


"""simple docstring"""






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 			SCREAMING_SNAKE_CASE_  (   a__):




							'''simple docstring'''





							def        UpperCAmelCase (						self	,					lowerCamelCase__	,					lowerCamelCase__=False)   ->	Dict:







								'''simple docstring'''




								snake_case__  :						Dict		=      (
								    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(_lowerCamelCase)	,					"wb").close()
								snake_case__  :						List[str]		=      pa.Table.from_pydict({"filename": [Path(_lowerCamelCase).name] * 100})
								if take == -1:
									snake_case__  :						Any		=      len(_lowerCamelCase) - skip
								if skip is not None and take is not None:
									snake_case__  :						List[str]		=      pa_table.slice(_lowerCamelCase	,					_lowerCamelCase)
								return pa_table


class 			SCREAMING_SNAKE_CASE_  (   a__):




							'''simple docstring'''





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







								'''simple docstring'''




								snake_case__  :						Any		=      '''my_name'''
								snake_case__  :						List[Any]		=      SplitInfo(name="train"	,					num_examples=100)
								snake_case__  :						List[Any]		=      SplitInfo(name="test"	,					num_examples=100)
								snake_case__  :						Dict		=      [train_info, test_info]
								snake_case__  :						Any		=      SplitDict()
								split_dict.add(_lowerCamelCase)
								split_dict.add(_lowerCamelCase)
								snake_case__  :						Tuple		=      DatasetInfo(splits=_lowerCamelCase)

								with tempfile.TemporaryDirectory() as tmp_dir:
									snake_case__  :						List[str]		=      ReaderTest(_lowerCamelCase	,					_lowerCamelCase)

									snake_case__  :						List[str]		=      '''test[:33%]'''
									snake_case__  :						Tuple		=      Dataset(**reader.read(_lowerCamelCase	,					_lowerCamelCase	,					_lowerCamelCase))
									self.assertEqual(dset["filename"][0]	,					f"""{name}-test""")
									self.assertEqual(dset.num_rows	,					33)
									self.assertEqual(dset.num_columns	,					1)

									snake_case__  :						Optional[int]		=      ['''train''', '''test[:33%]''']
									snake_case__  :						Any		=      [Split.TRAIN, ReadInstruction.from_spec("test[:33%]")]
									for instructions in [instructionsa, instructionsa]:
										snake_case__  :						List[Any]		=      [reader.read(_lowerCamelCase	,					_lowerCamelCase	,					_lowerCamelCase) for instr in instructions]
										snake_case__  :						Tuple		=      (Dataset(**_lowerCamelCase) 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	,					_lowerCamelCase)
										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	,					_lowerCamelCase)
										self.assertEqual(str(test_dset.split)	,					"test[:33%]")
										del train_dset, test_dset




							def        UpperCAmelCase (						self)   ->	str:







								'''simple docstring'''




								snake_case__  :						str		=      '''my_name'''
								snake_case__  :						int		=      SplitInfo(name="train"	,					num_examples=1_000	,					shard_lengths=[100] * 10)
								snake_case__  :						Dict		=      [train_info]
								snake_case__  :						List[str]		=      SplitDict()
								split_dict.add(_lowerCamelCase)
								snake_case__  :						Any		=      DatasetInfo(splits=_lowerCamelCase)

								with tempfile.TemporaryDirectory() as tmp_dir:
									snake_case__  :						Tuple		=      ReaderTest(_lowerCamelCase	,					_lowerCamelCase)

									snake_case__  :						Union[str, Any]		=      '''train[:33%]'''
									snake_case__  :						Union[str, Any]		=      Dataset(**reader.read(_lowerCamelCase	,					_lowerCamelCase	,					_lowerCamelCase))
									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        UpperCAmelCase (						self)   ->	Optional[Any]:







								'''simple docstring'''




								snake_case__  :						int		=      SplitInfo(name="train"	,					num_examples=100)
								snake_case__  :						Optional[int]		=      SplitInfo(name="test"	,					num_examples=100)
								snake_case__  :						Optional[int]		=      SplitDict()
								split_dict.add(_lowerCamelCase)
								split_dict.add(_lowerCamelCase)
								snake_case__  :						Any		=      DatasetInfo(splits=_lowerCamelCase)

								with tempfile.TemporaryDirectory() as tmp_dir:
									snake_case__  :						int		=      ReaderTest(_lowerCamelCase	,					_lowerCamelCase)

									snake_case__  :						Optional[Any]		=      [
									    {'''filename''': os.path.join(_lowerCamelCase	,					"train")},
									    {'''filename''': os.path.join(_lowerCamelCase	,					"test"), '''skip''': 10, '''take''': 10},
									]
									snake_case__  :						List[Any]		=      Dataset(**reader.read_files(_lowerCamelCase	,					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 			A__		(					_UpperCAmelCase    :      Any				,    _UpperCAmelCase    :      Union[str, Any]				,    _UpperCAmelCase    :      List[str]	)							->	Union[str, Any]:

	'''simple docstring'''


	snake_case__  :						int		=      arrow_file
	with assert_arrow_memory_increases() if in_memory else assert_arrow_memory_doesnt_increase():
		snake_case__  :						Dict		=      ArrowReader.read_table(lowerCamelCase__				,    in_memory=lowerCamelCase__	)
	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 			A__		(					_UpperCAmelCase    :      Union[str, Any]				,    _UpperCAmelCase    :      List[Any]				,    _UpperCAmelCase    :      Optional[Any]	)							->	Optional[int]:

