


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 				_lowercase     (		SCREAMING_SNAKE_CASE_ :		Tuple							,	SCREAMING_SNAKE_CASE_ :		str						):





			"""simple docstring"""




			UpperCamelCase								=       []
			for part_id in partition_order:
						UpperCamelCase								=       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 				_lowercase     (		):





			"""simple docstring"""




			UpperCamelCase								=       pyspark.sql.SparkSession.builder.master("""local[*]"""						).appName("""pyspark"""						).getOrCreate()
			UpperCamelCase								=       spark.range(100						).repartition(1						)
			UpperCamelCase								=       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 				_lowercase     (		):





			"""simple docstring"""




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

			for i, (row_id, row_dict) in enumerate(generate_fn()						):
						UpperCamelCase	,	UpperCamelCase								=       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 				_lowercase     (		):





			"""simple docstring"""




			UpperCamelCase								=       pyspark.sql.SparkSession.builder.master("""local[*]"""						).appName("""pyspark"""						).getOrCreate()
			UpperCamelCase								=       spark.range(10						).repartition(1						)
			UpperCamelCase								=       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 				_lowercase     (		):





			"""simple docstring"""




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

						UpperCamelCase								=       SparkExamplesIterable(A__						).shuffle_data_sources(A__						)
						assert shuffled_it.n_shards == 3
						for i, (row_id, row_dict) in enumerate(A__						):
									UpperCamelCase	,	UpperCamelCase								=       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 				_lowercase     (		):





			"""simple docstring"""




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

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

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





			"""simple docstring"""




			UpperCamelCase								=       pyspark.sql.SparkSession.builder.master("""local[*]"""						).appName("""pyspark"""						).getOrCreate()
			UpperCamelCase								=       spark.range(100						).repartition(1						)
			UpperCamelCase								=       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'''
from typing import Any







class   a_ :




			def __init__(       self					,   UpperCAmelCase	):
				a_      				=						data
				a_      				=						None







class   a_ :




			def __init__(       self	):
				a_      				=						None




			def 					lowerCAmelCase__					(       self	):
				a_      				=						self.head
				while temp is not None:
					print(temp.data					,   end=""" """	)
					a_      				=						temp.next
				print()




			def 					lowerCAmelCase__					(       self					,   UpperCAmelCase	):
				a_      				=						Node(UpperCAmelCase	)
				a_      				=						self.head
				a_      				=						new_node






			def 					lowerCAmelCase__					(       self					,   UpperCAmelCase					,   UpperCAmelCase	):
				if node_data_a == node_data_a:
					return
				else:
					a_      				=						self.head
					while node_a is not None and node_a.data != node_data_a:
						a_      				=						node_a.next

					a_      				=						self.head
					while node_a is not None and node_a.data != node_data_a:
						a_      				=						node_a.next

					if node_a is None or node_a is None:
						return

					a_				,  a_      				=						node_a.data, node_a.data


if __name__ == "__main__":
		lowercase__											=LinkedList()
		for i in range(5, 0, -1):
				ll.push(i)

		ll.print_list()

		ll.swap_nodes(1, 4)
		print('After swapping')
		ll.print_list()
