






"""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 			lowerCAmelCase__     (     UpperCamelCase__     ,   UpperCamelCase__				):



  '''simple docstring'''
  _a  :       Union[str, Any]             =	[]
  for part_id in partition_order:
    _a  :       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 			lowerCAmelCase__     (     ):



  '''simple docstring'''
  _a  :       Any             =	pyspark.sql.SparkSession.builder.master("""local[*]"""				).appName("""pyspark"""				).getOrCreate()
  _a  :       Optional[Any]             =	spark.range(1_0_0				).repartition(1				)
  _a  :       Optional[int]             =	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=1_6				)
  # Given that the dataframe has 100 rows and each partition has 2 rows, we expect 50 partitions.
  assert spark_builder.df.rdd.getNumPartitions() == 5_0

@require_not_windows
@require_dill_gt_0_3_2
def 			lowerCAmelCase__     (     ):



  '''simple docstring'''
  _a  :       Any             =	pyspark.sql.SparkSession.builder.master("""local[*]"""				).appName("""pyspark"""				).getOrCreate()
  _a  :       Dict             =	spark.range(1_0				).repartition(2				)
  _a  :       Any             =	[1, 0]
  _a  :       Tuple             =	_generate_iterable_examples(__lowerCAmelCase     ,   __lowerCAmelCase				)  # Reverse the partitions.
  _a  :       Any             =	_get_expected_row_ids_and_row_dicts_for_partition_order(__lowerCAmelCase     ,   __lowerCAmelCase				)

  for i, (row_id, row_dict) in enumerate(generate_fn()				):
    _a  :       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 			lowerCAmelCase__     (     ):



  '''simple docstring'''
  _a  :       Any             =	pyspark.sql.SparkSession.builder.master("""local[*]"""				).appName("""pyspark"""				).getOrCreate()
  _a  :       List[Any]             =	spark.range(1_0				).repartition(1				)
  _a  :       int             =	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 			lowerCAmelCase__     (     ):



  '''simple docstring'''
  _a  :       List[str]             =	pyspark.sql.SparkSession.builder.master("""local[*]"""				).appName("""pyspark"""				).getOrCreate()
  _a  :       Tuple             =	spark.range(3_0				).repartition(3				)
  # Mock the generator so that shuffle reverses the partition indices.
  with patch("""numpy.random.Generator"""				) as generator_mock:
    _a  :       Union[str, Any]             =	lambda UpperCamelCase__				: x.reverse()
    _a  :       List[str]             =	_get_expected_row_ids_and_row_dicts_for_partition_order(__lowerCAmelCase     ,   [2, 1, 0]				)

    _a  :       List[str]             =	SparkExamplesIterable(__lowerCAmelCase				).shuffle_data_sources(__lowerCAmelCase				)
    assert shuffled_it.n_shards == 3
    for i, (row_id, row_dict) in enumerate(__lowerCAmelCase				):
      _a  :       Optional[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 			lowerCAmelCase__     (     ):



  '''simple docstring'''
  _a  :       Union[str, Any]             =	pyspark.sql.SparkSession.builder.master("""local[*]"""				).appName("""pyspark"""				).getOrCreate()
  _a  :       Dict             =	spark.range(2_0				).repartition(4				)

  # Partitions 0 and 2
  _a  :       List[Any]             =	SparkExamplesIterable(__lowerCAmelCase				).shard_data_sources(worker_id=0     ,   num_workers=2				)
  assert shard_it_a.n_shards == 2
  _a  :       int             =	_get_expected_row_ids_and_row_dicts_for_partition_order(__lowerCAmelCase     ,   [0, 2]				)
  for i, (row_id, row_dict) in enumerate(__lowerCAmelCase				):
    _a  :       Dict             =	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  :       List[str]             =	SparkExamplesIterable(__lowerCAmelCase				).shard_data_sources(worker_id=1     ,   num_workers=2				)
  assert shard_it_a.n_shards == 2
  _a  :       List[Any]             =	_get_expected_row_ids_and_row_dicts_for_partition_order(__lowerCAmelCase     ,   [1, 3]				)
  for i, (row_id, row_dict) in enumerate(__lowerCAmelCase				):
    _a  :       Optional[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 			lowerCAmelCase__     (     ):



