuple,		lowercase:     str					)				->		str:
       A						:     Any         =tmp_path / 'cache'
       A						:     Dict         ={'col_1': 'string', 'col_2': 'int64', 'col_3': 'float64'}
       with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
              A						:     Dict         =JsonDatasetReader(lowercase,		cache_dir=lowercase,		keep_in_memory=lowercase					).read()
       _check_json_dataset(lowercase,		lowercase					)



@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 A__  (			lowercase:     Optional[int],		lowercase:     Any,		lowercase:     Union[str, Any]					)				->		Tuple:
       A						:     Tuple         =tmp_path / 'cache'
       A						:     Optional[Any]         ={'col_1': 'string', 'col_2': 'int64', 'col_3': 'float64'}
       A						:     Optional[Any]         =features.copy() if features else default_expected_features
       A						:     Union[str, Any]         =(
           Features({feature: Value(lowercase					) for feature, dtype in features.items()}					) if features is not None else None
       )
       A						:     str         =JsonDatasetReader(lowercase,		features=lowercase,		cache_dir=lowercase					).read()
       _check_json_dataset(lowercase,		lowercase					)



@pytest.mark.parametrize(
    'features',		[
        None,
        {'col_3': 'float64', 'col_1': 'string', 'col_2': 'int64'},
    ],		)
def A__  (			lowercase:     Optional[int],		lowercase:     str,		lowercase:     Dict					)				->		Optional[int]:
       A						:     int         =tmp_path / 'cache'
       A						:     Tuple         ={'col_3': 'float64', 'col_1': 'string', 'col_2': 'int64'}
       A						:     int         =features.copy() if features else default_expected_features
       A						:     str         =(
           Features({feature: Value(lowercase					) for feature, dtype in features.items()}					) if features is not None else None
       )
       A						:     Optional[int]         =JsonDatasetReader(lowercase,		features=lowercase,		cache_dir=lowercase					).read()
       assert isinstance(lowercase,		lowercase					)
       assert dataset.num_rows == 2
       assert dataset.num_columns == 3
       assert dataset.column_names == ["col_3", "col_1", "col_2"]
       for feature, expected_dtype in expected_features.items():
              assert dataset.features[feature].dtype == expected_dtype



def A__  (			lowercase:     Optional[Any],		lowercase:     str					)				->		Tuple:
       # jsonl_312_path features are {"col_3": "float64", "col_1": "string", "col_2": "int64"}
       A						:     str         ={'col_2': 'int64', 'col_3': 'float64', 'col_1': 'string'}
       A						:     Dict         =features.copy()
       A						:     List[str]         =(
           Features({feature: Value(lowercase					) for feature, dtype in features.items()}					) if features is not None else None
       )
       A						:     int         =tmp_path / 'cache'
       A						:     Optional[int]         =JsonDatasetReader(lowercase,		features=lowercase,		cache_dir=lowercase					).read()
       assert isinstance(lowercase,		lowercase					)
       assert dataset.num_rows == 2
       assert dataset.num_columns == 3
       assert dataset.column_names == ["col_2", "col_3", "col_1"]
       for feature, expected_dtype in expected_features.items():
              assert dataset.features[feature].dtype == expected_dtype



@pytest.mark.parametrize('split',		[None, NamedSplit('train'					), 'train', 'test']					)
def A__  (			lowercase:     Union[str, Any],		lowercase:     Any,		lowercase:     str					)				->		Optional[Any]:
       A						:     Optional[int]         =tmp_path / 'cache'
       A						:     Optional[Any]         ={'col_1': 'string', 'col_2': 'int64', 'col_3': 'float64'}
       A						:     str         =JsonDatasetReader(lowercase,		cache_dir=lowercase,		split=lowercase					).read()
       _check_json_dataset(lowercase,		lowercase					)
       assert dataset.split == split if split else "train"



@pytest.mark.parametrize('path_type',		[str, list]					)
def A__  (			lowercase:     Optional[Any],		lowercase:     int,		lowercase:     Union[str, Any]					)				->		List[Any]:
       if issubclass(lowercase,		lowercase					):
              A						:     int         =jsonl_path
       elif issubclass(lowercase,		lowercase					):
              A						:     Any         =[jsonl_path]
       A						:     Optional[Any]         =tmp_path / 'cache'
       A						:     Tuple         ={'col_1': 'string', 'col_2': 'int64', 'col_3': 'float64'}
       A						:     List[str]         =JsonDatasetReader(lowercase,		cache_dir=lowercase					).read()
       _check_json_dataset(lowercase,		lowercase					)



def A__  (			lowercase:     List[str],		lowercase:     Tuple,		lowercase:     Optional[Any]=("train",)					)				->		Tuple:
       assert isinstance(lowercase,		lowercase					)
       for split in splits:
              A						:     List[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 A__  (			lowercase:     Tuple,		lowercase:     Optional[int],		lowercase:     Any					)				->		str:
       A						:     List[str]         =tmp_path / 'cache'
       A						:     Union[str, Any]         ={'col_1': 'string', 'col_2': 'int64', 'col_3': 'float64'}
       with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
              A						:     str         =JsonDatasetReader({'train': jsonl_path},		cache_dir=lowercase,		keep_in_memory=lowercase					).read()
       _check_json_datasetdict(lowercase,		lowercase					)



