




"""simple docstring"""




import pyarrow.parquet as pq
import pytest

from datasets import Audio, Dataset, DatasetDict, Features, NamedSplit, Sequence, Value, config
from datasets.features.image import Image
from datasets.io.parquet import ParquetDatasetReader, ParquetDatasetWriter, get_writer_batch_size

from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases



def 					a__				(       snake_case__ ,				snake_case__       )		->      str:
			assert isinstance(snake_case__ ,				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 					a__				(       snake_case__ ,				snake_case__ ,				snake_case__       )		->      str:
			lowerCamelCase       =      tmp_path / """cache"""
			lowerCamelCase       =      {"""col_1""": """string""", """col_2""": """int64""", """col_3""": """float64"""}
			with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
						lowerCamelCase       =      ParquetDatasetReader(snake_case__ ,				cache_dir=snake_case__ ,				keep_in_memory=snake_case__       ).read()
			_check_parquet_dataset(snake_case__ ,				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 					a__				(       snake_case__ ,				snake_case__ ,				snake_case__       )		->      Tuple:
			lowerCamelCase       =      tmp_path / """cache"""
			lowerCamelCase       =      {"""col_1""": """string""", """col_2""": """int64""", """col_3""": """float64"""}
			lowerCamelCase       =      features.copy() if features else default_expected_features
			lowerCamelCase       =      (
			    Features({feature: Value(snake_case__       ) for feature, dtype in features.items()}       ) if features is not None else None
			)
			lowerCamelCase       =      ParquetDatasetReader(snake_case__ ,				features=snake_case__ ,				cache_dir=snake_case__       ).read()
			_check_parquet_dataset(snake_case__ ,				snake_case__       )



@pytest.mark.parametrize("""split""" ,				[None, NamedSplit("""train"""       ), """train""", """test"""]       )
def 					a__				(       snake_case__ ,				snake_case__ ,				snake_case__       )		->      Tuple:
			lowerCamelCase       =      tmp_path / """cache"""
			lowerCamelCase       =      {"""col_1""": """string""", """col_2""": """int64""", """col_3""": """float64"""}
			lowerCamelCase       =      ParquetDatasetReader(snake_case__ ,				cache_dir=snake_case__ ,				split=snake_case__       ).read()
			_check_parquet_dataset(snake_case__ ,				snake_case__       )
			assert dataset.split == split if split else "train"



@pytest.mark.parametrize("""path_type""" ,				[str, list]       )
def 					a__				(       snake_case__ ,				snake_case__ ,				snake_case__       )		->      str:
			if issubclass(snake_case__ ,				snake_case__       ):
						lowerCamelCase       =      parquet_path
			elif issubclass(snake_case__ ,				snake_case__       ):
						lowerCamelCase       =      [parquet_path]
			lowerCamelCase       =      tmp_path / """cache"""
			lowerCamelCase       =      {"""col_1""": """string""", """col_2""": """int64""", """col_3""": """float64"""}
			lowerCamelCase       =      ParquetDatasetReader(snake_case__ ,				cache_dir=snake_case__       ).read()
			_check_parquet_dataset(snake_case__ ,				snake_case__       )



def 					a__				(       snake_case__ ,				snake_case__ ,				snake_case__=("train",)       )		->      Optional[Any]:
			assert isinstance(snake_case__ ,				snake_case__       )
			for split in splits:
						lowerCamelCase       =      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__				(       snake_case__ ,				snake_case__ ,				snake_case__       )		->      Any:
			lowerCamelCase       =      tmp_path / """cache"""
			lowerCamelCase       =      {"""col_1""": """string""", """col_2""": """int64""", """col_3""": """float64"""}
			with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
						lowerCamelCase       =      ParquetDatasetReader(
						    {"""train""": parquet_path} ,				cache_dir=snake_case__ ,				keep_in_memory=snake_case__       ).read()
			_check_parquet_datasetdict(snake_case__ ,				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 					a__				(       snake_case__ ,				snake_case__ ,				snake_case__       )		->      List[str]:
			lowerCamelCase       =      tmp_path / """cache"""
			lowerCamelCase       =      {"""col_1""": """string""", """col_2""": """int64""", """col_3""": """float64"""}
			lowerCamelCase       =      features.copy() if features else default_expected_features
			lowerCamelCase       =      (
			    Features({feature: Value(snake_case__       ) for feature, dtype in features.items()}       ) if features is not None else None
			)
			lowerCamelCase       =      ParquetDatasetReader({"""train""": parquet_path} ,				features=snake_case__ ,				cache_dir=snake_case__       ).read()
			_check_parquet_datasetdict(snake_case__ ,				snake_case__       )



@pytest.mark.parametrize("""split""" ,				[None, NamedSplit("""train"""       ), """train""", """test"""]       )
def 					a__				(       snake_case__ ,				snake_case__ ,				snake_case__       )		->      List[Any]:
			if split:
						lowerCamelCase       =      {split: parquet_path}
			else:
						lowerCamelCase       =      """train"""
						lowerCamelCase       =      {"""train""": parquet_path, """test""": parquet_path}
			lowerCamelCase       =      tmp_path / """cache"""
			lowerCamelCase       =      {"""col_1""": """string""", """col_2""": """int64""", """col_3""": """float64"""}
			lowerCamelCase       =      ParquetDatasetReader(snake_case__ ,				cache_dir=snake_case__       ).read()
			_check_parquet_datasetdict(snake_case__ ,				snake_case__ ,				splits=list(path.keys()       )       )
			assert all(dataset[split].split == split for split in path.keys()       )



