


import os
import tempfile
from functools import partial
from unittest import TestCase
from unittest.mock import patch

import datasets
import datasets.config

from .utils import require_beam







class  snake_case_     (datasets.BeamBasedBuilder   ):
				def 				lowerCamelCase__(   self     :Dict   )      ->					int:
											return datasets.DatasetInfo(
											    features=datasets.Features({'content': datasets.Value('string'   )}   )    ,supervised_keys=__A    ,)
				def 				lowerCamelCase__(   self     :Optional[int]    ,__snake_case     :Any    ,__snake_case     :List[str]   )      ->					str:
											return [datasets.SplitGenerator(name=datasets.Split.TRAIN    ,gen_kwargs={'examples': get_test_dummy_examples()}   )]



				def 				lowerCamelCase__(   self     :List[str]    ,__snake_case     :str    ,__snake_case     :List[str]   )      ->					Dict:
											import apache_beam as beam

											return pipeline | "Load Examples" >> beam.Create(__A   )







class  snake_case_     (datasets.BeamBasedBuilder   ):
				def 				lowerCamelCase__(   self     :Optional[Any]   )      ->					Optional[int]:
											return datasets.DatasetInfo(
											    features=datasets.Features({'a': datasets.Sequence({'b': datasets.Value('string'   )}   )}   )    ,supervised_keys=__A    ,)
				def 				lowerCamelCase__(   self     :int    ,__snake_case     :str    ,__snake_case     :str   )      ->					Tuple:
											return [
											    datasets.SplitGenerator(name=datasets.Split.TRAIN    ,gen_kwargs={'examples': get_test_nested_examples()}   )
											]



				def 				lowerCamelCase__(   self     :Optional[Any]    ,__snake_case     :Dict    ,__snake_case     :int   )      ->					Tuple:
											import apache_beam as beam

											return pipeline | "Load Examples" >> beam.Create(__A   )






def 							__lowercase     (				):
							return [(i, {"content": content}) for i, content in enumerate(['foo', 'bar', 'foobar']     )]






def 							__lowercase     (				):
							return [(i, {"a": {"b": [content]}}) for i, content in enumerate(['foo', 'bar', 'foobar']     )]







class  snake_case_     (lowerCamelCase_   ):
				@require_beam
				def 				lowerCamelCase__(   self     :Union[str, Any]   )      ->					str:
											a__    =  len(get_test_dummy_examples()   )
											with tempfile.TemporaryDirectory() as tmp_cache_dir:
																		a__    =  DummyBeamDataset(cache_dir=__A    ,beam_runner='DirectRunner'   )
																		builder.download_and_prepare()
																		self.assertTrue(
																		    os.path.exists(
																		        os.path.join(__A    ,builder.name    ,'default'    ,'0.0.0'    ,F'{builder.name}-train.arrow'   )   )   )
																		self.assertDictEqual(builder.info.features    ,datasets.Features({'content': datasets.Value('string'   )}   )   )
																		a__    =  builder.as_dataset()
																		self.assertEqual(dset['train'].num_rows    ,__A   )
																		self.assertEqual(dset['train'].info.splits['train'].num_examples    ,__A   )
																		self.assertDictEqual(dset['train'][0]    ,get_test_dummy_examples()[0][1]   )
																		self.assertDictEqual(
																		    dset['train'][expected_num_examples - 1]    ,get_test_dummy_examples()[expected_num_examples - 1][1]   )
																		self.assertTrue(
																		    os.path.exists(os.path.join(__A    ,builder.name    ,'default'    ,'0.0.0'    ,'dataset_info.json'   )   )   )
																		del dset
				@require_beam
				def 				lowerCamelCase__(   self     :Tuple   )      ->					Dict:
											import apache_beam as beam

