




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 		lowercase_       (	lowerCAmelCase__				):




					def     _lowercase						(   self:		Any,     _lowercase:		int,     _lowercase:		Optional[int]=False):


									'''simple docstring'''


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





class 		lowercase_       (	lowerCAmelCase__				):




					def     _lowercase						(   self:		List[Any]):


									'''simple docstring'''


									__lowerCAmelCase					=  """my_name"""
									__lowerCAmelCase					=  SplitInfo(name="""train""",     num_examples=100)
									__lowerCAmelCase					=  SplitInfo(name="""test""",     num_examples=100)
									__lowerCAmelCase					=  [train_info, test_info]
									__lowerCAmelCase					=  SplitDict()
									split_dict.add(_lowercase)
									split_dict.add(_lowercase)
									__lowerCAmelCase					=  DatasetInfo(splits=_lowercase)

									with tempfile.TemporaryDirectory() as tmp_dir:
													__lowerCAmelCase					=  ReaderTest(_lowercase,     _lowercase)

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

													__lowerCAmelCase					=  ["""train""", """test[:33%]"""]
													__lowerCAmelCase					=  [Split.TRAIN, ReadInstruction.from_spec("""test[:33%]""")]
													for instructions in [instructionsa, instructionsa]:
																	__lowerCAmelCase					=  [reader.read(_lowercase,     _lowercase,     _lowercase) for instr in instructions]
																	__lowerCAmelCase	,				__lowerCAmelCase					=  (Dataset(**_lowercase) 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,     _lowercase)
																	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,     _lowercase)
																	self.assertEqual(str(test_dset.split),     """test[:33%]""")
																	del train_dset, test_dset




					def     _lowercase						(   self:		Any):


									'''simple docstring'''


									__lowerCAmelCase					=  """my_name"""
									__lowerCAmelCase					=  SplitInfo(name="""train""",     num_examples=1000,     shard_lengths=[100] * 10)
									__lowerCAmelCase					=  [train_info]
									__lowerCAmelCase					=  SplitDict()
									split_dict.add(_lowercase)
									__lowerCAmelCase					=  DatasetInfo(splits=_lowercase)

									with tempfile.TemporaryDirectory() as tmp_dir:
													__lowerCAmelCase					=  ReaderTest(_lowercase,     _lowercase)

													__lowerCAmelCase					=  """train[:33%]"""
													__lowerCAmelCase					=  Dataset(**reader.read(_lowercase,     _lowercase,     _lowercase))
													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     _lowercase						(   self:		Union[str, Any]):


									'''simple docstring'''


									__lowerCAmelCase					=  SplitInfo(name="""train""",     num_examples=100)
									__lowerCAmelCase					=  SplitInfo(name="""test""",     num_examples=100)
									__lowerCAmelCase					=  SplitDict()
									split_dict.add(_lowercase)
									split_dict.add(_lowercase)
									__lowerCAmelCase					=  DatasetInfo(splits=_lowercase)

									with tempfile.TemporaryDirectory() as tmp_dir:
													__lowerCAmelCase					=  ReaderTest(_lowercase,     _lowercase)

													__lowerCAmelCase					=  [
													    {"""filename""": os.path.join(_lowercase,     """train""")},
													    {"""filename""": os.path.join(_lowercase,     """test"""), """skip""": 10, """take""": 10},
													]
													__lowerCAmelCase					=  Dataset(**reader.read_files(_lowercase,     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__						,			UpperCamelCase__						,			UpperCamelCase__   )     ->     Tuple:







				'''simple docstring'''


				__lowerCAmelCase					=  arrow_file
				with assert_arrow_memory_increases() if in_memory else assert_arrow_memory_doesnt_increase():
								__lowerCAmelCase					=  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__						,			UpperCamelCase__						,			UpperCamelCase__   )     ->     Tuple:







				'''simple docstring'''


				__lowerCAmelCase					=  arrow_file
				__lowerCAmelCase					=  ArrowReader(""""""						,			UpperCamelCase__   )
				with assert_arrow_memory_increases() if in_memory else assert_arrow_memory_doesnt_increase():
								__lowerCAmelCase					=  reader.read_files([{"""filename""": filename}]						,			in_memory=UpperCamelCase__   )
				assert dataset_kwargs.keys() == {"arrow_table", "info", "split"}
				__lowerCAmelCase					=  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  (						)     ->     List[Any]:







