






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__  (				_UpperCamelCase       ,							_UpperCamelCase) ->			List[Any]:
      """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(_UpperCamelCase):
                  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__  (				) ->			str:
      """simple docstring"""

      UpperCamelCase					       =  pyspark.sql.SparkSession.builder.master('local[*]').appName('pyspark').getOrCreate()
      UpperCamelCase					       =  spark.range(1_00).repartition(1)
      UpperCamelCase					       =  Spark(_UpperCamelCase)
      # 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__  (				) ->			int:
      """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(_UpperCamelCase       ,							_UpperCamelCase)  # Reverse the partitions.
      UpperCamelCase					       =  _get_expected_row_ids_and_row_dicts_for_partition_order(_UpperCamelCase       ,							_UpperCamelCase)

      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 		lowercase__  (				) ->			List[Any]:
      """simple docstring"""

      UpperCamelCase					       =  pyspark.sql.SparkSession.builder.master('local[*]').appName('pyspark').getOrCreate()
      UpperCamelCase					       =  spark.range(10).repartition(1)
      UpperCamelCase					       =  SparkExamplesIterable(_UpperCamelCase)
      assert it.n_shards == 1
      for i, (row_id, row_dict) in enumerate(_UpperCamelCase):
            assert row_id == F'0_{i}'
            assert row_dict == {"id": i}
@require_not_windows
@require_dill_gt_0_3_2
def 		lowercase__  (				) ->			List[str]:
      """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 _UpperCamelCase: x.reverse()
            UpperCamelCase					       =  _get_expected_row_ids_and_row_dicts_for_partition_order(_UpperCamelCase       ,							[2, 1, 0])

            UpperCamelCase					       =  SparkExamplesIterable(_UpperCamelCase).shuffle_data_sources(_UpperCamelCase)
            assert shuffled_it.n_shards == 3
            for i, (row_id, row_dict) in enumerate(_UpperCamelCase):
                  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 		lowercase__  (				) ->			Union[str, Any]:
      """simple docstring"""

      UpperCamelCase					       =  pyspark.sql.SparkSession.builder.master('local[*]').appName('pyspark').getOrCreate()
      UpperCamelCase					       =  spark.range(20).repartition(4)

      # Partitions 0 and 2
      UpperCamelCase					       =  SparkExamplesIterable(_UpperCamelCase).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(_UpperCamelCase       ,							[0, 2])
      for i, (row_id, row_dict) in enumerate(_UpperCamelCase):
            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(_UpperCamelCase).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(_UpperCamelCase       ,							[1, 3])
      for i, (row_id, row_dict) in enumerate(_UpperCamelCase):
            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 		lowercase__  (				) ->			List[str]:
      """simple docstring"""

      UpperCamelCase					       =  pyspark.sql.SparkSession.builder.master('local[*]').appName('pyspark').getOrCreate()
      UpperCamelCase					       =  spark.range(1_00).repartition(1)
      UpperCamelCase					       =  Spark(_UpperCamelCase)
      # 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











from pathlib import Path

import fire
def 		lowercase__  (				_UpperCamelCase       ,							_UpperCamelCase       ,							_UpperCamelCase) ->			Optional[int]:
      """simple docstring"""

      UpperCamelCase					       =  Path(_UpperCamelCase)
      UpperCamelCase					       =  Path(_UpperCamelCase)
      dest_dir.mkdir(exist_ok=_UpperCamelCase)
      for path in src_dir.iterdir():
            UpperCamelCase					       =  [x.rstrip() for x in list(path.open().readlines())][:n]
            UpperCamelCase					       =  dest_dir.joinpath(path.name)
            print(_UpperCamelCase)
            dest_path.open('w').write('\n'.join(_UpperCamelCase))


if __name__ == "__main__":
       fire.Fire(minify)



