


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    snake_case_     (  snake_case			,							snake_case     )  ->				str:
       assert isinstance(a_			,							a_     )
       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    snake_case_     (  snake_case			,							snake_case			,							snake_case     )  ->				Optional[Any]:
       lowercase__:   Optional[int]  			=   tmp_path / '''cache'''
       lowercase__:   List[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():
              lowercase__:   List[Any]  			=   JsonDatasetReader(a_			,							cache_dir=a_			,							keep_in_memory=a_     ).read()
       _check_json_dataset(a_			,							a_     )




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




@pytest.mark.parametrize(
    'features'			,							[
        None,
        {'col_3': 'float64', 'col_1': 'string', 'col_2': 'int64'},
    ]			,							)
def    snake_case_     (  snake_case			,							snake_case			,							snake_case     )  ->				Any:
       lowercase__:   int  			=   tmp_path / '''cache'''
       lowercase__:   Union[str, Any]  			=   {'''col_3''': '''float64''', '''col_1''': '''string''', '''col_2''': '''int64'''}
       lowercase__:   Tuple  			=   features.copy() if features else default_expected_features
       lowercase__:   Dict  			=   (
           Features({feature: Value(a_     ) for feature, dtype in features.items()}     ) if features is not None else None
       )
       lowercase__:   Tuple  			=   JsonDatasetReader(a_			,							features=a_			,							cache_dir=a_     ).read()
       assert isinstance(a_			,							a_     )
       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    snake_case_     (  snake_case			,							snake_case     )  ->				Union[str, Any]:
       # jsonl_312_path features are {"col_3": "float64", "col_1": "string", "col_2": "int64"}
       lowercase__:   List[Any]  			=   {'''col_2''': '''int64''', '''col_3''': '''float64''', '''col_1''': '''string'''}
       lowercase__:   Any  			=   features.copy()
       lowercase__:   Optional[Any]  			=   (
           Features({feature: Value(a_     ) for feature, dtype in features.items()}     ) if features is not None else None
       )
       lowercase__:   Dict  			=   tmp_path / '''cache'''
       lowercase__:   Union[str, Any]  			=   JsonDatasetReader(a_			,							features=a_			,							cache_dir=a_     ).read()
       assert isinstance(a_			,							a_     )
       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    snake_case_     (  snake_case			,							snake_case			,							snake_case     )  ->				List[Any]:
       lowercase__:   int  			=   tmp_path / '''cache'''
       lowercase__:   Optional[Any]  			=   {'''col_1''': '''string''', '''col_2''': '''int64''', '''col_3''': '''float64'''}
       lowercase__:   Dict  			=   JsonDatasetReader(a_			,							cache_dir=a_			,							split=a_     ).read()
       _check_json_dataset(a_			,							a_     )
       assert dataset.split == split if split else "train"




@pytest.mark.parametrize('path_type'			,							[str, list]     )
def    snake_case_     (  snake_case			,							snake_case			,							snake_case     )  ->				Dict:
       if issubclass(a_			,							a_     ):
              lowercase__:   Any  			=   jsonl_path
       elif issubclass(a_			,							a_     ):
              lowercase__:   Dict  			=   [jsonl_path]
       lowercase__:   List[str]  			=   tmp_path / '''cache'''
       lowercase__:   int  			=   {'''col_1''': '''string''', '''col_2''': '''int64''', '''col_3''': '''float64'''}
       lowercase__:   str  			=   JsonDatasetReader(a_			,							cache_dir=a_     ).read()
       _check_json_dataset(a_			,							a_     )




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




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




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




def    snake_case_     (  snake_case     )  ->				Tuple:
       return json.load(a_     )




def    snake_case_     (  snake_case     )  ->				Optional[int]:
       return [json.loads(a_     ) for line in buffer]





class   __a			:
 @pytest.mark.parametrize('lines, load_json_function'				, [(True, load_json_lines), (False, load_json)] )
 def 		SCREAMING_SNAKE_CASE__   (   self				, lowerCAmelCase__				, lowerCAmelCase__				, lowerCAmelCase__ )					->				Union[str, Any]:




        '''simple docstring'''






        with io.BytesIO() as buffer:
               JsonDatasetWriter(SCREAMING_SNAKE_CASE__				, SCREAMING_SNAKE_CASE__				, lines=SCREAMING_SNAKE_CASE__ ).write()
               buffer.seek(0 )
               lowercase__:   Union[str, Any]  			=   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				, lowerCAmelCase__				, lowerCAmelCase__				, lowerCAmelCase__				, lowerCAmelCase__				, lowerCAmelCase__ )					->				Any:




        '''simple docstring'''






        with io.BytesIO() as buffer:
               JsonDatasetWriter(SCREAMING_SNAKE_CASE__				, SCREAMING_SNAKE_CASE__				, lines=SCREAMING_SNAKE_CASE__				, orient=SCREAMING_SNAKE_CASE__ ).write()
               buffer.seek(0 )
               lowercase__:   Union[str, 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				, lowerCAmelCase__				, lowerCAmelCase__				, lowerCAmelCase__ )					->				Optional[Any]:




        '''simple docstring'''






        with io.BytesIO() as buffer:
               JsonDatasetWriter(SCREAMING_SNAKE_CASE__				, SCREAMING_SNAKE_CASE__				, lines=SCREAMING_SNAKE_CASE__				, num_proc=2 ).write()
               buffer.seek(0 )
               lowercase__:   Union[str, Any]  			=   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				, lowerCAmelCase__				, lowerCAmelCase__				, lowerCAmelCase__				, lowerCAmelCase__				, lowerCAmelCase__ )					->				str:




        '''simple docstring'''






        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 )
               lowercase__:   Optional[int]  			=   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				, lowerCAmelCase__ )					->				Optional[int]:




        '''simple docstring'''






        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				, lowerCAmelCase__				, lowerCAmelCase__				, lowerCAmelCase__				, lowerCAmelCase__				, lowerCAmelCase__ )					->				Any:




        '''simple docstring'''
        lowercase__:   Optional[Any]  			=   tmp_path_factory.mktemp('data' ) / F'test.json.{extension}'
        lowercase__:   int  			=   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:
               lowercase__:   List[Any]  			=   f.read()
        with fsspec.open(SCREAMING_SNAKE_CASE__				, 'rb'				, compression='infer' ) as f:
               lowercase__:   Union[str, Any]  			=   f.read()
        assert exported_content == original_content









"""simple docstring"""
from manim import *






class 					_SCREAMING_SNAKE_CASE(   A  ):




       def     _UpperCamelCase     (						self							)			->      str:





             """simple docstring"""






             __SCREAMING_SNAKE_CASE   :Optional[Any]						=  Rectangle(height=0.5		,width=0.5							)
             __SCREAMING_SNAKE_CASE   :List[str]						=  Rectangle(height=0.4_6		,width=0.4_6							).set_stroke(width=0							)

             __SCREAMING_SNAKE_CASE   :List[str]						=  [mem.copy() for i in range(6							)]
             __SCREAMING_SNAKE_CASE   :List[str]						=  [mem.copy() for i in range(6							)]
             __SCREAMING_SNAKE_CASE   :Optional[int]						=  VGroup(*SCREAMING_SNAKE_CASE__							).arrange(SCREAMING_SNAKE_CASE__		,buff=0							)
             __SCREAMING_SNAKE_CASE   :Optional[Any]						=  VGroup(*SCREAMING_SNAKE_CASE__							).arrange(SCREAMING_SNAKE_CASE__		,buff=0							)
             __SCREAMING_SNAKE_CASE   :Any						=  VGroup(SCREAMING_SNAKE_CASE__		,SCREAMING_SNAKE_CASE__							).arrange(SCREAMING_SNAKE_CASE__		,buff=0							)
             __SCREAMING_SNAKE_CASE   :Tuple						=  Text('''CPU'''		,font_size=24							)
             __SCREAMING_SNAKE_CASE   :Optional[Any]						=  Group(SCREAMING_SNAKE_CASE__		,SCREAMING_SNAKE_CASE__							).arrange(SCREAMING_SNAKE_CASE__		,buff=0.5		,aligned_edge=SCREAMING_SNAKE_CASE__							)
             cpu.move_to([-2.5, -0.5, 0]							)
             self.add(SCREAMING_SNAKE_CASE__							)

             __SCREAMING_SNAKE_CASE   :List[Any]						=  [mem.copy() for i in range(1							)]
             __SCREAMING_SNAKE_CASE   :str						=  VGroup(*SCREAMING_SNAKE_CASE__							).arrange(SCREAMING_SNAKE_CASE__		,buff=0							)
             __SCREAMING_SNAKE_CASE   :Union[str, Any]						=  Text('''GPU'''		,font_size=24							)
             __SCREAMING_SNAKE_CASE   :int						=  Group(SCREAMING_SNAKE_CASE__		,SCREAMING_SNAKE_CASE__							).arrange(SCREAMING_SNAKE_CASE__		,buff=0.5		,aligned_edge=SCREAMING_SNAKE_CASE__							)
             gpu.align_to(SCREAMING_SNAKE_CASE__		,SCREAMING_SNAKE_CASE__							)
             gpu.set_x(gpu.get_x() - 1							)

             self.add(SCREAMING_SNAKE_CASE__							)

