




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 				__snake_case     (_a						):



				def 					SCREAMING_SNAKE_CASE				(					self					:						Dict						,		_UpperCAmelCase					:						Dict						,		_UpperCAmelCase					:						int=False					)     ->			Tuple:





								'''simple docstring'''




								_lowerCAmelCase    ,			_lowerCAmelCase    ,			_lowerCAmelCase			:			Tuple        =					(
								    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()
								_lowerCAmelCase			:			int        =					pa.Table.from_pydict({"""filename""": [Path(_UpperCAmelCase					).name] * 100}					)
								if take == -1:
												_lowerCAmelCase			:			Tuple        =					len(_UpperCAmelCase					) - skip
								if skip is not None and take is not None:
												_lowerCAmelCase			:			int        =					pa_table.slice(_UpperCAmelCase						,		_UpperCAmelCase					)
								return pa_table






class 				__snake_case     (_a						):



				def 					SCREAMING_SNAKE_CASE				(					self					:						Optional[Any]					)     ->			List[Any]:





								'''simple docstring'''




								_lowerCAmelCase			:			List[Any]        =					"""my_name"""
								_lowerCAmelCase			:			Optional[int]        =					SplitInfo(name="""train"""						,		num_examples=100					)
								_lowerCAmelCase			:			Optional[Any]        =					SplitInfo(name="""test"""						,		num_examples=100					)
								_lowerCAmelCase			:			Any        =					[train_info, test_info]
								_lowerCAmelCase			:			Union[str, Any]        =					SplitDict()
								split_dict.add(_UpperCAmelCase					)
								split_dict.add(_UpperCAmelCase					)
								_lowerCAmelCase			:			List[str]        =					DatasetInfo(splits=_UpperCAmelCase					)

								with tempfile.TemporaryDirectory() as tmp_dir:
												_lowerCAmelCase			:			Optional[Any]        =					ReaderTest(_UpperCAmelCase						,		_UpperCAmelCase					)

												_lowerCAmelCase			:			Union[str, Any]        =					"""test[:33%]"""
												_lowerCAmelCase			:			Dict        =					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					)

												_lowerCAmelCase			:			Any        =					["""train""", """test[:33%]"""]
												_lowerCAmelCase			:			Any        =					[Split.TRAIN, ReadInstruction.from_spec("""test[:33%]"""					)]
												for instructions in [instructionsa, instructionsa]:
																_lowerCAmelCase			:			Optional[Any]        =					[reader.read(_UpperCAmelCase						,		_UpperCAmelCase						,		_UpperCAmelCase					) for instr in instructions]
																_lowerCAmelCase    ,			_lowerCAmelCase			:			Optional[int]        =					(Dataset(**_UpperCAmelCase					) for dataset_kwargs in datasets_kwargs)
																self.assertEqual(train_dset["""filename"""][0]						,		f"{name}-train"					)
																self.assertEqual(train_dset.num_rows						,		100					)
																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					:						Tuple					)     ->			str:





								'''simple docstring'''




								_lowerCAmelCase			:			Dict        =					"""my_name"""
								_lowerCAmelCase			:			Dict        =					SplitInfo(name="""train"""						,		num_examples=1000						,		shard_lengths=[100] * 10					)
								_lowerCAmelCase			:			Tuple        =					[train_info]
								_lowerCAmelCase			:			Optional[Any]        =					SplitDict()
								split_dict.add(_UpperCAmelCase					)
								_lowerCAmelCase			:			str        =					DatasetInfo(splits=_UpperCAmelCase					)

								with tempfile.TemporaryDirectory() as tmp_dir:
												_lowerCAmelCase			:			int        =					ReaderTest(_UpperCAmelCase						,		_UpperCAmelCase					)

												_lowerCAmelCase			:			str        =					"""train[:33%]"""
												_lowerCAmelCase			:			str        =					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						,		330					)
												self.assertEqual(dset.num_columns						,		1					)



				def 					SCREAMING_SNAKE_CASE				(					self					:						Union[str, Any]					)     ->			str:





