



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						(UpperCamelCase			):





     def 						__snake_case     (							self			:				Dict  ,	UpperCamelCase			:				Union[str, Any]  ,	UpperCamelCase			:				Tuple=False					)->Optional[int]:
      __SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE							:     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()
      __SCREAMING_SNAKE_CASE							:     Optional[int]							=						pa.Table.from_pydict({"filename": [Path(UpperCamelCase					).name] * 1_0_0}					)
      if take == -1:
       __SCREAMING_SNAKE_CASE							:     Tuple							=						len(UpperCamelCase					) - skip
      if skip is not None and take is not None:
       __SCREAMING_SNAKE_CASE							:     Any							=						pa_table.slice(UpperCamelCase  ,	UpperCamelCase					)
      return pa_table






class    _SCREAMING_SNAKE_CASE						(UpperCamelCase			):





     def 						__snake_case     (							self			:				Optional[int]					)->Dict:
      __SCREAMING_SNAKE_CASE							:     str							=						"my_name"
      __SCREAMING_SNAKE_CASE							:     Any							=						SplitInfo(name="train"  ,	num_examples=1_0_0					)
      __SCREAMING_SNAKE_CASE							:     Optional[int]							=						SplitInfo(name="test"  ,	num_examples=1_0_0					)
      __SCREAMING_SNAKE_CASE							:     Optional[Any]							=						[train_info, test_info]
      __SCREAMING_SNAKE_CASE							:     Dict							=						SplitDict()
      split_dict.add(UpperCamelCase					)
      split_dict.add(UpperCamelCase					)
      __SCREAMING_SNAKE_CASE							:     Union[str, Any]							=						DatasetInfo(splits=UpperCamelCase					)

      with tempfile.TemporaryDirectory() as tmp_dir:
       __SCREAMING_SNAKE_CASE							:     Union[str, Any]							=						ReaderTest(UpperCamelCase  ,	UpperCamelCase					)

       __SCREAMING_SNAKE_CASE							:     List[Any]							=						"test[:33%]"
       __SCREAMING_SNAKE_CASE							:     str							=						Dataset(**reader.read(UpperCamelCase  ,	UpperCamelCase  ,	UpperCamelCase					)					)
       self.assertEqual(dset["filename"][0]  ,	F"""{name}-test"""					)
       self.assertEqual(dset.num_rows  ,	3_3					)
       self.assertEqual(dset.num_columns  ,	1					)

       __SCREAMING_SNAKE_CASE							:     str							=						["train", "test[:33%]"]
       __SCREAMING_SNAKE_CASE							:     Union[str, Any]							=						[Split.TRAIN, ReadInstruction.from_spec("test[:33%]"					)]
       for instructions in [instructionsa, instructionsa]:
        __SCREAMING_SNAKE_CASE							:     Tuple							=						[reader.read(UpperCamelCase  ,	UpperCamelCase  ,	UpperCamelCase					) for instr in instructions]
        __SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE							:     Union[str, Any]							=						(Dataset(**UpperCamelCase					) for dataset_kwargs in datasets_kwargs)
        self.assertEqual(train_dset["filename"][0]  ,	F"""{name}-train"""					)
        self.assertEqual(train_dset.num_rows  ,	1_0_0					)
        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  ,	3_3					)
        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 						__snake_case     (							self			:				Tuple					)->Optional[int]:
      __SCREAMING_SNAKE_CASE							:     Tuple							=						"my_name"
      __SCREAMING_SNAKE_CASE							:     Union[str, Any]							=						SplitInfo(name="train"  ,	num_examples=1_0_0_0  ,	shard_lengths=[1_0_0] * 1_0					)
      __SCREAMING_SNAKE_CASE							:     Optional[int]							=						[train_info]
      __SCREAMING_SNAKE_CASE							:     Tuple							=						SplitDict()
      split_dict.add(UpperCamelCase					)
      __SCREAMING_SNAKE_CASE							:     Optional[Any]							=						DatasetInfo(splits=UpperCamelCase					)

      with tempfile.TemporaryDirectory() as tmp_dir:
       __SCREAMING_SNAKE_CASE							:     str							=						ReaderTest(UpperCamelCase  ,	UpperCamelCase					)

