


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

import numpy as np


def      _snake_case						(						_snake_case				:			int ,   _snake_case				:			Dict			):
      lowerCAmelCase					:	List[Any]       =   f'''{sampling_rate}'''
      lowerCAmelCase					:	Union[str, Any]       =   "1"
      lowerCAmelCase					:	Optional[Any]       =   "f32le"
      lowerCAmelCase					:	str       =   [
          "ffmpeg",
          "-i",
          "pipe:0",
          "-ac",
          ac,
          "-ar",
          ar,
          "-f",
          format_for_conversion,
          "-hide_banner",
          "-loglevel",
          "quiet",
          "pipe:1",
      ]

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


def      _snake_case						(						_snake_case				:			str ,   _snake_case				:			Union[str, Any] ,   _snake_case				:			Optional[Any] = "f32le" ,   ):
      lowerCAmelCase					:	Union[str, Any]       =   f'''{sampling_rate}'''
      lowerCAmelCase					:	Union[str, Any]       =   "1"
      if format_for_conversion == "s16le":
            lowerCAmelCase					:	Tuple       =   2
      elif format_for_conversion == "f32le":
            lowerCAmelCase					:	List[str]       =   4
      else:
            raise ValueError(f'''Unhandled format `{format_for_conversion}`. Please use `s16le` or `f32le`'''			)

      lowerCAmelCase					:	Tuple       =   platform.system()
      if system == "Linux":
            lowerCAmelCase					:	Any       =   "alsa"
            lowerCAmelCase					:	str       =   "default"
      elif system == "Darwin":
            lowerCAmelCase					:	str       =   "avfoundation"
            lowerCAmelCase					:	Optional[Any]       =   ":0"
      elif system == "Windows":
            lowerCAmelCase					:	Dict       =   "dshow"
            lowerCAmelCase					:	Union[str, Any]       =   "default"

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


def      _snake_case						(						_snake_case				:			List[str] ,   _snake_case				:			Any ,   _snake_case				:			Union[str, Any] = None ,   _snake_case				:			Optional[Any] = None ,   _snake_case				:			Union[str, Any] = "f32le" ,   ):



      if stream_chunk_s is not None:
            lowerCAmelCase					:	Optional[Any]       =   stream_chunk_s
      else:
            lowerCAmelCase					:	Optional[Any]       =   chunk_length_s

      lowerCAmelCase					:	Union[str, Any]       =   ffmpeg_microphone(_snake_case ,   _snake_case ,   format_for_conversion=_snake_case			)
      if format_for_conversion == "s16le":
            lowerCAmelCase					:	str       =   np.intaa
            lowerCAmelCase					:	Union[str, Any]       =   2
      elif format_for_conversion == "f32le":
            lowerCAmelCase					:	Optional[Any]       =   np.floataa
            lowerCAmelCase					:	List[str]       =   4
      else:
            raise ValueError(f'''Unhandled format `{format_for_conversion}`. Please use `s16le` or `f32le`'''			)

      if stride_length_s is None:
            lowerCAmelCase					:	Optional[int]       =   chunk_length_s / 6
      lowerCAmelCase					:	Union[str, Any]       =   int(round(sampling_rate * chunk_length_s			)			) * size_of_sample
      if isinstance(_snake_case ,   (int, float)			):
            lowerCAmelCase					:	Optional[int]       =   [stride_length_s, stride_length_s]

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


def      _snake_case						(						_snake_case				:			List[str] ,   _snake_case				:			Dict ,   _snake_case				:			Any ,   _snake_case				:			int = False			):
      lowerCAmelCase					:	int       =   b""
      lowerCAmelCase					:	List[Any]       =   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}'''			)
      lowerCAmelCase					:	Optional[int]       =   0
      for raw in iterator:
            acc += raw
            if stream and len(_snake_case			) < chunk_len:
                  lowerCAmelCase					:	Union[str, Any]       =   (_stride_left, 0)
                  yield {"raw": acc[:chunk_len], "stride": stride, "partial": True}
            else:
                  while len(_snake_case			) >= chunk_len:
                        # We are flushing the accumulator
                        lowerCAmelCase					:	Optional[Any]       =   (_stride_left, stride_right)
                        lowerCAmelCase					:	Tuple       =   {"raw": acc[:chunk_len], "stride": stride}
                        if stream:
                              lowerCAmelCase					:	int       =   False
                        yield item
                        lowerCAmelCase					:	List[Any]       =   stride_left
                        lowerCAmelCase					:	str       =   acc[chunk_len - stride_left - stride_right :]
    # Last chunk
      if len(_snake_case			) > stride_left:
            lowerCAmelCase					:	int       =   {"raw": acc, "stride": (_stride_left, 0)}
            if stream:
                  lowerCAmelCase					:	Any       =   False
            yield item






