
"""simple docstring"""




# flake8: noqa
# Lint as: python3

from typing import Dict, List, Optional, Type

from .. import config
from ..utils import logging
from .formatting import (
    ArrowFormatter,
    CustomFormatter,
    Formatter,
    PandasFormatter,
    PythonFormatter,
    TensorFormatter,
    format_table,
    query_table,
)
from .np_formatter import NumpyFormatter


A__      :	int          =    logging.get_logger(__name__)

A__      :	Dict[Optional[str], Type[Formatter]]          =    {}
A__      :	Dict[Optional[str], str]          =    {}
A__      :	Dict[Optional[str], Exception]          =    {}



def 							a__ (				lowerCAmelCase	:       type       ,    lowerCAmelCase	:       Optional[str]       ,    lowerCAmelCase	:       Optional[List[str]] = None       ,    ):






     '''simple docstring'''
     UpperCAmelCase__							: Optional[Any] 							=						aliases if aliases is not None else []
     if format_type in _FORMAT_TYPES:
          logger.warning(
              F"Overwriting format type '{format_type}' ({_FORMAT_TYPES[format_type].__name__} -> {formatter_cls.__name__})"		)
     UpperCAmelCase__							: Union[str, Any] 							=						formatter_cls
     for alias in set(aliases + [format_type]		):
          if alias in _FORMAT_TYPES_ALIASES:
               logger.warning(
                   F"Overwriting format type alias '{alias}' ({_FORMAT_TYPES_ALIASES[alias]} -> {format_type})"		)
          UpperCAmelCase__							: Union[str, Any] 							=						format_type



def 							a__ (				lowerCAmelCase	:       Exception       ,    lowerCAmelCase	:       Optional[str]       ,    lowerCAmelCase	:       Optional[List[str]] = None		):






     '''simple docstring'''
     UpperCAmelCase__							: Dict 							=						aliases if aliases is not None else []
     for alias in set(aliases + [format_type]		):
          UpperCAmelCase__							: Any 							=						unavailable_error


# Here we define all the available formatting functions that can be used by `Dataset.set_format`
_register_formatter(PythonFormatter, None, aliases=["""python"""])
_register_formatter(ArrowFormatter, """arrow""", aliases=["""pa""", """pyarrow"""])
_register_formatter(NumpyFormatter, """numpy""", aliases=["""np"""])
_register_formatter(PandasFormatter, """pandas""", aliases=["""pd"""])
_register_formatter(CustomFormatter, """custom""")

if config.TORCH_AVAILABLE:
    from .torch_formatter import TorchFormatter

    _register_formatter(TorchFormatter, """torch""", aliases=["""pt""", """pytorch"""])
else:
    A__      :	Union[str, Any]          =    ValueError("""PyTorch needs to be installed to be able to return PyTorch tensors.""")
    _register_unavailable_formatter(_torch_error, """torch""", aliases=["""pt""", """pytorch"""])

if config.TF_AVAILABLE:
    from .tf_formatter import TFFormatter

    _register_formatter(TFFormatter, """tensorflow""", aliases=["""tf"""])
else:
    A__      :	Union[str, Any]          =    ValueError("""Tensorflow needs to be installed to be able to return Tensorflow tensors.""")
    _register_unavailable_formatter(_tf_error, """tensorflow""", aliases=["""tf"""])

if config.JAX_AVAILABLE:
    from .jax_formatter import JaxFormatter

    _register_formatter(JaxFormatter, """jax""", aliases=[])
else:
    A__      :	Any          =    ValueError("""JAX needs to be installed to be able to return JAX arrays.""")
    _register_unavailable_formatter(_jax_error, """jax""", aliases=[])



def 							a__ (				lowerCAmelCase	:       Optional[str]		):






     '''simple docstring'''
     if format_type in _FORMAT_TYPES_ALIASES:
          return _FORMAT_TYPES_ALIASES[format_type]
     else:
          return format_type



def 							a__ (				lowerCAmelCase	:       Optional[str]       ,    **lowerCAmelCase	:       Optional[int]		):






