import os
from typing import Optional

import fsspec
from fsspec.archive import AbstractArchiveFileSystem
from fsspec.utils import DEFAULT_BLOCK_SIZE





class UpperCAmelCase						(					__a  ):


				'''simple docstring'''






				lowerCamelCase_    =					''''''
				lowerCamelCase_    =					(
				    None  # protocol passed in prefix to the url. ex: "gzip", for gzip://file.txt::http://foo.bar/file.txt.gz
				)
				lowerCamelCase_    =					None  # compression type in fsspec. ex: "gzip"
				lowerCamelCase_    =					None  # extension of the filename to strip. ex: "".gz" to get file.txt from file.txt.gz
				def __init__(						self		,	lowercase = ""		,	lowercase = None		,	lowercase = None		,	**lowercase					):



						"""simple docstring"""





						super().__init__(self		,	**_UpperCamelCase					)
						# always open as "rb" since fsspec can then use the TextIOWrapper to make it work for "r" mode
						A_		:				Any     =      fsspec.open(
						    _UpperCamelCase		,	mode='rb'		,	protocol=_UpperCamelCase		,	compression=self.compression		,	client_kwargs={
						        'requote_redirect_url': False,  # see https://github.com/huggingface/datasets/pull/5459
						        'trust_env': True,  # Enable reading proxy env variables.
						        **(target_options or {}).pop('client_kwargs'		,	{}					),  # To avoid issues if it was already passed.
						    }		,	**(target_options or {})		,	)
						A_		:				str     =      os.path.basename(self.file.path.split('::'					)[0]					)
						A_		:				Union[str, Any]     =      (
						    self.compressed_name[: self.compressed_name.rindex('.'					)]
						    if '.' in self.compressed_name
						    else self.compressed_name
						)
						A_		:				int     =      None
				@classmethod
				def   lowerCAmelCase_   (						cls		,	lowercase					):



						"""simple docstring"""





						return super()._strip_protocol(_UpperCamelCase					).lstrip('/'					)
				def   lowerCAmelCase_   (						self					):



						"""simple docstring"""





						if self.dir_cache is None:
								A_		:				Optional[Any]     =      {**self.file.fs.info(self.file.path					), 'name': self.uncompressed_name}
								A_		:				Optional[Any]     =      {f['name']: f}
				def   lowerCAmelCase_   (						self		,	lowercase					):



						"""simple docstring"""





						return self.file.open().read()







				def   lowerCAmelCase_   (						self		,	lowercase		,	lowercase = "rb"		,	lowercase=None		,	lowercase=True		,	lowercase=None		,	**lowercase		,	):



						"""simple docstring"""





						A_		:				str     =      self._strip_protocol(_UpperCamelCase					)
						if mode != "rb":
								raise ValueError(F'''Tried to read with mode {mode} on file {self.file.path} opened with mode \'rb\''''					)
						return self.file.open()





class UpperCAmelCase						(					__a  ):


				'''simple docstring'''






				lowerCamelCase_    =					'''bz2'''
				lowerCamelCase_    =					'''bz2'''
				lowerCamelCase_    =					'''.bz2'''





class UpperCAmelCase						(					__a  ):


				'''simple docstring'''






				lowerCamelCase_    =					'''gzip'''
				lowerCamelCase_    =					'''gzip'''
				lowerCamelCase_    =					'''.gz'''





class UpperCAmelCase						(					__a  ):


				'''simple docstring'''






				lowerCamelCase_    =					'''lz4'''
				lowerCamelCase_    =					'''lz4'''
				lowerCamelCase_    =					'''.lz4'''





class UpperCAmelCase						(					__a  ):


				'''simple docstring'''






				lowerCamelCase_    =					'''xz'''
				lowerCamelCase_    =					'''xz'''
				lowerCamelCase_    =					'''.xz'''





class UpperCAmelCase						(					__a  ):


