



import datetime
import platform
import subprocess
from typing import Optional, Tuple, Union

import numpy as np





def 							A     (					_UpperCAmelCase    :       bytes							,       _UpperCAmelCase    :       int   )    ->			np.array:







			'''simple docstring'''
			_UpperCAmelCase			=       F"{sampling_rate}"
			_UpperCAmelCase			=       '1'
			_UpperCAmelCase			=       'f32le'
			_UpperCAmelCase			=       [
			    'ffmpeg',
			    '-i',
			    'pipe:0',
			    '-ac',
			    ac,
			    '-ar',
			    ar,
			    '-f',
			    format_for_conversion,
			    '-hide_banner',
			    '-loglevel',
			    'quiet',
			    'pipe:1',
			]

			try:
						with subprocess.Popen(_UpperCAmelCase							,       stdin=subprocess.PIPE							,       stdout=subprocess.PIPE   ) as ffmpeg_process:
									_UpperCAmelCase			=       ffmpeg_process.communicate(_UpperCAmelCase   )
			except FileNotFoundError as error:
						raise ValueError('ffmpeg was not found but is required to load audio files from filename'   ) from error
			_UpperCAmelCase			=       output_stream[0]
			_UpperCAmelCase			=       np.frombuffer(_UpperCAmelCase							,       np.floataa   )
			if audio.shape[0] == 0:
						raise ValueError('Malformed soundfile'   )
			return audio





def 							A     (					_UpperCAmelCase    :       int							,       _UpperCAmelCase    :       float							,       _UpperCAmelCase    :       str = "f32le"							,       )    ->			Optional[Any]:







			'''simple docstring'''
			_UpperCAmelCase			=       F"{sampling_rate}"
			_UpperCAmelCase			=       '1'
			if format_for_conversion == "s16le":
						_UpperCAmelCase			=       2
			elif format_for_conversion == "f32le":
						_UpperCAmelCase			=       4
			else:
						raise ValueError(F"Unhandled format `{format_for_conversion}`. Please use `s16le` or `f32le`"   )

			_UpperCAmelCase			=       platform.system()
			if system == "Linux":
						_UpperCAmelCase			=       'alsa'
						_UpperCAmelCase			=       'default'
			elif system == "Darwin":
						_UpperCAmelCase			=       'avfoundation'
						_UpperCAmelCase			=       ':0'
			elif system == "Windows":
						_UpperCAmelCase			=       'dshow'
						_UpperCAmelCase			=       'default'

			_UpperCAmelCase			=       [
			    'ffmpeg',
			    '-f',
			    format_,
			    '-i',
			    input_,
			    '-ac',
			    ac,
			    '-ar',
			    ar,
			    '-f',
			    format_for_conversion,
			    '-fflags',
			    'nobuffer',
			    '-hide_banner',
			    '-loglevel',
			    'quiet',
			    'pipe:1',
			]
			_UpperCAmelCase			=       int(round(sampling_rate * chunk_length_s   )   ) * size_of_sample
			_UpperCAmelCase			=       _ffmpeg_stream(_UpperCAmelCase							,       _UpperCAmelCase   )
			for item in iterator:
						yield item





def 							A     (					_UpperCAmelCase    :       int							,       _UpperCAmelCase    :       float							,       _UpperCAmelCase    :       Optional[int] = None							,       _UpperCAmelCase    :       Optional[Union[Tuple[float, float], float]] = None							,       _UpperCAmelCase    :       str = "f32le"							,       )    ->			Union[str, Any]:







			'''simple docstring'''
			if stream_chunk_s is not None:
						_UpperCAmelCase			=       stream_chunk_s
			else:
						_UpperCAmelCase			=       chunk_length_s

			_UpperCAmelCase			=       ffmpeg_microphone(_UpperCAmelCase							,       _UpperCAmelCase							,       format_for_conversion=_UpperCAmelCase   )
			if format_for_conversion == "s16le":
						_UpperCAmelCase			=       np.intaa
						_UpperCAmelCase			=       2
			elif format_for_conversion == "f32le":
						_UpperCAmelCase			=       np.floataa
						_UpperCAmelCase			=       4
			else:
						raise ValueError(F"Unhandled format `{format_for_conversion}`. Please use `s16le` or `f32le`"   )

			if stride_length_s is None:
						_UpperCAmelCase			=       chunk_length_s / 6
			_UpperCAmelCase			=       int(round(sampling_rate * chunk_length_s   )   ) * size_of_sample
			if isinstance(_UpperCAmelCase							,       (int, float)   ):
						_UpperCAmelCase			=       [stride_length_s, stride_length_s]

			_UpperCAmelCase			=       int(round(sampling_rate * stride_length_s[0]   )   ) * size_of_sample
			_UpperCAmelCase			=       int(round(sampling_rate * stride_length_s[1]   )   ) * size_of_sample
			_UpperCAmelCase			=       datetime.datetime.now()
			_UpperCAmelCase			=       datetime.timedelta(seconds=_UpperCAmelCase   )
			for item in chunk_bytes_iter(_UpperCAmelCase							,       _UpperCAmelCase							,       stride=(stride_left, stride_right)							,       stream=_UpperCAmelCase   ):
						# Put everything back in numpy scale
						_UpperCAmelCase			=       np.frombuffer(item['raw']							,       dtype=_UpperCAmelCase   )
						_UpperCAmelCase			=       (
						    item['stride'][0] // size_of_sample,
						    item['stride'][1] // size_of_sample,
						)
						_UpperCAmelCase			=       sampling_rate
						audio_time += delta
						if datetime.datetime.now() > audio_time + 10 * delta:
									# We're late !! SKIP
									continue
						yield item





def 							A     (					_UpperCAmelCase    :       Optional[int]							,       _UpperCAmelCase    :       int							,       _UpperCAmelCase    :       Tuple[int, int]							,       _UpperCAmelCase    :       bool = False   )    ->			List[Any]:







