


'''simple docstring'''

import multiprocessing
import os
from typing import BinaryIO, Optional, Union

import fsspec

from .. import Dataset, Features, NamedSplit, config
from ..formatting import query_table
from ..packaged_modules.json.json import Json
from ..utils import logging
from ..utils.typing import NestedDataStructureLike, PathLike
from .abc import AbstractDatasetReader





class 	snake_case       (       snake_case__     ):





  """simple docstring"""




  def __init__(       self     ,    UpperCamelCase     ,    UpperCamelCase = None     ,    UpperCamelCase = None     ,    UpperCamelCase = None     ,    UpperCamelCase = False     ,    UpperCamelCase = False     ,    UpperCamelCase = None     ,    UpperCamelCase = None     ,    **UpperCamelCase     ,    ):







   """simple docstring"""
   super().__init__(
       _UpperCamelCase     ,    split=_UpperCamelCase     ,    features=_UpperCamelCase     ,    cache_dir=_UpperCamelCase     ,    keep_in_memory=_UpperCamelCase     ,    streaming=_UpperCamelCase     ,    num_proc=_UpperCamelCase     ,    **_UpperCamelCase     ,    )
   lowerCamelCase_						=    field
   lowerCamelCase_						=    path_or_paths if isinstance(_UpperCamelCase     ,    _UpperCamelCase	) else {self.split: path_or_paths}
   lowerCamelCase_						=    Json(
       cache_dir=_UpperCamelCase     ,    data_files=_UpperCamelCase     ,    features=_UpperCamelCase     ,    field=_UpperCamelCase     ,    **_UpperCamelCase     ,    )







  def     snake_case						(       self	):







   """simple docstring"""


   if self.streaming:
    lowerCamelCase_						=    self.builder.as_streaming_dataset(split=self.split	)
   # Build regular (map-style) dataset
   else:
    lowerCamelCase_						=    None
    lowerCamelCase_						=    None
    lowerCamelCase_						=    None
    lowerCamelCase_						=    None

    self.builder.download_and_prepare(
        download_config=_UpperCamelCase     ,    download_mode=_UpperCamelCase     ,    verification_mode=_UpperCamelCase     ,    base_path=_UpperCamelCase     ,    num_proc=self.num_proc     ,    )
    lowerCamelCase_						=    self.builder.as_dataset(
        split=self.split     ,    verification_mode=_UpperCamelCase     ,    in_memory=self.keep_in_memory	)
   return dataset





class 	snake_case       :





  """simple docstring"""




  def __init__(       self     ,    UpperCamelCase     ,    UpperCamelCase     ,    UpperCamelCase = None     ,    UpperCamelCase = None     ,    **UpperCamelCase     ,    ):







   """simple docstring"""


   if num_proc is not None and num_proc <= 0:
    raise ValueError(f'''num_proc {num_proc} must be an integer > 0.'''	)

   lowerCamelCase_						=    dataset
   lowerCamelCase_						=    path_or_buf
   lowerCamelCase_						=    batch_size if batch_size else config.DEFAULT_MAX_BATCH_SIZE
   lowerCamelCase_						=    num_proc
   lowerCamelCase_						=    "utf-8"
   lowerCamelCase_						=    to_json_kwargs






  def     snake_case						(       self	):







   """simple docstring"""
   lowerCamelCase_						=    self.to_json_kwargs.pop("path_or_buf"     ,    _UpperCamelCase	)
   lowerCamelCase_						=    self.to_json_kwargs.pop("orient"     ,    "records"	)
   lowerCamelCase_						=    self.to_json_kwargs.pop("lines"     ,    True if orient == "records" else False	)
   lowerCamelCase_						=    self.to_json_kwargs.pop("index"     ,    False if orient in ["split", "table"] else True	)
   lowerCamelCase_						=    self.to_json_kwargs.pop("compression"     ,    _UpperCamelCase	)

   if compression not in [None, "infer", "gzip", "bz2", "xz"]:
    raise NotImplementedError(f'''`datasets` currently does not support {compression} compression'''	)

   if isinstance(self.path_or_buf     ,    (str, bytes, os.PathLike)	):
    with fsspec.open(self.path_or_buf     ,    "wb"     ,    compression=_UpperCamelCase	) as buffer:
     lowerCamelCase_						=    self._write(file_obj=_UpperCamelCase     ,    orient=_UpperCamelCase     ,    lines=_UpperCamelCase     ,    index=_UpperCamelCase     ,    **self.to_json_kwargs	)
   else:
    if compression:
     raise NotImplementedError(
         f'''The compression parameter is not supported when writing to a buffer, but compression={compression}'''
         " was passed. Please provide a local path instead."	)
    lowerCamelCase_						=    self._write(
        file_obj=self.path_or_buf     ,    orient=_UpperCamelCase     ,    lines=_UpperCamelCase     ,    index=_UpperCamelCase     ,    **self.to_json_kwargs	)
   return written






  def     snake_case						(       self     ,    UpperCamelCase	):