				'''simple docstring'''






				lowerCamelCase_    =					'''zstd'''
				lowerCamelCase_    =					'''zstd'''
				lowerCamelCase_    =					'''.zst'''
				def __init__(						self		,	lowercase		,	lowercase = "rb"		,	lowercase = None		,	lowercase = None		,	lowercase = DEFAULT_BLOCK_SIZE		,	**lowercase		,	):



						"""simple docstring"""





						super().__init__(
						    fo=_UpperCamelCase		,	mode=_UpperCamelCase		,	target_protocol=_UpperCamelCase		,	target_options=_UpperCamelCase		,	block_size=_UpperCamelCase		,	**_UpperCamelCase		,	)
						# We need to wrap the zstd decompressor to avoid this error in fsspec==2021.7.0 and zstandard==0.15.2:
						#
						# File "/Users/user/.virtualenvs/hf-datasets/lib/python3.7/site-packages/fsspec/core.py", line 145, in open
						#     out.close = close
						# AttributeError: 'zstd.ZstdDecompressionReader' object attribute 'close' is read-only
						#
						# see https://github.com/intake/filesystem_spec/issues/725
						A_		:				Tuple     =      self.file.__enter__





						class UpperCAmelCase						:


										'''simple docstring'''






										def __init__(						self		,	lowercase					):



												"""simple docstring"""





												A_		:				Dict     =      file_
										def __enter__(						self					):



												"""simple docstring"""





												self._file.__enter__()
												return self
										def __exit__(						self		,	*lowercase		,	**lowercase					):



												"""simple docstring"""





												self._file.__exit__(*_UpperCamelCase		,	**_UpperCamelCase					)
										def __iter__(						self					):



												"""simple docstring"""





												return iter(self._file					)
										def   lowerCAmelCase_   (						self					):



												"""simple docstring"""





												return next(self._file					)







										def __getattr__(						self		,	lowercase					):



												"""simple docstring"""





												return getattr(self._file		,	_UpperCamelCase					)

						def fixed_enter(*lowercase		,	**lowercase					):
								return WrappedFile(_enter(*_UpperCamelCase		,	**_UpperCamelCase					)					)

						A_		:				Tuple     =      fixed_enter








from typing import List, Optional, TypeVar

from .arrow_dataset import Dataset, _concatenate_map_style_datasets, _interleave_map_style_datasets
from .dataset_dict import DatasetDict, IterableDatasetDict
from .info import DatasetInfo
from .iterable_dataset import IterableDataset, _concatenate_iterable_datasets, _interleave_iterable_datasets
from .splits import NamedSplit
from .utils import logging
from .utils.py_utils import Literal


_A   =     logging.get_logger(__name__)


_A   =     TypeVar("DatasetType", Dataset, IterableDataset)






def    lowerCamelCase__				(				__lowerCAmelCase  :  List[DatasetType]    ,							__lowerCAmelCase  :  Optional[List[float]] = None    ,							__lowerCAmelCase  :  Optional[int] = None    ,							__lowerCAmelCase  :  Optional[DatasetInfo] = None    ,							__lowerCAmelCase  :  Optional[NamedSplit] = None    ,							__lowerCAmelCase  :  Literal["first_exhausted", "all_exhausted"] = "first_exhausted"    ,							):




			"""simple docstring"""


			from .arrow_dataset import Dataset
			from .iterable_dataset import IterableDataset

