"""simple docstring"""







# Lint as: python3
import os
import re
import urllib.parse
from pathlib import Path
from typing import Callable, List, Optional, Union
from zipfile import ZipFile

from ..utils.file_utils import cached_path, hf_github_url
from ..utils.logging import get_logger
from ..utils.version import Version


__SCREAMING_SNAKE_CASE    	=get_logger(__name__)







class        UpperCamelCase		:
   lowercase							=  'dummy_data'
   lowercase							=  'datasets'
   lowercase							=  False
   def __init__(			self     ,__UpperCamelCase     ,__UpperCamelCase     ,__UpperCamelCase     ,__UpperCamelCase = None     ,__UpperCamelCase = False     ,__UpperCamelCase = True     ,__UpperCamelCase = None     ,)	->      Optional[Any]:


        '''simple docstring'''


        lowercase_	:				int													=	0
        lowercase_	:				List[str]													=	dataset_name
        lowercase_	:				Optional[Any]													=	cache_dir
        lowercase_	:				List[str]													=	use_local_dummy_data
        lowercase_	:				int													=	config
        # download_callbacks take a single url as input
        lowercase_	:				List[Callable]													=	download_callbacks or []
        # if False, it doesn't load existing files and it returns the paths of the dummy files relative
        # to the dummy_data zip file root
        lowercase_	:				Any													=	load_existing_dummy_data

        # TODO(PVP, QL) might need to make this more general
        lowercase_	:				Any													=	str(__UpperCamelCase			)
        # to be downloaded
        lowercase_	:				Tuple													=	None
        lowercase_	:				Tuple													=	None
   @property
   def 			_UpperCAmelCase   (			self			)	->      Optional[int]:


        '''simple docstring'''


        if self._dummy_file is None:
             lowercase_	:				Optional[Any]													=	self.download_dummy_data()
        return self._dummy_file
   @property
   def 			_UpperCAmelCase   (			self			)	->      Optional[Any]:


        '''simple docstring'''


        if self.config is not None:
             # structure is dummy / config_name / version_name
             return os.path.join('dummy'     ,self.config.name     ,self.version_name			)
        # structure is dummy / version_name
        return os.path.join('dummy'     ,self.version_name			)
   @property
   def 			_UpperCAmelCase   (			self			)	->      List[str]:


        '''simple docstring'''


        return os.path.join(self.dummy_data_folder     ,'dummy_data.zip'			)
   def 			_UpperCAmelCase   (			self			)	->      Optional[Any]:


        '''simple docstring'''


        lowercase_	:				List[str]													=	(
            self.local_path_to_dummy_data if self.use_local_dummy_data is True else self.github_path_to_dummy_data
        )

        lowercase_	:				Optional[int]													=	cached_path(
            __UpperCamelCase     ,cache_dir=self.cache_dir     ,extract_compressed_file=__UpperCamelCase     ,force_extract=__UpperCamelCase			)

        return os.path.join(__UpperCamelCase     ,self.dummy_file_name			)
   @property
   def 			_UpperCAmelCase   (			self			)	->      Tuple:


        '''simple docstring'''


        return os.path.join(self.datasets_scripts_dir     ,self.dataset_name     ,self.dummy_zip_file			)
   @property
   def 			_UpperCAmelCase   (			self			)	->      List[str]:


        '''simple docstring'''


        if self._bucket_url is None:
             lowercase_	:				int													=	hf_github_url(self.dataset_name     ,self.dummy_zip_file.replace(os.sep     ,'/'			)			)
        return self._bucket_url
   @property
   def 			_UpperCAmelCase   (			self			)	->      List[Any]:


        '''simple docstring'''


        if os.path.isdir(self.dummy_file			):
             return self.dummy_file
        # else cut off path to file -> example `xsum`.
        return "/".join(self.dummy_file.replace(os.sep     ,'/'			).split('/'			)[:-1]			)
   def 			_UpperCAmelCase   (			self     ,__UpperCamelCase     ,*__UpperCamelCase			)	->      Dict:


        '''simple docstring'''


        if self.load_existing_dummy_data:
             # dummy data is downloaded and tested
             lowercase_	:				Tuple													=	self.dummy_file
        else:
             # dummy data cannot be downloaded and only the path to dummy file is returned
             lowercase_	:				int													=	self.dummy_file_name

