


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        A       (      _lowerCamelCase       ,				_lowerCamelCase						):





							'''simple docstring'''




							_lowerCAmelCase  :							int				     =					[]
							for part_id in partition_order:
														_lowerCAmelCase  :							List[Any]				     =					df.where(F"SPARK_PARTITION_ID() = {part_id}"						).collect()
														for row_idx, row in enumerate(_lowerCamelCase						):
																					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        A       (      ):





							'''simple docstring'''




							_lowerCAmelCase  :							Optional[Any]				     =					pyspark.sql.SparkSession.builder.master("local[*]"						).appName("pyspark"						).getOrCreate()
							_lowerCAmelCase  :							List[Any]				     =					spark.range(100						).repartition(1						)
							_lowerCAmelCase  :							Optional[Any]				     =					Spark(_lowerCamelCase						)
							# 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        A       (      ):





							'''simple docstring'''




							_lowerCAmelCase  :							Dict				     =					pyspark.sql.SparkSession.builder.master("local[*]"						).appName("pyspark"						).getOrCreate()
							_lowerCAmelCase  :							Dict				     =					spark.range(10						).repartition(2						)
							_lowerCAmelCase  :							Union[str, Any]				     =					[1, 0]
							_lowerCAmelCase  :							Any				     =					_generate_iterable_examples(_lowerCamelCase       ,				_lowerCamelCase						)  # Reverse the partitions.
							_lowerCAmelCase  :							Dict				     =					_get_expected_row_ids_and_row_dicts_for_partition_order(_lowerCamelCase       ,				_lowerCamelCase						)

							for i, (row_id, row_dict) in enumerate(generate_fn()						):
														_lowerCAmelCase  :							Dict				     =					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        A       (      ):





							'''simple docstring'''




							_lowerCAmelCase  :							Any				     =					pyspark.sql.SparkSession.builder.master("local[*]"						).appName("pyspark"						).getOrCreate()
							_lowerCAmelCase  :							List[Any]				     =					spark.range(10						).repartition(1						)
							_lowerCAmelCase  :							Dict				     =					SparkExamplesIterable(_lowerCamelCase						)
							assert it.n_shards == 1
							for i, (row_id, row_dict) in enumerate(_lowerCamelCase						):
														assert row_id == F"0_{i}"
														assert row_dict == {"id": i}






@require_not_windows
@require_dill_gt_0_3_2
def        A       (      ):





							'''simple docstring'''




							_lowerCAmelCase  :							Optional[Any]				     =					pyspark.sql.SparkSession.builder.master("local[*]"						).appName("pyspark"						).getOrCreate()
							_lowerCAmelCase  :							Tuple				     =					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 _lowerCamelCase						: x.reverse()
														_lowerCAmelCase  :							Tuple				     =					_get_expected_row_ids_and_row_dicts_for_partition_order(_lowerCamelCase       ,				[2, 1, 0]						)

														_lowerCAmelCase  :							List[str]				     =					SparkExamplesIterable(_lowerCamelCase						).shuffle_data_sources(_lowerCamelCase						)
														assert shuffled_it.n_shards == 3
														for i, (row_id, row_dict) in enumerate(_lowerCamelCase						):
																					_lowerCAmelCase  :							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        A       (      ):





							'''simple docstring'''




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

							# Partitions 0 and 2
							_lowerCAmelCase  :							Optional[int]				     =					SparkExamplesIterable(_lowerCamelCase						).shard_data_sources(worker_id=0       ,				num_workers=2						)
							assert shard_it_a.n_shards == 2
							_lowerCAmelCase  :							Tuple				     =					_get_expected_row_ids_and_row_dicts_for_partition_order(_lowerCamelCase       ,				[0, 2]						)
							for i, (row_id, row_dict) in enumerate(_lowerCamelCase						):
														_lowerCAmelCase  :							Optional[Any]				     =					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  :							str				     =					SparkExamplesIterable(_lowerCamelCase						).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(_lowerCamelCase       ,				[1, 3]						)
							for i, (row_id, row_dict) in enumerate(_lowerCamelCase						):
														_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        A       (      ):





							'''simple docstring'''




							_lowerCAmelCase  :							List[Any]				     =					pyspark.sql.SparkSession.builder.master("local[*]"						).appName("pyspark"						).getOrCreate()
							_lowerCAmelCase  :							Optional[int]				     =					spark.range(100						).repartition(1						)
							_lowerCAmelCase  :							Optional[Any]				     =					Spark(_lowerCamelCase						)
							# 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





from __future__ import annotations

from collections.abc import MutableSequence



class 						UpperCAmelCase_					:







							def __init__(     self,    __a,    __a):

														'''simple docstring'''

														if len(__a) != degree + 1:
																					raise ValueError(
																					    "The number of coefficients should be equal to the degree + 1.")

