


import io
import itertools
import json
from dataclasses import dataclass
from typing import Optional

import pyarrow as pa
import pyarrow.json as paj

import datasets
from datasets.table import table_cast
from datasets.utils.file_utils import readline


lowerCAmelCase       =							datasets.utils.logging.get_logger(__name__)


@dataclass
class        _a							(			datasets.BuilderConfig			):
							_lowercase	:			Optional[datasets.Features]        = None
							_lowercase	:			str        = "utf-8"
							_lowercase	:			Optional[str]        = None
							_lowercase	:			Optional[str]        = None
							_lowercase	:			bool        = True  # deprecated
							_lowercase	:			Optional[int]        = None  # deprecated
							_lowercase	:			int        = 10 << 20  # 10MB
							_lowercase	:			Optional[bool]        = None


class        _a							(			datasets.ArrowBasedBuilder			):
							_lowercase	:			Optional[int]        = JsonConfig

							def       lowerCamelCase_ (							self:	Union[str, Any]							)			->   Union[str, Any]:





									"""simple docstring"""







									if self.config.block_size is not None:
											logger.warning('''The JSON loader parameter `block_size` is deprecated. Please use `chunksize` instead'''							)
											lowercase__            =      self.config.block_size
									if self.config.use_threads is not True:
											logger.warning(
											    '''The JSON loader parameter `use_threads` is deprecated and doesn\'t have any effect anymore.'''							)
									if self.config.newlines_in_values is not None:
											raise ValueError('''The JSON loader parameter `newlines_in_values` is no longer supported'''							)
									return datasets.DatasetInfo(features=self.config.features							)

							def       lowerCamelCase_ (							self:	Any    ,						UpperCamelCase_:	Optional[int]							)			->   Optional[int]:





									"""simple docstring"""







									if not self.config.data_files:
											raise ValueError(f'At least one data file must be specified, but got data_files={self.config.data_files}'							)
									lowercase__            =      dl_manager.download_and_extract(self.config.data_files							)
									if isinstance(UpperCamelCase_    ,						(str, list, tuple)							):
											lowercase__            =      data_files
											if isinstance(UpperCamelCase_    ,						UpperCamelCase_							):
													lowercase__            =      [files]
											lowercase__            =      [dl_manager.iter_files(UpperCamelCase_							) for file in files]
											return [datasets.SplitGenerator(name=datasets.Split.TRAIN    ,						gen_kwargs={'''files''': files}							)]
									lowercase__            =      []
									for split_name, files in data_files.items():
											if isinstance(UpperCamelCase_    ,						UpperCamelCase_							):
													lowercase__            =      [files]
											lowercase__            =      [dl_manager.iter_files(UpperCamelCase_							) for file in files]
											splits.append(datasets.SplitGenerator(name=UpperCamelCase_    ,						gen_kwargs={'''files''': files}							)							)
									return splits

							def       lowerCamelCase_ (							self:	Optional[int]    ,						UpperCamelCase_:	pa.Table							)			->   pa.Table:





									"""simple docstring"""







									if self.config.features is not None:
											# adding missing columns
											for column_name in set(self.config.features							) - set(pa_table.column_names							):
													lowercase__            =      self.config.features.arrow_schema.field(UpperCamelCase_							).type
													lowercase__            =      pa_table.append_column(UpperCamelCase_    ,						pa.array([None] * len(UpperCamelCase_							)    ,						type=UpperCamelCase_							)							)
											# more expensive cast to support nested structures with keys in a different order
											# allows str <-> int/float or str to Audio for example
											lowercase__            =      table_cast(UpperCamelCase_    ,						self.config.features.arrow_schema							)
									return pa_table


							def       lowerCamelCase_ (							self:	List[Any]    ,						UpperCamelCase_:	Union[str, Any]							)			->   str:





									"""simple docstring"""







									for file_idx, file in enumerate(itertools.chain.from_iterable(UpperCamelCase_							)							):
											# If the file is one json object and if we need to look at the list of items in one specific field
											if self.config.field is not None:
													with open(UpperCamelCase_    ,						encoding=self.config.encoding    ,						errors=self.config.encoding_errors							) as f:
															lowercase__            =      json.load(UpperCamelCase_							)

													# We keep only the field we are interested in
													lowercase__            =      dataset[self.config.field]

													# We accept two format: a list of dicts or a dict of lists
													if isinstance(UpperCamelCase_    ,						(list, tuple)							):
															lowercase__            =      set().union(*[row.keys() for row in dataset]							)
															lowercase__            =      {col: [row.get(UpperCamelCase_							) for row in dataset] for col in keys}
													else:
															lowercase__            =      dataset
													lowercase__            =      pa.Table.from_pydict(UpperCamelCase_							)
													yield file_idx, self._cast_table(UpperCamelCase_							)