   """simple docstring"""
   lowerCamelCase_					,lowerCamelCase_					,lowerCamelCase_					,lowerCamelCase_					,lowerCamelCase_						=    args

   lowerCamelCase_						=    query_table(
       table=self.dataset.data     ,    key=slice(_UpperCamelCase     ,    offset + self.batch_size	)     ,    indices=self.dataset._indices     ,    )
   lowerCamelCase_						=    batch.to_pandas().to_json(
       path_or_buf=_UpperCamelCase     ,    orient=_UpperCamelCase     ,    lines=_UpperCamelCase     ,    index=_UpperCamelCase     ,    **_UpperCamelCase	)
   if not json_str.endswith("\n"	):
    json_str += "\n"
   return json_str.encode(self.encoding	)







  def     snake_case						(       self     ,    UpperCamelCase     ,    UpperCamelCase     ,    UpperCamelCase     ,    UpperCamelCase     ,    **UpperCamelCase     ,    ):







   """simple docstring"""
   lowerCamelCase_						=    0

   if self.num_proc is None or self.num_proc == 1:
    for offset in logging.tqdm(
        range(0     ,    len(self.dataset	)     ,    self.batch_size	)     ,    unit="ba"     ,    disable=not logging.is_progress_bar_enabled()     ,    desc="Creating json from Arrow format"     ,    ):
     lowerCamelCase_						=    self._batch_json((offset, orient, lines, index, to_json_kwargs)	)
     written += file_obj.write(_UpperCamelCase	)
   else:
    lowerCamelCase_					,lowerCamelCase_						=    len(self.dataset	), self.batch_size
    with multiprocessing.Pool(self.num_proc	) as pool:
     for json_str in logging.tqdm(
         pool.imap(
             self._batch_json     ,    [(offset, orient, lines, index, to_json_kwargs) for offset in range(0     ,    _UpperCamelCase     ,    _UpperCamelCase	)]     ,    )     ,    total=(num_rows // batch_size) + 1 if num_rows % batch_size else num_rows // batch_size     ,    unit="ba"     ,    disable=not logging.is_progress_bar_enabled()     ,    desc="Creating json from Arrow format"     ,    ):
      written += file_obj.write(_UpperCamelCase	)

   return written






from __future__ import annotations

class     __snake_case    :
       """simple docstring"""







       def __init__(		self      , _UpperCamelCase      , _UpperCamelCase   )      ->							Tuple:






              """simple docstring"""


              __snake_case	,    __snake_case       	=							text, pattern
              __snake_case	,    __snake_case       	=							len(_UpperCamelCase   ), len(_UpperCamelCase   )


       def 			a		(		self      , _UpperCamelCase   )      ->							int:






              """simple docstring"""


              for i in range(self.patLen - 1      , -1      , -1   ):
                     if char == self.pattern[i]:
                            return i
              return -1


       def 			a		(		self      , _UpperCamelCase   )      ->							int:






              """simple docstring"""


              for i in range(self.patLen - 1      , -1      , -1   ):
                     if self.pattern[i] != self.text[current_pos + i]:
                            return current_pos + i
              return -1






       def 			a		(		self   )      ->							list[int]:






              """simple docstring"""


              __snake_case       	=							[]
              for i in range(self.textLen - self.patLen + 1   ):
                     __snake_case       	=							self.mismatch_in_text(_UpperCamelCase   )
                     if mismatch_index == -1:
                            positions.append(_UpperCamelCase   )
                     else:
                            __snake_case       	=							self.match_in_pattern(self.text[mismatch_index]   )
                            __snake_case       	=							(
                                mismatch_index - match_index
                            )  # shifting index lgtm [py/multiple-definition]
              return positions






UpperCamelCase__		 =     '''ABAABA'''
UpperCamelCase__		 =     '''AB'''
UpperCamelCase__		 =     BoyerMooreSearch(text, pattern)
UpperCamelCase__		 =     bms.bad_character_heuristic()

if len(positions) == 0:
    print('''No match found''')
else:
    print('''Pattern found in following positions: ''')
    print(positions)