								'''simple docstring'''




								_lowerCAmelCase			:			List[Any]        =					SplitInfo(name="""train"""						,		num_examples=100					)
								_lowerCAmelCase			:			Tuple        =					SplitInfo(name="""test"""						,		num_examples=100					)
								_lowerCAmelCase			:			Dict        =					SplitDict()
								split_dict.add(_UpperCAmelCase					)
								split_dict.add(_UpperCAmelCase					)
								_lowerCAmelCase			:			str        =					DatasetInfo(splits=_UpperCAmelCase					)

								with tempfile.TemporaryDirectory() as tmp_dir:
												_lowerCAmelCase			:			int        =					ReaderTest(_UpperCAmelCase						,		_UpperCAmelCase					)

												_lowerCAmelCase			:			List[str]        =					[
												    {"""filename""": os.path.join(_UpperCAmelCase						,		"""train"""					)},
												    {"""filename""": os.path.join(_UpperCAmelCase						,		"""test"""					), """skip""": 10, """take""": 10},
												]
												_lowerCAmelCase			:			int        =					Dataset(**reader.read_files(_UpperCAmelCase						,		original_instructions="""train+test[10:20]"""					)					)
												self.assertEqual(dset.num_rows						,		110					)
												self.assertEqual(dset.num_columns						,		1					)
												del dset






@pytest.mark.parametrize("""in_memory"""					,			[False, True]				)
def 							_UpperCAmelCase     (UpperCamelCase_       :       Optional[Any]					,			UpperCamelCase_       :       List[str]					,			UpperCamelCase_       :       Union[str, Any]				):
				'''simple docstring'''
				_lowerCAmelCase			:			str        =					arrow_file
				with assert_arrow_memory_increases() if in_memory else assert_arrow_memory_doesnt_increase():
								_lowerCAmelCase			:			Dict        =					ArrowReader.read_table(UpperCamelCase_					,			in_memory=UpperCamelCase_				)
				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 							_UpperCAmelCase     (UpperCamelCase_       :       Dict					,			UpperCamelCase_       :       int					,			UpperCamelCase_       :       Optional[int]				):
				'''simple docstring'''
				_lowerCAmelCase			:			Union[str, Any]        =					arrow_file
				_lowerCAmelCase			:			Any        =					ArrowReader(""""""					,			UpperCamelCase_				)
				with assert_arrow_memory_increases() if in_memory else assert_arrow_memory_doesnt_increase():
								_lowerCAmelCase			:			Optional[Any]        =					reader.read_files([{"""filename""": filename}]					,			in_memory=UpperCamelCase_				)
				assert dataset_kwargs.keys() == {"arrow_table", "info", "split"}
				_lowerCAmelCase			:			Union[str, Any]        =					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 							_UpperCAmelCase     ():
				'''simple docstring'''
				assert ReadInstruction("""train"""					,			to=10					,			unit="""abs"""				).to_spec() == "train[:10]"
				assert ReadInstruction("""train"""					,			from_=-80					,			to=10					,			unit="""%"""				).to_spec() == "train[-80%:10%]"

				_lowerCAmelCase			:			int        =					"""train+test"""
				assert ReadInstruction.from_spec(UpperCamelCase_				).to_spec() == spec_train_test

				_lowerCAmelCase			:			Any        =					"""train[2:10]"""
				assert ReadInstruction.from_spec(UpperCamelCase_				).to_spec() == spec_train_abs

				_lowerCAmelCase			:			Optional[Any]        =					"""train[15%:-20%]"""
				assert ReadInstruction.from_spec(UpperCamelCase_				).to_spec() == spec_train_pct

				_lowerCAmelCase			:			Optional[int]        =					"""train[:10%](closest)"""
				assert ReadInstruction.from_spec(UpperCamelCase_				).to_spec() == "train[:10%]"

				_lowerCAmelCase			:			Any        =					"""train[:10%](pct1_dropremainder)"""
				assert ReadInstruction.from_spec(UpperCamelCase_				).to_spec() == spec_train_pct_rounding

