

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       __snake_case						( __UpperCamelCase	: List[Any]				,__UpperCamelCase	: List[str]    ):



      """simple docstring"""

      A_						  =				[]
      for part_id in partition_order:
            A_						  =				df.where(f'''SPARK_PARTITION_ID() = {part_id}'''    ).collect()
            for row_idx, row in enumerate(snake_case__    ):
                  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       __snake_case						( ):



      """simple docstring"""

      A_						  =				pyspark.sql.SparkSession.builder.master("local[*]"    ).appName("pyspark"    ).getOrCreate()
      A_						  =				spark.range(100    ).repartition(1    )
      A_						  =				Spark(snake_case__    )
      # 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       __snake_case						( ):



      """simple docstring"""

      A_						  =				pyspark.sql.SparkSession.builder.master("local[*]"    ).appName("pyspark"    ).getOrCreate()
      A_						  =				spark.range(10    ).repartition(2    )
      A_						  =				[1, 0]
      A_						  =				_generate_iterable_examples(snake_case__				,snake_case__    )  # Reverse the partitions.
      A_						  =				_get_expected_row_ids_and_row_dicts_for_partition_order(snake_case__				,snake_case__    )

      for i, (row_id, row_dict) in enumerate(generate_fn()    ):
            A_						  =				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       __snake_case						( ):



      """simple docstring"""

      A_						  =				pyspark.sql.SparkSession.builder.master("local[*]"    ).appName("pyspark"    ).getOrCreate()
      A_						  =				spark.range(10    ).repartition(1    )
      A_						  =				SparkExamplesIterable(snake_case__    )
      assert it.n_shards == 1
      for i, (row_id, row_dict) in enumerate(snake_case__    ):
            assert row_id == f'''0_{i}'''
            assert row_dict == {"id": i}

@require_not_windows
@require_dill_gt_0_3_2
def       __snake_case						( ):



      """simple docstring"""

      A_						  =				pyspark.sql.SparkSession.builder.master("local[*]"    ).appName("pyspark"    ).getOrCreate()
      A_						  =				spark.range(30    ).repartition(3    )
      # Mock the generator so that shuffle reverses the partition indices.
      with patch("numpy.random.Generator"    ) as generator_mock:
            A_						  =				lambda __UpperCamelCase    : x.reverse()
            A_						  =				_get_expected_row_ids_and_row_dicts_for_partition_order(snake_case__				,[2, 1, 0]    )

            A_						  =				SparkExamplesIterable(snake_case__    ).shuffle_data_sources(snake_case__    )
            assert shuffled_it.n_shards == 3
            for i, (row_id, row_dict) in enumerate(snake_case__    ):
                  A_						  =				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       __snake_case						( ):



      """simple docstring"""

      A_						  =				pyspark.sql.SparkSession.builder.master("local[*]"    ).appName("pyspark"    ).getOrCreate()
      A_						  =				spark.range(20    ).repartition(4    )

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

      # Partitions 1 and 3
      A_						  =				SparkExamplesIterable(snake_case__    ).shard_data_sources(worker_id=1				,num_workers=2    )
      assert shard_it_a.n_shards == 2
      A_						  =				_get_expected_row_ids_and_row_dicts_for_partition_order(snake_case__				,[1, 3]    )
      for i, (row_id, row_dict) in enumerate(snake_case__    ):
            A_						  =				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       __snake_case						( ):



      """simple docstring"""

      A_						  =				pyspark.sql.SparkSession.builder.master("local[*]"    ).appName("pyspark"    ).getOrCreate()
      A_						  =				spark.range(100    ).repartition(1    )
      A_						  =				Spark(snake_case__    )
      # 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







lowerCamelCase__       		=  8.3_1_4_4_5_9_8






def 	UpperCamelCase	(							snake_case__  : float						,snake_case__  : float	):




     '''simple docstring'''






     if temperature < 0:
          raise Exception("""Temperature cannot be less than 0 K"""	)
     if molar_mass <= 0:
          raise Exception("""Molar mass cannot be less than or equal to 0 kg/mol"""	)
     else:
          return (3 * UNIVERSAL_GAS_CONSTANT * temperature / molar_mass) ** 0.5


if __name__ == "__main__":
     import doctest

     # run doctest
     doctest.testmod()

     # example
     lowerCamelCase__       		=  300
     lowerCamelCase__       		=  28
     lowerCamelCase__       		=  rms_speed_of_molecule(temperature, molar_mass)
     print(f'''Vrms of Nitrogen gas at 300 K is {vrms} m/s''')


