"""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


__A  =				False, False, False






@dataclass
class  _snake_case     :
						snake_case__			  =			None
						snake_case__			  =			True
						snake_case__			  =			True
						snake_case__			  =			None
						# Automatically constructed
						snake_case__			  =			"dict"
						snake_case__			  =			pa.struct({"bytes": pa.binary(), "path": pa.string()}		)
						snake_case__			  =			field(default="Audio"				, init=__UpperCAmelCase				, repr=__UpperCAmelCase		)






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






						def       lowerCamelCase__     (       self      :			Optional[Any]							,					UpperCAmelCase      :			Union[str, bytes, 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
																				__lowerCamelCase					:		List[Any]		   =     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!)
																																		__lowerCamelCase					:		Any		   =     np.frombuffer(value["bytes"]							,					dtype=np.intaa    ).astype(np.floataa    ) / 32767
																											else:
																																		__lowerCamelCase					:		List[str]		   =     np.memmap(value["path"]							,					dtype="h"							,					mode="r"    ).astype(np.floataa    ) / 32767

																											__lowerCamelCase					:		Optional[Any]		   =     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       lowerCamelCase__     (       self      :			Optional[Any]							,					UpperCAmelCase      :			dict							,					UpperCAmelCase      :			Optional[Dict[str, Union[str, bool, None]]] = None    ):







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

													__lowerCamelCase   ,  __lowerCamelCase					:		Union[str, 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

													__lowerCamelCase					:		int		   =     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:
																				__lowerCamelCase					:		List[Any]		   =     token_per_repo_id or {}
																				__lowerCamelCase					:		List[Any]		   =     path.split("::"    )[-1]
																				try:
																											__lowerCamelCase					:		Tuple		   =     string_to_dict(lowerCAmelCase_							,					config.HUB_DATASETS_URL    )["repo_id"]
																											__lowerCamelCase					:		str		   =     token_per_repo_id[repo_id]
																				except (ValueError, KeyError):
																											__lowerCamelCase					:		List[Any]		   =     None

																				with xopen(lowerCAmelCase_							,					"rb"							,					use_auth_token=lowerCAmelCase_    ) as f:
																											__lowerCamelCase   ,  __lowerCamelCase					:		List[str]		   =     sf.read(lowerCAmelCase_    )

													else:
																				__lowerCamelCase   ,  __lowerCamelCase					:		List[Any]		   =     sf.read(lowerCAmelCase_    )

													__lowerCamelCase					:		Any		   =     array.T
													if self.mono:
																				__lowerCamelCase					:		Tuple		   =     librosa.to_mono(lowerCAmelCase_    )
													if self.sampling_rate and self.sampling_rate != sampling_rate:
																				__lowerCamelCase					:		str		   =     librosa.resample(lowerCAmelCase_							,					orig_sr=lowerCAmelCase_							,					target_sr=self.sampling_rate    )
																				__lowerCamelCase					:		Tuple		   =     self.sampling_rate

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






						def       lowerCamelCase__     (       self      :			Optional[int]    ):
													from .features import Value

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






						def       lowerCamelCase__     (       self      :			Union[str, Any]							,					UpperCAmelCase      :			Union[pa.StringArray, pa.StructArray]    ):







													if pa.types.is_string(storage.type    ):
																				__lowerCamelCase					:		str		   =     pa.array([None] * len(lowerCAmelCase_    )							,					type=pa.binary()    )
																				__lowerCamelCase					:		List[str]		   =     pa.StructArray.from_arrays([bytes_array, storage]							,					["bytes", "path"]							,					mask=storage.is_null()    )
													elif pa.types.is_binary(storage.type    ):
																				__lowerCamelCase					:		Union[str, Any]		   =     pa.array([None] * len(lowerCAmelCase_    )							,					type=pa.string()    )
																				__lowerCamelCase					:		List[Any]		   =     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"    ):
																				__lowerCamelCase					:		Union[str, 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:
																											__lowerCamelCase					:		List[str]		   =     storage.field("bytes"    )
																				else:
																											__lowerCamelCase					:		int		   =     pa.array([None] * len(lowerCAmelCase_    )							,					type=pa.binary()    )
																				if storage.type.get_field_index("path"    ) >= 0:
																											__lowerCamelCase					:		Dict		   =     storage.field("path"    )
																				else:
																											__lowerCamelCase					:		Optional[Any]		   =     pa.array([None] * len(lowerCAmelCase_    )							,					type=pa.string()    )
																				__lowerCamelCase					:		Any		   =     pa.StructArray.from_arrays([bytes_array, path_array]							,					["bytes", "path"]							,					mask=storage.is_null()    )
													return array_cast(lowerCAmelCase_							,					self.pa_type    )







						def       lowerCamelCase__     (       self      :			Dict							,					UpperCAmelCase      :			pa.StructArray    ):







													@no_op_if_value_is_null
													def path_to_bytes(UpperCAmelCase      :			Optional[Any]    ):
																				with xopen(lowerCAmelCase_							,					"rb"    ) as f:
																											__lowerCamelCase					:		int		   =     f.read()
																				return bytes_

													__lowerCamelCase					:		Union[str, 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()							,					)
													__lowerCamelCase					:		List[Any]		   =     pa.array(
													    [os.path.basename(lowerCAmelCase_    ) if path is not None else None for path in storage.field("path"    ).to_pylist()]							,					type=pa.string()							,					)
													__lowerCamelCase					:		Dict		   =     pa.StructArray.from_arrays([bytes_array, path_array]							,					["bytes", "path"]							,					mask=bytes_array.is_null()    )
													return array_cast(lowerCAmelCase_							,					self.pa_type    )
"""simple docstring"""





import math


def    lowercase_   (   _lowerCamelCase:	int      ) ->      bool:



							'''simple docstring'''

							if 1 < number < 4:
														# 2 and 3 are primes
														return True
							elif number < 2 or number % 2 == 0 or number % 3 == 0:
														# Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
														return False

							# All primes number are in format of 6k +/- 1
							for i in range(5						,   int(math.sqrt(_lowerCamelCase      ) + 1      )						,   6      ):
														if number % i == 0 or number % (i + 2) == 0:
																					return False
							return True


def    lowercase_   (   _lowerCamelCase:	int = 10001      ) ->      int:



							'''simple docstring'''

							try:
														__lowerCamelCase					:		Optional[int]		   =     int(_lowerCamelCase      )
							except (TypeError, ValueError):
														raise TypeError("Parameter nth must be int or castable to int."      ) from None
							if nth <= 0:
														raise ValueError("Parameter nth must be greater than or equal to one."      )
							__lowerCamelCase					:		list[int]		   =     []
							__lowerCamelCase					:		Tuple		   =     2
							while len(_lowerCamelCase      ) < nth:
														if is_prime(_lowerCamelCase      ):
																					primes.append(_lowerCamelCase      )
																					num += 1
														else:
																					num += 1
							return primes[len(_lowerCamelCase      ) - 1]


if __name__ == "__main__":
				print(F"""{solution() = }""")