



from collections import Counter
from pathlib import Path
from typing import Optional, Tuple

import yaml



class 				__snake_case						(     yaml.SafeLoader						):




							def    UpperCAmelCase__			(       self     :       Dict				,				A_     :       Tuple):
									lowerCAmelCase_			:     Tuple									= [self.constructed_objects[key_node] for key_node, _ in node.value]
									lowerCAmelCase_			:     List[str]									= [tuple(A_) if isinstance(A_				,				A_) else key for key in keys]
									lowerCAmelCase_			:     Tuple									= Counter(A_)
									lowerCAmelCase_			:     Union[str, Any]									= [key for key in counter if counter[key] > 1]
									if duplicate_keys:
											raise TypeError(F"""Got duplicate yaml keys: {duplicate_keys}""")







							def    UpperCAmelCase__			(       self     :       int				,				A_     :       Optional[Any]				,				A_     :       int=False):
									lowerCAmelCase_			:     int									= super().construct_mapping(A_				,				deep=A_)
									self._check_no_duplicates_on_constructed_node(A_)
									return mapping





def 			UpperCamelCase(  __UpperCamelCase							:		str ):
		lowerCAmelCase_			:     int									= list(readme_content.splitlines() )
		if full_content and full_content[0] == "---" and "---" in full_content[1:]:
				lowerCAmelCase_			:     int									= full_content[1:].index('''---''' ) + 1
				lowerCAmelCase_			:     List[str]									= '''\n'''.join(full_content[1:sep_idx] )
				return yamlblock, "\n".join(full_content[sep_idx + 1 :] )

		return None, "\n".join(__UpperCamelCase )



class 				__snake_case						(     UpperCamelCase_						):
							# class attributes
							_a			      = {'''train_eval_index'''}  # train-eval-index in the YAML metadata




							@classmethod
							def    UpperCAmelCase__			(       cls     :       Optional[Any]				,				A_     :       Path):
									with open(A_				,				encoding='''utf-8''') as readme_file:
											lowerCAmelCase_					,  lowerCAmelCase_			:     Any									= _split_yaml_from_readme(readme_file.read())
									if yaml_string is not None:
											return cls.from_yaml_string(A_)
									else:
											return cls()




							def    UpperCAmelCase__			(       self     :       Any				,				A_     :       Path):
									if path.exists():
											with open(A_				,				encoding='''utf-8''') as readme_file:
													lowerCAmelCase_			:     Tuple									= readme_file.read()
									else:
											lowerCAmelCase_			:     Optional[int]									= None
									lowerCAmelCase_			:     Any									= self._to_readme(A_)
									with open(A_				,				'''w'''				,				encoding='''utf-8''') as readme_file:
											readme_file.write(A_)




							def    UpperCAmelCase__			(       self     :       Any				,				A_     :       Optional[str] = None):
									if readme_content is not None:
											lowerCAmelCase_					,  lowerCAmelCase_			:     str									= _split_yaml_from_readme(A_)
											lowerCAmelCase_			:     Tuple									= '''---\n''' + self.to_yaml_string() + '''---\n''' + content
									else:
											lowerCAmelCase_			:     Tuple									= '''---\n''' + self.to_yaml_string() + '''---\n'''
									return full_content




							@classmethod
							def    UpperCAmelCase__			(       cls     :       str				,				A_     :       str):
									lowerCAmelCase_			:     str									= yaml.load(A_				,				Loader=_NoDuplicateSafeLoader) or {}

									# Convert the YAML keys to DatasetMetadata fields
									lowerCAmelCase_			:     Union[str, Any]									= {
									    (key.replace('''-'''				,				'''_''') if key.replace('''-'''				,				'''_''') in cls._FIELDS_WITH_DASHES else key): value
									    for key, value in metadata_dict.items()
									}
									return cls(**A_)







							def    UpperCAmelCase__			(       self     :       Optional[int]):
									return yaml.safe_dump(
									    {
									        (key.replace('''_'''				,				'''-''') if key in self._FIELDS_WITH_DASHES else key): value
									        for key, value in self.items()
									    }				,				sort_keys=A_				,				allow_unicode=A_				,				encoding='''utf-8'''				,				).decode('''utf-8''')





