




'''simple docstring'''






from __future__ import annotations

import requests

_lowerCAmelCase      	=					set(
    '''approved_at_utc approved_by author_flair_background_color\nauthor_flair_css_class author_flair_richtext author_flair_template_id author_fullname\nauthor_premium can_mod_post category clicked content_categories created_utc downs\nedited gilded gildings hidden hide_score is_created_from_ads_ui is_meta\nis_original_content is_reddit_media_domain is_video link_flair_css_class\nlink_flair_richtext link_flair_text link_flair_text_color media_embed mod_reason_title\nname permalink pwls quarantine saved score secure_media secure_media_embed selftext\nsubreddit subreddit_name_prefixed subreddit_type thumbnail title top_awarded_type\ntotal_awards_received ups upvote_ratio url user_reports'''.split()
)

def 			__lowerCAmelCase					(    snake_case__					,      snake_case__ = 1					,      snake_case__ = "new"					,      snake_case__ = None						):
			__UpperCamelCase      :			Optional[Any]									=   wanted_data or []
			if invalid_search_terms := ", ".join(sorted(set(_lowerCAmelCase						) - valid_terms						)						):
						__UpperCamelCase      :			str									=   F"Invalid search term: {invalid_search_terms}"
						raise ValueError(_lowerCAmelCase						)
			__UpperCamelCase      :			Union[str, Any]									=   requests.get(
			    F"https://reddit.com/r/{subreddit}/{age}.json?limit={limit}"					,      headers={"User-agent": "A random string"}					,      )
			if response.status_code == 429:
						raise requests.HTTPError

			__UpperCamelCase      :			List[Any]									=   response.json()
			if not wanted_data:
						return {id_: data["data"]["children"][id_] for id_ in range(_lowerCAmelCase						)}

			__UpperCamelCase      :			Optional[int]									=   {}
			for id_ in range(_lowerCAmelCase						):
						__UpperCamelCase      :			Any									=   {
						    item: data['data']['children'][id_]['data'][item] for item in wanted_data
						}
			return data_dict


if __name__ == "__main__":
				# If you get Error 429, that means you are rate limited.Try after some time
				print(get_subreddit_data('''learnpython''', wanted_data=['''title''', '''url''', '''selftext''']))








'''simple docstring'''





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

import numpy as np

def        a_     (							_lowerCAmelCase       ,_lowerCAmelCase       )      ->      np.array:
  __lowerCamelCase       :       Any           = F'{sampling_rate}'
  __lowerCamelCase       :       List[str]           = '1'
  __lowerCamelCase       :       int           = 'f32le'
  __lowerCamelCase       :       Dict           = [
      'ffmpeg',
      '-i',
      'pipe:0',
      '-ac',
      ac,
      '-ar',
      ar,
      '-f',
      format_for_conversion,
      '-hide_banner',
      '-loglevel',
      'quiet',
      'pipe:1',
  ]

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

def        a_     (							_lowerCAmelCase       ,_lowerCAmelCase       ,_lowerCAmelCase = "f32le"       ,)      ->      Dict:
  __lowerCamelCase       :       Optional[Any]           = F'{sampling_rate}'
  __lowerCamelCase       :       Optional[int]           = '1'
  if format_for_conversion == "s16le":
    __lowerCamelCase       :       List[Any]           = 2
  elif format_for_conversion == "f32le":
    __lowerCamelCase       :       Tuple           = 4
  else:
    raise ValueError(F'Unhandled format `{format_for_conversion}`. Please use `s16le` or `f32le`'       )

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

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

def        a_     (							_lowerCAmelCase       ,_lowerCAmelCase       ,_lowerCAmelCase = None       ,_lowerCAmelCase = None       ,_lowerCAmelCase = "f32le"       ,)      ->      List[str]:
  if stream_chunk_s is not None:
    __lowerCamelCase       :       int           = stream_chunk_s
  else:
    __lowerCamelCase       :       List[Any]           = chunk_length_s

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

  if stride_length_s is None:
    __lowerCamelCase       :       Any           = chunk_length_s / 6
  __lowerCamelCase       :       List[str]           = int(round(sampling_rate * chunk_length_s       )       ) * size_of_sample
  if isinstance(_lowerCAmelCase       ,(int, float)       ):
    __lowerCamelCase       :       Tuple           = [stride_length_s, stride_length_s]

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

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


def        a_     (							_lowerCAmelCase       ,_lowerCAmelCase       )      ->      Tuple:
  __lowerCamelCase       :       int           = 2**24  # 16Mo
  try:
    with subprocess.Popen(_lowerCAmelCase       ,stdout=subprocess.PIPE       ,bufsize=_lowerCAmelCase       ) as ffmpeg_process:
      while True:
        __lowerCamelCase       :       Union[str, Any]           = ffmpeg_process.stdout.read(_lowerCAmelCase       )
        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






