



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


UpperCAmelCase_ ,UpperCAmelCase_ ,UpperCAmelCase_		 =					False, False, False


@dataclass
class 	lowerCamelCase__	:



 """simple docstring"""

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

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

 def     snake_case_      (    self					:					Any			,						__lowerCAmelCase					:					Union[str, bytes, dict]      )   ->	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
       _A      =       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!)
             _A      =       np.frombuffer(value['''bytes''']			,						dtype=np.intaa      ).astype(np.floataa      ) / 3_27_67
          else:
             _A      =       np.memmap(value['''path''']			,						dtype='''h'''			,						mode='''r'''      ).astype(np.floataa      ) / 3_27_67

          _A      =       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     snake_case_      (    self					:					Union[str, Any]			,						__lowerCAmelCase					:					dict			,						__lowerCAmelCase					:					Optional[Dict[str, Union[str, bool, None]]] = None      )   ->	dict:
    if not self.decode:
       raise RuntimeError('''Decoding is disabled for this feature. Please use Audio(decode=True) instead.'''      )

    _A  ,    _A      =       (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

    _A      =       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:
       _A      =       token_per_repo_id or {}
       _A      =       path.split('''::'''      )[-1]
       try:
          _A      =       string_to_dict(__lowerCAmelCase			,						config.HUB_DATASETS_URL      )['''repo_id''']
          _A      =       token_per_repo_id[repo_id]
       except (ValueError, KeyError):
          _A      =       None

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

    else:
       _A  ,    _A      =       sf.read(__lowerCAmelCase      )

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

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

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

 def     snake_case_      (    self					:					Optional[Any]			,						__lowerCAmelCase					:					pa.StructArray      )   ->	pa.StructArray:

    @no_op_if_value_is_null
    def path_to_bytes(__lowerCAmelCase					:					Union[str, Any]      ):
       with xopen(__lowerCAmelCase			,						'''rb'''      ) as f:
          _A      =       f.read()
       return bytes_

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








UpperCAmelCase_		 =					2_5_6
# Modulus to hash a string
UpperCAmelCase_		 =					1_0_0_0_0_0_3

def 	SCREAMING_SNAKE_CASE_							(	_snake_case	:str	,   _snake_case	:str				)  ->     bool:
   _A      =       len(_snake_case				)
   _A      =       len(_snake_case				)
   if p_len > t_len:
      return False

   _A      =       0
   _A      =       0
   _A      =       1

   # Calculating the hash of pattern and substring of text
   for i in range(_snake_case				):
      _A      =       (ord(pattern[i]				) + p_hash * alphabet_size) % modulus
      _A      =       (ord(text[i]				) + text_hash * alphabet_size) % modulus
      if i == p_len - 1:
         continue
      _A      =       (modulus_power * alphabet_size) % modulus

   for i in range(0	,   t_len - p_len + 1				):
      if text_hash == p_hash and text[i : i + p_len] == pattern:
         return True
      if i == t_len - p_len:
         continue
      # Calculate the https://en.wikipedia.org/wiki/Rolling_hash
      _A      =       (
          (text_hash - ord(text[i]				) * modulus_power) * alphabet_size
          + ord(text[i + p_len]				)
      ) % modulus
   return False

def 	SCREAMING_SNAKE_CASE_							(	)  ->     None:
   _A      =       '''abc1abc12'''
   _A      =       '''alskfjaldsabc1abc1abc12k23adsfabcabc'''
   _A      =       '''alskfjaldsk23adsfabcabc'''
   assert rabin_karp(_snake_case	,   _snake_case				) and not rabin_karp(_snake_case	,   _snake_case				)

   # Test 2)
   _A      =       '''ABABX'''
   _A      =       '''ABABZABABYABABX'''
   assert rabin_karp(_snake_case	,   _snake_case				)

   # Test 3)
   _A      =       '''AAAB'''
   _A      =       '''ABAAAAAB'''
   assert rabin_karp(_snake_case	,   _snake_case				)

   # Test 4)
   _A      =       '''abcdabcy'''
   _A      =       '''abcxabcdabxabcdabcdabcy'''
   assert rabin_karp(_snake_case	,   _snake_case				)

   # Test 5)
   _A      =       '''Lü'''
   _A      =       '''Lüsai'''
   assert rabin_karp(_snake_case	,   _snake_case				)
   _A      =       '''Lue'''
   assert not rabin_karp(_snake_case	,   _snake_case				)
   print('''Success.'''				)


if __name__ == "__main__":
   test_rabin_karp()



