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 			UpperCamelCase					(			__lowercase			):

     '''simple docstring'''

     def __init__(       self					,					A_					,					A_ = None					,					A_ = None					,					A_ = None					,					A_ = False					,					A_ = False					,					A_ = None					,					**A_					,					)			->					int:






           """simple docstring"""
           super().__init__(
               A_					,					split=A_					,					features=A_					,					cache_dir=A_					,					keep_in_memory=A_					,					streaming=A_					,					num_proc=A_					,					**A_					,					)
           _lowerCamelCase           =					path_or_paths if isinstance(A_					,					A_    ) else {self.split: path_or_paths}
           _lowerCamelCase           =					Csv(
               cache_dir=A_					,					data_files=A_					,					features=A_					,					**A_					,					)





     def 		UpperCamelCase_    (       self    )			->					Optional[Any]:






           """simple docstring"""
           # Build iterable dataset
           if self.streaming:
                 _lowerCamelCase           =					self.builder.as_streaming_dataset(split=self.split    )
           # Build regular (map-style) dataset
           else:
                 _lowerCamelCase           =					None
                 _lowerCamelCase           =					None
                 _lowerCamelCase           =					None
                 _lowerCamelCase           =					None

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





class 			UpperCamelCase					:

     '''simple docstring'''

     def __init__(       self					,					A_					,					A_					,					A_ = None					,					A_ = None					,					**A_					,					)			->					List[str]:






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

           _lowerCamelCase           =					dataset
           _lowerCamelCase           =					path_or_buf
           _lowerCamelCase           =					batch_size if batch_size else config.DEFAULT_MAX_BATCH_SIZE
           _lowerCamelCase           =					num_proc
           _lowerCamelCase           =					'''utf-8'''
           _lowerCamelCase           =					to_csv_kwargs



     def 		UpperCamelCase_    (       self    )			->					int:






           """simple docstring"""
           _lowerCamelCase           =					self.to_csv_kwargs.pop('''path_or_buf'''					,					A_    )
           _lowerCamelCase           =					self.to_csv_kwargs.pop('''header'''					,					A_    )
           _lowerCamelCase           =					self.to_csv_kwargs.pop('''index'''					,					A_    )

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



     def 		UpperCamelCase_    (       self					,					A_    )			->					List[Any]:






           """simple docstring"""
           _lowerCamelCase     ,       _lowerCamelCase     ,       _lowerCamelCase     ,       _lowerCamelCase           =					args

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





     def 		UpperCamelCase_    (       self					,					A_					,					A_					,					A_					,					**A_    )			->					int:






           """simple docstring"""
           _lowerCamelCase           =					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'''					,					):
                       _lowerCamelCase           =					self._batch_csv((offset, header, index, to_csv_kwargs)    )
                       written += file_obj.write(A_    )

           else:
                 _lowerCamelCase     ,       _lowerCamelCase           =					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					,					A_					,					A_    )]					,					)					,					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(A_    )

           return written
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run

import sys
import warnings
from os.path import abspath, dirname, join


# allow having multiple repository checkouts and not needing to remember to rerun
# 'pip install -e .[dev]' when switching between checkouts and running tests.
snake_case__						      =			abspath(join(dirname(dirname(dirname(__file__))), 'src'))
sys.path.insert(1, git_repo_path)


# silence FutureWarning warnings in tests since often we can't act on them until
# they become normal warnings - i.e. the tests still need to test the current functionality
warnings.simplefilter(action='ignore', category=FutureWarning)
def    __magic_name__(	__UpperCAmelCase		)    ->     int:



      '''simple docstring'''

      from transformers.testing_utils import pytest_addoption_shared

      pytest_addoption_shared(__UpperCAmelCase		)




def    __magic_name__(	__UpperCAmelCase		)    ->     List[str]:



      '''simple docstring'''

      from transformers.testing_utils import pytest_terminal_summary_main

      _lowerCamelCase           =					terminalreporter.config.getoption('''--make-reports'''		)
      if make_reports:
            pytest_terminal_summary_main(__UpperCAmelCase			,    id=__UpperCAmelCase		)