@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 A__  (			lowercase:     Optional[int],		lowercase:     Optional[int],		lowercase:     Optional[int]					)				->		Tuple:
       A						:     Any         =tmp_path / 'cache'
       A						:     List[str]         ={'col_1': 'string', 'col_2': 'int64', 'col_3': 'float64'}
       A						:     str         =features.copy() if features else default_expected_features
       A						:     Dict         =(
           Features({feature: Value(lowercase					) for feature, dtype in features.items()}					) if features is not None else None
       )
       A						:     Optional[Any]         =JsonDatasetReader({'train': jsonl_path},		features=lowercase,		cache_dir=lowercase					).read()
       _check_json_datasetdict(lowercase,		lowercase					)



@pytest.mark.parametrize('split',		[None, NamedSplit('train'					), 'train', 'test']					)
def A__  (			lowercase:     Any,		lowercase:     List[Any],		lowercase:     List[Any]					)				->		Tuple:
       if split:
              A						:     Optional[int]         ={split: jsonl_path}
       else:
              A						:     Dict         ='train'
              A						:     Optional[Any]         ={'train': jsonl_path, 'test': jsonl_path}
       A						:     Tuple         =tmp_path / 'cache'
       A						:     List[str]         ={'col_1': 'string', 'col_2': 'int64', 'col_3': 'float64'}
       A						:     List[Any]         =JsonDatasetReader(lowercase,		cache_dir=lowercase					).read()
       _check_json_datasetdict(lowercase,		lowercase,		splits=list(path.keys()					)					)
       assert all(dataset[split].split == split for split in path.keys()					)



def A__  (			lowercase:     List[Any]					)				->		Tuple:
       return json.load(lowercase					)



def A__  (			lowercase:     List[Any]					)				->		Tuple:
       return [json.loads(lowercase					) for line in buffer]



class  SCREAMING_SNAKE_CASE_ :
  '''simple docstring'''


  @pytest.mark.parametrize('lines, load_json_function'      ,	[(True, load_json_lines), (False, load_json)]     )
  def 		SCREAMING_SNAKE_CASE_		(				self    :					List[Any]      ,	SCREAMING_SNAKE_CASE__    :					int      ,	SCREAMING_SNAKE_CASE__    :					Optional[Any]      ,	SCREAMING_SNAKE_CASE__    :					Optional[Any]     )    ->				Any:
         with io.BytesIO() as buffer:
                JsonDatasetWriter(SCREAMING_SNAKE_CASE__      ,	SCREAMING_SNAKE_CASE__      ,	lines=SCREAMING_SNAKE_CASE__     ).write()
                buffer.seek(0     )
                A						:     int         =load_json_function(SCREAMING_SNAKE_CASE__     )
         assert isinstance(SCREAMING_SNAKE_CASE__      ,	SCREAMING_SNAKE_CASE__     )
         assert isinstance(exported_content[0]      ,	SCREAMING_SNAKE_CASE__     )
         assert len(SCREAMING_SNAKE_CASE__     ) == 10







  @pytest.mark.parametrize(
      'orient, container, keys, len_at'      ,	[
          ('records', list, {'tokens', 'labels', 'answers', 'id'}, None),
          ('split', dict, {'columns', 'data'}, 'data'),
          ('index', dict, set('0123456789'     ), None),
          ('columns', dict, {'tokens', 'labels', 'answers', 'id'}, 'tokens'),
          ('values', list, None, None),
          ('table', dict, {'schema', 'data'}, 'data'),
      ]      ,	)
  def 		SCREAMING_SNAKE_CASE_		(				self    :					List[str]      ,	SCREAMING_SNAKE_CASE__    :					Dict      ,	SCREAMING_SNAKE_CASE__    :					Dict      ,	SCREAMING_SNAKE_CASE__    :					Optional[int]      ,	SCREAMING_SNAKE_CASE__    :					Optional[Any]      ,	SCREAMING_SNAKE_CASE__    :					Any     )    ->				Optional[Any]:
         with io.BytesIO() as buffer:
                JsonDatasetWriter(SCREAMING_SNAKE_CASE__      ,	SCREAMING_SNAKE_CASE__      ,	lines=SCREAMING_SNAKE_CASE__      ,	orient=SCREAMING_SNAKE_CASE__     ).write()
                buffer.seek(0     )
                A						:     Any         =load_json(SCREAMING_SNAKE_CASE__     )
         assert isinstance(SCREAMING_SNAKE_CASE__      ,	SCREAMING_SNAKE_CASE__     )
         if keys:
                if container is dict:
                       assert exported_content.keys() == keys
                else:
                       assert exported_content[0].keys() == keys
         else:
                assert not hasattr(SCREAMING_SNAKE_CASE__      ,	'keys'     ) and not hasattr(exported_content[0]      ,	'keys'     )
         if len_at:
                assert len(exported_content[len_at]     ) == 10
         else:
                assert len(SCREAMING_SNAKE_CASE__     ) == 10