def      _snake_case						(						_snake_case				:			Any ,   _snake_case				:			Optional[int]			):
      lowerCAmelCase					:	Optional[int]       =   2**24  # 16Mo
      try:
            with subprocess.Popen(_snake_case ,   stdout=subprocess.PIPE ,   bufsize=_snake_case			) as ffmpeg_process:
                  while True:
                        lowerCAmelCase					:	List[Any]       =   ffmpeg_process.stdout.read(_snake_case			)
                        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






"""simple docstring"""





import os
from collections import namedtuple

import pytest

from datasets import ClassLabel, Features, Sequence, Value
from datasets.commands.test import TestCommand
from datasets.info import DatasetInfo, DatasetInfosDict


snake_case__		:     Optional[Any]    				=				namedtuple(
    '''_TestCommandArgs''',
    [
        '''dataset''',
        '''name''',
        '''cache_dir''',
        '''data_dir''',
        '''all_configs''',
        '''save_infos''',
        '''ignore_verifications''',
        '''force_redownload''',
        '''clear_cache''',
    ],
    defaults=[None, None, None, False, False, False, False, False],
)


def      _snake_case						(						_snake_case				:			List[Any] ,   _snake_case				:			List[str]			):
      return (abs(source - target			) / target) < 0.01






@pytest.mark.integration
def      _snake_case						(						_snake_case				:			Any			):
      lowerCAmelCase					:	Union[str, Any]       =   _TestCommandArgs(dataset=_snake_case ,   all_configs=_snake_case ,   save_infos=_snake_case			)
      lowerCAmelCase					:	str       =   TestCommand(*_snake_case			)
      test_command.run()
      lowerCAmelCase					:	str       =   os.path.join(_snake_case ,   '''README.md'''			)
      assert os.path.exists(_snake_case			)
      lowerCAmelCase					:	Tuple       =   DatasetInfosDict.from_directory(_snake_case			)
      lowerCAmelCase					:	List[str]       =   DatasetInfosDict(
          {
              '''default''': DatasetInfo(
                  features=Features(
                      {
                          '''tokens''': Sequence(Value('''string'''			)			),
                          '''ner_tags''': Sequence(
                              ClassLabel(names=['''O''', '''B-PER''', '''I-PER''', '''B-ORG''', '''I-ORG''', '''B-LOC''', '''I-LOC''']			)			),
                          '''langs''': Sequence(Value('''string'''			)			),
                          '''spans''': Sequence(Value('''string'''			)			),
                      }			) ,   splits=[
                      {
                          '''name''': '''train''',
                          '''num_bytes''': 2351563,
                          '''num_examples''': 10000,
                      },
                      {
                          '''name''': '''validation''',
                          '''num_bytes''': 238418,
                          '''num_examples''': 1000,
                      },
                  ] ,   download_size=3940680 ,   dataset_size=2589981 ,   )
          }			)
      assert dataset_infos.keys() == expected_dataset_infos.keys()
      for key in DatasetInfo._INCLUDED_INFO_IN_YAML:
            lowerCAmelCase,      lowerCAmelCase					:	Union[str, Any]       =   getattr(dataset_infos['''default'''] ,   _snake_case			), getattr(expected_dataset_infos['''default'''] ,   _snake_case			)
            if key == "num_bytes":
                  assert is_apercent_close(_snake_case ,   _snake_case			)
            elif key == "splits":
                  assert list(_snake_case			) == list(_snake_case			)
                  for split in result:
                        assert result[split].name == expected[split].name
                        assert result[split].num_examples == expected[split].num_examples
                        assert is_apercent_close(result[split].num_bytes ,   expected[split].num_bytes			)
            else:
                  result == expected


