

import os
import tempfile
from pathlib import Path
from unittest import TestCase

import pyarrow as pa
import pytest

from datasets.arrow_dataset import Dataset
from datasets.arrow_reader import ArrowReader, BaseReader, FileInstructions, ReadInstruction, make_file_instructions
from datasets.info import DatasetInfo
from datasets.splits import NamedSplit, Split, SplitDict, SplitInfo

from .utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases

class 					__UpperCamelCase					(       SCREAMING_SNAKE_CASE      ):







	def 						_SCREAMING_SNAKE_CASE				( self:			Dict	,			__UpperCamelCase:			Any	,			__UpperCamelCase:			int=False   ):

						'''simple docstring'''





						__magic_name__,						__magic_name__,						__magic_name__				=     (
						    filename_skip_take['filename'],
						    filename_skip_take['skip'] if 'skip' in filename_skip_take else None,
						    filename_skip_take['take'] if 'take' in filename_skip_take else None,
						)
						open(os.path.join(__UpperCamelCase   )	,			'wb'   ).close()
						__magic_name__				=     pa.Table.from_pydict({'filename': [Path(__UpperCamelCase   ).name] * 1_00}   )
						if take == -1:
											__magic_name__				=     len(__UpperCamelCase   ) - skip
						if skip is not None and take is not None:
											__magic_name__				=     pa_table.slice(__UpperCamelCase	,			__UpperCamelCase   )
						return pa_table




class 					__UpperCamelCase					(       SCREAMING_SNAKE_CASE      ):







	def 						_SCREAMING_SNAKE_CASE				( self:			Tuple   ):

						'''simple docstring'''





						__magic_name__				=     'my_name'
						__magic_name__				=     SplitInfo(name='train'	,			num_examples=1_00   )
						__magic_name__				=     SplitInfo(name='test'	,			num_examples=1_00   )
						__magic_name__				=     [train_info, test_info]
						__magic_name__				=     SplitDict()
						split_dict.add(__UpperCamelCase   )
						split_dict.add(__UpperCamelCase   )
						__magic_name__				=     DatasetInfo(splits=__UpperCamelCase   )

						with tempfile.TemporaryDirectory() as tmp_dir:
											__magic_name__				=     ReaderTest(__UpperCamelCase	,			__UpperCamelCase   )

											__magic_name__				=     'test[:33%]'
											__magic_name__				=     Dataset(**reader.read(__UpperCamelCase	,			__UpperCamelCase	,			__UpperCamelCase   )   )
											self.assertEqual(dset['filename'][0]	,			F'{name}-test'   )
											self.assertEqual(dset.num_rows	,			33   )
											self.assertEqual(dset.num_columns	,			1   )

											__magic_name__				=     ['train', 'test[:33%]']
											__magic_name__				=     [Split.TRAIN, ReadInstruction.from_spec('test[:33%]'   )]
											for instructions in [instructionsa, instructionsa]:
																__magic_name__				=     [reader.read(__UpperCamelCase	,			__UpperCamelCase	,			__UpperCamelCase   ) for instr in instructions]
																__magic_name__,						__magic_name__				=     (Dataset(**__UpperCamelCase   ) for dataset_kwargs in datasets_kwargs)
																self.assertEqual(train_dset['filename'][0]	,			F'{name}-train'   )
																self.assertEqual(train_dset.num_rows	,			1_00   )
																self.assertEqual(train_dset.num_columns	,			1   )
																self.assertIsInstance(train_dset.split	,			__UpperCamelCase   )
																self.assertEqual(str(train_dset.split   )	,			'train'   )
																self.assertEqual(test_dset['filename'][0]	,			F'{name}-test'   )
																self.assertEqual(test_dset.num_rows	,			33   )
																self.assertEqual(test_dset.num_columns	,			1   )
																self.assertIsInstance(test_dset.split	,			__UpperCamelCase   )
																self.assertEqual(str(test_dset.split   )	,			'test[:33%]'   )
																del train_dset, test_dset







	def 						_SCREAMING_SNAKE_CASE				( self:			Dict   ):

						'''simple docstring'''





