


'''simple docstring'''

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__				( __A      ):







				"""simple docstring"""



				def __init__(self       ,			__lowercase       ,			__lowercase = None       ,			__lowercase = None       ,			__lowercase = None       ,			__lowercase = False       ,			__lowercase = False       ,			__lowercase = None       ,			__lowercase = None       ,			**__lowercase       ,			):
										super().__init__(
										    __lowercase       ,			split=__lowercase       ,			features=__lowercase       ,			cache_dir=__lowercase       ,			keep_in_memory=__lowercase       ,			streaming=__lowercase       ,			num_proc=__lowercase       ,			**__lowercase       ,			)
										__lowerCAmelCase							       =				field
										__lowerCAmelCase							       =				path_or_paths if isinstance(__lowercase       ,			__lowercase		) else {self.split: path_or_paths}
										__lowerCAmelCase							       =				Json(
										    cache_dir=__lowercase       ,			data_files=__lowercase       ,			features=__lowercase       ,			field=__lowercase       ,			**__lowercase       ,			)




				def 					_snake_case  (self		):
										# Build iterable dataset
										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=__lowercase       ,			download_mode=__lowercase       ,			verification_mode=__lowercase       ,			base_path=__lowercase       ,			num_proc=self.num_proc       ,			)
																__lowerCAmelCase							       =				self.builder.as_dataset(
																    split=self.split       ,			verification_mode=__lowercase       ,			in_memory=self.keep_in_memory		)
										return dataset


class       a__				:







				"""simple docstring"""



				def __init__(self       ,			__lowercase       ,			__lowercase       ,			__lowercase = None       ,			__lowercase = None       ,			**__lowercase       ,			):
										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 					_snake_case  (self		):
										__lowerCAmelCase							       =				self.to_json_kwargs.pop('''path_or_buf'''       ,			__lowercase		)
										__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'''       ,			__lowercase		)

										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=__lowercase		) as buffer:
																						__lowerCAmelCase							       =				self._write(file_obj=__lowercase       ,			orient=__lowercase       ,			lines=__lowercase       ,			index=__lowercase       ,			**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=__lowercase       ,			lines=__lowercase       ,			index=__lowercase       ,			**self.to_json_kwargs		)
										return written




				def 					_snake_case  (self       ,			__lowercase		):
										__lowerCAmelCase       ,					__lowerCAmelCase       ,					__lowerCAmelCase       ,					__lowerCAmelCase       ,					__lowerCAmelCase							       =				args

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




				def 					_snake_case  (self       ,			__lowercase       ,			__lowercase       ,			__lowercase       ,			__lowercase       ,			**__lowercase       ,			):
										__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(__lowercase		)
										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       ,			__lowercase       ,			__lowercase		)]       ,			)       ,			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(__lowercase		)

										return written





'''simple docstring'''

import json
import sys

def 							__magic_name__(						lowerCamelCase,				lowerCamelCase):
						with open(lowerCamelCase,				encoding='''utf-8''') as f:
												__lowerCAmelCase							       =				json.load(lowerCamelCase)

						__lowerCAmelCase							       =				['''<details>''', '''<summary>Show updated benchmarks!</summary>''', ''' ''']

						for benchmark_name in sorted(lowerCamelCase):
												__lowerCAmelCase							       =				results[benchmark_name]

												__lowerCAmelCase							       =				benchmark_name.split('''/''')[-1]
												output_md.append(F"""### Benchmark: {benchmark_file_name}""")

												__lowerCAmelCase							       =				'''| metric |'''
												__lowerCAmelCase							       =				'''|--------|'''
												__lowerCAmelCase							       =				'''| new / old (diff) |'''
												for metric_name in sorted(lowerCamelCase):
																		__lowerCAmelCase							       =				benchmark_res[metric_name]
																		__lowerCAmelCase							       =				metric_vals['''new''']
																		__lowerCAmelCase							       =				metric_vals.get('''old''',				lowerCamelCase)
																		__lowerCAmelCase							       =				metric_vals.get('''diff''',				lowerCamelCase)

																		__lowerCAmelCase							       =				F""" {new_val:f}""" if isinstance(lowerCamelCase,				(int, float)) else '''None'''

																		if old_val is not None:
																								val_str += F""" / {old_val:f}""" if isinstance(lowerCamelCase,				(int, float)) else "None"
																		if dif_val is not None:
																								val_str += F""" ({dif_val:f})""" if isinstance(lowerCamelCase,				(int, float)) else "None"

																		title += " " + metric_name + " |"
																		lines += "---|"
																		value += val_str + " |"

												output_md += [title, lines, value, " "]

						output_md.append('''</details>''')

						with open(lowerCamelCase,				'''w''',				encoding='''utf-8''') as f:
												f.writelines('''\n'''.join(lowerCamelCase))


if __name__ == "__main__":
	_UpperCAmelCase				: str							    =				sys.argv[1]
	_UpperCAmelCase				: Optional[Any]							    =				sys.argv[2]

	format_json_to_md(input_json_file, output_md_file)