											a__    =  beam.io.parquetio.WriteToParquet

											a__    =  len(get_test_dummy_examples()   )
											with tempfile.TemporaryDirectory() as tmp_cache_dir:
																		a__    =  DummyBeamDataset(cache_dir=__A    ,beam_runner='DirectRunner'   )
																		with patch('apache_beam.io.parquetio.WriteToParquet'   ) as write_parquet_mock:
																									a__    =  partial(__A    ,num_shards=2   )
																									builder.download_and_prepare()
																		self.assertTrue(
																		    os.path.exists(
																		        os.path.join(
																		            __A    ,builder.name    ,'default'    ,'0.0.0'    ,F'{builder.name}-train-00000-of-00002.arrow'   )   )   )
																		self.assertTrue(
																		    os.path.exists(
																		        os.path.join(
																		            __A    ,builder.name    ,'default'    ,'0.0.0'    ,F'{builder.name}-train-00000-of-00002.arrow'   )   )   )
																		self.assertDictEqual(builder.info.features    ,datasets.Features({'content': datasets.Value('string'   )}   )   )
																		a__    =  builder.as_dataset()
																		self.assertEqual(dset['train'].num_rows    ,__A   )
																		self.assertEqual(dset['train'].info.splits['train'].num_examples    ,__A   )
																		# Order is not preserved when sharding, so we just check that all the elements are there
																		self.assertListEqual(sorted(dset['train']['content']   )    ,sorted(['foo', 'bar', 'foobar']   )   )
																		self.assertTrue(
																		    os.path.exists(os.path.join(__A    ,builder.name    ,'default'    ,'0.0.0'    ,'dataset_info.json'   )   )   )
																		del dset
				@require_beam
				def 				lowerCamelCase__(   self     :List[str]   )      ->					int:
											with tempfile.TemporaryDirectory() as tmp_cache_dir:
																		a__    =  DummyBeamDataset(cache_dir=__A   )
																		self.assertRaises(datasets.builder.MissingBeamOptions    ,builder.download_and_prepare   )



				@require_beam
				def 				lowerCamelCase__(   self     :List[str]   )      ->					List[Any]:
											a__    =  len(get_test_nested_examples()   )
											with tempfile.TemporaryDirectory() as tmp_cache_dir:
																		a__    =  NestedBeamDataset(cache_dir=__A    ,beam_runner='DirectRunner'   )
																		builder.download_and_prepare()
																		self.assertTrue(
																		    os.path.exists(
																		        os.path.join(__A    ,builder.name    ,'default'    ,'0.0.0'    ,F'{builder.name}-train.arrow'   )   )   )
																		self.assertDictEqual(
																		    builder.info.features    ,datasets.Features({'a': datasets.Sequence({'b': datasets.Value('string'   )}   )}   )   )
																		a__    =  builder.as_dataset()
																		self.assertEqual(dset['train'].num_rows    ,__A   )
																		self.assertEqual(dset['train'].info.splits['train'].num_examples    ,__A   )
																		self.assertDictEqual(dset['train'][0]    ,get_test_nested_examples()[0][1]   )
																		self.assertDictEqual(
																		    dset['train'][expected_num_examples - 1]    ,get_test_nested_examples()[expected_num_examples - 1][1]   )
																		self.assertTrue(
																		    os.path.exists(os.path.join(__A    ,builder.name    ,'default'    ,'0.0.0'    ,'dataset_info.json'   )   )   )
																		del dset








from __future__ import annotations






def 							__lowercase     (				__lowerCAmelCase							:       list[int]     ):  # This function is recursive
							a__    =  len(__lowerCAmelCase     )
							# If the array contains only one element, we return it (it's the stop condition of
							# recursion)
							if array_length <= 1:
														return array
														# Else
							a__    =  array[0]
							a__    =  False
							a__    =  1
							a__    =  []
							while not is_found and i < array_length:
														if array[i] < pivot:
																					a__    =  True
																					a__    =  [element for element in array[i:] if element >= array[i]]
																					a__    =  longest_subsequence(__lowerCAmelCase     )
																					if len(__lowerCAmelCase     ) > len(__lowerCAmelCase     ):
																												a__    =  temp_array
														else:
																					i += 1

							a__    =  [element for element in array[1:] if element >= pivot]
							a__    =  [pivot, *longest_subsequence(__lowerCAmelCase     )]
							if len(__lowerCAmelCase     ) > len(__lowerCAmelCase     ):
														return temp_array
							else:
														return longest_subseq


if __name__ == "__main__":
						import doctest

						doctest.testmod()




