

import copy
from dataclasses import dataclass
from pathlib import Path
from typing import Dict, Optional, Union


@dataclass
class 				SCREAMING_SNAKE_CASE__ :
    __lowerCamelCase						:	Optional[Union[str, Path]]														=					None
    __lowerCamelCase						:	bool														=					False
    __lowerCamelCase						:	bool														=					False
    __lowerCamelCase						:	bool														=					False
    __lowerCamelCase						:	Optional[Dict]														=					None
    __lowerCamelCase						:	Optional[str]														=					None
    __lowerCamelCase						:	bool														=					False
    __lowerCamelCase						:	bool														=					False
    __lowerCamelCase						:	bool														=					False
    __lowerCamelCase						:	bool														=					True
    __lowerCamelCase						:	Optional[int]														=					None
    __lowerCamelCase						:	int														=					1
    __lowerCamelCase						:	Optional[Union[str, bool]]														=					None
    __lowerCamelCase						:	bool														=					False
    __lowerCamelCase						:	Optional[Dict]														=					None
    __lowerCamelCase						:	Optional[str]														=					None





    def 				snake_case_    (				self):
         return self.__class__(**{k: copy.deepcopy(a) for k, v in self.__dict__.items()})




from typing import Optional

import pyspark

from .. import Features, NamedSplit
from ..download import DownloadMode
from ..packaged_modules.spark.spark import Spark
from .abc import AbstractDatasetReader


class 				SCREAMING_SNAKE_CASE__ (__snake_case					):





    def __init__(				self						,       a						,       a = None						,       a = None						,       a = True						,       a = None						,       a = False						,       a = None						,       a = True						,       a = "arrow"						,       **a						,       ):
         super().__init__(
             split=a						,       features=a						,       cache_dir=a						,       keep_in_memory=a						,       streaming=a						,       **a						,       )
         lowercase__   :       Optional[int]				=	load_from_cache_file
         lowercase__   :       Optional[int]				=	file_format
         lowercase__   :       int				=	Spark(
             df=a						,       features=a						,       cache_dir=a						,       working_dir=a						,       **a						,       )





    def 				snake_case_    (				self):
         if self.streaming:
              return self.builder.as_streaming_dataset(split=self.split)
         lowercase__   :       Dict				=	None if self._load_from_cache_file else DownloadMode.FORCE_REDOWNLOAD
         self.builder.download_and_prepare(
             download_mode=a						,       file_format=self._file_format						,       )
         return self.builder.as_dataset(split=self.split)

