






'''simple docstring'''

from __future__ import annotations

from random import random







class 	SCREAMING_SNAKE_CASE	:




       def __init__(					self      : Tuple	,    A__      : int | None = None					):


            """simple docstring"""







            __lowerCamelCase						:       int				   =				value
            __lowerCamelCase						:       Dict				   =				random()
            __lowerCamelCase						:       Node | None				   =				None
            __lowerCamelCase						:       Node | None				   =				None




       def __repr__(					self      : Any					):


            """simple docstring"""







            from pprint import pformat

            if self.left is None and self.right is None:
                 return f"'{self.value}: {self.prior:.5}'"
            else:
                 return pformat(
                     {f"{self.value}: {self.prior:.5}": (self.left, self.right)}	,    indent=1					)




       def __str__(					self      : List[Any]					):


            """simple docstring"""







            __lowerCamelCase						:       List[str]				   =				str(self.value					) + """ """
            __lowerCamelCase						:       Any				   =				str(self.left or """"""					)
            __lowerCamelCase						:       List[str]				   =				str(self.right or """"""					)
            return value + left + right

def     __lowercase  (_lowercase,						_lowercase     )   ->     tuple[Node | None, Node | None]:


     """simple docstring"""
     if root is None:  # None tree is split into 2 Nones
          return None, None
     elif root.value is None:
          return None, None
     else:
          if value < root.value:
               __lowerCamelCase   ,      __lowerCamelCase						:       int				   =				split(root.left,						_lowercase     )
               return left, root
          else:
               __lowerCamelCase   ,      __lowerCamelCase						:       Union[str, Any]				   =				split(root.right,						_lowercase     )
               return root, right
def     __lowercase  (_lowercase,						_lowercase     )   ->     Node | None:


     """simple docstring"""
     if (not left) or (not right):  # If one node is None, return the other
          return left or right
     elif left.prior < right.prior:
          __lowerCamelCase						:       Tuple				   =				merge(left.right,						_lowercase     )
          return left
     else:
          __lowerCamelCase						:       int				   =				merge(_lowercase,						right.left     )
          return right
def     __lowercase  (_lowercase,						_lowercase     )   ->     Node | None:


     """simple docstring"""
     __lowerCamelCase						:       List[str]				   =				Node(_lowercase     )
     __lowerCamelCase   ,      __lowerCamelCase						:       List[Any]				   =				split(_lowercase,						_lowercase     )
     return merge(merge(_lowercase,						_lowercase     ),						_lowercase     )
def     __lowercase  (_lowercase,						_lowercase     )   ->     Node | None:


     """simple docstring"""
     __lowerCamelCase   ,      __lowerCamelCase						:       int				   =				split(_lowercase,						value - 1     )
     __lowerCamelCase   ,      __lowerCamelCase						:       List[str]				   =				split(_lowercase,						_lowercase     )
     return merge(_lowercase,						_lowercase     )
def     __lowercase  (_lowercase     )   ->     None:


     """simple docstring"""
     if not root:  # None
          return
     else:
          inorder(root.left     )
          print(root.value,						end=""","""     )
          inorder(root.right     )
def     __lowercase  (_lowercase,						_lowercase     )   ->     Node | None:


     """simple docstring"""
     for arg in args.split():
          if arg[0] == "+":
               __lowerCamelCase						:       Dict				   =				insert(_lowercase,						int(arg[1:]     )     )

          elif arg[0] == "-":
               __lowerCamelCase						:       List[str]				   =				erase(_lowercase,						int(arg[1:]     )     )

          else:
               print("""Unknown command"""     )

     return root
def     __lowercase  ()   ->     None:


     """simple docstring"""
     __lowerCamelCase						:       str				   =				None
     print(
         """enter numbers to create a tree, + value to add value into treap, """
         """- value to erase all nodes with value. 'q' to quit. """     )

     __lowerCamelCase						:       int				   =				input()
     while args != "q":
          __lowerCamelCase						:       List[Any]				   =				interact_treap(_lowercase,						_lowercase     )
          print(_lowercase     )
          __lowerCamelCase						:       List[Any]				   =				input()

     print("""good by!"""     )


if __name__ == "__main__":
   import doctest

   doctest.testmod()
   main()











'''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     __lowercase  (_lowercase,						_lowercase     )   ->     List[str]:


