
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      :				Any          = False, False, False


@dataclass
class        lowercase      :
  __lowercase : List[Any]			  =       None
  __lowercase : Tuple			  =       True
  __lowercase : Any			  =       True
  __lowercase : Union[str, Any]			  =       None
  # Automatically constructed
  __lowercase : int			  =       "dict"
  __lowercase : int			  =       pa.struct({"bytes": pa.binary(), "path": pa.string()}     )
  __lowercase : Tuple			  =       field(default="Audio"						,     init=lowercase__						,     repr=lowercase__     )



  def __call__(				self )						->      Tuple:
    """simple docstring"""
    return self.pa_type



  def __UpperCamelCase				(				self       ,   A_ )						->      Optional[int]:
    """simple docstring"""
    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(UpperCAmelCase__       ,   UpperCAmelCase__ ):
      return {"bytes": None, "path": value}
    elif isinstance(UpperCAmelCase__       ,   UpperCAmelCase__ ):
      return {"bytes": value, "path": None}
    elif "array" in value:
      # convert the audio array to wav bytes
      UpperCamelCase						=  BytesIO()
      sf.write(UpperCAmelCase__       ,   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!)
          UpperCamelCase						=  np.frombuffer(value['bytes']       ,   dtype=np.intaa ).astype(np.floataa ) / 32_767
        else:
          UpperCamelCase						=  np.memmap(value['path']       ,   dtype='h'       ,   mode='r' ).astype(np.floataa ) / 32_767

        UpperCamelCase						=  BytesIO(bytes() )
        sf.write(UpperCAmelCase__       ,   UpperCAmelCase__       ,   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 )						->      Union[str, Any]:
    """simple docstring"""
    if not self.decode:
      raise RuntimeError('Decoding is disabled for this feature. Please use Audio(decode=True) instead.' )

    UpperCamelCase						=  (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

    UpperCamelCase						=  xsplitext(UpperCAmelCase__ )[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:
      UpperCamelCase						=  token_per_repo_id or {}
      UpperCamelCase						=  path.split('::' )[-1]
      try:
        UpperCamelCase						=  string_to_dict(UpperCAmelCase__       ,   config.HUB_DATASETS_URL )['''repo_id''']
        UpperCamelCase						=  token_per_repo_id[repo_id]
      except (ValueError, KeyError):
        UpperCamelCase						=  None

      with xopen(UpperCAmelCase__       ,   'rb'       ,   use_auth_token=UpperCAmelCase__ ) as f:
        UpperCamelCase						=  sf.read(UpperCAmelCase__ )

    else:
      UpperCamelCase						=  sf.read(UpperCAmelCase__ )

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

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



  def __UpperCamelCase				(				self )						->      str:
    """simple docstring"""
    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_ )						->      int:
    """simple docstring"""
    if pa.types.is_string(storage.type ):
      UpperCamelCase						=  pa.array([None] * len(UpperCAmelCase__ )       ,   type=pa.binary() )
      UpperCamelCase						=  pa.StructArray.from_arrays([bytes_array, storage]       ,   ['bytes', 'path']       ,   mask=storage.is_null() )
    elif pa.types.is_binary(storage.type ):
      UpperCamelCase						=  pa.array([None] * len(UpperCAmelCase__ )       ,   type=pa.string() )
      UpperCamelCase						=  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' ):
      UpperCamelCase						=  pa.array([Audio().encode_example(UpperCAmelCase__ ) 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:
        UpperCamelCase						=  storage.field('bytes' )
      else:
        UpperCamelCase						=  pa.array([None] * len(UpperCAmelCase__ )       ,   type=pa.binary() )
      if storage.type.get_field_index('path' ) >= 0:
        UpperCamelCase						=  storage.field('path' )
      else:
        UpperCamelCase						=  pa.array([None] * len(UpperCAmelCase__ )       ,   type=pa.string() )
      UpperCamelCase						=  pa.StructArray.from_arrays([bytes_array, path_array]       ,   ['bytes', 'path']       ,   mask=storage.is_null() )
    return array_cast(UpperCAmelCase__       ,   self.pa_type )



  def __UpperCamelCase				(				self       ,   A_ )						->      Union[str, Any]:
    """simple docstring"""

    @no_op_if_value_is_null
    def path_to_bytes(A_ ):
      with xopen(UpperCAmelCase__       ,   'rb' ) as f:
        UpperCamelCase						=  f.read()
      return bytes_

    UpperCamelCase						=  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()       ,   )
    UpperCamelCase						=  pa.array(
        [os.path.basename(UpperCAmelCase__ ) if path is not None else None for path in storage.field('path' ).to_pylist()]       ,   type=pa.string()       ,   )
    UpperCamelCase						=  pa.StructArray.from_arrays([bytes_array, path_array]       ,   ['bytes', 'path']       ,   mask=bytes_array.is_null() )
    return array_cast(UpperCAmelCase__       ,   self.pa_type )


import pytest

import datasets.config
from datasets.utils.info_utils import is_small_dataset


@pytest.mark.parametrize('dataset_size'					, [None, 400 * 2**20, 600 * 2**20]				)
@pytest.mark.parametrize('input_in_memory_max_size'					, ['default', 0, 100 * 2**20, 900 * 2**20]				)
def    A (      lowercase					, lowercase					, lowercase				)     ->						Union[str, Any]:
		'''simple docstring'''

		if input_in_memory_max_size != "default":
				monkeypatch.setattr(datasets.config					, 'IN_MEMORY_MAX_SIZE'					, lowercase				)
		UpperCamelCase						=  datasets.config.IN_MEMORY_MAX_SIZE
		if input_in_memory_max_size == "default":
				assert in_memory_max_size == 0
		else:
				assert in_memory_max_size == input_in_memory_max_size
		if dataset_size and in_memory_max_size:
				UpperCamelCase						=  dataset_size < in_memory_max_size
		else:
				UpperCamelCase						=  False
		UpperCamelCase						=  is_small_dataset(lowercase				)
		assert result == expected