														_lowerCAmelCase  :							list[float]				     =					list(__a)
														_lowerCAmelCase  :							Any				     =					degree







							def __add__(     self,    __a):

														'''simple docstring'''

														if self.degree > polynomial_a.degree:
																					_lowerCAmelCase  :							Dict				     =					self.coefficients[:]
																					for i in range(polynomial_a.degree + 1):
																												coefficients[i] += polynomial_a.coefficients[i]
																					return Polynomial(self.degree,    __a)
														else:
																					_lowerCAmelCase  :							Union[str, Any]				     =					polynomial_a.coefficients[:]
																					for i in range(self.degree + 1):
																												coefficients[i] += self.coefficients[i]
																					return Polynomial(polynomial_a.degree,    __a)







							def __sub__(     self,    __a):

														'''simple docstring'''

														return self + polynomial_a * Polynomial(0,    [-1])







							def __neg__(     self):

														'''simple docstring'''

														return Polynomial(self.degree,    [-c for c in self.coefficients])







							def __mul__(     self,    __a):

														'''simple docstring'''

														_lowerCAmelCase  :							list[float]				     =					[0] * (self.degree + polynomial_a.degree + 1)
														for i in range(self.degree + 1):
																					for j in range(polynomial_a.degree + 1):
																												coefficients[i + j] += (
																												    self.coefficients[i] * polynomial_a.coefficients[j]
																												)

														return Polynomial(self.degree + polynomial_a.degree,    __a)







							def      snake_case__   (     self,    __a):

														'''simple docstring'''

														_lowerCAmelCase  :							int | float				     =					0
														for i in range(self.degree + 1):
																					result += self.coefficients[i] * (substitution**i)
														return result







							def __str__(     self):

														'''simple docstring'''

														_lowerCAmelCase  :							List[str]				     =					""
														for i in range(self.degree,    -1,    -1):
																					if self.coefficients[i] == 0:
																												continue
																					elif self.coefficients[i] > 0:
																												if polynomial:
																																			polynomial += " + "
																					else:
																												polynomial += " - "

																					if i == 0:
																												polynomial += str(abs(self.coefficients[i]))
																					elif i == 1:
																												polynomial += str(abs(self.coefficients[i])) + "x"
																					else:
																												polynomial += str(abs(self.coefficients[i])) + "x^" + str(__a)

														return polynomial







							def __repr__(     self):

														'''simple docstring'''

														return self.__str__()







							def      snake_case__   (     self):

														'''simple docstring'''

														_lowerCAmelCase  :							list[float]				     =					[0] * self.degree
														for i in range(self.degree):
																					_lowerCAmelCase  :							List[Any]				     =					self.coefficients[i + 1] * (i + 1)
														return Polynomial(self.degree - 1,    __a)







							def      snake_case__   (     self,    __a = 0):

														'''simple docstring'''

														_lowerCAmelCase  :							list[float]				     =					[0] * (self.degree + 2)
														_lowerCAmelCase  :							Optional[Any]				     =					constant
														for i in range(self.degree + 1):
																					_lowerCAmelCase  :							Dict				     =					self.coefficients[i] / (i + 1)
														return Polynomial(self.degree + 1,    __a)







							def __eq__(     self,    __a):

														'''simple docstring'''

														if not isinstance(__a,    __a):
																					return False

														if self.degree != polynomial_a.degree:
																					return False

														for i in range(self.degree + 1):
																					if self.coefficients[i] != polynomial_a.coefficients[i]:
																												return False

														return True







							def __ne__(     self,    __a):

														'''simple docstring'''

														return not self.__eq__(__a)
