






import json
import sys





def 	lowerCAmelCase_		(lowercase__						:       List[Any]     ,					lowercase__						:       int       )		->    Union[str, Any]:


				'''simple docstring'''




				with open(lowercase__     ,					encoding='''utf-8'''       ) as f:
								lowerCAmelCase__      			=						json.load(lowercase__       )

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

				for benchmark_name in sorted(lowercase__       ):
								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(lowercase__       ):
												lowerCAmelCase__      			=						benchmark_res[metric_name]
												lowerCAmelCase__      			=						metric_vals['''new''']
												lowerCAmelCase__      			=						metric_vals.get('''old'''     ,					lowercase__       )
												lowerCAmelCase__      			=						metric_vals.get('''diff'''     ,					lowercase__       )

												lowerCAmelCase__      			=						f' {new_val:f}' if isinstance(lowercase__     ,					(int, float)       ) else '''None'''

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

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

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

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

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


if __name__ == "__main__":
			_UpperCAmelCase			:		Tuple   				=    sys.argv[1]
			_UpperCAmelCase			:		Dict   				=    sys.argv[2]

			format_json_to_md(input_json_file, output_md_file)













from typing import Optional

import pyspark

from .. import Features, NamedSplit
from ..download import DownloadMode
from ..packaged_modules.spark.spark import Spark
from .abc import AbstractDatasetReader
class  lowerCAmelCase_       (				snake_case__					):




							def __init__(   self     :   str ,							SCREAMING_SNAKE_CASE_     :   pyspark.sql.DataFrame ,							SCREAMING_SNAKE_CASE_     :   Optional[NamedSplit] = None ,							SCREAMING_SNAKE_CASE_     :   Optional[Features] = None ,							SCREAMING_SNAKE_CASE_     :   bool = True ,							SCREAMING_SNAKE_CASE_     :   str = None ,							SCREAMING_SNAKE_CASE_     :   bool = False ,							SCREAMING_SNAKE_CASE_     :   str = None ,							SCREAMING_SNAKE_CASE_     :   bool = True ,							SCREAMING_SNAKE_CASE_     :   str = "arrow" ,							**SCREAMING_SNAKE_CASE_     :   Optional[Any] ,							):
											super().__init__(
											    split=SCREAMING_SNAKE_CASE_ ,							features=SCREAMING_SNAKE_CASE_ ,							cache_dir=SCREAMING_SNAKE_CASE_ ,							keep_in_memory=SCREAMING_SNAKE_CASE_ ,							streaming=SCREAMING_SNAKE_CASE_ ,							**SCREAMING_SNAKE_CASE_ ,							)
											lowerCAmelCase__      			=						load_from_cache_file
											lowerCAmelCase__      			=						file_format
											lowerCAmelCase__      			=						Spark(
											    df=SCREAMING_SNAKE_CASE_ ,							features=SCREAMING_SNAKE_CASE_ ,							cache_dir=SCREAMING_SNAKE_CASE_ ,							working_dir=SCREAMING_SNAKE_CASE_ ,							**SCREAMING_SNAKE_CASE_ ,							)




							def 						__snake_case					(   self     :   List[str]	):
											if self.streaming:
															return self.builder.as_streaming_dataset(split=self.split	)
											lowerCAmelCase__      			=						None if self._load_from_cache_file else DownloadMode.FORCE_REDOWNLOAD
											self.builder.download_and_prepare(
											    download_mode=SCREAMING_SNAKE_CASE_ ,							file_format=self._file_format ,							)
											return self.builder.as_dataset(split=self.split	)





