



'''simple docstring'''




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							:Tuple       = datasets.utils.logging.get_logger(__name__)







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







class      _lowerCAmelCase							(      datasets.ArrowBasedBuilder			):
	__SCREAMING_SNAKE_CASE       :		List[Any]		      = JsonConfig


	def    _a     (self							):
				if self.config.block_size is not None:
							logger.warning("""The JSON loader parameter `block_size` is deprecated. Please use `chunksize` instead"""							)
							A_     :						Optional[int]     =					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    _a     (self	,				lowercase							):
				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}'							)
				A_     :						Optional[Any]     =					dl_manager.download_and_extract(self.config.data_files							)
				if isinstance(lowercase	,				(str, list, tuple)							):
							A_     :						str     =					data_files
							if isinstance(lowercase	,				lowercase							):
										A_     :						Optional[int]     =					[files]
							A_     :						List[Any]     =					[dl_manager.iter_files(lowercase							) for file in files]
							return [datasets.SplitGenerator(name=datasets.Split.TRAIN	,				gen_kwargs={"""files""": files}							)]
				A_     :						Any     =					[]
				for split_name, files in data_files.items():
							if isinstance(lowercase	,				lowercase							):
										A_     :						Optional[Any]     =					[files]
							A_     :						List[Any]     =					[dl_manager.iter_files(lowercase							) for file in files]
							splits.append(datasets.SplitGenerator(name=lowercase	,				gen_kwargs={"""files""": files}							)							)
				return splits


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


	def    _a     (self	,				lowercase							):
				for file_idx, file in enumerate(itertools.chain.from_iterable(lowercase							)							):
							# 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(lowercase	,				encoding=self.config.encoding	,				errors=self.config.encoding_errors							) as f:
													A_     :						str     =					json.load(lowercase							)

										# We keep only the field we are interested in
										A_     :						List[Any]     =					dataset[self.config.field]

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

							# If the file has one json object per line
							else:
										with open(lowercase	,				"""rb"""							) as f:
													A_     :						int     =					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
													A_     :						Union[str, Any]     =					max(self.config.chunksize // 32	,				16 << 10							)
													A_     :						int     =					(
													    self.config.encoding_errors if self.config.encoding_errors is not None else """strict"""
													)
													while True:
																A_     :						Any     =					f.read(self.config.chunksize							)
																if not batch:
																			break
																# Finish current line
																try:
																			batch += f.readline()
																except (AttributeError, io.UnsupportedOperation):
																			batch += readline(lowercase							)
																# PyArrow only accepts utf-8 encoded bytes
																if self.config.encoding != "utf-8":
																			A_     :						Optional[Any]     =					batch.decode(self.config.encoding	,				errors=lowercase							).encode("""utf-8"""							)
																try:
																			while True:
																						try:
																									A_     :						Optional[int]     =					paj.read_json(
																									    io.BytesIO(lowercase							)	,				read_options=paj.ReadOptions(block_size=lowercase							)							)
																									break
																						except (pa.ArrowInvalid, pa.ArrowNotImplementedError) as e:
																									if (
																									    isinstance(lowercase	,				pa.ArrowInvalid							)
																									    and "straddling" not in str(lowercase							)
																									    or block_size > len(lowercase							)
																									):
																												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(lowercase							)} 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(
																						    lowercase	,				encoding=self.config.encoding	,				errors=self.config.encoding_errors							) as f:
																									A_     :						Optional[Any]     =					json.load(lowercase							)
																			except json.JSONDecodeError:
																						logger.error(F'Failed to read file \'{file}\' with error {type(lowercase							)}: {e}'							)
																						raise e
																			# If possible, parse the file as a list of json objects and exit the loop
																			if isinstance(lowercase	,				lowercase							):  # list is the only sequence type supported in JSON
																						try:
																									A_     :						Dict     =					set().union(*[row.keys() for row in dataset]							)
																									A_     :						Optional[int]     =					{col: [row.get(lowercase							) for row in dataset] for col in keys}
																									A_     :						Tuple     =					pa.Table.from_pydict(lowercase							)
																						except (pa.ArrowInvalid, AttributeError) as e:
																									logger.error(F'Failed to read file \'{file}\' with error {type(lowercase							)}: {e}'							)
																									raise ValueError(F'Not able to read records in the JSON file at {file}.'							) from None
																						yield file_idx, self._cast_table(lowercase							)
																						break
																			else:
																						logger.error(F'Failed to read file \'{file}\' with error {type(lowercase							)}: {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(lowercase							)
																batch_idx += 1




'''simple docstring'''




lowerCamelCase							:Any       = {
    '''A''': '''.-''', '''B''': '''-...''', '''C''': '''-.-.''', '''D''': '''-..''', '''E''': '''.''', '''F''': '''..-.''', '''G''': '''--.''',
    '''H''': '''....''', '''I''': '''..''', '''J''': '''.---''', '''K''': '''-.-''', '''L''': '''.-..''', '''M''': '''--''', '''N''': '''-.''',
    '''O''': '''---''', '''P''': '''.--.''', '''Q''': '''--.-''', '''R''': '''.-.''', '''S''': '''...''', '''T''': '''-''', '''U''': '''..-''',
    '''V''': '''...-''', '''W''': '''.--''', '''X''': '''-..-''', '''Y''': '''-.--''', '''Z''': '''--..''', '''1''': '''.----''',
    '''2''': '''..---''', '''3''': '''...--''', '''4''': '''....-''', '''5''': '''.....''', '''6''': '''-....''', '''7''': '''--...''',
    '''8''': '''---..''', '''9''': '''----.''', '''0''': '''-----''', '''&''': '''.-...''', '''@''': '''.--.-.''',
    ''':''': '''---...''', ''',''': '''--..--''', '''.''': '''.-.-.-''', '''\'''': '''.----.''', '''"''': '''.-..-.''',
    '''?''': '''..--..''', '''/''': '''-..-.''', '''=''': '''-...-''', '''+''': '''.-.-.''', '''-''': '''-....-''',
    '''(''': '''-.--.''', ''')''': '''-.--.-''', '''!''': '''-.-.--''', ''' ''': '''/'''
}  # Exclamation mark is not in ITU-R recommendation
# fmt: on
lowerCamelCase							:Any       = {value: key for key, value in MORSE_CODE_DICT.items()}



def      a      (			lowerCamelCase__   ):
			'''simple docstring'''





			return " ".join(MORSE_CODE_DICT[char] for char in message.upper()   )



def      a      (			lowerCamelCase__   ):
			'''simple docstring'''





			return "".join(REVERSE_DICT[char] for char in message.split()   )



def      a      (			):
			'''simple docstring'''





			A_     :						List[str]     =					"""Morse code here!"""
			print(lowerCamelCase__   )
			A_     :						str     =					encrypt(lowerCamelCase__   )
			print(lowerCamelCase__   )
			A_     :						Dict     =					decrypt(lowerCamelCase__   )
			print(lowerCamelCase__   )


if __name__ == "__main__":
						main()