  @pytest.mark.parametrize('lines, load_json_function'      ,	[(True, load_json_lines), (False, load_json)]     )
  def 		SCREAMING_SNAKE_CASE_		(				self    :					List[Any]      ,	SCREAMING_SNAKE_CASE__    :					Dict      ,	SCREAMING_SNAKE_CASE__    :					Optional[int]      ,	SCREAMING_SNAKE_CASE__    :					List[Any]     )    ->				Optional[int]:
         with io.BytesIO() as buffer:
                JsonDatasetWriter(SCREAMING_SNAKE_CASE__      ,	SCREAMING_SNAKE_CASE__      ,	lines=SCREAMING_SNAKE_CASE__      ,	num_proc=2     ).write()
                buffer.seek(0     )
                A						:     int         =load_json_function(SCREAMING_SNAKE_CASE__     )
         assert isinstance(SCREAMING_SNAKE_CASE__      ,	SCREAMING_SNAKE_CASE__     )
         assert isinstance(exported_content[0]      ,	SCREAMING_SNAKE_CASE__     )
         assert len(SCREAMING_SNAKE_CASE__     ) == 10







  @pytest.mark.parametrize(
      'orient, container, keys, len_at'      ,	[
          ('records', list, {'tokens', 'labels', 'answers', 'id'}, None),
          ('split', dict, {'columns', 'data'}, 'data'),
          ('index', dict, set('0123456789'     ), None),
          ('columns', dict, {'tokens', 'labels', 'answers', 'id'}, 'tokens'),
          ('values', list, None, None),
          ('table', dict, {'schema', 'data'}, 'data'),
      ]      ,	)
  def 		SCREAMING_SNAKE_CASE_		(				self    :					Tuple      ,	SCREAMING_SNAKE_CASE__    :					List[Any]      ,	SCREAMING_SNAKE_CASE__    :					List[Any]      ,	SCREAMING_SNAKE_CASE__    :					List[str]      ,	SCREAMING_SNAKE_CASE__    :					Tuple      ,	SCREAMING_SNAKE_CASE__    :					Optional[Any]     )    ->				Optional[Any]:
         with io.BytesIO() as buffer:
                JsonDatasetWriter(SCREAMING_SNAKE_CASE__      ,	SCREAMING_SNAKE_CASE__      ,	lines=SCREAMING_SNAKE_CASE__      ,	orient=SCREAMING_SNAKE_CASE__      ,	num_proc=2     ).write()
                buffer.seek(0     )
                A						:     List[Any]         =load_json(SCREAMING_SNAKE_CASE__     )
         assert isinstance(SCREAMING_SNAKE_CASE__      ,	SCREAMING_SNAKE_CASE__     )
         if keys:
                if container is dict:
                       assert exported_content.keys() == keys
                else:
                       assert exported_content[0].keys() == keys
         else:
                assert not hasattr(SCREAMING_SNAKE_CASE__      ,	'keys'     ) and not hasattr(exported_content[0]      ,	'keys'     )
         if len_at:
                assert len(exported_content[len_at]     ) == 10
         else:
                assert len(SCREAMING_SNAKE_CASE__     ) == 10







  def 		SCREAMING_SNAKE_CASE_		(				self    :					str      ,	SCREAMING_SNAKE_CASE__    :					Optional[Any]     )    ->				List[Any]:
         with pytest.raises(SCREAMING_SNAKE_CASE__     ):
                with io.BytesIO() as buffer:
                       JsonDatasetWriter(SCREAMING_SNAKE_CASE__      ,	SCREAMING_SNAKE_CASE__      ,	num_proc=0     )







  @pytest.mark.parametrize('compression, extension'      ,	[('gzip', 'gz'), ('bz2', 'bz2'), ('xz', 'xz')]     )
  def 		SCREAMING_SNAKE_CASE_		(				self    :					Dict      ,	SCREAMING_SNAKE_CASE__    :					Optional[Any]      ,	SCREAMING_SNAKE_CASE__    :					Optional[Any]      ,	SCREAMING_SNAKE_CASE__    :					List[str]      ,	SCREAMING_SNAKE_CASE__    :					Optional[int]      ,	SCREAMING_SNAKE_CASE__    :					Dict     )    ->				str:
         A						:     Union[str, Any]         =tmp_path_factory.mktemp('data'     ) / f'test.json.{extension}'
         A						:     Union[str, Any]         =str(shared_datadir / f'test_file.json.{extension}'     )
         JsonDatasetWriter(SCREAMING_SNAKE_CASE__      ,	SCREAMING_SNAKE_CASE__      ,	compression=SCREAMING_SNAKE_CASE__     ).write()

         with fsspec.open(SCREAMING_SNAKE_CASE__      ,	'rb'      ,	compression='infer'     ) as f:
                A						:     str         =f.read()
         with fsspec.open(SCREAMING_SNAKE_CASE__      ,	'rb'      ,	compression='infer'     ) as f:
                A						:     List[str]         =f.read()
         assert exported_content == original_content






