

from abc import ABC, abstractmethod
from typing import Optional, Union

from .. import Dataset, DatasetDict, Features, IterableDataset, IterableDatasetDict, NamedSplit
from ..utils.typing import NestedDataStructureLike, PathLike



class SCREAMING_SNAKE_CASE     (  lowerCAmelCase_			):
  """simple docstring"""






  def __init__(      self			:   Tuple	,							lowerCAmelCase			:   Optional[int] = None	,							lowerCAmelCase			:   Optional[int] = None	,							lowerCAmelCase			:   Union[str, Any] = None	,							lowerCAmelCase			:   Any = None	,							lowerCAmelCase			:   Dict = False	,							lowerCAmelCase			:   Union[str, Any] = False	,							lowerCAmelCase			:   Tuple = None	,							**lowerCAmelCase			:   int	,							)							->     Dict:






     """simple docstring"""







     __lowerCAmelCase  :      List[str]    =						path_or_paths
     __lowerCAmelCase  :      List[Any]    =						split if split or isinstance(__SCREAMING_SNAKE_CASE	,							__SCREAMING_SNAKE_CASE   ) else """train"""
     __lowerCAmelCase  :      Optional[Any]    =						features
     __lowerCAmelCase  :      int    =						cache_dir
     __lowerCAmelCase  :      Optional[int]    =						keep_in_memory
     __lowerCAmelCase  :      Optional[Any]    =						streaming
     __lowerCAmelCase  :      Dict    =						num_proc
     __lowerCAmelCase  :      Dict    =						kwargs







  @abstractmethod
  def 	SCREAMING_SNAKE_CASE   (      self			:   List[str]   )							->     Dict:






     """simple docstring"""







     pass






class SCREAMING_SNAKE_CASE     (  lowerCAmelCase_			):
  """simple docstring"""






  def __init__(      self			:   Tuple	,							lowerCAmelCase			:   str = None	,							lowerCAmelCase			:   Dict = None	,							lowerCAmelCase			:   Optional[Any] = False	,							lowerCAmelCase			:   Optional[Any] = False	,							lowerCAmelCase			:   Union[str, Any] = None	,							**lowerCAmelCase			:   Tuple	,							)							->     Tuple:






     """simple docstring"""







     __lowerCAmelCase  :      List[Any]    =						features
     __lowerCAmelCase  :      str    =						cache_dir
     __lowerCAmelCase  :      Optional[Any]    =						keep_in_memory
     __lowerCAmelCase  :      Union[str, Any]    =						streaming
     __lowerCAmelCase  :      Dict    =						num_proc
     __lowerCAmelCase  :      Optional[Any]    =						kwargs







  @abstractmethod
  def 	SCREAMING_SNAKE_CASE   (      self			:   List[Any]   )							->     Dict:






     """simple docstring"""







     pass





# Lint as: python3
# pylint: enable=line-too-long
# pylint: disable=g-import-not-at-top,g-bad-import-order,wrong-import-position

__UpperCAmelCase								=			"""2.13.1"""

import platform

import pyarrow
from packaging import version


if version.parse(platform.python_version()) < version.parse("""3.7"""):
   raise ImportWarning(
       """To use `datasets`, Python>=3.7 is required, and the current version of Python doesn't match this condition."""
   )

if version.parse(pyarrow.__version__).major < 8:
   raise ImportWarning(
       """To use `datasets`, the module `pyarrow>=8.0.0` is required, and the current version of `pyarrow` doesn't match this condition.\n"""
       """If you are running this in a Google Colab, you should probably just restart the runtime to use the right version of `pyarrow`."""
   )

del platform
del pyarrow
del version

from .arrow_dataset import Dataset
from .arrow_reader import ReadInstruction
from .builder import ArrowBasedBuilder, BeamBasedBuilder, BuilderConfig, DatasetBuilder, GeneratorBasedBuilder
from .combine import concatenate_datasets, interleave_datasets
from .dataset_dict import DatasetDict, IterableDatasetDict
from .download import *
from .features import *
from .fingerprint import disable_caching, enable_caching, is_caching_enabled, set_caching_enabled
from .info import DatasetInfo, MetricInfo
from .inspect import (
    get_dataset_config_info,
    get_dataset_config_names,
    get_dataset_infos,
    get_dataset_split_names,
    inspect_dataset,
    inspect_metric,
    list_datasets,
    list_metrics,
)
from .iterable_dataset import IterableDataset
from .load import load_dataset, load_dataset_builder, load_from_disk, load_metric
from .metric import Metric
from .splits import (
    NamedSplit,
    NamedSplitAll,
    Split,
    SplitBase,
    SplitDict,
    SplitGenerator,
    SplitInfo,
    SubSplitInfo,
    percent,
)
from .tasks import *
from .utils import *
from .utils import logging


# deprecated modules
from datasets import arrow_dataset as _arrow_dataset  # isort:skip
from datasets import utils as _utils  # isort:skip
from datasets.utils import download_manager as _deprecated_download_manager  # isort:skip

__UpperCAmelCase								=			concatenate_datasets
__UpperCAmelCase								=			DownloadConfig
__UpperCAmelCase								=			DownloadManager
__UpperCAmelCase								=			DownloadMode
__UpperCAmelCase								=			DownloadConfig
__UpperCAmelCase								=			DownloadMode
__UpperCAmelCase								=			DownloadManager

del _arrow_dataset, _utils, _deprecated_download_manager


