"""simple docstring"""


import itertools
import string
from collections.abc import Generator, Iterable






def     __UpperCAmelCase					(			lowercase   ,lowercase		):







  """simple docstring"""
  _UpperCAmelCase						 =      iter(lowercase		)
  while True:
    _UpperCAmelCase						 =      tuple(itertools.islice(lowercase   ,lowercase		)		)
    if not chunk:
      return
    yield chunk






def     __UpperCAmelCase					(			lowercase		):







  """simple docstring"""
  _UpperCAmelCase						 =      """""".join([c.upper() for c in dirty if c in string.ascii_letters]		)
  _UpperCAmelCase						 =      """"""

  if len(lowercase		) < 2:
    return dirty

  for i in range(len(lowercase		) - 1		):
    clean += dirty[i]

    if dirty[i] == dirty[i + 1]:
      clean += "X"

  clean += dirty[-1]

  if len(lowercase		) & 1:
    clean += "X"

  return clean






def     __UpperCAmelCase					(			lowercase		):







  """simple docstring"""
  # I and J are used interchangeably to allow
  # us to use a 5x5 table (25 letters)
  _UpperCAmelCase						 =      """ABCDEFGHIKLMNOPQRSTUVWXYZ"""
  # we're using a list instead of a '2d' array because it makes the math
  # for setting up the table and doing the actual encoding/decoding simpler
  _UpperCAmelCase						 =      []

  # copy key chars into the table if they are in `alphabet` ignoring duplicates
  for char in key.upper():
    if char not in table and char in alphabet:
      table.append(lowercase		)

    # fill the rest of the table in with the remaining alphabet chars
  for char in alphabet:
    if char not in table:
      table.append(lowercase		)

  return table






def     __UpperCAmelCase					(			lowercase   ,lowercase		):







  """simple docstring"""
  _UpperCAmelCase						 =      generate_table(lowercase		)
  _UpperCAmelCase						 =      prepare_input(lowercase		)
  _UpperCAmelCase						 =      """"""

  # https://en.wikipedia.org/wiki/Playfair_cipher#Description
  for chara, chara in chunker(lowercase   ,2		):
    _UpperCAmelCase ,				_UpperCAmelCase						 =      divmod(table.index(lowercase		)   ,5		)
    _UpperCAmelCase ,				_UpperCAmelCase						 =      divmod(table.index(lowercase		)   ,5		)

    if rowa == rowa:
      ciphertext += table[rowa * 5 + (cola + 1) % 5]
      ciphertext += table[rowa * 5 + (cola + 1) % 5]
    elif cola == cola:
      ciphertext += table[((rowa + 1) % 5) * 5 + cola]
      ciphertext += table[((rowa + 1) % 5) * 5 + cola]
    else:  # rectangle
      ciphertext += table[rowa * 5 + cola]
      ciphertext += table[rowa * 5 + cola]

  return ciphertext






def     __UpperCAmelCase					(			lowercase   ,lowercase		):







  """simple docstring"""
  _UpperCAmelCase						 =      generate_table(lowercase		)
  _UpperCAmelCase						 =      """"""

  # https://en.wikipedia.org/wiki/Playfair_cipher#Description
  for chara, chara in chunker(lowercase   ,2		):
    _UpperCAmelCase ,				_UpperCAmelCase						 =      divmod(table.index(lowercase		)   ,5		)
    _UpperCAmelCase ,				_UpperCAmelCase						 =      divmod(table.index(lowercase		)   ,5		)

    if rowa == rowa:
      plaintext += table[rowa * 5 + (cola - 1) % 5]
      plaintext += table[rowa * 5 + (cola - 1) % 5]
    elif cola == cola:
      plaintext += table[((rowa - 1) % 5) * 5 + cola]
      plaintext += table[((rowa - 1) % 5) * 5 + cola]
    else:  # rectangle
      plaintext += table[rowa * 5 + cola]
      plaintext += table[rowa * 5 + cola]

  return plaintext

"""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     __UpperCAmelCase					(			lowercase   ,lowercase		):







  """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(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     __UpperCAmelCase					(			):







  """simple docstring"""
  _UpperCAmelCase						 =      pyspark.sql.SparkSession.builder.master("""local[*]"""		).appName("""pyspark"""		).getOrCreate()
  _UpperCAmelCase						 =      spark.range(1_00		).repartition(1		)
  _UpperCAmelCase						 =      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     __UpperCAmelCase					(			):







  """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(lowercase   ,lowercase		)  # Reverse the partitions.
  _UpperCAmelCase						 =      _get_expected_row_ids_and_row_dicts_for_partition_order(lowercase   ,lowercase		)

  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     __UpperCAmelCase					(			):







  """simple docstring"""
  _UpperCAmelCase						 =      pyspark.sql.SparkSession.builder.master("""local[*]"""		).appName("""pyspark"""		).getOrCreate()
  _UpperCAmelCase						 =      spark.range(10		).repartition(1		)
  _UpperCAmelCase						 =      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     __UpperCAmelCase					(			):







  """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 lowercase		: x.reverse()
    _UpperCAmelCase						 =      _get_expected_row_ids_and_row_dicts_for_partition_order(lowercase   ,[2, 1, 0]		)

    _UpperCAmelCase						 =      SparkExamplesIterable(lowercase		).shuffle_data_sources(lowercase		)
    assert shuffled_it.n_shards == 3
    for i, (row_id, row_dict) in enumerate(lowercase		):
      _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     __UpperCAmelCase					(			):







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

  # Partitions 0 and 2
  _UpperCAmelCase						 =      SparkExamplesIterable(lowercase		).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(lowercase   ,[0, 2]		)
  for i, (row_id, row_dict) in enumerate(lowercase		):
    _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(lowercase		).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(lowercase   ,[1, 3]		)
  for i, (row_id, row_dict) in enumerate(lowercase		):
    _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     __UpperCAmelCase					(			):







  """simple docstring"""
  _UpperCAmelCase						 =      pyspark.sql.SparkSession.builder.master("""local[*]"""		).appName("""pyspark"""		).getOrCreate()
  _UpperCAmelCase						 =      spark.range(1_00		).repartition(1		)
  _UpperCAmelCase						 =      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() == 1_00
