


'''simple docstring'''






import operator as op


def       _snake_case     (  A )		->					List[Any]:
							lowerCAmelCase__      =			[]
							lowerCAmelCase__      =			lambda A				,					A : int(x / y )  # noqa: E731 integer division operation
							lowerCAmelCase__      =			{
							    '''^''': op.pow,
							    '''*''': op.mul,
							    '''/''': div,
							    '''+''': op.add,
							    '''-''': op.sub,
							}  # operators & their respective operation

							# print table header
							print('''Symbol'''.center(8 )				,					'''Action'''.center(12 )				,					'''Stack'''				,					sep=''' | ''' )
							print('''-''' * (30 + len(A )) )

							for x in post_fix:
														if x.isdigit():  # if x in digit
																					stack.append(A )  # append x to stack
																					# output in tabular format
																					print(x.rjust(8 )				,					('''push(''' + x + ''')''').ljust(12 )				,					''','''.join(A )				,					sep=''' | ''' )
														else:
																					lowerCAmelCase__      =			stack.pop()  # pop stack
																					# output in tabular format
																					print(''''''.rjust(8 )				,					('''pop(''' + b + ''')''').ljust(12 )				,					''','''.join(A )				,					sep=''' | ''' )

																					lowerCAmelCase__      =			stack.pop()  # pop stack
																					# output in tabular format
																					print(''''''.rjust(8 )				,					('''pop(''' + a + ''')''').ljust(12 )				,					''','''.join(A )				,					sep=''' | ''' )

																					stack.append(
																					    str(opr[x](int(A )				,					int(A ) ) ) )  # evaluate the 2 values popped from stack & push result to stack
																					# output in tabular format
																					print(
																					    x.rjust(8 )				,					('''push(''' + a + x + b + ''')''').ljust(12 )				,					''','''.join(A )				,					sep=''' | '''				,					)

							return int(stack[0] )


if __name__ == "__main__":
		__UpperCAmelCase					       =							input('''\n\nEnter a Postfix Equation (space separated) = ''').split(''' ''')
		print('''\n\tResult = ''', solve(Postfix))



'''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       _snake_case     (  A				,					A )		->					List[Any]:
							lowerCAmelCase__      =			[]
							for part_id in partition_order:
														lowerCAmelCase__      =			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       _snake_case     (  )		->					Tuple:
							lowerCAmelCase__      =			pyspark.sql.SparkSession.builder.master('''local[*]''' ).appName('''pyspark''' ).getOrCreate()
							lowerCAmelCase__      =			spark.range(100 ).repartition(1 )
							lowerCAmelCase__      =			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       _snake_case     (  )		->					Optional[int]:
							lowerCAmelCase__      =			pyspark.sql.SparkSession.builder.master('''local[*]''' ).appName('''pyspark''' ).getOrCreate()
							lowerCAmelCase__      =			spark.range(10 ).repartition(2 )
							lowerCAmelCase__      =			[1, 0]
							lowerCAmelCase__      =			_generate_iterable_examples(A				,					A )  # Reverse the partitions.
							lowerCAmelCase__      =			_get_expected_row_ids_and_row_dicts_for_partition_order(A				,					A )

							for i, (row_id, row_dict) in enumerate(generate_fn() ):
														lowerCAmelCase__     ,      lowerCAmelCase__      =			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     (  )		->					Optional[Any]:
							lowerCAmelCase__      =			pyspark.sql.SparkSession.builder.master('''local[*]''' ).appName('''pyspark''' ).getOrCreate()
							lowerCAmelCase__      =			spark.range(10 ).repartition(1 )
							lowerCAmelCase__      =			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       _snake_case     (  )		->					Union[str, Any]:
							lowerCAmelCase__      =			pyspark.sql.SparkSession.builder.master('''local[*]''' ).appName('''pyspark''' ).getOrCreate()
							lowerCAmelCase__      =			spark.range(30 ).repartition(3 )
							# Mock the generator so that shuffle reverses the partition indices.
							with patch('''numpy.random.Generator''' ) as generator_mock:
														lowerCAmelCase__      =			lambda A : x.reverse()
														lowerCAmelCase__      =			_get_expected_row_ids_and_row_dicts_for_partition_order(A				,					[2, 1, 0] )

														lowerCAmelCase__      =			SparkExamplesIterable(A ).shuffle_data_sources(A )
														assert shuffled_it.n_shards == 3
														for i, (row_id, row_dict) in enumerate(A ):
																					lowerCAmelCase__     ,      lowerCAmelCase__      =			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     (  )		->					Dict:
							lowerCAmelCase__      =			pyspark.sql.SparkSession.builder.master('''local[*]''' ).appName('''pyspark''' ).getOrCreate()
							lowerCAmelCase__      =			spark.range(20 ).repartition(4 )

							# Partitions 0 and 2
							lowerCAmelCase__      =			SparkExamplesIterable(A ).shard_data_sources(worker_id=0				,					num_workers=2 )
							assert shard_it_a.n_shards == 2
							lowerCAmelCase__      =			_get_expected_row_ids_and_row_dicts_for_partition_order(A				,					[0, 2] )
							for i, (row_id, row_dict) in enumerate(A ):
														lowerCAmelCase__     ,      lowerCAmelCase__      =			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__      =			SparkExamplesIterable(A ).shard_data_sources(worker_id=1				,					num_workers=2 )
							assert shard_it_a.n_shards == 2
							lowerCAmelCase__      =			_get_expected_row_ids_and_row_dicts_for_partition_order(A				,					[1, 3] )
							for i, (row_id, row_dict) in enumerate(A ):
														lowerCAmelCase__     ,      lowerCAmelCase__      =			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     (  )		->					Dict:
							lowerCAmelCase__      =			pyspark.sql.SparkSession.builder.master('''local[*]''' ).appName('''pyspark''' ).getOrCreate()
							lowerCAmelCase__      =			spark.range(100 ).repartition(1 )
							lowerCAmelCase__      =			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