
'''simple docstring'''



import os
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, Optional, Union

import numpy as np
import pyarrow as pa

from .. import config
from ..download.streaming_download_manager import xopen, xsplitext
from ..table import array_cast
from ..utils.py_utils import no_op_if_value_is_null, string_to_dict


if TYPE_CHECKING:
     from .features import FeatureType


UpperCamelCase__							,      UpperCamelCase__							,      UpperCamelCase__      :		Union[str, Any]       							=  False, False, False

@dataclass
class    _a				:





       """simple docstring"""




       SCREAMING_SNAKE_CASE      =  None
       SCREAMING_SNAKE_CASE      =  True
       SCREAMING_SNAKE_CASE      =  True
       SCREAMING_SNAKE_CASE      =  None
       # Automatically constructed
       SCREAMING_SNAKE_CASE      =  "dict"
       SCREAMING_SNAKE_CASE      =  pa.struct({'bytes': pa.binary(), 'path': pa.string()})
       SCREAMING_SNAKE_CASE      =  field(default='Audio'  ,					init=_lowerCamelCase  ,					repr=_lowerCamelCase)






       def __call__(							self      )    ->			Dict:
          return self.pa_type






       def        UpperCamelCase				(							self       ,							A__      )    ->			dict:
          try:
             import soundfile as sf  # soundfile is a dependency of librosa, needed to decode audio files.
          except ImportError as err:
             raise ImportError("""To support encoding audio data, please install 'soundfile'."""      ) from err
          if isinstance(A__       ,							A__      ):
             return {"bytes": None, "path": value}
          elif isinstance(A__       ,							A__      ):
             return {"bytes": value, "path": None}
          elif "array" in value:
             # convert the audio array to wav bytes
             _SCREAMING_SNAKE_CASE      =				BytesIO()
             sf.write(A__       ,							value["""array"""]       ,							value["""sampling_rate"""]       ,							format="""wav"""      )
             return {"bytes": buffer.getvalue(), "path": None}
          elif value.get("""path"""      ) is not None and os.path.isfile(value["""path"""]      ):
             # we set "bytes": None to not duplicate the data if they're already available locally
             if value["path"].endswith("""pcm"""      ):
                # "PCM" only has raw audio bytes
                if value.get("""sampling_rate"""      ) is None:
                   # At least, If you want to convert "PCM-byte" to "WAV-byte", you have to know sampling rate
                   raise KeyError("""To use PCM files, please specify a 'sampling_rate' in Audio object"""      )
                if value.get("""bytes"""      ):
                   # If we already had PCM-byte, we don`t have to make "read file, make bytes" (just use it!)
                   _SCREAMING_SNAKE_CASE      =				np.frombuffer(value["""bytes"""]       ,							dtype=np.intaa      ).astype(np.floataa      ) / 3_27_67
                else:
                   _SCREAMING_SNAKE_CASE      =				np.memmap(value["""path"""]       ,							dtype="""h"""       ,							mode="""r"""      ).astype(np.floataa      ) / 3_27_67

                _SCREAMING_SNAKE_CASE      =				BytesIO(bytes()      )
                sf.write(A__       ,							A__       ,							value["""sampling_rate"""]       ,							format="""wav"""      )
                return {"bytes": buffer.getvalue(), "path": None}
             else:
                return {"bytes": None, "path": value.get("""path"""      )}
          elif value.get("""bytes"""      ) is not None or value.get("""path"""      ) is not None:
             # store the audio bytes, and path is used to infer the audio format using the file extension
             return {"bytes": value.get("""bytes"""      ), "path": value.get("""path"""      )}
          else:
             raise ValueError(
                 F"An audio sample should have one of 'path' or 'bytes' but they are missing or None in {value}."      )






       def        UpperCamelCase				(							self       ,							A__       ,							A__ = None      )    ->			dict:
          if not self.decode:
             raise RuntimeError("""Decoding is disabled for this feature. Please use Audio(decode=True) instead."""      )

          _SCREAMING_SNAKE_CASE ,							_SCREAMING_SNAKE_CASE      =				(value["""path"""], BytesIO(value["""bytes"""]      )) if value["""bytes"""] is not None else (value["""path"""], None)
          if path is None and file is None:
             raise ValueError(F"An audio sample should have one of 'path' or 'bytes' but both are None in {value}."      )

          try:
             import librosa
             import soundfile as sf
          except ImportError as err:
             raise ImportError("""To support decoding audio files, please install 'librosa' and 'soundfile'."""      ) from err

          _SCREAMING_SNAKE_CASE      =				xsplitext(A__      )[1][1:].lower() if path is not None else None
          if not config.IS_OPUS_SUPPORTED and audio_format == "opus":
             raise RuntimeError(
                 """Decoding 'opus' files requires system library 'libsndfile'>=1.0.31, """
                 """You can try to update `soundfile` python library: `pip install \"soundfile>=0.12.1\"`. """      )
          elif not config.IS_MP3_SUPPORTED and audio_format == "mp3":
             raise RuntimeError(
                 """Decoding 'mp3' files requires system library 'libsndfile'>=1.1.0, """
                 """You can try to update `soundfile` python library: `pip install \"soundfile>=0.12.1\"`. """      )

          if file is None:
             _SCREAMING_SNAKE_CASE      =				token_per_repo_id or {}
             _SCREAMING_SNAKE_CASE      =				path.split("""::"""      )[-1]
             try:
                _SCREAMING_SNAKE_CASE      =				string_to_dict(A__       ,							config.HUB_DATASETS_URL      )["""repo_id"""]
                _SCREAMING_SNAKE_CASE      =				token_per_repo_id[repo_id]
             except (ValueError, KeyError):
                _SCREAMING_SNAKE_CASE      =				None

             with xopen(A__       ,							"""rb"""       ,							use_auth_token=A__      ) as f:
                _SCREAMING_SNAKE_CASE ,							_SCREAMING_SNAKE_CASE      =				sf.read(A__      )

          else:
             _SCREAMING_SNAKE_CASE ,							_SCREAMING_SNAKE_CASE      =				sf.read(A__      )