				_lowerCAmelCase			:			List[str]        =					"""train[:10%](pct1_dropremainder)+test[-10%:](pct1_dropremainder)"""
				assert ReadInstruction.from_spec(UpperCamelCase_				).to_spec() == spec_train_test_pct_rounding




def 							_UpperCAmelCase     ():
				'''simple docstring'''
				_lowerCAmelCase			:			Dict        =					"""dummy"""
				_lowerCAmelCase			:			Optional[Any]        =					[SplitInfo(name="""train"""					,			num_examples=100				)]
				_lowerCAmelCase			:			Tuple        =					"""train[:33%]"""
				_lowerCAmelCase			:			Union[str, Any]        =					"""arrow"""
				_lowerCAmelCase			:			List[Any]        =					"""prefix"""

				_lowerCAmelCase			:			str        =					make_file_instructions(UpperCamelCase_					,			UpperCamelCase_					,			UpperCamelCase_					,			UpperCamelCase_					,			UpperCamelCase_				)
				assert isinstance(UpperCamelCase_					,			UpperCamelCase_				)
				assert file_instructions.num_examples == 33
				assert file_instructions.file_instructions == [
				    {"filename": os.path.join(UpperCamelCase_					,			F"{name}-train.arrow"				), "skip": 0, "take": 33}
				]

				_lowerCAmelCase			:			List[str]        =					[SplitInfo(name="""train"""					,			num_examples=100					,			shard_lengths=[10] * 10				)]
				_lowerCAmelCase			:			int        =					make_file_instructions(UpperCamelCase_					,			UpperCamelCase_					,			UpperCamelCase_					,			UpperCamelCase_					,			UpperCamelCase_				)
				assert isinstance(UpperCamelCase_					,			UpperCamelCase_				)
				assert file_instructions.num_examples == 33
				assert file_instructions.file_instructions == [
				    {"filename": os.path.join(UpperCamelCase_					,			F"{name}-train-00000-of-00010.arrow"				), "skip": 0, "take": -1},
				    {"filename": os.path.join(UpperCamelCase_					,			F"{name}-train-00001-of-00010.arrow"				), "skip": 0, "take": -1},
				    {"filename": os.path.join(UpperCamelCase_					,			F"{name}-train-00002-of-00010.arrow"				), "skip": 0, "take": -1},
				    {"filename": os.path.join(UpperCamelCase_					,			F"{name}-train-00003-of-00010.arrow"				), "skip": 0, "take": 3},
				]





@pytest.mark.parametrize("""name, expected_exception"""					,			[(None, TypeError), ("""""", ValueError)]				)
def 							_UpperCAmelCase     (UpperCamelCase_       :       str					,			UpperCamelCase_       :       int				):
				'''simple docstring'''
				_lowerCAmelCase			:			Optional[int]        =					[SplitInfo(name="""train"""					,			num_examples=100				)]
				_lowerCAmelCase			:			List[str]        =					"""train"""
				_lowerCAmelCase			:			str        =					"""arrow"""
				_lowerCAmelCase			:			Dict        =					"""prefix_path"""
				with pytest.raises(UpperCamelCase_				):
								_lowerCAmelCase			:			str        =					make_file_instructions(UpperCamelCase_					,			UpperCamelCase_					,			UpperCamelCase_					,			UpperCamelCase_					,			UpperCamelCase_				)





"""simple docstring"""


def    a__       ( __lowercase = 20      )		->		int:

				try:
								_A         =	int(__lowercase      )
				except (TypeError, ValueError):
								raise TypeError("Parameter n must be int or castable to int."      )
				if n <= 0:
								raise ValueError("Parameter n must be greater than or equal to one."      )
				_A         =	0
				while 1:
								i += n * (n - 1)
								_A         =	0
								for j in range(2   ,	__lowercase      ):
												if i % j != 0:
																_A         =	1
																break
								if nfound == 0:
												if i == 0:
																_A         =	1
												return i
				return None


if __name__ == "__main__":
		print(f'''{solution() = }''')