     '''simple docstring'''
     UpperCAmelCase__							: Optional[int] 							=						get_format_type_from_alias(lowerCAmelCase		)
     if format_type in _FORMAT_TYPES:
          return _FORMAT_TYPES[format_type](**lowerCAmelCase		)
     if format_type in _FORMAT_TYPES_ALIASES_UNAVAILABLE:
          raise _FORMAT_TYPES_ALIASES_UNAVAILABLE[format_type]
     else:
          raise ValueError(
              F"Return type should be None or selected in {list(type for type in _FORMAT_TYPES.keys() if type != None		)}, but got '{format_type}'"		)





"""simple docstring"""




from pathlib import PurePosixPath
from typing import Optional

import fsspec
from fsspec import AbstractFileSystem
from huggingface_hub.hf_api import DatasetInfo

from ..utils.file_utils import get_authentication_headers_for_url
from ..utils.hub import hf_hub_url







class   _lowercase						(       lowerCAmelCase_				):


     '''simple docstring'''





     _A								=							''
     _A								=							'hf-legacy'  # "hf://"" is reserved for hffs



     def __init__(      self ,			__UpperCamelCase = None ,			__UpperCamelCase = None ,			**__UpperCamelCase ,			)->					str:
          super().__init__(self ,			**__UpperCamelCase  )
          UpperCAmelCase__							: int 							=						repo_info
          UpperCAmelCase__							: Optional[int] 							=						token
          UpperCAmelCase__							: Optional[Any] 							=						None



     def  lowerCAmelCase__       (      self  )->					Optional[Any]:
          if self.dir_cache is None:
               UpperCAmelCase__							: str 							=						{}
               for hf_file in self.repo_info.siblings:
                    # TODO(QL): add sizes
                    UpperCAmelCase__							: str 							=						{
                        "name": hf_file.rfilename,
                        "size": None,
                        "type": "file",
                    }
                    self.dir_cache.update(
                        {
                            str(__UpperCamelCase  ): {"name": str(__UpperCamelCase  ), "size": None, "type": "directory"}
                            for d in list(PurePosixPath(hf_file.rfilename  ).parents  )[:-1]
                        }  )



     def  lowerCAmelCase__       (      self ,			__UpperCamelCase ,			__UpperCamelCase = "rb" ,			**__UpperCamelCase ,			)->					List[Any]:
          if not isinstance(self.repo_info ,			__UpperCamelCase  ):
               raise NotImplementedError(F"Open is only implemented for dataset repositories, but got {self.repo_info}"  )
          UpperCAmelCase__							: Union[str, Any] 							=						hf_hub_url(self.repo_info.id ,			__UpperCamelCase ,			revision=self.repo_info.sha  )
          return fsspec.open(
              __UpperCamelCase ,			mode=__UpperCamelCase ,			headers=get_authentication_headers_for_url(__UpperCamelCase ,			use_auth_token=self.token  ) ,			client_kwargs={"trust_env": True} ,			).open()



     def  lowerCAmelCase__       (      self ,			__UpperCamelCase ,			**__UpperCamelCase  )->					List[str]:
          self._get_dirs()
          UpperCAmelCase__							: Union[str, Any] 							=						self._strip_protocol(__UpperCamelCase  )
          if path in self.dir_cache:
               return self.dir_cache[path]
          else:
               raise FileNotFoundError(__UpperCamelCase  )



     def  lowerCAmelCase__       (      self ,			__UpperCamelCase ,			__UpperCamelCase=False ,			**__UpperCamelCase  )->					str:
          self._get_dirs()
          UpperCAmelCase__							: str 							=						PurePosixPath(path.strip("/"  )  )
          UpperCAmelCase__							: Optional[Any] 							=						{}
          for p, f in self.dir_cache.items():
               UpperCAmelCase__							: Optional[int] 							=						PurePosixPath(p.strip("/"  )  )
               UpperCAmelCase__							: Dict 							=						p.parent
               if root == path:
                    UpperCAmelCase__							: Tuple 							=						f
          UpperCAmelCase__							: List[Any] 							=						list(paths.values()  )
          if detail:
               return out
          else:
               return sorted(f["name"] for f in out  )