       __SCREAMING_SNAKE_CASE							:     Union[str, Any]							=						"train[:33%]"
       __SCREAMING_SNAKE_CASE							:     Optional[int]							=						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_3_0					)
       self.assertEqual(dset.num_columns  ,	1					)






     def 						__snake_case     (							self			:				List[str]					)->Optional[int]:
      __SCREAMING_SNAKE_CASE							:     Dict							=						SplitInfo(name="train"  ,	num_examples=1_0_0					)
      __SCREAMING_SNAKE_CASE							:     Union[str, Any]							=						SplitInfo(name="test"  ,	num_examples=1_0_0					)
      __SCREAMING_SNAKE_CASE							:     str							=						SplitDict()
      split_dict.add(UpperCamelCase					)
      split_dict.add(UpperCamelCase					)
      __SCREAMING_SNAKE_CASE							:     List[str]							=						DatasetInfo(splits=UpperCamelCase					)

      with tempfile.TemporaryDirectory() as tmp_dir:
       __SCREAMING_SNAKE_CASE							:     List[Any]							=						ReaderTest(UpperCamelCase  ,	UpperCamelCase					)

       __SCREAMING_SNAKE_CASE							:     int							=						[
           {"filename": os.path.join(UpperCamelCase  ,	"train"					)},
           {"filename": os.path.join(UpperCamelCase  ,	"test"					), "skip": 1_0, "take": 1_0},
       ]
       __SCREAMING_SNAKE_CASE							:     List[Any]							=						Dataset(**reader.read_files(UpperCamelCase  ,	original_instructions="train+test[10:20]"					)					)
       self.assertEqual(dset.num_rows  ,	1_1_0					)
       self.assertEqual(dset.num_columns  ,	1					)
       del dset






@pytest.mark.parametrize("in_memory"		,						[False, True]  )
def 						_lowerCAmelCase    (					__lowerCamelCase :  Dict		,						__lowerCamelCase :  Any		,						__lowerCamelCase :  Optional[Any]  ):



 """simple docstring"""





 __SCREAMING_SNAKE_CASE							:     int							=						arrow_file
 with assert_arrow_memory_increases() if in_memory else assert_arrow_memory_doesnt_increase():
  __SCREAMING_SNAKE_CASE							:     Optional[Any]							=						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 						_lowerCAmelCase    (					__lowerCamelCase :  int		,						__lowerCamelCase :  List[str]		,						__lowerCamelCase :  Dict  ):



 """simple docstring"""





 __SCREAMING_SNAKE_CASE							:     Any							=						arrow_file
 __SCREAMING_SNAKE_CASE							:     Optional[Any]							=						ArrowReader(""		,						__lowerCamelCase  )
 with assert_arrow_memory_increases() if in_memory else assert_arrow_memory_doesnt_increase():
  __SCREAMING_SNAKE_CASE							:     List[Any]							=						reader.read_files([{"filename": filename}]		,						in_memory=__lowerCamelCase  )
 assert dataset_kwargs.keys() == {"arrow_table", "info", "split"}
 __SCREAMING_SNAKE_CASE							:     Tuple							=						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 						_lowerCAmelCase    (					):



 """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%]"

 __SCREAMING_SNAKE_CASE							:     Tuple							=						"train+test"
 assert ReadInstruction.from_spec(__lowerCamelCase  ).to_spec() == spec_train_test

 __SCREAMING_SNAKE_CASE							:     List[Any]							=						"train[2:10]"
 assert ReadInstruction.from_spec(__lowerCamelCase  ).to_spec() == spec_train_abs

 __SCREAMING_SNAKE_CASE							:     Optional[int]							=						"train[15%:-20%]"
 assert ReadInstruction.from_spec(__lowerCamelCase  ).to_spec() == spec_train_pct

 __SCREAMING_SNAKE_CASE							:     Union[str, Any]							=						"train[:10%](closest)"
 assert ReadInstruction.from_spec(__lowerCamelCase  ).to_spec() == "train[:10%]"

 __SCREAMING_SNAKE_CASE							:     List[Any]							=						"train[:10%](pct1_dropremainder)"
 assert ReadInstruction.from_spec(__lowerCamelCase  ).to_spec() == spec_train_pct_rounding

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






def 						_lowerCAmelCase    (					):



 """simple docstring"""