        # special case when data_url is a dict
        if isinstance(__UpperCamelCase     ,__UpperCamelCase			):
             return self.create_dummy_data_dict(__UpperCamelCase     ,__UpperCamelCase			)
        elif isinstance(__UpperCamelCase     ,(list, tuple)			):
             return self.create_dummy_data_list(__UpperCamelCase     ,__UpperCamelCase			)
        else:
             return self.create_dummy_data_single(__UpperCamelCase     ,__UpperCamelCase			)
   def 			_UpperCAmelCase   (			self     ,__UpperCamelCase     ,*__UpperCamelCase			)	->      Any:


        '''simple docstring'''


        return self.download_and_extract(__UpperCamelCase			)
   def 			_UpperCAmelCase   (			self     ,__UpperCamelCase     ,__UpperCamelCase			)	->      str:


        '''simple docstring'''


        return self.download_and_extract(__UpperCamelCase			)
   def 			_UpperCAmelCase   (			self     ,__UpperCamelCase     ,*__UpperCamelCase     ,**__UpperCamelCase			)	->      Tuple:


        '''simple docstring'''


        return path
   def 			_UpperCAmelCase   (			self			)	->      Any:


        '''simple docstring'''


        return {}
   def 			_UpperCAmelCase   (			self     ,__UpperCamelCase     ,__UpperCamelCase			)	->      Union[str, Any]:


        '''simple docstring'''


        lowercase_	:				Optional[int]													=	{}
        for key, single_urls in data_url.items():
             for download_callback in self.download_callbacks:
                  if isinstance(__UpperCamelCase     ,__UpperCamelCase			):
                       for single_url in single_urls:
                            download_callback(__UpperCamelCase			)
                  else:
                       lowercase_	:				Tuple													=	single_urls
                       download_callback(__UpperCamelCase			)
            # we force the name of each key to be the last file / folder name of the url path
            # if the url has arguments, we need to encode them with urllib.parse.quote_plus
             if isinstance(__UpperCamelCase     ,__UpperCamelCase			):
                  lowercase_	:				Optional[int]													=	[os.path.join(__UpperCamelCase     ,urllib.parse.quote_plus(Path(__UpperCamelCase			).name			)			) for x in single_urls]
             else:
                  lowercase_	:				str													=	single_urls
                  lowercase_	:				List[str]													=	os.path.join(__UpperCamelCase     ,urllib.parse.quote_plus(Path(__UpperCamelCase			).name			)			)
             lowercase_	:				Any													=	value

        # make sure that values are unique
        if all(isinstance(__UpperCamelCase     ,__UpperCamelCase			) for i in dummy_data_dict.values()			) and len(set(dummy_data_dict.values()			)			) < len(
            dummy_data_dict.values()			):
             # append key to value to make its name unique
             lowercase_	:				Optional[Any]													=	{key: value + key for key, value in dummy_data_dict.items()}

        return dummy_data_dict
   def 			_UpperCAmelCase   (			self     ,__UpperCamelCase     ,__UpperCamelCase			)	->      Any:


        '''simple docstring'''


        lowercase_	:				str													=	[]
        # trick: if there are many shards named like `data.txt-000001-of-00300`, only use the first one
        lowercase_	:				Tuple													=	all(bool(re.findall('[0-9]{3,}-of-[0-9]{3,}'     ,__UpperCamelCase			)			) for url in data_url			)
        lowercase_	:				List[str]													=	all(
            url.startswith('https://ftp.ncbi.nlm.nih.gov/pubmed/baseline/pubmed'			) for url in data_url			)
        if data_url and (is_tf_records or is_pubmed_records):
             lowercase_	:				Dict													=	[data_url[0]] * len(__UpperCamelCase			)
        for single_url in data_url:
             for download_callback in self.download_callbacks:
                  download_callback(__UpperCamelCase			)
             # we force the name of each key to be the last file / folder name of the url path
             # if the url has arguments, we need to encode them with urllib.parse.quote_plus
             lowercase_	:				Any													=	os.path.join(__UpperCamelCase     ,urllib.parse.quote_plus(single_url.split('/'			)[-1]			)			)
             dummy_data_list.append(__UpperCamelCase			)
        return dummy_data_list
   def 			_UpperCAmelCase   (			self     ,__UpperCamelCase     ,__UpperCamelCase			)	->      Tuple:


        '''simple docstring'''


        for download_callback in self.download_callbacks:
             download_callback(__UpperCamelCase			)
        # we force the name of each key to be the last file / folder name of the url path
        # if the url has arguments, we need to encode them with urllib.parse.quote_plus
        lowercase_	:				int													=	os.path.join(__UpperCamelCase     ,urllib.parse.quote_plus(data_url.split('/'			)[-1]			)			)
        if os.path.exists(__UpperCamelCase			) or not self.load_existing_dummy_data:
             return value
        else:
             # Backward compatibility, maybe deprecate at one point.
             # For many datasets with single url calls to dl_manager.download_and_extract,
             # the dummy_data.zip file is actually the zipped downloaded file
             # while now we expected the dummy_data.zip file to be a directory containing
             # the downloaded file.
             return path_to_dummy_data
   def 			_UpperCAmelCase   (			self			)	->      Optional[int]:


        '''simple docstring'''


        pass
   def 			_UpperCAmelCase   (			self			)	->      int:


        '''simple docstring'''


        pass
   def 			_UpperCAmelCase   (			self     ,__UpperCamelCase			)	->      int:


        '''simple docstring'''


        def _iter_archive_members(__UpperCamelCase			):
             # this preserves the order of the members inside the ZIP archive
             lowercase_	:				str													=	Path(self.dummy_file			).parent
             lowercase_	:				List[Any]													=	path.relative_to(__UpperCamelCase			)
             with ZipFile(self.local_path_to_dummy_data			) as zip_file:
                  lowercase_	:				Tuple													=	zip_file.namelist()
             for member in members:
                  if member.startswith(relative_path.as_posix()			):
                       yield dummy_parent_path.joinpath(__UpperCamelCase			)

        lowercase_	:				List[str]													=	Path(__UpperCamelCase			)
        lowercase_	:				Optional[int]													=	_iter_archive_members(__UpperCamelCase			) if self.use_local_dummy_data else path.rglob('*'			)
        for file_path in file_paths:
             if file_path.is_file() and not file_path.name.startswith(('.', '__')			):
                  yield file_path.relative_to(__UpperCamelCase			).as_posix(), file_path.open('rb'			)







   def 			_UpperCAmelCase   (			self     ,__UpperCamelCase			)	->      Optional[Any]:


        '''simple docstring'''


        if not isinstance(__UpperCamelCase     ,__UpperCamelCase			):
             lowercase_	:				Optional[Any]													=	[paths]
        for path in paths:
             if os.path.isfile(__UpperCamelCase			):
                  if os.path.basename(__UpperCamelCase			).startswith(('.', '__')			):
                       return
                  yield path
             else:
                  for dirpath, dirnames, filenames in os.walk(__UpperCamelCase			):
                       if os.path.basename(__UpperCamelCase			).startswith(('.', '__')			):
                            continue
                       dirnames.sort()
                       for filename in sorted(__UpperCamelCase			):
                            if filename.startswith(('.', '__')			):
                                 continue
                            yield os.path.join(__UpperCamelCase     ,__UpperCamelCase			)


"""simple docstring"""







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

import yaml







class        UpperCamelCase		(			yaml.SafeLoader  ):
   def 			_UpperCAmelCase   (			self     ,__UpperCamelCase			)	->      Optional[int]:


        '''simple docstring'''


        lowercase_	:				str													=	[self.constructed_objects[key_node] for key_node, _ in node.value]
        lowercase_	:				str													=	[tuple(__UpperCamelCase			) if isinstance(__UpperCamelCase     ,__UpperCamelCase			) else key for key in keys]
        lowercase_	:				List[Any]													=	Counter(__UpperCamelCase			)
        lowercase_	:				str													=	[key for key in counter if counter[key] > 1]
        if duplicate_keys:
             raise TypeError(f'''Got duplicate yaml keys: {duplicate_keys}'''			)







   def 			_UpperCAmelCase   (			self     ,__UpperCamelCase     ,__UpperCamelCase=False			)	->      List[Any]:


        '''simple docstring'''


        lowercase_	:				Optional[int]													=	super().construct_mapping(__UpperCamelCase     ,deep=__UpperCamelCase			)
        self._check_no_duplicates_on_constructed_node(__UpperCamelCase			)
        return mapping






def 			lowercase__(       __SCREAMING_SNAKE_CASE							:     str      ):
     lowercase_	:				Tuple													=	list(readme_content.splitlines()      )
     if full_content and full_content[0] == "---" and "---" in full_content[1:]:
          lowercase_	:				Dict													=	full_content[1:].index('---'      ) + 1
          lowercase_	:				Optional[int]													=	'\n'.join(full_content[1:sep_idx]      )
          return yamlblock, "\n".join(full_content[sep_idx + 1 :]      )

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







class        UpperCamelCase		(			lowercase_  ):
   # class attributes
   lowercase							=  {'train_eval_index'}  # train-eval-index in the YAML metadata
   @classmethod
   def 			_UpperCAmelCase   (			cls     ,__UpperCamelCase			)	->      "DatasetMetadata":


        '''simple docstring'''


        with open(__UpperCamelCase     ,encoding='utf-8'			) as readme_file:
             lowercase_							,  lowercase_	:				Optional[int]													=	_split_yaml_from_readme(readme_file.read()			)
        if yaml_string is not None:
             return cls.from_yaml_string(__UpperCamelCase			)
        else:
             return cls()
   def 			_UpperCAmelCase   (			self     ,__UpperCamelCase			)	->      List[Any]:


        '''simple docstring'''


        if path.exists():
             with open(__UpperCamelCase     ,encoding='utf-8'			) as readme_file:
                  lowercase_	:				Dict													=	readme_file.read()
        else:
             lowercase_	:				int													=	None
        lowercase_	:				Any													=	self._to_readme(__UpperCamelCase			)
        with open(__UpperCamelCase     ,'w'     ,encoding='utf-8'			) as readme_file:
             readme_file.write(__UpperCamelCase			)
   def 			_UpperCAmelCase   (			self     ,__UpperCamelCase = None			)	->      str:


        '''simple docstring'''


        if readme_content is not None:
             lowercase_							,  lowercase_	:				Optional[Any]													=	_split_yaml_from_readme(__UpperCamelCase			)
             lowercase_	:				Optional[Any]													=	'---\n' + self.to_yaml_string() + '---\n' + content
        else:
             lowercase_	:				Tuple													=	'---\n' + self.to_yaml_string() + '---\n'
        return full_content
   @classmethod
   def 			_UpperCAmelCase   (			cls     ,__UpperCamelCase			)	->      "DatasetMetadata":


        '''simple docstring'''


        lowercase_	:				List[str]													=	yaml.load(__UpperCamelCase     ,Loader=_NoDuplicateSafeLoader			) or {}

        # Convert the YAML keys to DatasetMetadata fields
        lowercase_	:				Dict													=	{
            (key.replace('-'     ,'_'			) if key.replace('-'     ,'_'			) in cls._FIELDS_WITH_DASHES else key): value
            for key, value in metadata_dict.items()
        }
        return cls(**__UpperCamelCase			)







   def 			_UpperCAmelCase   (			self			)	->      str:


        '''simple docstring'''


        return yaml.safe_dump(
            {
                (key.replace('_'     ,'-'			) if key in self._FIELDS_WITH_DASHES else key): value
                for key, value in self.items()
            }     ,sort_keys=__UpperCamelCase     ,allow_unicode=__UpperCamelCase     ,encoding='utf-8'     ,).decode('utf-8'			)






__SCREAMING_SNAKE_CASE    	={
    "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

       __SCREAMING_SNAKE_CASE    	=ArgumentParser(usage="Validate the yaml metadata block of a README.md file.")
       ap.add_argument("readme_filepath")
       __SCREAMING_SNAKE_CASE    	=ap.parse_args()

       __SCREAMING_SNAKE_CASE    	=Path(args.readme_filepath)
       __SCREAMING_SNAKE_CASE    	=DatasetMetadata.from_readme(readme_filepath)
       print(dataset_metadata)
       dataset_metadata.to_readme(readme_filepath)