						__magic_name__				=     'my_name'
						__magic_name__				=     SplitInfo(name='train'	,			num_examples=10_00	,			shard_lengths=[1_00] * 10   )
						__magic_name__				=     [train_info]
						__magic_name__				=     SplitDict()
						split_dict.add(__UpperCamelCase   )
						__magic_name__				=     DatasetInfo(splits=__UpperCamelCase   )

						with tempfile.TemporaryDirectory() as tmp_dir:
											__magic_name__				=     ReaderTest(__UpperCamelCase	,			__UpperCamelCase   )

											__magic_name__				=     'train[:33%]'
											__magic_name__				=     Dataset(**reader.read(__UpperCamelCase	,			__UpperCamelCase	,			__UpperCamelCase   )   )
											self.assertEqual(dset['filename'][0]	,			F'{name}-train-00000-of-00010'   )
											self.assertEqual(dset['filename'][-1]	,			F'{name}-train-00003-of-00010'   )
											self.assertEqual(dset.num_rows	,			3_30   )
											self.assertEqual(dset.num_columns	,			1   )







	def 						_SCREAMING_SNAKE_CASE				( self:			List[str]   ):

						'''simple docstring'''





						__magic_name__				=     SplitInfo(name='train'	,			num_examples=1_00   )
						__magic_name__				=     SplitInfo(name='test'	,			num_examples=1_00   )
						__magic_name__				=     SplitDict()
						split_dict.add(__UpperCamelCase   )
						split_dict.add(__UpperCamelCase   )
						__magic_name__				=     DatasetInfo(splits=__UpperCamelCase   )

						with tempfile.TemporaryDirectory() as tmp_dir:
											__magic_name__				=     ReaderTest(__UpperCamelCase	,			__UpperCamelCase   )

											__magic_name__				=     [
											    {'filename': os.path.join(__UpperCamelCase	,			'train'   )},
											    {'filename': os.path.join(__UpperCamelCase	,			'test'   ), 'skip': 10, 'take': 10},
											]
											__magic_name__				=     Dataset(**reader.read_files(__UpperCamelCase	,			original_instructions='train+test[10:20]'   )   )
											self.assertEqual(dset.num_rows	,			1_10   )
											self.assertEqual(dset.num_columns	,			1   )
											del dset




@pytest.mark.parametrize('in_memory'       ,[False, True]					)
def        _lowercase  (					a_					:       int       ,a_					:       str       ,a_					:       Tuple					)					->						Any:




					'''simple docstring'''







					__magic_name__				=     arrow_file
					with assert_arrow_memory_increases() if in_memory else assert_arrow_memory_doesnt_increase():
										__magic_name__				=     ArrowReader.read_table(a_       ,in_memory=a_					)
					assert table.shape == dataset.data.shape
					assert set(table.column_names					) == set(dataset.data.column_names					)
					assert dict(table.to_pydict()					) == dict(dataset.data.to_pydict()					)  # to_pydict returns OrderedDict




@pytest.mark.parametrize('in_memory'       ,[False, True]					)
def        _lowercase  (					a_					:       Optional[int]       ,a_					:       int       ,a_					:       Tuple					)					->						List[str]:




					'''simple docstring'''







					__magic_name__				=     arrow_file
					__magic_name__				=     ArrowReader(''       ,a_					)
					with assert_arrow_memory_increases() if in_memory else assert_arrow_memory_doesnt_increase():
										__magic_name__				=     reader.read_files([{'filename': filename}]       ,in_memory=a_					)
					assert dataset_kwargs.keys() == {"arrow_table", "info", "split"}
					__magic_name__				=     dataset_kwargs['arrow_table']
					assert table.shape == dataset.data.shape
					assert set(table.column_names					) == set(dataset.data.column_names					)
					assert dict(table.to_pydict()					) == dict(dataset.data.to_pydict()					)  # to_pydict returns OrderedDict




def        _lowercase  (					)					->						List[Any]:




