






"""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


lowerCAmelCase__						, lowerCAmelCase__						, lowerCAmelCase__    						=			False, False, False


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







						def __call__(    self							)		->							List[str]:
										return self.pa_type







						def 			A      (    self   ,				lowerCAmelCase_							)		->							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(__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
														_SCREAMING_SNAKE_CASE   :		str       		=    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!)
																						_SCREAMING_SNAKE_CASE   :		Any       		=    np.frombuffer(value['bytes']   ,				dtype=np.intaa							).astype(np.floataa							) / 3_2_7_6_7
																		else:
																						_SCREAMING_SNAKE_CASE   :		Dict       		=    np.memmap(value['path']   ,				dtype='h'   ,				mode='r'							).astype(np.floataa							) / 3_2_7_6_7

																		_SCREAMING_SNAKE_CASE   :		List[str]       		=    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 			A      (    self   ,				lowerCAmelCase_   ,				lowerCAmelCase_ = 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   :		List[Any]       		=    (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   :		Union[str, Any]       		=    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:
														_SCREAMING_SNAKE_CASE   :		Any       		=    token_per_repo_id or {}
														_SCREAMING_SNAKE_CASE   :		Dict       		=    path.split('::'							)[-1]
														try:
																		_SCREAMING_SNAKE_CASE   :		List[str]       		=    string_to_dict(__lowerCAmelCase   ,				config.HUB_DATASETS_URL							)['repo_id']
																		_SCREAMING_SNAKE_CASE   :		Tuple       		=    token_per_repo_id[repo_id]
														except (ValueError, KeyError):
																		_SCREAMING_SNAKE_CASE   :		List[str]       		=    None

														with xopen(__lowerCAmelCase   ,				'rb'   ,				use_auth_token=__lowerCAmelCase							) as f:
																		_SCREAMING_SNAKE_CASE		,						_SCREAMING_SNAKE_CASE   :		str       		=    sf.read(__lowerCAmelCase							)

										else:
														_SCREAMING_SNAKE_CASE		,						_SCREAMING_SNAKE_CASE   :		Dict       		=    sf.read(__lowerCAmelCase							)

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

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







						def 			A      (    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 			A      (    self   ,				lowerCAmelCase_							)		->							pa.StructArray:
										if pa.types.is_string(storage.type							):
														_SCREAMING_SNAKE_CASE   :		Any       		=    pa.array([None] * len(__lowerCAmelCase							)   ,				type=pa.binary()							)
														_SCREAMING_SNAKE_CASE   :		str       		=    pa.StructArray.from_arrays([bytes_array, storage]   ,				['bytes', 'path']   ,				mask=storage.is_null()							)
										elif pa.types.is_binary(storage.type							):
														_SCREAMING_SNAKE_CASE   :		int       		=    pa.array([None] * len(__lowerCAmelCase							)   ,				type=pa.string()							)
														_SCREAMING_SNAKE_CASE   :		Tuple       		=    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   :		Any       		=    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:
																		_SCREAMING_SNAKE_CASE   :		Optional[Any]       		=    storage.field('bytes'							)
														else:
																		_SCREAMING_SNAKE_CASE   :		str       		=    pa.array([None] * len(__lowerCAmelCase							)   ,				type=pa.binary()							)
														if storage.type.get_field_index('path'							) >= 0:
																		_SCREAMING_SNAKE_CASE   :		str       		=    storage.field('path'							)
														else:
																		_SCREAMING_SNAKE_CASE   :		int       		=    pa.array([None] * len(__lowerCAmelCase							)   ,				type=pa.string()							)
														_SCREAMING_SNAKE_CASE   :		Optional[Any]       		=    pa.StructArray.from_arrays([bytes_array, path_array]   ,				['bytes', 'path']   ,				mask=storage.is_null()							)
										return array_cast(__lowerCAmelCase   ,				self.pa_type							)







						def 			A      (    self   ,				lowerCAmelCase_							)		->							pa.StructArray:

										@no_op_if_value_is_null
										def path_to_bytes(lowerCAmelCase_							):
														with xopen(__lowerCAmelCase   ,				'rb'							) as f:
																		_SCREAMING_SNAKE_CASE   :		Any       		=    f.read()
														return bytes_

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






from __future__ import annotations

def 	SCREAMING_SNAKE_CASE_							(	_snake_case	:dict	,   _snake_case	:str				)  ->     set[str]:
   _A  ,    _A      =       set(_snake_case				), [start]

   while stack:
      _A      =       stack.pop()
      explored.add(_snake_case				)
      # Differences from BFS:
      # 1) pop last element instead of first one
      # 2) add adjacent elements to stack without exploring them
      for adj in reversed(graph[v]				):
         if adj not in explored:
            stack.append(_snake_case				)
   return explored


UpperCAmelCase_		 =					{
    """A""": ["""B""", """C""", """D"""],
    """B""": ["""A""", """D""", """E"""],
    """C""": ["""A""", """F"""],
    """D""": ["""B""", """D"""],
    """E""": ["""B""", """F"""],
    """F""": ["""C""", """E""", """G"""],
    """G""": ["""F"""],
}

if __name__ == "__main__":
   import doctest

   doctest.testmod()
   print(depth_first_search(G, """A"""))