				'''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					=  """train+test"""
				assert ReadInstruction.from_spec(UpperCamelCase__   ).to_spec() == spec_train_test

				__lowerCAmelCase					=  """train[2:10]"""
				assert ReadInstruction.from_spec(UpperCamelCase__   ).to_spec() == spec_train_abs

				__lowerCAmelCase					=  """train[15%:-20%]"""
				assert ReadInstruction.from_spec(UpperCamelCase__   ).to_spec() == spec_train_pct

				__lowerCAmelCase					=  """train[:10%](closest)"""
				assert ReadInstruction.from_spec(UpperCamelCase__   ).to_spec() == "train[:10%]"

				__lowerCAmelCase					=  """train[:10%](pct1_dropremainder)"""
				assert ReadInstruction.from_spec(UpperCamelCase__   ).to_spec() == spec_train_pct_rounding

				__lowerCAmelCase					=  """train[:10%](pct1_dropremainder)+test[-10%:](pct1_dropremainder)"""
				assert ReadInstruction.from_spec(UpperCamelCase__   ).to_spec() == spec_train_test_pct_rounding





def      UpperCAmelCase  (						)     ->     List[str]:







				'''simple docstring'''


				__lowerCAmelCase					=  """dummy"""
				__lowerCAmelCase					=  [SplitInfo(name="""train"""						,			num_examples=1_00   )]
				__lowerCAmelCase					=  """train[:33%]"""
				__lowerCAmelCase					=  """arrow"""
				__lowerCAmelCase					=  """prefix"""

				__lowerCAmelCase					=  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					=  [SplitInfo(name="""train"""						,			num_examples=1_00						,			shard_lengths=[10] * 10   )]
				__lowerCAmelCase					=  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__						,			UpperCamelCase__   )     ->     Tuple:







				'''simple docstring'''


				__lowerCAmelCase					=  [SplitInfo(name="""train"""						,			num_examples=1_00   )]
				__lowerCAmelCase					=  """train"""
				__lowerCAmelCase					=  """arrow"""
				__lowerCAmelCase					=  """prefix_path"""
				with pytest.raises(UpperCamelCase__   ):
								__lowerCAmelCase					=  make_file_instructions(UpperCamelCase__						,			UpperCamelCase__						,			UpperCamelCase__						,			UpperCamelCase__						,			UpperCamelCase__   )











import csv
import os

import pytest

from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.csv import CsvDatasetReader, CsvDatasetWriter

from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases





def      UpperCAmelCase  (						UpperCamelCase__						,			UpperCamelCase__   )     ->     Tuple:







				'''simple docstring'''


				assert isinstance(UpperCamelCase__						,			UpperCamelCase__   )
				assert dataset.num_rows == 4
				assert dataset.num_columns == 3
				assert dataset.column_names == ["col_1", "col_2", "col_3"]
				for feature, expected_dtype in expected_features.items():
								assert dataset.features[feature].dtype == expected_dtype





@pytest.mark.parametrize("""keep_in_memory"""						,			[False, True]   )
def      UpperCAmelCase  (						UpperCamelCase__						,			UpperCamelCase__						,			UpperCamelCase__   )     ->     Union[str, Any]:







				'''simple docstring'''


				__lowerCAmelCase					=  tmp_path / """cache"""
				__lowerCAmelCase					=  {"""col_1""": """int64""", """col_2""": """int64""", """col_3""": """float64"""}
				with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
								__lowerCAmelCase					=  CsvDatasetReader(UpperCamelCase__						,			cache_dir=UpperCamelCase__						,			keep_in_memory=UpperCamelCase__   ).read()
				_check_csv_dataset(UpperCamelCase__						,			UpperCamelCase__   )





@pytest.mark.parametrize(
    """features"""						,			[
        None,
        {"""col_1""": """string""", """col_2""": """int64""", """col_3""": """float64"""},
        {"""col_1""": """string""", """col_2""": """string""", """col_3""": """string"""},
        {"""col_1""": """int32""", """col_2""": """int32""", """col_3""": """int32"""},
        {"""col_1""": """float32""", """col_2""": """float32""", """col_3""": """float32"""},
    ]						,			)
def      UpperCAmelCase  (						UpperCamelCase__						,			UpperCamelCase__						,			UpperCamelCase__   )     ->     Tuple:







				'''simple docstring'''