											# If the file has one json object per line
											else:
													with open(UpperCamelCase_    ,						'''rb'''							) as f:
															lowercase__            =      0
															# Use block_size equal to the chunk size divided by 32 to leverage multithreading
															# Set a default minimum value of 16kB if the chunk size is really small
															lowercase__            =      max(self.config.chunksize // 32    ,						16 << 10							)
															lowercase__            =      (
															    self.config.encoding_errors if self.config.encoding_errors is not None else '''strict'''
															)
															while True:
																	lowercase__            =      f.read(self.config.chunksize							)
																	if not batch:
																			break
																	# Finish current line
																	try:
																			batch += f.readline()
																	except (AttributeError, io.UnsupportedOperation):
																			batch += readline(UpperCamelCase_							)
																	# PyArrow only accepts utf-8 encoded bytes
																	if self.config.encoding != "utf-8":
																			lowercase__            =      batch.decode(self.config.encoding    ,						errors=UpperCamelCase_							).encode('''utf-8'''							)
																	try:
																			while True:
																					try:
																							lowercase__            =      paj.read_json(
																							    io.BytesIO(UpperCamelCase_							)    ,						read_options=paj.ReadOptions(block_size=UpperCamelCase_							)							)
																							break
																					except (pa.ArrowInvalid, pa.ArrowNotImplementedError) as e:
																							if (
																							    isinstance(UpperCamelCase_    ,						pa.ArrowInvalid							)
																							    and "straddling" not in str(UpperCamelCase_							)
																							    or block_size > len(UpperCamelCase_							)
																							):
																									raise
																							else:
																									# Increase the block size in case it was too small.
																									# The block size will be reset for the next file.
																									logger.debug(
																									    f'Batch of {len(UpperCamelCase_							)} bytes couldn\'t be parsed with block_size={block_size}. Retrying with block_size={block_size * 2}.'							)
																									block_size *= 2
																	except pa.ArrowInvalid as e:
																			try:
																					with open(
																					    UpperCamelCase_    ,						encoding=self.config.encoding    ,						errors=self.config.encoding_errors							) as f:
																							lowercase__            =      json.load(UpperCamelCase_							)
																			except json.JSONDecodeError:
																					logger.error(f'Failed to read file \'{file}\' with error {type(UpperCamelCase_							)}: {e}'							)
																					raise e
																			# If possible, parse the file as a list of json objects and exit the loop
																			if isinstance(UpperCamelCase_    ,						UpperCamelCase_							):  # list is the only sequence type supported in JSON
																					try:
																							lowercase__            =      set().union(*[row.keys() for row in dataset]							)
																							lowercase__            =      {col: [row.get(UpperCamelCase_							) for row in dataset] for col in keys}
																							lowercase__            =      pa.Table.from_pydict(UpperCamelCase_							)
																					except (pa.ArrowInvalid, AttributeError) as e:
																							logger.error(f'Failed to read file \'{file}\' with error {type(UpperCamelCase_							)}: {e}'							)
																							raise ValueError(f'Not able to read records in the JSON file at {file}.'							) from None
																					yield file_idx, self._cast_table(UpperCamelCase_							)
																					break
																			else:
																					logger.error(f'Failed to read file \'{file}\' with error {type(UpperCamelCase_							)}: {e}'							)
																					raise ValueError(
																					    f'Not able to read records in the JSON file at {file}. '
																					    f'You should probably indicate the field of the JSON file containing your records. '
																					    f'This JSON file contain the following fields: {str(list(dataset.keys()							)							)}. '
																					    f'Select the correct one and provide it as `field=\'XXX\'` to the dataset loading method. '							) from None
                        # Uncomment for debugging (will print the Arrow table size and elements)
                        # logger.warning(f"pa_table: {pa_table} num rows: {pa_table.num_rows}")
                        # logger.warning('\n'.join(str(pa_table.slice(i, 1).to_pydict()) for i in range(pa_table.num_rows)))
																	yield (file_idx, batch_idx), self._cast_table(UpperCamelCase_							)
																	batch_idx += 1






from __future__ import annotations


class        _a							:

							def __init__(							self:	Union[str, Any]    ,						UpperCamelCase_:	str    ,						UpperCamelCase_:	str							)			->   List[Any]:





									"""simple docstring"""







									lowercase__     ,		lowercase__            =      text, pattern
									lowercase__     ,		lowercase__            =      len(UpperCamelCase_							), len(UpperCamelCase_							)

							def       lowerCamelCase_ (							self:	Optional[int]    ,						UpperCamelCase_:	str							)			->   int:





									"""simple docstring"""







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

							def       lowerCamelCase_ (							self:	Optional[int]    ,						UpperCamelCase_:	int							)			->   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       lowerCamelCase_ (							self:	List[Any]							)			->   list[int]:





									"""simple docstring"""







									lowercase__            =      []
									for i in range(self.textLen - self.patLen + 1							):
											lowercase__            =      self.mismatch_in_text(UpperCamelCase_							)
											if mismatch_index == -1:
													positions.append(UpperCamelCase_							)
											else:
													lowercase__            =      self.match_in_pattern(self.text[mismatch_index]							)
													lowercase__            =      (
													    mismatch_index - match_index
													)  # shifting index lgtm [py/multiple-definition]
									return positions
lowerCAmelCase       =							'ABAABA'
lowerCAmelCase       =							'AB'
lowerCAmelCase       =							BoyerMooreSearch(text, pattern)
lowerCAmelCase       =							bms.bad_character_heuristic()

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