  '''simple docstring'''
  _a  :       int             =	pyspark.sql.SparkSession.builder.master("""local[*]"""				).appName("""pyspark"""				).getOrCreate()
  _a  :       Dict             =	spark.range(1_0_0				).repartition(1				)
  _a  :       Tuple             =	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() == 1_0_0






import math
import sys



def 			_lowerCAmelCase       (					__lowerCAmelCase      )   ->					str:


				"""simple docstring"""

				snake_case__	:      Optional[Any]     		=	''''''
				try:
								with open(__lowerCAmelCase  ,  '''rb'''      ) as binary_file:
												snake_case__	:      int     		=	binary_file.read()
								for dat in data:
												snake_case__	:      Any     		=	f"""{dat:08b}"""
												result += curr_byte
								return result
				except OSError:
								print('''File not accessible'''      )
								sys.exit()



def 			_lowerCAmelCase       (					__lowerCAmelCase      )   ->					str:


				"""simple docstring"""

				snake_case__	:      List[str]     		=	{'''0''': '''0''', '''1''': '''1'''}
				snake_case__		, snake_case__	:      List[Any]     		=	'''''', ''''''
				snake_case__	:      Tuple     		=	len(__lowerCAmelCase      )

				for i in range(len(__lowerCAmelCase      )      ):
								curr_string += data_bits[i]
								if curr_string not in lexicon:
												continue

								snake_case__	:      Tuple     		=	lexicon[curr_string]
								result += last_match_id
								snake_case__	:      Any     		=	last_match_id + '''0'''

								if math.loga(__lowerCAmelCase      ).is_integer():
												snake_case__	:      Tuple     		=	{}
												for curr_key in list(__lowerCAmelCase      ):
																snake_case__	:      Union[str, Any]     		=	lexicon.pop(__lowerCAmelCase      )
												snake_case__	:      Optional[Any]     		=	new_lex

								snake_case__	:      Tuple     		=	last_match_id + '''1'''
								index += 1
								snake_case__	:      Dict     		=	''''''
				return result



def 			_lowerCAmelCase       (					__lowerCAmelCase  ,  __lowerCAmelCase      )   ->					None:


				"""simple docstring"""

				snake_case__	:      Dict     		=	8
				try:
								with open(__lowerCAmelCase  ,  '''wb'''      ) as opened_file:
												snake_case__	:      Union[str, Any]     		=	[
												    to_write[i : i + byte_length]
												    for i in range(0  ,  len(__lowerCAmelCase      )  ,  __lowerCAmelCase      )
												]

												if len(result_byte_array[-1]      ) % byte_length == 0:
																result_byte_array.append('''10000000'''      )
												else:
																result_byte_array[-1] += "1" + "0" * (
																    byte_length - len(result_byte_array[-1]      ) - 1
																)

												for elem in result_byte_array[:-1]:
																opened_file.write(int(__lowerCAmelCase  ,  2      ).to_bytes(1  ,  byteorder='''big'''      )      )
				except OSError:
								print('''File not accessible'''      )
								sys.exit()



def 			_lowerCAmelCase       (					__lowerCAmelCase      )   ->					str:


				"""simple docstring"""

				snake_case__	:      Any     		=	0
				for letter in data_bits:
								if letter == "1":
												break
								counter += 1

				snake_case__	:      Optional[int]     		=	data_bits[counter:]
				snake_case__	:      int     		=	data_bits[counter + 1 :]
				return data_bits



def 			_lowerCAmelCase       (					__lowerCAmelCase  ,  __lowerCAmelCase      )   ->					None:


				"""simple docstring"""

				snake_case__	:      Union[str, Any]     		=	read_file_binary(__lowerCAmelCase      )
				snake_case__	:      List[str]     		=	remove_prefix(__lowerCAmelCase      )
				snake_case__	:      Any     		=	decompress_data(__lowerCAmelCase      )
				write_file_binary(__lowerCAmelCase  ,  __lowerCAmelCase      )


if __name__ == "__main__":
				compress(sys.argv[1], sys.argv[2])

