




"""simple docstring"""
from unittest.mock import patch

import pyspark

from datasets.packaged_modules.spark.spark import (
    Spark,
    SparkExamplesIterable,
    _generate_iterable_examples,
)

from ..utils import (
    require_dill_gt_0_3_2,
    require_not_windows,
)





def 						UpperCAmelCase				(			A__:    Optional[Any]							,				A__:    Union[str, Any]     )  ->     int:
			__lowerCamelCase					:	Optional[Any]	       =				[]
			for part_id in partition_order:
						__lowerCamelCase					:	Dict	       =				df.where(f'''SPARK_PARTITION_ID() = {part_id}'''     ).collect()
						for row_idx, row in enumerate(A__     ):
									expected_row_ids_and_row_dicts.append((f'''{part_id}_{row_idx}''', row.asDict())     )
			return expected_row_ids_and_row_dicts





@require_not_windows
@require_dill_gt_0_3_2
def 						UpperCAmelCase				(			)  ->     List[str]:
			__lowerCamelCase					:	Union[str, Any]	       =				pyspark.sql.SparkSession.builder.master('local[*]'     ).appName('pyspark'     ).getOrCreate()
			__lowerCamelCase					:	Dict	       =				spark.range(100     ).repartition(1     )
			__lowerCamelCase					:	Dict	       =				Spark(A__     )
			# The id ints will be converted to Pyarrow int64s, so each row will be 8 bytes. Setting a max_shard_size of 16 means
			# that each partition can hold 2 rows.
			spark_builder._repartition_df_if_needed(max_shard_size=16     )
			# Given that the dataframe has 100 rows and each partition has 2 rows, we expect 50 partitions.
			assert spark_builder.df.rdd.getNumPartitions() == 50





@require_not_windows
@require_dill_gt_0_3_2
def 						UpperCAmelCase				(			)  ->     Union[str, Any]:
			__lowerCamelCase					:	List[str]	       =				pyspark.sql.SparkSession.builder.master('local[*]'     ).appName('pyspark'     ).getOrCreate()
			__lowerCamelCase					:	Union[str, Any]	       =				spark.range(10     ).repartition(2     )
			__lowerCamelCase					:	List[Any]	       =				[1, 0]
			__lowerCamelCase					:	Any	       =				_generate_iterable_examples(A__							,				A__     )  # Reverse the partitions.
			__lowerCamelCase					:	List[Any]	       =				_get_expected_row_ids_and_row_dicts_for_partition_order(A__							,				A__     )

			for i, (row_id, row_dict) in enumerate(generate_fn()     ):
						__lowerCamelCase					:	Optional[int]	       =				expected_row_ids_and_row_dicts[i]
						assert row_id == expected_row_id
						assert row_dict == expected_row_dict





@require_not_windows
@require_dill_gt_0_3_2
def 						UpperCAmelCase				(			)  ->     Any:
			__lowerCamelCase					:	str	       =				pyspark.sql.SparkSession.builder.master('local[*]'     ).appName('pyspark'     ).getOrCreate()
			__lowerCamelCase					:	str	       =				spark.range(10     ).repartition(1     )
			__lowerCamelCase					:	List[str]	       =				SparkExamplesIterable(A__     )
			assert it.n_shards == 1
			for i, (row_id, row_dict) in enumerate(A__     ):
						assert row_id == f'''0_{i}'''
						assert row_dict == {"id": i}





@require_not_windows
@require_dill_gt_0_3_2
def 						UpperCAmelCase				(			)  ->     Union[str, Any]:
			__lowerCamelCase					:	str	       =				pyspark.sql.SparkSession.builder.master('local[*]'     ).appName('pyspark'     ).getOrCreate()
			__lowerCamelCase					:	List[str]	       =				spark.range(30     ).repartition(3     )
			# Mock the generator so that shuffle reverses the partition indices.
			with patch('numpy.random.Generator'     ) as generator_mock:
						__lowerCamelCase					:	Optional[Any]	       =				lambda A__     : x.reverse()
						__lowerCamelCase					:	List[str]	       =				_get_expected_row_ids_and_row_dicts_for_partition_order(A__							,				[2, 1, 0]     )

						__lowerCamelCase					:	str	       =				SparkExamplesIterable(A__     ).shuffle_data_sources(A__     )
						assert shuffled_it.n_shards == 3
						for i, (row_id, row_dict) in enumerate(A__     ):
									__lowerCamelCase					:	Any	       =				expected_row_ids_and_row_dicts[i]
									assert row_id == expected_row_id
									assert row_dict == expected_row_dict