 __SCREAMING_SNAKE_CASE							:     str							=						"dummy"
 __SCREAMING_SNAKE_CASE							:     str							=						[SplitInfo(name="train"		,						num_examples=100  )]
 __SCREAMING_SNAKE_CASE							:     Union[str, Any]							=						"train[:33%]"
 __SCREAMING_SNAKE_CASE							:     int							=						"arrow"
 __SCREAMING_SNAKE_CASE							:     Tuple							=						"prefix"

 __SCREAMING_SNAKE_CASE							:     Dict							=						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}
 ]

 __SCREAMING_SNAKE_CASE							:     List[Any]							=						[SplitInfo(name="train"		,						num_examples=100		,						shard_lengths=[10] * 10  )]
 __SCREAMING_SNAKE_CASE							:     Optional[Any]							=						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 						_lowerCAmelCase    (					__lowerCamelCase :  Dict		,						__lowerCamelCase :  Optional[Any]  ):



 """simple docstring"""





 __SCREAMING_SNAKE_CASE							:     int							=						[SplitInfo(name="train"		,						num_examples=100  )]
 __SCREAMING_SNAKE_CASE							:     Dict							=						"train"
 __SCREAMING_SNAKE_CASE							:     List[Any]							=						"arrow"
 __SCREAMING_SNAKE_CASE							:     Optional[int]							=						"prefix_path"
 with pytest.raises(__lowerCamelCase  ):
  __SCREAMING_SNAKE_CASE							:     int							=						make_file_instructions(__lowerCamelCase		,						__lowerCamelCase		,						__lowerCamelCase		,						__lowerCamelCase		,						__lowerCamelCase  )












'''simple docstring'''







import json
import os
from dataclasses import dataclass

import numpy as np
import pyarrow as pa

import datasets
from utils import get_duration


A					       =10_00_00_00_00_00
A					       =1_00_00

A       , A					       =os.path.split(__file__)
A					       =os.path.join(RESULTS_BASEPATH, 'results', RESULTS_FILENAME.replace('.py', '.json'))





def 		snake_case_				(_a      :				int       ,  _a      :				int	):
    UpperCAmelCase     			=						pa.Table.from_pydict({'''col''': [0] * chunk_size}	)
    UpperCAmelCase     			=						pa.concat_tables([table] * (num_examples // chunk_size)	)
    return datasets.Dataset(_a       ,  fingerprint='''table_100B'''	)


@dataclass
class      _a    :
       __a							:	int
       __a							:	int
       __a							:	int
       __a							:	int
       def        A (      self		:      List[str]							):



           '''simple docstring'''

           UpperCAmelCase     			=						np.random.default_rng(self.seed							)
           UpperCAmelCase     			=						rng.integers(low=self.low  ,							high=self.high  ,							size=self.size							).tolist()
       def __iter__(      self		:      Tuple							):



           '''simple docstring'''

           return iter(self._sampled_values							)







       def __len__(      self		:      Dict							):



           '''simple docstring'''

           return self.size






@get_duration
def 		snake_case_				(_a      :				datasets.Dataset	):
    UpperCAmelCase     			=						dataset[0]





@get_duration
def 		snake_case_				(_a      :				datasets.Dataset	):
    UpperCAmelCase     			=						dataset[-1]





@get_duration
def 		snake_case_				(_a      :				datasets.Dataset	):
    UpperCAmelCase     			=						dataset[range(len(_a	) // 2       ,  len(_a	) // 2 + 1_0_2_4	)]





@get_duration
def 		snake_case_				(_a      :				datasets.Dataset	):
    UpperCAmelCase     			=						dataset[RandIter(0       ,  len(_a	)       ,  1_0_2_4       ,  seed=4_2	)]





def 		snake_case_				():
    UpperCAmelCase     			=						{'''num examples''': SPEED_TEST_N_EXAMPLES}
    UpperCAmelCase     			=						(get_first_row, get_last_row, get_batch_of_aaaa_rows, get_batch_of_aaaa_random_rows)
    print('''generating dataset'''	)
    UpperCAmelCase     			=						generate_100B_dataset(num_examples=_a       ,  chunk_size=_a	)
    print('''Functions'''	)
    for func in functions:
        print(func.__name__	)
        UpperCAmelCase     			=						func(_a	)

    with open(_a       ,  '''wb'''	) as f:
        f.write(json.dumps(_a	).encode('''utf-8'''	)	)


if __name__ == "__main__":  # useful to run the profiler
   benchmark_table_100B()