A__  :  str								=					{
    '''image-classification''': [],
    '''translation''': [],
    '''image-segmentation''': [],
    '''fill-mask''': [],
    '''automatic-speech-recognition''': [],
    '''token-classification''': [],
    '''sentence-similarity''': [],
    '''audio-classification''': [],
    '''question-answering''': [],
    '''summarization''': [],
    '''zero-shot-classification''': [],
    '''table-to-text''': [],
    '''feature-extraction''': [],
    '''other''': [],
    '''multiple-choice''': [],
    '''text-classification''': [],
    '''text-to-image''': [],
    '''text2text-generation''': [],
    '''zero-shot-image-classification''': [],
    '''tabular-classification''': [],
    '''tabular-regression''': [],
    '''image-to-image''': [],
    '''tabular-to-text''': [],
    '''unconditional-image-generation''': [],
    '''text-retrieval''': [],
    '''text-to-speech''': [],
    '''object-detection''': [],
    '''audio-to-audio''': [],
    '''text-generation''': [],
    '''conversational''': [],
    '''table-question-answering''': [],
    '''visual-question-answering''': [],
    '''image-to-text''': [],
    '''reinforcement-learning''': [],
    '''voice-activity-detection''': [],
    '''time-series-forecasting''': [],
    '''document-question-answering''': [],
}


if __name__ == "__main__":
						from argparse import ArgumentParser

						A__  :  Dict								=					ArgumentParser(usage='''Validate the yaml metadata block of a README.md file.''')
						ap.add_argument('''readme_filepath''')
						A__  :  Optional[int]								=					ap.parse_args()

						A__  :  Optional[Any]								=					Path(args.readme_filepath)
						A__  :  Optional[Any]								=					DatasetMetadata.from_readme(readme_filepath)
						print(dataset_metadata)
						dataset_metadata.to_readme(readme_filepath)










from datetime import datetime as dt
import os

from github import Github


A__  :  List[str]								=					[
    '''good first issue''',
    '''good second issue''',
    '''good difficult issue''',
    '''feature request''',
    '''new model''',
    '''wip''',
]


def 			UpperCamelCase(  ):
		lowerCAmelCase_			:     Union[str, Any]									= Github(os.environ['''GITHUB_TOKEN'''] )
		lowerCAmelCase_			:     Tuple									= g.get_repo('''huggingface/transformers''' )
		lowerCAmelCase_			:     int									= repo.get_issues(state='''open''' )

		for issue in open_issues:
				lowerCAmelCase_			:     Optional[Any]									= sorted([comment for comment in issue.get_comments()]     ,key=lambda __UpperCamelCase : i.created_at     ,reverse=__UpperCamelCase )
				lowerCAmelCase_			:     Tuple									= comments[0] if len(__UpperCamelCase ) > 0 else None
				if (
				    last_comment is not None
				    and last_comment.user.login == "github-actions[bot]"
				    and (dt.utcnow() - issue.updated_at).days > 7
				    and (dt.utcnow() - issue.created_at).days >= 30
				    and not any(label.name.lower() in LABELS_TO_EXEMPT for label in issue.get_labels() )
				):
						# print(f"Would close issue {issue.number} since it has been 7 days of inactivity since bot mention.")
						issue.edit(state='''closed''' )
				elif (
				    (dt.utcnow() - issue.updated_at).days > 23
				    and (dt.utcnow() - issue.created_at).days >= 30
				    and not any(label.name.lower() in LABELS_TO_EXEMPT for label in issue.get_labels() )
				):
						# print(f"Would add stale comment to {issue.number}")
						issue.create_comment(
						    '''This issue has been automatically marked as stale because it has not had '''
						    '''recent activity. If you think this still needs to be addressed '''
						    '''please comment on this thread.\n\nPlease note that issues that do not follow the '''
						    '''[contributing guidelines](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md) '''
						    '''are likely to be ignored.''' )


if __name__ == "__main__":
						main()