				__lowerCAmelCase					=  tmp_path / """cache"""
				# CSV file loses col_1 string dtype information: default now is "int64" instead of "string"
				__lowerCAmelCase					=  {"""col_1""": """int64""", """col_2""": """int64""", """col_3""": """float64"""}
				__lowerCAmelCase					=  features.copy() if features else default_expected_features
				__lowerCAmelCase					=  (
				    Features({feature: Value(UpperCamelCase__   ) for feature, dtype in features.items()}   ) if features is not None else None
				)
				__lowerCAmelCase					=  CsvDatasetReader(UpperCamelCase__						,			features=UpperCamelCase__						,			cache_dir=UpperCamelCase__   ).read()
				_check_csv_dataset(UpperCamelCase__						,			UpperCamelCase__   )





@pytest.mark.parametrize("""split"""						,			[None, NamedSplit("""train"""   ), """train""", """test"""]   )
def      UpperCAmelCase  (						UpperCamelCase__						,			UpperCamelCase__						,			UpperCamelCase__   )     ->     Optional[Any]:







				'''simple docstring'''


				__lowerCAmelCase					=  tmp_path / """cache"""
				__lowerCAmelCase					=  {"""col_1""": """int64""", """col_2""": """int64""", """col_3""": """float64"""}
				__lowerCAmelCase					=  CsvDatasetReader(UpperCamelCase__						,			cache_dir=UpperCamelCase__						,			split=UpperCamelCase__   ).read()
				_check_csv_dataset(UpperCamelCase__						,			UpperCamelCase__   )
				assert dataset.split == split if split else "train"





@pytest.mark.parametrize("""path_type"""						,			[str, list]   )
def      UpperCAmelCase  (						UpperCamelCase__						,			UpperCamelCase__						,			UpperCamelCase__   )     ->     List[Any]:







				'''simple docstring'''


				if issubclass(UpperCamelCase__						,			UpperCamelCase__   ):
								__lowerCAmelCase					=  csv_path
				elif issubclass(UpperCamelCase__						,			UpperCamelCase__   ):
								__lowerCAmelCase					=  [csv_path]
				__lowerCAmelCase					=  tmp_path / """cache"""
				__lowerCAmelCase					=  {"""col_1""": """int64""", """col_2""": """int64""", """col_3""": """float64"""}
				__lowerCAmelCase					=  CsvDatasetReader(UpperCamelCase__						,			cache_dir=UpperCamelCase__   ).read()
				_check_csv_dataset(UpperCamelCase__						,			UpperCamelCase__   )





def      UpperCAmelCase  (						UpperCamelCase__						,			UpperCamelCase__						,			UpperCamelCase__=("train",)   )     ->     Optional[int]:







				'''simple docstring'''


				assert isinstance(UpperCamelCase__						,			UpperCamelCase__   )
				for split in splits:
								__lowerCAmelCase					=  dataset_dict[split]
								assert dataset.num_rows == 4
								assert dataset.num_columns == 3
								assert dataset.column_names == ["col_1", "col_2", "col_3"]
								for feature, expected_dtype in expected_features.items():
												assert dataset.features[feature].dtype == expected_dtype





@pytest.mark.parametrize("""keep_in_memory"""						,			[False, True]   )
def      UpperCAmelCase  (						UpperCamelCase__						,			UpperCamelCase__						,			UpperCamelCase__   )     ->     List[Any]:







				'''simple docstring'''


				__lowerCAmelCase					=  tmp_path / """cache"""
				__lowerCAmelCase					=  {"""col_1""": """int64""", """col_2""": """int64""", """col_3""": """float64"""}
				with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
								__lowerCAmelCase					=  CsvDatasetReader({"""train""": csv_path}						,			cache_dir=UpperCamelCase__						,			keep_in_memory=UpperCamelCase__   ).read()
				_check_csv_datasetdict(UpperCamelCase__						,			UpperCamelCase__   )





@pytest.mark.parametrize(
    """features"""						,			[
        None,
        {"""col_1""": """string""", """col_2""": """int64""", """col_3""": """float64"""},
        {"""col_1""": """string""", """col_2""": """string""", """col_3""": """string"""},
        {"""col_1""": """int32""", """col_2""": """int32""", """col_3""": """int32"""},
        {"""col_1""": """float32""", """col_2""": """float32""", """col_3""": """float32"""},
    ]						,			)
def      UpperCAmelCase  (						UpperCamelCase__						,			UpperCamelCase__						,			UpperCamelCase__   )     ->     List[Any]:







				'''simple docstring'''


				__lowerCAmelCase					=  tmp_path / """cache"""
				# CSV file loses col_1 string dtype information: default now is "int64" instead of "string"
				__lowerCAmelCase					=  {"""col_1""": """int64""", """col_2""": """int64""", """col_3""": """float64"""}
				__lowerCAmelCase					=  features.copy() if features else default_expected_features
				__lowerCAmelCase					=  (
				    Features({feature: Value(UpperCamelCase__   ) for feature, dtype in features.items()}   ) if features is not None else None
				)
				__lowerCAmelCase					=  CsvDatasetReader({"""train""": csv_path}						,			features=UpperCamelCase__						,			cache_dir=UpperCamelCase__   ).read()
				_check_csv_datasetdict(UpperCamelCase__						,			UpperCamelCase__   )





@pytest.mark.parametrize("""split"""						,			[None, NamedSplit("""train"""   ), """train""", """test"""]   )
def      UpperCAmelCase  (						UpperCamelCase__						,			UpperCamelCase__						,			UpperCamelCase__   )     ->     Tuple:







				'''simple docstring'''


				if split:
								__lowerCAmelCase					=  {split: csv_path}
				else:
								__lowerCAmelCase					=  {"""train""": csv_path, """test""": csv_path}
				__lowerCAmelCase					=  tmp_path / """cache"""
				__lowerCAmelCase					=  {"""col_1""": """int64""", """col_2""": """int64""", """col_3""": """float64"""}
				__lowerCAmelCase					=  CsvDatasetReader(UpperCamelCase__						,			cache_dir=UpperCamelCase__   ).read()
				_check_csv_datasetdict(UpperCamelCase__						,			UpperCamelCase__						,			splits=list(path.keys()   )   )
				assert all(dataset[split].split == split for split in path.keys()   )





def      UpperCAmelCase  (						UpperCamelCase__   )     ->     str:







				'''simple docstring'''


				with open(UpperCamelCase__						,			encoding="""utf-8"""   ) as csvfile:
								yield from csv.reader(UpperCamelCase__   )





def      UpperCAmelCase  (						UpperCamelCase__						,			UpperCamelCase__   )     ->     List[Any]:







				'''simple docstring'''


				__lowerCAmelCase					=  tmp_path / """cache"""
				__lowerCAmelCase					=  os.path.join(UpperCamelCase__						,			"""tmp.csv"""   )
				__lowerCAmelCase					=  CsvDatasetReader({"""train""": csv_path}						,			cache_dir=UpperCamelCase__   ).read()
				CsvDatasetWriter(dataset["""train"""]						,			UpperCamelCase__						,			num_proc=1   ).write()

				__lowerCAmelCase					=  iter_csv_file(UpperCamelCase__   )
				__lowerCAmelCase					=  iter_csv_file(UpperCamelCase__   )

				for rowa, rowa in zip(UpperCamelCase__						,			UpperCamelCase__   ):
								assert rowa == rowa





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







				'''simple docstring'''


				__lowerCAmelCase					=  tmp_path / """cache"""
				__lowerCAmelCase					=  os.path.join(UpperCamelCase__						,			"""tmp.csv"""   )
				__lowerCAmelCase					=  CsvDatasetReader({"""train""": csv_path}						,			cache_dir=UpperCamelCase__   ).read()
				CsvDatasetWriter(dataset["""train"""]						,			UpperCamelCase__						,			num_proc=2   ).write()

				__lowerCAmelCase					=  iter_csv_file(UpperCamelCase__   )
				__lowerCAmelCase					=  iter_csv_file(UpperCamelCase__   )

				for rowa, rowa in zip(UpperCamelCase__						,			UpperCamelCase__   ):
								assert rowa == rowa





def      UpperCAmelCase  (						UpperCamelCase__						,			UpperCamelCase__   )     ->     Dict:







				'''simple docstring'''


				__lowerCAmelCase					=  tmp_path / """cache"""
				__lowerCAmelCase					=  os.path.join(UpperCamelCase__						,			"""tmp.csv"""   )
				__lowerCAmelCase					=  CsvDatasetReader({"""train""": csv_path}						,			cache_dir=UpperCamelCase__   ).read()
				with pytest.raises(UpperCamelCase__   ):
								CsvDatasetWriter(dataset["""train"""]						,			UpperCamelCase__						,			num_proc=0   )