					'''simple docstring'''







					assert ReadInstruction('train'       ,to=1_0       ,unit='abs'					).to_spec() == "train[:10]"
					assert ReadInstruction('train'       ,from_=-8_0       ,to=1_0       ,unit='%'					).to_spec() == "train[-80%:10%]"

					__magic_name__				=     'train+test'
					assert ReadInstruction.from_spec(a_					).to_spec() == spec_train_test

					__magic_name__				=     'train[2:10]'
					assert ReadInstruction.from_spec(a_					).to_spec() == spec_train_abs

					__magic_name__				=     'train[15%:-20%]'
					assert ReadInstruction.from_spec(a_					).to_spec() == spec_train_pct

					__magic_name__				=     'train[:10%](closest)'
					assert ReadInstruction.from_spec(a_					).to_spec() == "train[:10%]"

					__magic_name__				=     'train[:10%](pct1_dropremainder)'
					assert ReadInstruction.from_spec(a_					).to_spec() == spec_train_pct_rounding

					__magic_name__				=     'train[:10%](pct1_dropremainder)+test[-10%:](pct1_dropremainder)'
					assert ReadInstruction.from_spec(a_					).to_spec() == spec_train_test_pct_rounding




def        _lowercase  (					)					->						Tuple:




					'''simple docstring'''







					__magic_name__				=     'dummy'
					__magic_name__				=     [SplitInfo(name='train'       ,num_examples=1_0_0					)]
					__magic_name__				=     'train[:33%]'
					__magic_name__				=     'arrow'
					__magic_name__				=     'prefix'

					__magic_name__				=     make_file_instructions(a_       ,a_       ,a_       ,a_       ,a_					)
					assert isinstance(a_       ,a_					)
					assert file_instructions.num_examples == 3_3
					assert file_instructions.file_instructions == [
					    {"filename": os.path.join(a_       ,F'{name}-train.arrow'					), "skip": 0, "take": 3_3}
					]

					__magic_name__				=     [SplitInfo(name='train'       ,num_examples=1_0_0       ,shard_lengths=[1_0] * 1_0					)]
					__magic_name__				=     make_file_instructions(a_       ,a_       ,a_       ,a_       ,a_					)
					assert isinstance(a_       ,a_					)
					assert file_instructions.num_examples == 3_3
					assert file_instructions.file_instructions == [
					    {"filename": os.path.join(a_       ,F'{name}-train-00000-of-00010.arrow'					), "skip": 0, "take": -1},
					    {"filename": os.path.join(a_       ,F'{name}-train-00001-of-00010.arrow'					), "skip": 0, "take": -1},
					    {"filename": os.path.join(a_       ,F'{name}-train-00002-of-00010.arrow'					), "skip": 0, "take": -1},
					    {"filename": os.path.join(a_       ,F'{name}-train-00003-of-00010.arrow'					), "skip": 0, "take": 3},
					]




@pytest.mark.parametrize('name, expected_exception'       ,[(None, TypeError), ('', ValueError)]					)
def        _lowercase  (					a_					:       Tuple       ,a_					:       List[str]					)					->						Optional[Any]:




					'''simple docstring'''







					__magic_name__				=     [SplitInfo(name='train'       ,num_examples=1_0_0					)]
					__magic_name__				=     'train'
					__magic_name__				=     'arrow'
					__magic_name__				=     'prefix_path'
					with pytest.raises(a_					):
										__magic_name__				=     make_file_instructions(a_       ,a_       ,a_       ,a_       ,a_					)







def        _lowercase  (					a_					:       str       ,a_					:       List[str]					)					->						Optional[Any]:




					'''simple docstring'''







					sequence.append(a_					)

					__magic_name__				=     0
					while sequence[index] != target:
										index += 1

					sequence.pop()

					if index == len(a_					):
										return None

					return index


if __name__ == "__main__":
						A__							=				input("Enter numbers separated by comma:\n").strip()
						A__							=				[int(item) for item in user_input.split(",")]

						A__							=				input("Enter a single number to be found in the list:\n")
						A__							=				int(target_input)
						A__							=				sentinel_linear_search(sequence, target)
						if result is not None:
												print(f'''{target} found at positions: {result}''')
						else:
												print("Not found")




