




import os
from typing import BinaryIO, Optional, Union

import numpy as np
import pyarrow.parquet as pq

from .. import Audio, Dataset, Features, Image, NamedSplit, Value, config
from ..features.features import FeatureType, _visit
from ..formatting import query_table
from ..packaged_modules import _PACKAGED_DATASETS_MODULES
from ..packaged_modules.parquet.parquet import Parquet
from ..utils import logging
from ..utils.typing import NestedDataStructureLike, PathLike
from .abc import AbstractDatasetReader




def 						SCREAMING_SNAKE_CASE__ (   lowercase					)  ->       Optional[int]:
   snake_case				:    List[Any]           =	np.inf

   def set_batch_size(lowercase					) -> None:
      nonlocal batch_size
      if isinstance(lowercase						,lowercase					):
         snake_case				:    Tuple           =	min(lowercase						,config.PARQUET_ROW_GROUP_SIZE_FOR_IMAGE_DATASETS					)
      elif isinstance(lowercase						,lowercase					):
         snake_case				:    List[str]           =	min(lowercase						,config.PARQUET_ROW_GROUP_SIZE_FOR_AUDIO_DATASETS					)
      elif isinstance(lowercase						,lowercase					) and feature.dtype == "binary":
         snake_case				:    str           =	min(lowercase						,config.PARQUET_ROW_GROUP_SIZE_FOR_BINARY_DATASETS					)

   _visit(lowercase						,lowercase					)

   return None if batch_size is np.inf else batch_size




class 						__lowercase		(UpperCamelCase__							):




      """simple docstring"""





      def __init__(				self    ,				A    ,				A = None    ,				A = None    ,				A = None    ,				A = False    ,				A = False    ,				A = None    ,				**A    ,				)		->    Any:
         super().__init__(
             A    ,				split=A    ,				features=A    ,				cache_dir=A    ,				keep_in_memory=A    ,				streaming=A    ,				num_proc=A    ,				**A    ,				)
         snake_case				:    Optional[Any]           =	path_or_paths if isinstance(A    ,				A     ) else {self.split: path_or_paths}
         snake_case				:    int           =	_PACKAGED_DATASETS_MODULES["""parquet"""][1]
         snake_case				:    Tuple           =	Parquet(
             cache_dir=A    ,				data_files=A    ,				features=A    ,				hash=A    ,				**A    ,				)

      def      UpperCAmelCase				(				self     )		->    Union[str, Any]:
         # Build iterable dataset
         if self.streaming:
            snake_case				:    Union[str, Any]           =	self.builder.as_streaming_dataset(split=self.split     )
         # Build regular (map-style) dataset
         else:
            snake_case				:    Optional[Any]           =	None
            snake_case				:    int           =	None
            snake_case				:    Optional[Any]           =	None
            snake_case				:    Union[str, Any]           =	None

            self.builder.download_and_prepare(
                download_config=A    ,				download_mode=A    ,				verification_mode=A    ,				base_path=A    ,				num_proc=self.num_proc    ,				)
            snake_case				:    List[Any]           =	self.builder.as_dataset(
                split=self.split    ,				verification_mode=A    ,				in_memory=self.keep_in_memory     )
         return dataset




class 						__lowercase		:




      """simple docstring"""





      def __init__(				self    ,				A    ,				A    ,				A = None    ,				**A    ,				)		->    Tuple:
         snake_case				:    str           =	dataset
         snake_case				:    Dict           =	path_or_buf
         snake_case				:    Tuple           =	batch_size or get_writer_batch_size(dataset.features     )
         snake_case				:    Dict           =	parquet_writer_kwargs

      def      UpperCAmelCase				(				self     )		->    int:
         snake_case				:    Dict           =	self.batch_size if self.batch_size else config.DEFAULT_MAX_BATCH_SIZE

         if isinstance(self.path_or_buf    ,				(str, bytes, os.PathLike)     ):
            with open(self.path_or_buf    ,				"""wb+"""     ) as buffer:
               snake_case				:    Any           =	self._write(file_obj=A    ,				batch_size=A    ,				**self.parquet_writer_kwargs     )
         else:
            snake_case				:    Union[str, Any]           =	self._write(file_obj=self.path_or_buf    ,				batch_size=A    ,				**self.parquet_writer_kwargs     )
         return written

      def      UpperCAmelCase				(				self    ,				A    ,				A    ,				**A     )		->    int:
         snake_case				:    Any           =	0
         snake_case				:    int           =	parquet_writer_kwargs.pop("""path_or_buf"""    ,				A     )
         snake_case				:    List[str]           =	self.dataset.features.arrow_schema

         snake_case				:    List[str]           =	pq.ParquetWriter(A    ,				schema=A    ,				**A     )

         for offset in logging.tqdm(
             range(0    ,				len(self.dataset     )    ,				A     )    ,				unit="""ba"""    ,				disable=not logging.is_progress_bar_enabled()    ,				desc="""Creating parquet from Arrow format"""    ,				):
            snake_case				:    Optional[int]           =	query_table(
                table=self.dataset._data    ,				key=slice(A    ,				offset + batch_size     )    ,				indices=self.dataset._indices if self.dataset._indices is not None else None    ,				)
            writer.write_table(A     )
            written += batch.nbytes
         writer.close()
         return written











import pytest
import requests

from datasets.utils.file_utils import http_head

from .utils import OfflineSimulationMode, RequestWouldHangIndefinitelyError, offline




@pytest.mark.integration
def 						SCREAMING_SNAKE_CASE__ (   )  ->       List[Any]:
   with offline(OfflineSimulationMode.CONNECTION_TIMES_OUT					):
      with pytest.raises(lowercase					):
         requests.request("""GET"""						,"""https://huggingface.co"""					)
      with pytest.raises(requests.exceptions.ConnectTimeout					):
         requests.request("""GET"""						,"""https://huggingface.co"""						,timeout=1.0					)




@pytest.mark.integration
def 						SCREAMING_SNAKE_CASE__ (   )  ->       Any:
   with offline(OfflineSimulationMode.CONNECTION_FAILS					):
      with pytest.raises(requests.exceptions.ConnectionError					):
         requests.request("""GET"""						,"""https://huggingface.co"""					)




def 						SCREAMING_SNAKE_CASE__ (   )  ->       int:
   with offline(OfflineSimulationMode.HF_DATASETS_OFFLINE_SET_TO_1					):
      with pytest.raises(lowercase					):
         http_head("""https://huggingface.co"""					)





