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

import yaml


class 			lowercase_		(      yaml.SafeLoader       ):


       def 	_snake_case				(    self						,       __A				)						->    List[Any]:
              SCREAMING_SNAKE_CASE_							:				Dict		=[self.constructed_objects[key_node] for key_node, _ in node.value]
              SCREAMING_SNAKE_CASE_							:				int		=[tuple(__A				) if isinstance(__A						,       __A				) else key for key in keys]
              SCREAMING_SNAKE_CASE_							:				Union[str, Any]		=Counter(__A				)
              SCREAMING_SNAKE_CASE_							:				Optional[int]		=[key for key in counter if counter[key] > 1]
              if duplicate_keys:
                     raise TypeError(F'Got duplicate yaml keys: {duplicate_keys}'				)





       def 	_snake_case				(    self						,       __A						,       __A=False				)						->    Dict:
              SCREAMING_SNAKE_CASE_							:				Tuple		=super().construct_mapping(__A						,       deep=__A				)
              self._check_no_duplicates_on_constructed_node(__A				)
              return mapping






def 							SCREAMING_SNAKE_CASE_	(					UpperCAmelCase_	:     str				)			->						Tuple[Optional[str], str]:
       SCREAMING_SNAKE_CASE_							:				Tuple		=list(readme_content.splitlines()				)
       if full_content and full_content[0] == "---" and "---" in full_content[1:]:
              SCREAMING_SNAKE_CASE_							:				Any		=full_content[1:].index('''---'''				) + 1
              SCREAMING_SNAKE_CASE_							:				Union[str, Any]		='''\n'''.join(full_content[1:sep_idx]				)
              return yamlblock, "\n".join(full_content[sep_idx + 1 :]				)

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


class 			lowercase_		(      A       ):
       # class attributes
       __lowerCamelCase				       =						{"train_eval_index"}  # train-eval-index in the YAML metadata


       @classmethod
       def 	_snake_case				(    cls						,       __A				)						->    "DatasetMetadata":
              with open(__A						,       encoding='''utf-8'''				) as readme_file:
                     SCREAMING_SNAKE_CASE_	,     SCREAMING_SNAKE_CASE_							:				Union[str, Any]		=_split_yaml_from_readme(readme_file.read()				)
              if yaml_string is not None:
                     return cls.from_yaml_string(__A				)
              else:
                     return cls()


       def 	_snake_case				(    self						,       __A				)						->    Union[str, Any]:
              if path.exists():
                     with open(__A						,       encoding='''utf-8'''				) as readme_file:
                            SCREAMING_SNAKE_CASE_							:				Union[str, Any]		=readme_file.read()
              else:
                     SCREAMING_SNAKE_CASE_							:				int		=None
              SCREAMING_SNAKE_CASE_							:				Tuple		=self._to_readme(__A				)
              with open(__A						,       '''w'''						,       encoding='''utf-8'''				) as readme_file:
                     readme_file.write(__A				)


       def 	_snake_case				(    self						,       __A = None				)						->    str:
              if readme_content is not None:
                     SCREAMING_SNAKE_CASE_	,     SCREAMING_SNAKE_CASE_							:				str		=_split_yaml_from_readme(__A				)
                     SCREAMING_SNAKE_CASE_							:				Tuple		='''---\n''' + self.to_yaml_string() + '''---\n''' + content
              else:
                     SCREAMING_SNAKE_CASE_							:				Tuple		='''---\n''' + self.to_yaml_string() + '''---\n'''
              return full_content


       @classmethod
       def 	_snake_case				(    cls						,       __A				)						->    "DatasetMetadata":
              SCREAMING_SNAKE_CASE_							:				str		=yaml.load(__A						,       Loader=_NoDuplicateSafeLoader				) or {}

              # Convert the YAML keys to DatasetMetadata fields
              SCREAMING_SNAKE_CASE_							:				Optional[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 	_snake_case				(    self				)						->    str:
              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'''				)






_lowercase											=    {
    """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

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

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


import importlib
import os

import fsspec
import pytest
from fsspec import register_implementation
from fsspec.registry import _registry as _fsspec_registry

from datasets.filesystems import COMPRESSION_FILESYSTEMS, HfFileSystem, extract_path_from_uri, is_remote_filesystem

from .utils import require_lza, require_zstandard
def 							SCREAMING_SNAKE_CASE_	(					UpperCAmelCase_	:     List[Any]				)			->						Dict:
       assert "mock" in _fsspec_registry
       assert "bz2" in _fsspec_registry
def 							SCREAMING_SNAKE_CASE_	(					)			->						Union[str, Any]:
       assert "mock" not in _fsspec_registry
       assert "bz2" in _fsspec_registry
def 							SCREAMING_SNAKE_CASE_	(					)			->						Dict:
       SCREAMING_SNAKE_CASE_							:				Optional[Any]		='''mock-s3-bucket'''
       SCREAMING_SNAKE_CASE_							:				Any		=f's3://{mock_bucket}'
       SCREAMING_SNAKE_CASE_							:				Dict		=extract_path_from_uri(UpperCAmelCase_				)
       assert dataset_path.startswith('''s3://'''				) is False

       SCREAMING_SNAKE_CASE_							:				Dict		='''./local/path'''
       SCREAMING_SNAKE_CASE_							:				str		=extract_path_from_uri(UpperCAmelCase_				)
       assert dataset_path == new_dataset_path
def 							SCREAMING_SNAKE_CASE_	(					UpperCAmelCase_	:     Union[str, Any]				)			->						List[str]:
       SCREAMING_SNAKE_CASE_							:				Union[str, Any]		=is_remote_filesystem(UpperCAmelCase_				)
       assert is_remote is True