			if not datasets:
						raise ValueError("Unable to interleave an empty list of datasets."				)
			for i, dataset in enumerate(__lowerCAmelCase				):
						if not isinstance(__lowerCAmelCase    ,							(Dataset, IterableDataset)				):
									if isinstance(__lowerCAmelCase    ,							(DatasetDict, IterableDatasetDict)				):
												if not dataset:
															raise ValueError(
															    F"""Expected a list of Dataset objects or a list of IterableDataset objects, but element at position {i} """
															    "is an empty dataset dictionary."				)
												raise ValueError(
												    F"""Dataset at position {i} has at least one split: {list(__lowerCAmelCase				)}\n"""
												    F"""Please pick one to interleave with the other datasets, for example: dataset['{next(iter(__lowerCAmelCase				)				)}']"""				)
									raise ValueError(
									    F"""Expected a list of Dataset objects or a list of IterableDataset objects, but element at position {i} is a {type(__lowerCAmelCase				).__name__}."""				)
						if i == 0:
									lowerCAmelCase_	,  lowerCAmelCase_						=	(
									    (Dataset, IterableDataset) if isinstance(__lowerCAmelCase    ,							__lowerCAmelCase				) else (IterableDataset, Dataset)
									)
						elif not isinstance(__lowerCAmelCase    ,							__lowerCAmelCase				):
									raise ValueError(
									    F"""Unable to interleave a {dataset_type.__name__} (at position 0) with a {other_type.__name__} (at position {i}). Expected a list of Dataset objects or a list of IterableDataset objects."""				)
			if stopping_strategy not in ["first_exhausted", "all_exhausted"]:
						raise ValueError(F"""{stopping_strategy} is not supported. Please enter a valid stopping_strategy."""				)
			if dataset_type is Dataset:
						return _interleave_map_style_datasets(
						    __lowerCAmelCase    ,							__lowerCAmelCase    ,							__lowerCAmelCase    ,							info=__lowerCAmelCase    ,							split=__lowerCAmelCase    ,							stopping_strategy=__lowerCAmelCase				)
			else:
						return _interleave_iterable_datasets(
						    __lowerCAmelCase    ,							__lowerCAmelCase    ,							__lowerCAmelCase    ,							info=__lowerCAmelCase    ,							split=__lowerCAmelCase    ,							stopping_strategy=__lowerCAmelCase				)






def    lowerCamelCase__				(				__lowerCAmelCase  :  List[DatasetType]    ,							__lowerCAmelCase  :  Optional[DatasetInfo] = None    ,							__lowerCAmelCase  :  Optional[NamedSplit] = None    ,							__lowerCAmelCase  :  int = 0    ,							):




			"""simple docstring"""


			if not dsets:
						raise ValueError("Unable to concatenate an empty list of datasets."				)
			for i, dataset in enumerate(__lowerCAmelCase				):
						if not isinstance(__lowerCAmelCase    ,							(Dataset, IterableDataset)				):
									if isinstance(__lowerCAmelCase    ,							(DatasetDict, IterableDatasetDict)				):
												if not dataset:
															raise ValueError(
															    F"""Expected a list of Dataset objects or a list of IterableDataset objects, but element at position {i} """
															    "is an empty dataset dictionary."				)
												raise ValueError(
												    F"""Dataset at position {i} has at least one split: {list(__lowerCAmelCase				)}\n"""
												    F"""Please pick one to interleave with the other datasets, for example: dataset['{next(iter(__lowerCAmelCase				)				)}']"""				)
									raise ValueError(
									    F"""Expected a list of Dataset objects or a list of IterableDataset objects, but element at position {i} is a {type(__lowerCAmelCase				).__name__}."""				)
						if i == 0:
									lowerCAmelCase_	,  lowerCAmelCase_						=	(
									    (Dataset, IterableDataset) if isinstance(__lowerCAmelCase    ,							__lowerCAmelCase				) else (IterableDataset, Dataset)
									)
						elif not isinstance(__lowerCAmelCase    ,							__lowerCAmelCase				):
									raise ValueError(
									    F"""Unable to interleave a {dataset_type.__name__} (at position 0) with a {other_type.__name__} (at position {i}). Expected a list of Dataset objects or a list of IterableDataset objects."""				)
			if dataset_type is Dataset:
						return _concatenate_map_style_datasets(__lowerCAmelCase    ,							info=__lowerCAmelCase    ,							split=__lowerCAmelCase    ,							axis=__lowerCAmelCase				)
			else:
						return _concatenate_iterable_datasets(__lowerCAmelCase    ,							info=__lowerCAmelCase    ,							split=__lowerCAmelCase    ,							axis=__lowerCAmelCase				)