			'''simple docstring'''
			_UpperCAmelCase			=       B''
			_UpperCAmelCase	,					_UpperCAmelCase			=       stride
			if stride_left + stride_right >= chunk_len:
						raise ValueError(
						    F"Stride needs to be strictly smaller than chunk_len: ({stride_left}, {stride_right}) vs {chunk_len}"   )
			_UpperCAmelCase			=       0
			for raw in iterator:
						acc += raw
						if stream and len(_UpperCAmelCase   ) < chunk_len:
									_UpperCAmelCase			=       (_stride_left, 0)
									yield {"raw": acc[:chunk_len], "stride": stride, "partial": True}
						else:
									while len(_UpperCAmelCase   ) >= chunk_len:
												# We are flushing the accumulator
												_UpperCAmelCase			=       (_stride_left, stride_right)
												_UpperCAmelCase			=       {'raw': acc[:chunk_len], 'stride': stride}
												if stream:
															_UpperCAmelCase			=       False
												yield item
												_UpperCAmelCase			=       stride_left
												_UpperCAmelCase			=       acc[chunk_len - stride_left - stride_right :]
    # Last chunk
			if len(_UpperCAmelCase   ) > stride_left:
						_UpperCAmelCase			=       {'raw': acc, 'stride': (_stride_left, 0)}
						if stream:
									_UpperCAmelCase			=       False
						yield item





def 							A     (					_UpperCAmelCase    :       List[Any]							,       _UpperCAmelCase    :       int   )    ->			List[Any]:







			'''simple docstring'''
			_UpperCAmelCase			=       2**24  # 16Mo
			try:
						with subprocess.Popen(_UpperCAmelCase							,       stdout=subprocess.PIPE							,       bufsize=_UpperCAmelCase   ) as ffmpeg_process:
									while True:
												_UpperCAmelCase			=       ffmpeg_process.stdout.read(_UpperCAmelCase   )
												if raw == b"":
															break
												yield raw
			except FileNotFoundError as error:
						raise ValueError('ffmpeg was not found but is required to stream audio files from filename'   ) from error





from __future__ import annotations

from itertools import permutations
from random import randint
from timeit import repeat





def 							A     (					)    ->			tuple[list[int], int]:







			'''simple docstring'''
			_UpperCAmelCase			=       [randint(-1_000							,       1_000   ) for i in range(10   )]
			_UpperCAmelCase			=       randint(-5_000							,       5_000   )
			return (arr, r)


UpperCAmelCase__       =	make_dataset()





def 							A     (					_UpperCAmelCase    :       list[int]							,       _UpperCAmelCase    :       int   )    ->			tuple[int, ...]:







			'''simple docstring'''
			for triplet in permutations(_UpperCAmelCase							,       3   ):
						if sum(_UpperCAmelCase   ) == target:
									return tuple(sorted(_UpperCAmelCase   )   )
			return (0, 0, 0)





def 							A     (					_UpperCAmelCase    :       list[int]							,       _UpperCAmelCase    :       int   )    ->			tuple[int, int, int]:







			'''simple docstring'''
			arr.sort()
			_UpperCAmelCase			=       len(_UpperCAmelCase   )
			for i in range(n - 1   ):
						_UpperCAmelCase	,					_UpperCAmelCase			=       i + 1, n - 1
						while left < right:
									if arr[i] + arr[left] + arr[right] == target:
												return (arr[i], arr[left], arr[right])
									elif arr[i] + arr[left] + arr[right] < target:
												left += 1
									elif arr[i] + arr[left] + arr[right] > target:
												right -= 1
			return (0, 0, 0)





def 							A     (					)    ->			tuple[float, float]:







			'''simple docstring'''
			_UpperCAmelCase			=       '\nfrom __main__ import dataset, triplet_sum1, triplet_sum2\n'
			_UpperCAmelCase			=       '\ntriplet_sum1(*dataset)\n'
			_UpperCAmelCase			=       '\ntriplet_sum2(*dataset)\n'
			_UpperCAmelCase			=       repeat(setup=_UpperCAmelCase							,       stmt=_UpperCAmelCase							,       repeat=5							,       number=10_000   )
			_UpperCAmelCase			=       repeat(setup=_UpperCAmelCase							,       stmt=_UpperCAmelCase							,       repeat=5							,       number=10_000   )
			return (min(_UpperCAmelCase   ), min(_UpperCAmelCase   ))


if __name__ == "__main__":
							from doctest import testmod

							testmod()
							UpperCAmelCase__       =	solution_times()
							print(f"""The time for naive implementation is {times[0]}.""")
							print(f"""The time for optimized implementation is {times[1]}.""")