@require_not_windows
@require_dill_gt_0_3_2
def 						UpperCAmelCase				(			)  ->     Optional[int]:
			__lowerCamelCase					:	Dict	       =				pyspark.sql.SparkSession.builder.master('local[*]'     ).appName('pyspark'     ).getOrCreate()
			__lowerCamelCase					:	Dict	       =				spark.range(20     ).repartition(4     )

			# Partitions 0 and 2
			__lowerCamelCase					:	Tuple	       =				SparkExamplesIterable(A__     ).shard_data_sources(worker_id=0							,				num_workers=2     )
			assert shard_it_a.n_shards == 2
			__lowerCamelCase					:	Optional[int]	       =				_get_expected_row_ids_and_row_dicts_for_partition_order(A__							,				[0, 2]     )
			for i, (row_id, row_dict) in enumerate(A__     ):
						__lowerCamelCase					:	int	       =				expected_row_ids_and_row_dicts_a[i]
						assert row_id == expected_row_id
						assert row_dict == expected_row_dict

			# Partitions 1 and 3
			__lowerCamelCase					:	Optional[Any]	       =				SparkExamplesIterable(A__     ).shard_data_sources(worker_id=1							,				num_workers=2     )
			assert shard_it_a.n_shards == 2
			__lowerCamelCase					:	Union[str, Any]	       =				_get_expected_row_ids_and_row_dicts_for_partition_order(A__							,				[1, 3]     )
			for i, (row_id, row_dict) in enumerate(A__     ):
						__lowerCamelCase					:	Union[str, Any]	       =				expected_row_ids_and_row_dicts_a[i]
						assert row_id == expected_row_id
						assert row_dict == expected_row_dict






@require_not_windows
@require_dill_gt_0_3_2
def 						UpperCAmelCase				(			)  ->     str:
			__lowerCamelCase					:	List[Any]	       =				pyspark.sql.SparkSession.builder.master('local[*]'     ).appName('pyspark'     ).getOrCreate()
			__lowerCamelCase					:	str	       =				spark.range(100     ).repartition(1     )
			__lowerCamelCase					:	Dict	       =				Spark(A__     )
			# Choose a small max_shard_size for maximum partitioning.
			spark_builder._repartition_df_if_needed(max_shard_size=1     )
			# The new number of partitions should not be greater than the number of rows.
			assert spark_builder.df.rdd.getNumPartitions() == 100









"""simple docstring"""
a_				:    Dict										=     {
    '''meter''': '''m''',
    '''kilometer''': '''km''',
    '''megametre''': '''Mm''',
    '''gigametre''': '''Gm''',
    '''terametre''': '''Tm''',
    '''petametre''': '''Pm''',
    '''exametre''': '''Em''',
    '''zettametre''': '''Zm''',
    '''yottametre''': '''Ym''',
}
# Exponent of the factor(meter)
a_				:    Optional[int]										=     {
    '''m''': 0,
    '''km''': 3,
    '''Mm''': 6,
    '''Gm''': 9,
    '''Tm''': 12,
    '''Pm''': 15,
    '''Em''': 18,
    '''Zm''': 21,
    '''Ym''': 24,
}





def 						UpperCAmelCase				(			A__:    float							,				A__:    str							,				A__:    str     )  ->     float:
			__lowerCamelCase					:	List[Any]	       =				from_type.lower().strip('s'     )
			__lowerCamelCase					:	Optional[int]	       =				to_type.lower().strip('s'     )

			__lowerCamelCase					:	int	       =				UNIT_SYMBOL.get(A__							,				A__     )
			__lowerCamelCase					:	Dict	       =				UNIT_SYMBOL.get(A__							,				A__     )

			if from_sanitized not in METRIC_CONVERSION:
						__lowerCamelCase					:	Dict	       =				(
						    f'''Invalid \'from_type\' value: {from_type!r}.\n'''
						    f'''Conversion abbreviations are: {", ".join(A__     )}'''
						)
						raise ValueError(A__     )
			if to_sanitized not in METRIC_CONVERSION:
						__lowerCamelCase					:	Any	       =				(
						    f'''Invalid \'to_type\' value: {to_type!r}.\n'''
						    f'''Conversion abbreviations are: {", ".join(A__     )}'''
						)
						raise ValueError(A__     )
			__lowerCamelCase					:	Any	       =				METRIC_CONVERSION[from_sanitized]
			__lowerCamelCase					:	Tuple	       =				METRIC_CONVERSION[to_sanitized]
			__lowerCamelCase					:	Any	       =				1

			if from_exponent > to_exponent:
						__lowerCamelCase					:	Union[str, Any]	       =				from_exponent - to_exponent
			else:
						__lowerCamelCase					:	List[Any]	       =				-(to_exponent - from_exponent)

			return value * pow(10							,				A__     )


if __name__ == "__main__":
					from doctest import testmod

					testmod()