             __SCREAMING_SNAKE_CASE   :str						=  [mem.copy() for i in range(6							)]
             __SCREAMING_SNAKE_CASE   :int						=  VGroup(*SCREAMING_SNAKE_CASE__							).arrange(SCREAMING_SNAKE_CASE__		,buff=0							)

             __SCREAMING_SNAKE_CASE   :List[Any]						=  Text('''Model'''		,font_size=24							)
             __SCREAMING_SNAKE_CASE   :int						=  Group(SCREAMING_SNAKE_CASE__		,SCREAMING_SNAKE_CASE__							).arrange(SCREAMING_SNAKE_CASE__		,buff=0.5		,aligned_edge=SCREAMING_SNAKE_CASE__							)
             model.move_to([3, -1.0, 0]							)

             self.play(
                 Create(SCREAMING_SNAKE_CASE__		,run_time=1							)		,Create(SCREAMING_SNAKE_CASE__		,run_time=1							)		,Create(SCREAMING_SNAKE_CASE__		,run_time=1							)		,)

             __SCREAMING_SNAKE_CASE   :List[str]						=  MarkupText(
                 f'''First, an empty model skeleton is loaded\ninto <span fgcolor=\'{YELLOW}\'>memory</span> without using much RAM.'''		,font_size=24		,)

             __SCREAMING_SNAKE_CASE   :List[Any]						=  Square(side_length=2.2							)
             key.move_to([-5, 2, 0]							)

             __SCREAMING_SNAKE_CASE   :Optional[Any]						=  MarkupText(
                 f'''<b>Key:</b>\n\n<span fgcolor=\'{YELLOW}\'>●</span> Empty Model'''		,font_size=18		,)

             key_text.move_to([-5, 2.4, 0]							)

             step_a.move_to([2, 2, 0]							)
             self.play(Write(SCREAMING_SNAKE_CASE__		,run_time=2.5							)		,Write(SCREAMING_SNAKE_CASE__							)		,Write(SCREAMING_SNAKE_CASE__							)							)

             self.add(SCREAMING_SNAKE_CASE__							)

             __SCREAMING_SNAKE_CASE   :Union[str, Any]						=  []
             __SCREAMING_SNAKE_CASE   :int						=  []
             __SCREAMING_SNAKE_CASE   :List[Any]						=  []
             for i, rect in enumerate(SCREAMING_SNAKE_CASE__							):
                   __SCREAMING_SNAKE_CASE   :Any						=  Rectangle(height=0.4_6		,width=0.4_6							).set_stroke(width=0.0							).set_fill(SCREAMING_SNAKE_CASE__		,opacity=0.7							)
                   cpu_target.move_to(SCREAMING_SNAKE_CASE__							)
                   cpu_target.generate_target()
                   __SCREAMING_SNAKE_CASE   :Union[str, Any]						=  0.4_6 / 4
                   __SCREAMING_SNAKE_CASE   :Tuple						=  0.4_6 / 3

                   if i == 0:
                         cpu_target.target.next_to(cpu_left_col_base[0].get_corner(DOWN + LEFT							)		,buff=0.0_2		,direction=SCREAMING_SNAKE_CASE__							)
                         cpu_target.target.set_x(cpu_target.target.get_x() + 0.1							)
                   elif i == 3:
                         cpu_target.target.next_to(cpu_targs[0].target		,direction=SCREAMING_SNAKE_CASE__		,buff=0.0							)
                   else:
                         cpu_target.target.next_to(cpu_targs[i - 1].target		,direction=SCREAMING_SNAKE_CASE__		,buff=0.0							)
                   cpu_targs.append(SCREAMING_SNAKE_CASE__							)

                   first_animations.append(rect.animate(run_time=0.5							).set_stroke(SCREAMING_SNAKE_CASE__							)							)
                   second_animations.append(MoveToTarget(SCREAMING_SNAKE_CASE__		,run_time=1.5							)							)

             self.play(*SCREAMING_SNAKE_CASE__							)
             self.play(*SCREAMING_SNAKE_CASE__							)

             self.wait()