





'''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 :					List[str] 							=datasets.utils.logging.get_logger(__name__)
@dataclass
class 				a_       (    datasets.BuilderConfig							):
     __A								=      None
     __A								=      "utf-8"
     __A								=      None
     __A								=      None
     __A								=      True  # deprecated
     __A								=      None  # deprecated
     __A								=      10 << 20  # 10MB
     __A								=      None







class 				a_       (    datasets.ArrowBasedBuilder							):
     __A								=      JsonConfig





     def 							lowercase__				(			self		: Dict						):





        """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_      :Union[str, Any]         =			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 							lowercase__				(			self		: Union[str, Any]     ,				lowercase		: 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_      :Dict         =			dl_manager.download_and_extract(self.config.data_files						)
        if isinstance(_a     ,				(str, list, tuple)						):
           lowercase_      :Any         =			data_files
           if isinstance(_a     ,				_a						):
              lowercase_      :Any         =			[files]
           lowercase_      :int         =			[dl_manager.iter_files(_a						) for file in files]
           return [datasets.SplitGenerator(name=datasets.Split.TRAIN     ,				gen_kwargs={"files": files}						)]
        lowercase_      :str         =			[]
        for split_name, files in data_files.items():
           if isinstance(_a     ,				_a						):
              lowercase_      :int         =			[files]
           lowercase_      :List[Any]         =			[dl_manager.iter_files(_a						) for file in files]
           splits.append(datasets.SplitGenerator(name=_a     ,				gen_kwargs={"files": files}						)						)
        return splits





     def 							lowercase__				(			self		: str     ,				lowercase		: 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_      :Any         =			self.config.features.arrow_schema.field(_a						).type
              lowercase_      :str         =			pa_table.append_column(_a     ,				pa.array([None] * len(_a						)     ,				type=_a						)						)
           # 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(_a     ,				self.config.features.arrow_schema						)
        return pa_table







     def 							lowercase__				(			self		: Union[str, Any]     ,				lowercase		: Dict						):





        """simple docstring"""




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

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

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

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









'''simple docstring'''


import numpy as np
def 							UpperCAmelCase_  (						__lowerCamelCase : str     ,__lowerCamelCase : Optional[Any]     ,__lowerCamelCase : int     ,__lowerCamelCase : List[str]     ,__lowerCamelCase : List[Any]			):
   lowercase_      :Dict         =			int(np.ceil((x_end - xa) / h			)			)
   lowercase_      :Optional[int]         =			np.zeros((n + 1,)			)
   lowercase_      :Tuple         =			ya
   lowercase_      :List[str]         =			xa

   for k in range(__lowerCamelCase			):
      lowercase_      :Any         =			f(__lowerCamelCase     ,y[k]			)
      lowercase_      :Optional[Any]         =			f(x + 0.5 * h     ,y[k] + 0.5 * h * ka			)
      lowercase_      :Optional[Any]         =			f(x + 0.5 * h     ,y[k] + 0.5 * h * ka			)
      lowercase_      :Any         =			f(x + h     ,y[k] + h * ka			)
      lowercase_      :Tuple         =			y[k] + (1 / 6) * h * (ka + 2 * ka + 2 * ka + ka)
      x += h

   return y


if __name__ == "__main__":
 import doctest

 doctest.testmod()