          _SCREAMING_SNAKE_CASE      =				array.T
          if self.mono:
             _SCREAMING_SNAKE_CASE      =				librosa.to_mono(A__      )
          if self.sampling_rate and self.sampling_rate != sampling_rate:
             _SCREAMING_SNAKE_CASE      =				librosa.resample(A__       ,							orig_sr=A__       ,							target_sr=self.sampling_rate      )
             _SCREAMING_SNAKE_CASE      =				self.sampling_rate

          return {"path": path, "array": array, "sampling_rate": sampling_rate}






       def        UpperCamelCase				(							self      )    ->			Union["FeatureType", Dict[str, "FeatureType"]]:
          from .features import Value

          if self.decode:
             raise ValueError("""Cannot flatten a decoded Audio feature."""      )
          return {
              "bytes": Value("""binary"""      ),
              "path": Value("""string"""      ),
          }






       def        UpperCamelCase				(							self       ,							A__      )    ->			pa.StructArray:
          if pa.types.is_string(storage.type      ):
             _SCREAMING_SNAKE_CASE      =				pa.array([None] * len(A__      )       ,							type=pa.binary()      )
             _SCREAMING_SNAKE_CASE      =				pa.StructArray.from_arrays([bytes_array, storage]       ,							["""bytes""", """path"""]       ,							mask=storage.is_null()      )
          elif pa.types.is_binary(storage.type      ):
             _SCREAMING_SNAKE_CASE      =				pa.array([None] * len(A__      )       ,							type=pa.string()      )
             _SCREAMING_SNAKE_CASE      =				pa.StructArray.from_arrays([storage, path_array]       ,							["""bytes""", """path"""]       ,							mask=storage.is_null()      )
          elif pa.types.is_struct(storage.type      ) and storage.type.get_all_field_indices("""array"""      ):
             _SCREAMING_SNAKE_CASE      =				pa.array([Audio().encode_example(A__      ) if x is not None else None for x in storage.to_pylist()]      )
          elif pa.types.is_struct(storage.type      ):
             if storage.type.get_field_index("""bytes"""      ) >= 0:
                _SCREAMING_SNAKE_CASE      =				storage.field("""bytes"""      )
             else:
                _SCREAMING_SNAKE_CASE      =				pa.array([None] * len(A__      )       ,							type=pa.binary()      )
             if storage.type.get_field_index("""path"""      ) >= 0:
                _SCREAMING_SNAKE_CASE      =				storage.field("""path"""      )
             else:
                _SCREAMING_SNAKE_CASE      =				pa.array([None] * len(A__      )       ,							type=pa.string()      )
             _SCREAMING_SNAKE_CASE      =				pa.StructArray.from_arrays([bytes_array, path_array]       ,							["""bytes""", """path"""]       ,							mask=storage.is_null()      )
          return array_cast(A__       ,							self.pa_type      )






       def        UpperCamelCase				(							self       ,							A__      )    ->			pa.StructArray:

          @no_op_if_value_is_null
          def path_to_bytes(A__      ):
             with xopen(A__       ,							"""rb"""      ) as f:
                _SCREAMING_SNAKE_CASE      =				f.read()
             return bytes_

          _SCREAMING_SNAKE_CASE      =				pa.array(
              [
                  (path_to_bytes(x["""path"""]      ) if x["""bytes"""] is None else x["""bytes"""]) if x is not None else None
                  for x in storage.to_pylist()
              ]       ,							type=pa.binary()       ,							)
          _SCREAMING_SNAKE_CASE      =				pa.array(
              [os.path.basename(A__      ) if path is not None else None for path in storage.field("""path"""      ).to_pylist()]       ,							type=pa.string()       ,							)
          _SCREAMING_SNAKE_CASE      =				pa.StructArray.from_arrays([bytes_array, path_array]       ,							["""bytes""", """path"""]       ,							mask=bytes_array.is_null()      )
          return array_cast(A__       ,							self.pa_type      )








'''simple docstring'''



import pytest
import requests

from datasets.utils.file_utils import http_head

from .utils import OfflineSimulationMode, RequestWouldHangIndefinitelyError, offline
@pytest.mark.integration
def    lowerCAmelCase_	(				)     ->     List[Any]:




   """simple docstring"""
   with offline(OfflineSimulationMode.CONNECTION_TIMES_OUT						):
      with pytest.raises(SCREAMING_SNAKE_CASE_						):
         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    lowerCAmelCase_	(				)     ->     int:




   """simple docstring"""
   with offline(OfflineSimulationMode.CONNECTION_FAILS						):
      with pytest.raises(requests.exceptions.ConnectionError						):
         requests.request("""GET"""    ,      """https://huggingface.co"""						)







def    lowerCAmelCase_	(				)     ->     Optional[Any]:




   """simple docstring"""
   with offline(OfflineSimulationMode.HF_DATASETS_OFFLINE_SET_TO_1						):
      with pytest.raises(SCREAMING_SNAKE_CASE_						):
         http_head("""https://huggingface.co"""						)






