



"""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_   						=   datasets.utils.logging.get_logger(__name__)
@dataclass
class        __A       (	datasets.BuilderConfig    ):







		'''simple docstring'''





		lowerCAmelCase			:					Optional[datasets.Features]   	=				None
		lowerCAmelCase			:					str   	=				"utf-8"
		lowerCAmelCase			:					Optional[str]   	=				None
		lowerCAmelCase			:					Optional[str]   	=				None
		lowerCAmelCase			:					bool   	=				True  # deprecated
		lowerCAmelCase			:					Optional[int]   	=				None  # deprecated
		lowerCAmelCase			:					int   	=				1_0 << 2_0  # 10MB
		lowerCAmelCase			:					Optional[bool]   	=				None





class        __A       (	datasets.ArrowBasedBuilder    ):







		'''simple docstring'''





		lowerCAmelCase			:					int   	=				JsonConfig







		def 					UpperCAmelCase    (	self						:  int						)					->		int:






				"""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__   :    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 					UpperCAmelCase    (	self						:  Dict			,_snake_case						:  Optional[int]						)					->		Dict:






				"""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__   :    int				=			dl_manager.download_and_extract(self.config.data_files						)
				if isinstance(_snake_case			,(str, list, tuple)						):
						lowercase__   :    Any				=			data_files
						if isinstance(_snake_case			,_snake_case						):
								lowercase__   :    Optional[Any]				=			[files]
						lowercase__   :    int				=			[dl_manager.iter_files(_snake_case						) for file in files]
						return [datasets.SplitGenerator(name=datasets.Split.TRAIN			,gen_kwargs={'''files''': files}						)]
				lowercase__   :    Optional[Any]				=			[]
				for split_name, files in data_files.items():
						if isinstance(_snake_case			,_snake_case						):
								lowercase__   :    Tuple				=			[files]
						lowercase__   :    str				=			[dl_manager.iter_files(_snake_case						) for file in files]
						splits.append(datasets.SplitGenerator(name=_snake_case			,gen_kwargs={'''files''': files}						)						)
				return splits







		def 					UpperCAmelCase    (	self						:  int			,_snake_case						:  Optional[int]						)					->		Optional[Any]:






				"""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__   :    List[Any]				=			self.config.features.arrow_schema.field(_snake_case						).type
								lowercase__   :    Optional[Any]				=			pa_table.append_column(_snake_case			,pa.array([None] * len(_snake_case						)			,type=_snake_case						)						)
						# more expensive cast to support nested structures with keys in a different order
						# allows str <-> int/float or str to Audio for example
						lowercase__   :    Tuple				=			table_cast(_snake_case			,self.config.features.arrow_schema						)
				return pa_table







		def 					UpperCAmelCase    (	self						:  str			,_snake_case						:  int						)					->		List[str]:






				"""simple docstring"""



				for file_idx, file in enumerate(itertools.chain.from_iterable(_snake_case						)						):
						# 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(_snake_case			,encoding=self.config.encoding			,errors=self.config.encoding_errors						) as f:
										lowercase__   :    Optional[Any]				=			json.load(_snake_case						)

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

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

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



def 	snake_case__			(    SCREAMING_SNAKE_CASE_		:    str = "The quick brown fox jumps over the lazy dog"	,     ):



     '''simple docstring'''





     lowercase__    :   str      =       set()

     # Replace all the whitespace in our sentence
     lowercase__    :   Tuple      =       input_str.replace(' '	,     ''			)
     for alpha in input_str:
          if "a" <= alpha.lower() <= "z":
               frequency.add(alpha.lower()			)
     return len(SCREAMING_SNAKE_CASE_			) == 26

def 	snake_case__			(    SCREAMING_SNAKE_CASE_		:    str = "The quick brown fox jumps over the lazy dog"	,     ):



     '''simple docstring'''





     lowercase__    :   Dict      =       [False] * 26
     for char in input_str:
          if char.islower():
               lowercase__    :   List[Any]      =       True
          elif char.isupper():
               lowercase__    :   Optional[Any]      =       True
     return all(SCREAMING_SNAKE_CASE_			)

def 	snake_case__			(    SCREAMING_SNAKE_CASE_		:    str = "The quick brown fox jumps over the lazy dog"	,     ):



     '''simple docstring'''





     return len({char for char in input_str.lower() if char.isalpha()}			) == 26

def 	snake_case__			(    ):



     '''simple docstring'''





     from timeit import timeit

     lowercase__    :   Union[str, Any]      =       'from __main__ import is_pangram, is_pangram_faster, is_pangram_fastest'
     print(timeit('is_pangram()'	,     setup=SCREAMING_SNAKE_CASE_			)			)
     print(timeit('is_pangram_faster()'	,     setup=SCREAMING_SNAKE_CASE_			)			)
     print(timeit('is_pangram_fastest()'	,     setup=SCREAMING_SNAKE_CASE_			)			)
     # 5.348480500048026, 2.6477354579837993, 1.8470395830227062
     # 5.036091582966037, 2.644472333951853,  1.8869528750656173


if __name__ == "__main__":
       import doctest

       doctest.testmod()
       benchmark()