       SCREAMING_SNAKE_CASE_							:				Dict		=fsspec.filesystem('''file'''				)

       SCREAMING_SNAKE_CASE_							:				Optional[int]		=is_remote_filesystem(UpperCAmelCase_				)
       assert is_remote is False
@pytest.mark.parametrize('''compression_fs_class'''			,							UpperCAmelCase_				)
def 							SCREAMING_SNAKE_CASE_	(					UpperCAmelCase_	:     Union[str, Any]			,							UpperCAmelCase_	:     Any			,							UpperCAmelCase_	:     Optional[Any]			,							UpperCAmelCase_	:     Optional[Any]			,							UpperCAmelCase_	:     int			,							UpperCAmelCase_	:     str			,							UpperCAmelCase_	:     Any				)			->						List[Any]:
       SCREAMING_SNAKE_CASE_							:				str		={'''gzip''': gz_file, '''xz''': xz_file, '''zstd''': zstd_file, '''bz2''': bza_file, '''lz4''': lza_file}
       SCREAMING_SNAKE_CASE_							:				List[Any]		=input_paths[compression_fs_class.protocol]
       if input_path is None:
              SCREAMING_SNAKE_CASE_							:				List[str]		=f'for \'{compression_fs_class.protocol}\' compression protocol, '
              if compression_fs_class.protocol == "lz4":
                     reason += require_lza.kwargs["reason"]
              elif compression_fs_class.protocol == "zstd":
                     reason += require_zstandard.kwargs["reason"]
              pytest.skip(UpperCAmelCase_				)
       SCREAMING_SNAKE_CASE_							:				Union[str, Any]		=fsspec.filesystem(compression_fs_class.protocol			,							fo=UpperCAmelCase_				)
       assert isinstance(UpperCAmelCase_			,							UpperCAmelCase_				)
       SCREAMING_SNAKE_CASE_							:				str		=os.path.basename(UpperCAmelCase_				)
       SCREAMING_SNAKE_CASE_							:				Optional[Any]		=expected_filename[: expected_filename.rindex('''.'''				)]
       assert fs.glob('''*'''				) == [expected_filename]
       with fs.open(UpperCAmelCase_			,							'''r'''			,							encoding='''utf-8'''				) as f, open(UpperCAmelCase_			,							encoding='''utf-8'''				) as expected_file:
              assert f.read() == expected_file.read()
@pytest.mark.parametrize('''protocol'''			,							['''zip''', '''gzip''']				)
def 							SCREAMING_SNAKE_CASE_	(					UpperCAmelCase_	:     Any			,							UpperCAmelCase_	:     Union[str, Any]			,							UpperCAmelCase_	:     str				)			->						Any:
       SCREAMING_SNAKE_CASE_							:				Tuple		={'''zip''': zip_jsonl_path, '''gzip''': jsonl_gz_path}
       SCREAMING_SNAKE_CASE_							:				List[Any]		=compressed_file_paths[protocol]
       SCREAMING_SNAKE_CASE_							:				str		='''dataset.jsonl'''
       SCREAMING_SNAKE_CASE_							:				Dict		=f'{protocol}://{member_file_path}::{compressed_file_path}'
       SCREAMING_SNAKE_CASE_	,     *SCREAMING_SNAKE_CASE_							:				Dict		=fsspec.get_fs_token_paths(UpperCAmelCase_				)
       assert fs.isfile(UpperCAmelCase_				)
       assert not fs.isfile('''non_existing_''' + member_file_path				)
@pytest.mark.integration
def 							SCREAMING_SNAKE_CASE_	(					UpperCAmelCase_	:     List[str]			,							UpperCAmelCase_	:     Optional[int]			,							UpperCAmelCase_	:     Optional[int]			,							UpperCAmelCase_	:     int				)			->						int:
       SCREAMING_SNAKE_CASE_							:				Dict		=hf_api.dataset_info(UpperCAmelCase_			,							token=UpperCAmelCase_				)
       SCREAMING_SNAKE_CASE_							:				Optional[int]		=HfFileSystem(repo_info=UpperCAmelCase_			,							token=UpperCAmelCase_				)
       assert sorted(hffs.glob('''*'''				)				) == [".gitattributes", "data"]
       assert hffs.isdir('''data'''				)
       assert hffs.isfile('''.gitattributes'''				) and hffs.isfile('''data/text_data.txt'''				)
       with open(UpperCAmelCase_				) as f:
              assert hffs.open('''data/text_data.txt'''			,							'''r'''				).read() == f.read()

def 							SCREAMING_SNAKE_CASE_	(					)			->						Union[str, Any]:
       SCREAMING_SNAKE_CASE_							:				Tuple		='''bz2'''

       # Import module
       import datasets.filesystems

       # Overwrite protocol and reload
       register_implementation(UpperCAmelCase_			,							UpperCAmelCase_			,							clobber=UpperCAmelCase_				)
       with pytest.warns(UpperCAmelCase_				) as warning_info:
              importlib.reload(datasets.filesystems				)

       assert len(UpperCAmelCase_				) == 1
       assert (
           str(warning_info[0].message				)
           == f'A filesystem protocol was already set for {protocol} and will be overwritten.'
       )
