



'''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


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


@dataclass
class 					snake_case			(datasets.BuilderConfig ):
       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     =       10 << 20  # 10MB
       lowerCAmelCase__	:Optional[bool]     =       None





class 					snake_case			(datasets.ArrowBasedBuilder ):
       lowerCAmelCase__	:Tuple     =       JsonConfig



       def 				_a   (					self   )	->				Union[str, Any]:
           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 				_a   (					self  ,UpperCAmelCase_   )	->				int:
           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 				_a   (					self  ,UpperCAmelCase_   )	->				pa.Table:
           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 				_a   (					self  ,UpperCAmelCase_   )	->				str:
           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









'''simple docstring'''





from __future__ import annotations




def 							lowerCamelCase	(					_snake_case	:    list[int]							):





    '''simple docstring'''


    return len(set(_snake_case							)							) == len(_snake_case							)


if __name__ == "__main__":
 import doctest

 doctest.testmod()




