





import multiprocessing
import os
from typing import BinaryIO, Optional, Union

import fsspec

from .. import Dataset, Features, NamedSplit, config
from ..formatting import query_table
from ..packaged_modules.json.json import Json
from ..utils import logging
from ..utils.typing import NestedDataStructureLike, PathLike
from .abc import AbstractDatasetReader






class       __A					(					lowerCAmelCase				):

			'''simple docstring'''







			def __init__(					self ,						__lowerCAmelCase ,						__lowerCAmelCase = None ,						__lowerCAmelCase = None ,						__lowerCAmelCase = None ,						__lowerCAmelCase = False ,						__lowerCAmelCase = False ,						__lowerCAmelCase = None ,						__lowerCAmelCase = None ,						**__lowerCAmelCase ,						):



				'''simple docstring'''







				super().__init__(
				    __lowerCAmelCase ,						split=__lowerCAmelCase ,						features=__lowerCAmelCase ,						cache_dir=__lowerCAmelCase ,						keep_in_memory=__lowerCAmelCase ,						streaming=__lowerCAmelCase ,						num_proc=__lowerCAmelCase ,						**__lowerCAmelCase ,						)
				lowerCamelCase__              =	field
				lowerCamelCase__              =	path_or_paths if isinstance(__lowerCAmelCase ,						__lowerCAmelCase							) else {self.split: path_or_paths}
				lowerCamelCase__              =	Json(
				    cache_dir=__lowerCAmelCase ,						data_files=__lowerCAmelCase ,						features=__lowerCAmelCase ,						field=__lowerCAmelCase ,						**__lowerCAmelCase ,						)





			def 	__lowerCamelCase       (					self							):



				'''simple docstring'''







				if self.streaming:
					lowerCamelCase__              =	self.builder.as_streaming_dataset(split=self.split							)
				# Build regular (map-style) dataset
				else:
					lowerCamelCase__              =	None
					lowerCamelCase__              =	None
					lowerCamelCase__              =	None
					lowerCamelCase__              =	None

					self.builder.download_and_prepare(
					    download_config=__lowerCAmelCase ,						download_mode=__lowerCAmelCase ,						verification_mode=__lowerCAmelCase ,						base_path=__lowerCAmelCase ,						num_proc=self.num_proc ,						)
					lowerCamelCase__              =	self.builder.as_dataset(
					    split=self.split ,						verification_mode=__lowerCAmelCase ,						in_memory=self.keep_in_memory							)
				return dataset






class       __A					:

			'''simple docstring'''







			def __init__(					self ,						__lowerCAmelCase ,						__lowerCAmelCase ,						__lowerCAmelCase = None ,						__lowerCAmelCase = None ,						**__lowerCAmelCase ,						):



				'''simple docstring'''







				if num_proc is not None and num_proc <= 0:
					raise ValueError(F'num_proc {num_proc} must be an integer > 0.'							)

				lowerCamelCase__              =	dataset
				lowerCamelCase__              =	path_or_buf
				lowerCamelCase__              =	batch_size if batch_size else config.DEFAULT_MAX_BATCH_SIZE
				lowerCamelCase__              =	num_proc
				lowerCamelCase__              =	'''utf-8'''
				lowerCamelCase__              =	to_json_kwargs





			def 	__lowerCamelCase       (					self							):



				'''simple docstring'''







				lowerCamelCase__              =	self.to_json_kwargs.pop('''path_or_buf''' ,						__lowerCAmelCase							)
				lowerCamelCase__              =	self.to_json_kwargs.pop('''orient''' ,						'''records'''							)
				lowerCamelCase__              =	self.to_json_kwargs.pop('''lines''' ,						True if orient == '''records''' else False							)
				lowerCamelCase__              =	self.to_json_kwargs.pop('''index''' ,						False if orient in ['''split''', '''table'''] else True							)
				lowerCamelCase__              =	self.to_json_kwargs.pop('''compression''' ,						__lowerCAmelCase							)

				if compression not in [None, "infer", "gzip", "bz2", "xz"]:
					raise NotImplementedError(F'`datasets` currently does not support {compression} compression'							)

				if isinstance(self.path_or_buf ,						(str, bytes, os.PathLike)							):
					with fsspec.open(self.path_or_buf ,						'''wb''' ,						compression=__lowerCAmelCase							) as buffer:
						lowerCamelCase__              =	self._write(file_obj=__lowerCAmelCase ,						orient=__lowerCAmelCase ,						lines=__lowerCAmelCase ,						index=__lowerCAmelCase ,						**self.to_json_kwargs							)
				else:
					if compression:
						raise NotImplementedError(
						    F'The compression parameter is not supported when writing to a buffer, but compression={compression}'
						    ''' was passed. Please provide a local path instead.'''							)
					lowerCamelCase__              =	self._write(
					    file_obj=self.path_or_buf ,						orient=__lowerCAmelCase ,						lines=__lowerCAmelCase ,						index=__lowerCAmelCase ,						**self.to_json_kwargs							)
				return written





			def 	__lowerCamelCase       (					self ,						__lowerCAmelCase							):



