
'''simple docstring'''
import multiprocessing
import os
from typing import BinaryIO, Optional, Union

import fsspec

from .. import Dataset, Features, NamedSplit, config
from ..formatting import query_table
from ..packaged_modules.json.json import Json
from ..utils import logging
from ..utils.typing import NestedDataStructureLike, PathLike
from .abc import AbstractDatasetReader







class   a_ (      UpperCamelCase__					):




			def __init__(       self					,   UpperCAmelCase					,   UpperCAmelCase = None					,   UpperCAmelCase = None					,   UpperCAmelCase = None					,   UpperCAmelCase = False					,   UpperCAmelCase = False					,   UpperCAmelCase = None					,   UpperCAmelCase = None					,   **UpperCAmelCase					,   ):
				super().__init__(
				    UpperCAmelCase					,   split=UpperCAmelCase					,   features=UpperCAmelCase					,   cache_dir=UpperCAmelCase					,   keep_in_memory=UpperCAmelCase					,   streaming=UpperCAmelCase					,   num_proc=UpperCAmelCase					,   **UpperCAmelCase					,   )
				a_      				=						field
				a_      				=						path_or_paths if isinstance(UpperCAmelCase					,   UpperCAmelCase	) else {self.split: path_or_paths}
				a_      				=						Json(
				    cache_dir=UpperCAmelCase					,   data_files=UpperCAmelCase					,   features=UpperCAmelCase					,   field=UpperCAmelCase					,   **UpperCAmelCase					,   )






			def 					lowerCAmelCase__					(       self	):
				# Build iterable dataset
				if self.streaming:
					a_      				=						self.builder.as_streaming_dataset(split=self.split	)
				# Build regular (map-style) dataset
				else:
					a_      				=						None
					a_      				=						None
					a_      				=						None
					a_      				=						None

					self.builder.download_and_prepare(
					    download_config=UpperCAmelCase					,   download_mode=UpperCAmelCase					,   verification_mode=UpperCAmelCase					,   base_path=UpperCAmelCase					,   num_proc=self.num_proc					,   )
					a_      				=						self.builder.as_dataset(
					    split=self.split					,   verification_mode=UpperCAmelCase					,   in_memory=self.keep_in_memory	)
				return dataset







class   a_ :




			def __init__(       self					,   UpperCAmelCase					,   UpperCAmelCase					,   UpperCAmelCase = None					,   UpperCAmelCase = None					,   **UpperCAmelCase					,   ):
				if num_proc is not None and num_proc <= 0:
					raise ValueError(f'''num_proc {num_proc} must be an integer > 0.'''	)

				a_      				=						dataset
				a_      				=						path_or_buf
				a_      				=						batch_size if batch_size else config.DEFAULT_MAX_BATCH_SIZE
				a_      				=						num_proc
				a_      				=						"""utf-8"""
				a_      				=						to_json_kwargs




			def 					lowerCAmelCase__					(       self	):
				a_      				=						self.to_json_kwargs.pop("""path_or_buf"""					,   UpperCAmelCase	)
				a_      				=						self.to_json_kwargs.pop("""orient"""					,   """records"""	)
				a_      				=						self.to_json_kwargs.pop("""lines"""					,   True if orient == """records""" else False	)
				a_      				=						self.to_json_kwargs.pop("""index"""					,   False if orient in ["""split""", """table"""] else True	)
				a_      				=						self.to_json_kwargs.pop("""compression"""					,   UpperCAmelCase	)

				if compression not in [None, "infer", "gzip", "bz2", "xz"]:
					raise NotImplementedError(f'''`datasets` currently does not support {compression} compression'''	)

				if isinstance(self.path_or_buf					,   (str, bytes, os.PathLike)	):
					with fsspec.open(self.path_or_buf					,   """wb"""					,   compression=UpperCAmelCase	) as buffer:
						a_      				=						self._write(file_obj=UpperCAmelCase					,   orient=UpperCAmelCase					,   lines=UpperCAmelCase					,   index=UpperCAmelCase					,   **self.to_json_kwargs	)
				else:
					if compression:
						raise NotImplementedError(
						    f'''The compression parameter is not supported when writing to a buffer, but compression={compression}'''
						    """ was passed. Please provide a local path instead."""	)
					a_      				=						self._write(
					    file_obj=self.path_or_buf					,   orient=UpperCAmelCase					,   lines=UpperCAmelCase					,   index=UpperCAmelCase					,   **self.to_json_kwargs	)
				return written




			def 					lowerCAmelCase__					(       self					,   UpperCAmelCase	):
				a_				,  a_				,  a_				,  a_				,  a_      				=						args

				a_      				=						query_table(
				    table=self.dataset.data					,   key=slice(UpperCAmelCase					,   offset + self.batch_size	)					,   indices=self.dataset._indices					,   )
				a_      				=						batch.to_pandas().to_json(
				    path_or_buf=UpperCAmelCase					,   orient=UpperCAmelCase					,   lines=UpperCAmelCase					,   index=UpperCAmelCase					,   **UpperCAmelCase	)
				if not json_str.endswith("""\n"""	):
					json_str += "\n"
				return json_str.encode(self.encoding	)






			def 					lowerCAmelCase__					(       self					,   UpperCAmelCase					,   UpperCAmelCase					,   UpperCAmelCase					,   UpperCAmelCase					,   **UpperCAmelCase					,   ):
				a_      				=						0

				if self.num_proc is None or self.num_proc == 1:
					for offset in logging.tqdm(
					    range(0					,   len(self.dataset	)					,   self.batch_size	)					,   unit="""ba"""					,   disable=not logging.is_progress_bar_enabled()					,   desc="""Creating json from Arrow format"""					,   ):
						a_      				=						self._batch_json((offset, orient, lines, index, to_json_kwargs)	)
						written += file_obj.write(UpperCAmelCase	)
				else:
					a_				,  a_      				=						len(self.dataset	), self.batch_size
					with multiprocessing.Pool(self.num_proc	) as pool:
						for json_str in logging.tqdm(
						    pool.imap(
						        self._batch_json					,   [(offset, orient, lines, index, to_json_kwargs) for offset in range(0					,   UpperCAmelCase					,   UpperCAmelCase	)]					,   )					,   total=(num_rows // batch_size) + 1 if num_rows % batch_size else num_rows // batch_size					,   unit="""ba"""					,   disable=not logging.is_progress_bar_enabled()					,   desc="""Creating json from Arrow format"""					,   ):
							written += file_obj.write(UpperCAmelCase	)

				return written


'''simple docstring'''
import re






def      UpperCamelCase_				(      A__						):
	a_      				=						re.compile(r"""^(\+91[\-\s]?)?[0]?(91)?[789]\d{9}$"""						)
	if match := re.search(A__  ,      A__						):
		return match.string == phone
	return False


if __name__ == "__main__":
		print(indian_phone_validator('+918827897895'))
