




"""simple docstring"""







import multiprocessing
import os
from typing import BinaryIO, Optional, Union

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

class 							snake_case_ (				lowerCamelCase_ ):







   """simple docstring"""




   def __init__(		self					,				lowerCamelCase_					,				lowerCamelCase_ = None					,				lowerCamelCase_ = None					,				lowerCamelCase_ = None					,				lowerCamelCase_ = False					,				lowerCamelCase_ = False					,				lowerCamelCase_ = None					,				**lowerCamelCase_					,				)							->      Dict:
       super().__init__(
           lowerCamelCase_					,				split=lowerCamelCase_					,				features=lowerCamelCase_					,				cache_dir=lowerCamelCase_					,				keep_in_memory=lowerCamelCase_					,				streaming=lowerCamelCase_					,				num_proc=lowerCamelCase_					,				**lowerCamelCase_					,				)
       UpperCamelCase										=  path_or_paths if isinstance(lowerCamelCase_					,				lowerCamelCase_) else {self.split: path_or_paths}
       UpperCamelCase										=  Csv(
           cache_dir=lowerCamelCase_					,				data_files=lowerCamelCase_					,				features=lowerCamelCase_					,				**lowerCamelCase_					,				)







   def      UpperCAmelCase__ (		self)							->      Optional[int]:







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

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

class 							snake_case_ :







   """simple docstring"""




   def __init__(		self					,				lowerCamelCase_					,				lowerCamelCase_					,				lowerCamelCase_ = None					,				lowerCamelCase_ = None					,				**lowerCamelCase_					,				)							->      Optional[Any]:







       if num_proc is not None and num_proc <= 0:
           raise ValueError(F'num_proc {num_proc} must be an integer > 0.')

       UpperCamelCase										=  dataset
       UpperCamelCase										=  path_or_buf
       UpperCamelCase										=  batch_size if batch_size else config.DEFAULT_MAX_BATCH_SIZE
       UpperCamelCase										=  num_proc
       UpperCamelCase										=  "utf-8"
       UpperCamelCase										=  to_csv_kwargs







   def      UpperCAmelCase__ (		self)							->      str:
       UpperCamelCase										=  self.to_csv_kwargs.pop('''path_or_buf'''					,				lowerCamelCase_)
       UpperCamelCase										=  self.to_csv_kwargs.pop('''header'''					,				lowerCamelCase_)
       UpperCamelCase										=  self.to_csv_kwargs.pop('''index'''					,				lowerCamelCase_)

       if isinstance(self.path_or_buf					,				(str, bytes, os.PathLike)):
           with open(self.path_or_buf					,				'''wb+''') as buffer:
               UpperCamelCase										=  self._write(file_obj=lowerCamelCase_					,				header=lowerCamelCase_					,				index=lowerCamelCase_					,				**self.to_csv_kwargs)
       else:
           UpperCamelCase										=  self._write(file_obj=self.path_or_buf					,				header=lowerCamelCase_					,				index=lowerCamelCase_					,				**self.to_csv_kwargs)
       return written







   def      UpperCAmelCase__ (		self					,				lowerCamelCase_)							->      int:
       UpperCamelCase										=  args

       UpperCamelCase										=  query_table(
           table=self.dataset.data					,				key=slice(lowerCamelCase_					,				offset + self.batch_size)					,				indices=self.dataset._indices					,				)
       UpperCamelCase										=  batch.to_pandas().to_csv(
           path_or_buf=lowerCamelCase_					,				header=header if (offset == 0) else False					,				index=lowerCamelCase_					,				**lowerCamelCase_)
       return csv_str.encode(self.encoding)







   def      UpperCAmelCase__ (		self					,				lowerCamelCase_					,				lowerCamelCase_					,				lowerCamelCase_					,				**lowerCamelCase_)							->      Any:
       UpperCamelCase										=  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 CSV from Arrow format'''					,				):
               UpperCamelCase										=  self._batch_csv((offset, header, index, to_csv_kwargs))
               written += file_obj.write(lowerCamelCase_)

       else:
           UpperCamelCase										=  len(self.dataset), self.batch_size
           with multiprocessing.Pool(self.num_proc) as pool:
               for csv_str in logging.tqdm(
                   pool.imap(
                       self._batch_csv					,				[(offset, header, index, to_csv_kwargs) for offset in range(0					,				lowerCamelCase_					,				lowerCamelCase_)]					,				)					,				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 CSV from Arrow format'''					,				):
                   written += file_obj.write(lowerCamelCase_)

       return written





"""simple docstring"""







import os
from string import ascii_letters

SCREAMING_SNAKE_CASE_      =					ascii_letters + ' \t\n'





def     __snake_case   (							):


    """simple docstring"""







    UpperCamelCase										=  os.path.split(os.path.realpath(_lowercase						)						)
    UpperCamelCase										=  {}
    with open(path[0] + '''/dictionary.txt'''						) as dictionary_file:
        for word in dictionary_file.read().split('''\n'''						):
            UpperCamelCase										=  None
    return english_words


SCREAMING_SNAKE_CASE_      =					load_dictionary()





def     __snake_case   (							_lowercase						):


    """simple docstring"""







    UpperCamelCase										=  message.upper()
    UpperCamelCase										=  remove_non_letters(_lowercase						)
    UpperCamelCase										=  message.split()
    UpperCamelCase										=  len([word for word in possible_words if word in ENGLISH_WORDS]						)
    return float(_lowercase						) / len(_lowercase						)





def     __snake_case   (							_lowercase						):


    """simple docstring"""







    return "".join(symbol for symbol in message if symbol in LETTERS_AND_SPACE						)





def     __snake_case   (							_lowercase ,_lowercase = 20 ,_lowercase = 85						):


    """simple docstring"""







    UpperCamelCase										=  get_english_count(_lowercase						) * 100 >= word_percentage
    UpperCamelCase										=  len(remove_non_letters(_lowercase						)						)
    UpperCamelCase										=  (float(_lowercase						) / len(_lowercase						)) * 100
    UpperCamelCase										=  message_letters_percentage >= letter_percentage
    return words_match and letters_match


if __name__ == "__main__":
  import doctest

  doctest.testmod()