	'''simple docstring'''


	snake_case__  :						int		=      arrow_file
	snake_case__  :						Tuple		=      ArrowReader(""				,    lowerCamelCase__	)
	with assert_arrow_memory_increases() if in_memory else assert_arrow_memory_doesnt_increase():
		snake_case__  :						Any		=      reader.read_files([{"filename": filename}]				,    in_memory=lowerCamelCase__	)
	assert dataset_kwargs.keys() == {"arrow_table", "info", "split"}
	snake_case__  :						Optional[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 			A__		(					)							->	Dict:

	'''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%]"

	snake_case__  :						Any		=      '''train+test'''
	assert ReadInstruction.from_spec(lowerCamelCase__	).to_spec() == spec_train_test

	snake_case__  :						Tuple		=      '''train[2:10]'''
	assert ReadInstruction.from_spec(lowerCamelCase__	).to_spec() == spec_train_abs

	snake_case__  :						Optional[int]		=      '''train[15%:-20%]'''
	assert ReadInstruction.from_spec(lowerCamelCase__	).to_spec() == spec_train_pct

	snake_case__  :						List[Any]		=      '''train[:10%](closest)'''
	assert ReadInstruction.from_spec(lowerCamelCase__	).to_spec() == "train[:10%]"

	snake_case__  :						int		=      '''train[:10%](pct1_dropremainder)'''
	assert ReadInstruction.from_spec(lowerCamelCase__	).to_spec() == spec_train_pct_rounding

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



def 			A__		(					)							->	List[str]:

	'''simple docstring'''


	snake_case__  :						Optional[Any]		=      '''dummy'''
	snake_case__  :						List[str]		=      [SplitInfo(name="train"				,    num_examples=1_00	)]
	snake_case__  :						Union[str, Any]		=      '''train[:33%]'''
	snake_case__  :						str		=      '''arrow'''
	snake_case__  :						int		=      '''prefix'''

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

	snake_case__  :						Tuple		=      [SplitInfo(name="train"				,    num_examples=1_00				,    shard_lengths=[10] * 10	)]
	snake_case__  :						Optional[int]		=      make_file_instructions(lowerCamelCase__				,    lowerCamelCase__				,    lowerCamelCase__				,    lowerCamelCase__				,    lowerCamelCase__	)
	assert isinstance(lowerCamelCase__				,    lowerCamelCase__	)
	assert file_instructions.num_examples == 33
	assert file_instructions.file_instructions == [
	    {"filename": os.path.join(lowerCamelCase__				,    F"""{name}-train-00000-of-00010.arrow"""	), "skip": 0, "take": -1},
	    {"filename": os.path.join(lowerCamelCase__				,    F"""{name}-train-00001-of-00010.arrow"""	), "skip": 0, "take": -1},
	    {"filename": os.path.join(lowerCamelCase__				,    F"""{name}-train-00002-of-00010.arrow"""	), "skip": 0, "take": -1},
	    {"filename": os.path.join(lowerCamelCase__				,    F"""{name}-train-00003-of-00010.arrow"""	), "skip": 0, "take": 3},
	]



@pytest.mark.parametrize("name, expected_exception"				,    [(None, TypeError), ("", ValueError)]	)
def 			A__		(					_UpperCAmelCase    :      Optional[int]				,    _UpperCAmelCase    :      Dict	)							->	Tuple:

	'''simple docstring'''


	snake_case__  :						Optional[Any]		=      [SplitInfo(name="train"				,    num_examples=1_00	)]
	snake_case__  :						int		=      '''train'''
	snake_case__  :						List[Any]		=      '''arrow'''
	snake_case__  :						Union[str, Any]		=      '''prefix_path'''
	with pytest.raises(lowerCamelCase__	):
		snake_case__  :						Optional[Any]		=      make_file_instructions(lowerCamelCase__				,    lowerCamelCase__				,    lowerCamelCase__				,    lowerCamelCase__				,    lowerCamelCase__	)











'''simple docstring'''




import abc
import copy
import dataclasses
from dataclasses import dataclass
from typing import ClassVar, Dict, Type, TypeVar

from ..features import Features


snake_case__ 							=    TypeVar("""T""", bound="""TaskTemplate""")






@dataclass(frozen=a__  )
class      UpperCamelCase_  (abc.ABC  ):







						"""simple docstring"""


						_lowerCAmelCase         =       42
						_lowerCAmelCase         =       42
						_lowerCAmelCase         =       42







						def    _a     (  self   :							T				,			_lowerCamelCase   :							Features     ):





											"""simple docstring"""







											return copy.deepcopy(self     )







						@property
						def    _a     (  self   :							List[str]     ):





											"""simple docstring"""







											return Features(**self.input_schema				,			**self.label_schema     )







						@property
						@abc.abstractmethod
						def    _a     (  self   :							int     ):





											"""simple docstring"""







											raise NotImplementedError







						@classmethod
						def    _a     (  cls   :							Type[T]				,			_lowerCamelCase   :							dict     ):





											"""simple docstring"""







											A_			:  Dict			=				{f.name for f in dataclasses.fields(cls     )}
											return cls(**{k: v for k, v in template_dict.items() if k in field_names}     )



