
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


A		: Tuple								=     False, False, False



@dataclass
class    a_ :
			a	:			Optional[int]					   =							None
			a	:			bool					   =							True
			a	:			bool					   =							True
			a	:			Optional[str]					   =							None
			# Automatically constructed
			a	:			ClassVar[str]					   =							"dict"
			a	:			ClassVar[Any]					   =							pa.struct({'''bytes''': pa.binary(), '''path''': pa.string()}    )
			a	:			str					   =							field(default='''Audio'''					,			init=_a					,			repr=_a    )






			def __call__(      self  ):
									return self.pa_type






			def    UpperCamelCase_				(      self				,			__UpperCamelCase  ):




									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(lowerCAmelCase__				,			lowerCAmelCase__  ):
															return {"bytes": None, "path": value}
									elif isinstance(lowerCAmelCase__				,			lowerCAmelCase__  ):
															return {"bytes": value, "path": None}
									elif "array" in value:
															# convert the audio array to wav bytes
															_lowercase					       =					BytesIO()
															sf.write(lowerCAmelCase__				,			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!)
																											_lowercase					       =					np.frombuffer(value["""bytes"""]				,			dtype=np.intaa  ).astype(np.floataa  ) / 32_767
																					else:
																											_lowercase					       =					np.memmap(value["""path"""]				,			dtype="""h"""				,			mode="""r"""  ).astype(np.floataa  ) / 32_767

																					_lowercase					       =					BytesIO(bytes()  )
																					sf.write(lowerCAmelCase__				,			lowerCAmelCase__				,			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				,			__UpperCamelCase				,			__UpperCamelCase = None  ):




									if not self.decode:
															raise RuntimeError("""Decoding is disabled for this feature. Please use Audio(decode=True) instead."""  )

									_lowercase       ,						_lowercase					       =					(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

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

															with xopen(lowerCAmelCase__				,			"""rb"""				,			use_auth_token=lowerCAmelCase__  ) as f:
																					_lowercase       ,						_lowercase					       =					sf.read(lowerCAmelCase__  )

									else:
															_lowercase       ,						_lowercase					       =					sf.read(lowerCAmelCase__  )

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

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






			def    UpperCamelCase_				(      self  ):
									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				,			__UpperCamelCase  ):




									if pa.types.is_string(storage.type  ):
															_lowercase					       =					pa.array([None] * len(lowerCAmelCase__  )				,			type=pa.binary()  )
															_lowercase					       =					pa.StructArray.from_arrays([bytes_array, storage]				,			["""bytes""", """path"""]				,			mask=storage.is_null()  )
									elif pa.types.is_binary(storage.type  ):
															_lowercase					       =					pa.array([None] * len(lowerCAmelCase__  )				,			type=pa.string()  )
															_lowercase					       =					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"""  ):
															_lowercase					       =					pa.array([Audio().encode_example(lowerCAmelCase__  ) 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:
																					_lowercase					       =					storage.field("""bytes"""  )
															else:
																					_lowercase					       =					pa.array([None] * len(lowerCAmelCase__  )				,			type=pa.binary()  )
															if storage.type.get_field_index("""path"""  ) >= 0:
																					_lowercase					       =					storage.field("""path"""  )
															else:
																					_lowercase					       =					pa.array([None] * len(lowerCAmelCase__  )				,			type=pa.string()  )
															_lowercase					       =					pa.StructArray.from_arrays([bytes_array, path_array]				,			["""bytes""", """path"""]				,			mask=storage.is_null()  )
									return array_cast(lowerCAmelCase__				,			self.pa_type  )






			def    UpperCamelCase_				(      self				,			__UpperCamelCase  ):




									@no_op_if_value_is_null
									def path_to_bytes(__UpperCamelCase  ):
															with xopen(lowerCAmelCase__				,			"""rb"""  ) as f:
																					_lowercase					       =					f.read()
															return bytes_

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






'''simple docstring'''

def    a__							(							lowercase   :	int,   lowercase   :	int,   lowercase   :	int )						->						float:





     """simple docstring"""

     _UpperCamelCase							       =			(num_of_terms / 2) * (2 * first_term + (num_of_terms - 1) * common_diff)
     # formula for sum of series
     return total







def    a__							(							)						->						Tuple:





     """simple docstring"""

     print(sum_of_series(1,   1,   10 ) )


if __name__ == "__main__":
   import doctest

   doctest.testmod()