     """simple docstring"""
     __lowerCamelCase						:       Union[str, Any]				   =				[]
     for part_id in partition_order:
          __lowerCamelCase						:       Union[str, Any]				   =				df.where(f"SPARK_PARTITION_ID() = {part_id}"     ).collect()
          for row_idx, row in enumerate(_lowercase     ):
               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  ()   ->     Optional[int]:


     """simple docstring"""
     __lowerCamelCase						:       int				   =				pyspark.sql.SparkSession.builder.master("""local[*]"""     ).appName("""pyspark"""     ).getOrCreate()
     __lowerCamelCase						:       List[str]				   =				spark.range(100     ).repartition(1     )
     __lowerCamelCase						:       str				   =				Spark(_lowercase     )
     # 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  ()   ->     Optional[Any]:


     """simple docstring"""
     __lowerCamelCase						:       Any				   =				pyspark.sql.SparkSession.builder.master("""local[*]"""     ).appName("""pyspark"""     ).getOrCreate()
     __lowerCamelCase						:       Dict				   =				spark.range(10     ).repartition(2     )
     __lowerCamelCase						:       List[Any]				   =				[1, 0]
     __lowerCamelCase						:       Any				   =				_generate_iterable_examples(_lowercase,						_lowercase     )  # Reverse the partitions.
     __lowerCamelCase						:       int				   =				_get_expected_row_ids_and_row_dicts_for_partition_order(_lowercase,						_lowercase     )

     for i, (row_id, row_dict) in enumerate(generate_fn()     ):
          __lowerCamelCase   ,      __lowerCamelCase						:       str				   =				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  ()   ->     int:


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


     """simple docstring"""
     __lowerCamelCase						:       int				   =				pyspark.sql.SparkSession.builder.master("""local[*]"""     ).appName("""pyspark"""     ).getOrCreate()
     __lowerCamelCase						:       Optional[Any]				   =				spark.range(30     ).repartition(3     )
     # Mock the generator so that shuffle reverses the partition indices.
     with patch("""numpy.random.Generator"""     ) as generator_mock:
          __lowerCamelCase						:       Dict				   =				lambda _lowercase     : x.reverse()
          __lowerCamelCase						:       Union[str, Any]				   =				_get_expected_row_ids_and_row_dicts_for_partition_order(_lowercase,						[2, 1, 0]     )

          __lowerCamelCase						:       Tuple				   =				SparkExamplesIterable(_lowercase     ).shuffle_data_sources(_lowercase     )
          assert shuffled_it.n_shards == 3
          for i, (row_id, row_dict) in enumerate(_lowercase     ):
               __lowerCamelCase   ,      __lowerCamelCase						:       Union[str, 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     __lowercase  ()   ->     str:


     """simple docstring"""
     __lowerCamelCase						:       Union[str, Any]				   =				pyspark.sql.SparkSession.builder.master("""local[*]"""     ).appName("""pyspark"""     ).getOrCreate()
     __lowerCamelCase						:       List[str]				   =				spark.range(20     ).repartition(4     )

     # Partitions 0 and 2
     __lowerCamelCase						:       Union[str, Any]				   =				SparkExamplesIterable(_lowercase     ).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(_lowercase,						[0, 2]     )
     for i, (row_id, row_dict) in enumerate(_lowercase     ):
          __lowerCamelCase   ,      __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						:       List[str]				   =				SparkExamplesIterable(_lowercase     ).shard_data_sources(worker_id=1,						num_workers=2     )
     assert shard_it_a.n_shards == 2
     __lowerCamelCase						:       int				   =				_get_expected_row_ids_and_row_dicts_for_partition_order(_lowercase,						[1, 3]     )
     for i, (row_id, row_dict) in enumerate(_lowercase     ):
          __lowerCamelCase   ,      __lowerCamelCase						:       int				   =				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  ()   ->     int:


     """simple docstring"""
     __lowerCamelCase						:       Union[str, Any]				   =				pyspark.sql.SparkSession.builder.master("""local[*]"""     ).appName("""pyspark"""     ).getOrCreate()
     __lowerCamelCase						:       Dict				   =				spark.range(100     ).repartition(1     )
     __lowerCamelCase						:       Any				   =				Spark(_lowercase     )
     # 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