				'''simple docstring'''







				lowerCamelCase__       ,			lowerCamelCase__       ,			lowerCamelCase__       ,			lowerCamelCase__       ,			lowerCamelCase__              =	args

				lowerCamelCase__              =	query_table(
				    table=self.dataset.data ,						key=slice(__lowerCAmelCase ,						offset + self.batch_size							) ,						indices=self.dataset._indices ,						)
				lowerCamelCase__              =	batch.to_pandas().to_json(
				    path_or_buf=__lowerCAmelCase ,						orient=__lowerCAmelCase ,						lines=__lowerCAmelCase ,						index=__lowerCAmelCase ,						**__lowerCAmelCase							)
				if not json_str.endswith('''\n'''							):
					json_str += "\n"
				return json_str.encode(self.encoding							)





			def 	__lowerCamelCase       (					self ,						__lowerCAmelCase ,						__lowerCAmelCase ,						__lowerCAmelCase ,						__lowerCAmelCase ,						**__lowerCAmelCase ,						):



				'''simple docstring'''







				lowerCamelCase__              =	0

				if self.num_proc is None or self.num_proc == 1:
					for offset in logging.tqdm(
					    range(0 ,						len(self.dataset							) ,						self.batch_size							) ,						unit='''ba''' ,						disable=not logging.is_progress_bar_enabled() ,						desc='''Creating json from Arrow format''' ,						):
						lowerCamelCase__              =	self._batch_json((offset, orient, lines, index, to_json_kwargs)							)
						written += file_obj.write(__lowerCAmelCase							)
				else:
					lowerCamelCase__       ,			lowerCamelCase__              =	len(self.dataset							), self.batch_size
					with multiprocessing.Pool(self.num_proc							) as pool:
						for json_str in logging.tqdm(
						    pool.imap(
						        self._batch_json ,						[(offset, orient, lines, index, to_json_kwargs) for offset in range(0 ,						__lowerCAmelCase ,						__lowerCAmelCase							)] ,						) ,						total=(num_rows // batch_size) + 1 if num_rows % batch_size else num_rows // batch_size ,						unit='''ba''' ,						disable=not logging.is_progress_bar_enabled() ,						desc='''Creating json from Arrow format''' ,						):
							written += file_obj.write(__lowerCAmelCase							)

				return written










import os
from collections import namedtuple

import pytest

from datasets import ClassLabel, Features, Sequence, Value
from datasets.commands.test import TestCommand
from datasets.info import DatasetInfo, DatasetInfosDict


_a						=   namedtuple(
    "_TestCommandArgs",
    [
        "dataset",
        "name",
        "cache_dir",
        "data_dir",
        "all_configs",
        "save_infos",
        "ignore_verifications",
        "force_redownload",
        "clear_cache",
    ],
    defaults=[None, None, None, False, False, False, False, False],
)





def lowerCAmelCase__(__snake_case ,__snake_case							)       ->   List[str]:







	'''simple docstring'''







	return (abs(source - target							) / target) < 0.0_1





@pytest.mark.integration
def lowerCAmelCase__(__snake_case							)       ->   Tuple:







	'''simple docstring'''







	lowerCamelCase__              =	_TestCommandArgs(dataset=__snake_case ,all_configs=__snake_case ,save_infos=__snake_case							)
	lowerCamelCase__              =	TestCommand(*__snake_case							)
	test_command.run()
	lowerCamelCase__              =	os.path.join(__snake_case ,'''README.md'''							)
	assert os.path.exists(__snake_case							)
	lowerCamelCase__              =	DatasetInfosDict.from_directory(__snake_case							)
	lowerCamelCase__              =	DatasetInfosDict(
	    {
	        '''default''': DatasetInfo(
	            features=Features(
	                {
	                    '''tokens''': Sequence(Value('''string'''							)							),
	                    '''ner_tags''': Sequence(
	                        ClassLabel(names=['''O''', '''B-PER''', '''I-PER''', '''B-ORG''', '''I-ORG''', '''B-LOC''', '''I-LOC''']							)							),
	                    '''langs''': Sequence(Value('''string'''							)							),
	                    '''spans''': Sequence(Value('''string'''							)							),
	                }							) ,splits=[
	                {
	                    '''name''': '''train''',
	                    '''num_bytes''': 2351563,
	                    '''num_examples''': 10000,
	                },
	                {
	                    '''name''': '''validation''',
	                    '''num_bytes''': 238418,
	                    '''num_examples''': 1000,
	                },
	            ] ,download_size=3940680 ,dataset_size=2589981 ,)
	    }							)
	assert dataset_infos.keys() == expected_dataset_infos.keys()
	for key in DatasetInfo._INCLUDED_INFO_IN_YAML:
		lowerCamelCase__       ,			lowerCamelCase__              =	getattr(dataset_infos['''default'''] ,__snake_case							), getattr(expected_dataset_infos['''default'''] ,__snake_case							)
		if key == "num_bytes":
			assert is_apercent_close(__snake_case ,__snake_case							)
		elif key == "splits":
			assert list(__snake_case							) == list(__snake_case							)
			for split in result:
				assert result[split].name == expected[split].name
				assert result[split].num_examples == expected[split].num_examples
				assert is_apercent_close(result[split].num_bytes ,expected[split].num_bytes							)
		else:
			result == expected