def 					a__				(       snake_case__ ,				snake_case__       )		->      List[str]:
			lowerCamelCase       =      ParquetDatasetWriter(snake_case__ ,				tmp_path / """foo.parquet"""       )
			assert writer.write() > 0
			lowerCamelCase       =      pq.ParquetFile(tmp_path / """foo.parquet"""       )
			lowerCamelCase       =      pf.read()
			assert dataset.data.table == output_table



def 					a__				(       snake_case__ ,				snake_case__       )		->      str:
			lowerCamelCase       =      str(shared_datadir / """test_image_rgb.jpg"""       )
			lowerCamelCase       =      {"""image""": [image_path]}
			lowerCamelCase       =      Features({"""image""": Image()}       )
			lowerCamelCase       =      Dataset.from_dict(snake_case__ ,				features=snake_case__       )
			lowerCamelCase       =      ParquetDatasetWriter(snake_case__ ,				tmp_path / """foo.parquet"""       )
			assert writer.write() > 0

			lowerCamelCase       =      Dataset.from_parquet(str(tmp_path / """foo.parquet"""       )       )
			assert dataset.features == reloaded_dataset.features

			lowerCamelCase       =      ParquetDatasetReader(str(tmp_path / """foo.parquet"""       ) ,				streaming=snake_case__       ).read()
			assert dataset.features == reloaded_iterable_dataset.features



@pytest.mark.parametrize(
    """feature, expected""" ,				[
        (Features({"""foo""": Value("""int32"""       )}       ), None),
        (Features({"""image""": Image(), """foo""": Value("""int32"""       )}       ), config.PARQUET_ROW_GROUP_SIZE_FOR_IMAGE_DATASETS),
        (Features({"""nested""": Sequence(Audio()       )}       ), config.PARQUET_ROW_GROUP_SIZE_FOR_AUDIO_DATASETS),
    ] ,				)
def 					a__				(       snake_case__ ,				snake_case__       )		->      Tuple:
			assert get_writer_batch_size(snake_case__       ) == expected









"""simple docstring"""




from operator import delitem, getitem, setitem

import pytest

from data_structures.hashing.hash_map import HashMap



def 					a__				(       snake_case__       )		->      List[str]:
			return getitem, k



def 					a__				(       snake_case__ ,				snake_case__       )		->      Optional[Any]:
			return setitem, k, v



def 					a__				(       snake_case__       )		->      str:
			return delitem, k



def 					a__				(       snake_case__ ,				snake_case__ ,				*snake_case__       )		->      Union[str, Any]:
			try:
						return fun(snake_case__ ,				*snake_case__       ), None
			except Exception as e:
						return None, e


lowerCAmelCase							:    Optional[int]  							=							(
    _set("""key_a""", """val_a"""),
    _set("""key_b""", """val_b"""),
)

lowerCAmelCase							:    List[Any]  							=							[
    _set("""key_a""", """val_a"""),
    _set("""key_a""", """val_b"""),
]

lowerCAmelCase							:    List[Any]  							=							[
    _set("""key_a""", """val_a"""),
    _set("""key_b""", """val_b"""),
    _del("""key_a"""),
    _del("""key_b"""),
    _set("""key_a""", """val_a"""),
    _del("""key_a"""),
]

lowerCAmelCase							:    List[Any]  							=							[
    _get("""key_a"""),
    _del("""key_a"""),
    _set("""key_a""", """val_a"""),
    _del("""key_a"""),
    _del("""key_a"""),
    _get("""key_a"""),
]

lowerCAmelCase							:    Tuple  							=							[
    *[_set(x, x) for x in range(5)],  # guaranteed upsize
]

lowerCAmelCase							:    Tuple  							=							[
    *[_set(x, x) for x in range(5)],  # guaranteed upsize
    *[_del(x) for x in range(5)],
    _set("""key_a""", """val_b"""),
]



@pytest.mark.parametrize(
    """operations""" ,				(
        pytest.param(_add_items ,				id="""add items"""       ),
        pytest.param(_overwrite_items ,				id="""overwrite items"""       ),
        pytest.param(_delete_items ,				id="""delete items"""       ),
        pytest.param(_access_absent_items ,				id="""access absent items"""       ),
        pytest.param(_add_with_resize_up ,				id="""add with resize up"""       ),
        pytest.param(_add_with_resize_down ,				id="""add with resize down"""       ),
    ) ,				)
def 					a__				(       snake_case__       )		->      Any:
			lowerCamelCase       =      HashMap(initial_block_size=4       )
			lowerCamelCase       =      {}
			for _, (fun, *args) in enumerate(snake_case__       ):
						lowerCamelCase   ,     lowerCamelCase       =      _run_operation(snake_case__ ,				snake_case__ ,				*snake_case__       )
						lowerCamelCase   ,     lowerCamelCase       =      _run_operation(snake_case__ ,				snake_case__ ,				*snake_case__       )
						assert my_res == py_res
						assert str(snake_case__       ) == str(snake_case__       )
						assert set(snake_case__       ) == set(snake_case__       )
						assert len(snake_case__       ) == len(snake_case__       )
						assert set(my.items()       ) == set(py.items()       )



def 					a__				(       )		->      int:
			def is_public(snake_case__       ) -> bool:
						return not name.startswith("""_"""       )

			lowerCamelCase       =      {name for name in dir({}       ) if is_public(snake_case__       )}
			lowerCamelCase       =      {name for name in dir(HashMap()       ) if is_public(snake_case__       )}

			assert dict_public_names > hash_public_names



