



import os
import zipfile

import pytest

from datasets.utils.extract import (
    BzipaExtractor,
    Extractor,
    GzipExtractor,
    LzaExtractor,
    SevenZipExtractor,
    TarExtractor,
    XzExtractor,
    ZipExtractor,
    ZstdExtractor,
)

from .utils import require_lza, require_pyazr, require_zstandard


@pytest.mark.parametrize(
    """compression_format, is_archive""" ,  [
        ("""7z""", True),
        ("""bz2""", False),
        ("""gzip""", False),
        ("""lz4""", False),
        ("""tar""", True),
        ("""xz""", False),
        ("""zip""", True),
        ("""zstd""", False),
    ] ,  )
def 			_SCREAMING_SNAKE_CASE						(__lowerCAmelCase ,  __lowerCAmelCase ,  __lowerCAmelCase ,  __lowerCAmelCase ,  __lowerCAmelCase ,  __lowerCAmelCase ,  __lowerCAmelCase ,  __lowerCAmelCase ,  __lowerCAmelCase ,  __lowerCAmelCase ,  __lowerCAmelCase ,  __lowerCAmelCase ,  ) ->						str:







  '''simple docstring'''


  lowercase_								= {
      "7z": (seven_zip_file, SevenZipExtractor),
      "bz2": (bza_file, BzipaExtractor),
      "gzip": (gz_file, GzipExtractor),
      "lz4": (lza_file, LzaExtractor),
      "tar": (tar_file, TarExtractor),
      "xz": (xz_file, XzExtractor),
      "zip": (zip_file, ZipExtractor),
      "zstd": (zstd_file, ZstdExtractor),
  }
  lowercase_								= input_paths_and_base_extractors[compression_format]
  if input_path is None:
    lowercase_								= F'''for \'{compression_format}\' compression_format, '''
    if compression_format == "7z":
      reason += require_pyazr.kwargs["reason"]
    elif compression_format == "lz4":
      reason += require_lza.kwargs["reason"]
    elif compression_format == "zstd":
      reason += require_zstandard.kwargs["reason"]
    pytest.skip(_lowercase							)
  assert base_extractor.is_extractable(_lowercase							)
  lowercase_								= tmp_path / ("extracted" if is_archive else "extracted.txt")
  base_extractor.extract(_lowercase ,  _lowercase							)
  if is_archive:
    assert output_path.is_dir()
    for file_path in output_path.iterdir():
      assert file_path.name == text_file.name
      lowercase_								= file_path.read_text(encoding="""utf-8"""							)
  else:
    lowercase_								= output_path.read_text(encoding="""utf-8"""							)
  lowercase_								= text_file.read_text(encoding="""utf-8"""							)
  assert extracted_file_content == expected_file_content


@pytest.mark.parametrize(
    """compression_format, is_archive""" ,  [
        ("""7z""", True),
        ("""bz2""", False),
        ("""gzip""", False),
        ("""lz4""", False),
        ("""tar""", True),
        ("""xz""", False),
        ("""zip""", True),
        ("""zstd""", False),
    ] ,  )
def 			_SCREAMING_SNAKE_CASE						(__lowerCAmelCase ,  __lowerCAmelCase ,  __lowerCAmelCase ,  __lowerCAmelCase ,  __lowerCAmelCase ,  __lowerCAmelCase ,  __lowerCAmelCase ,  __lowerCAmelCase ,  __lowerCAmelCase ,  __lowerCAmelCase ,  __lowerCAmelCase ,  __lowerCAmelCase ,  ) ->						Union[str, Any]:







  '''simple docstring'''


  lowercase_								= {
      "7z": seven_zip_file,
      "bz2": bza_file,
      "gzip": gz_file,
      "lz4": lza_file,
      "tar": tar_file,
      "xz": xz_file,
      "zip": zip_file,
      "zstd": zstd_file,
  }
  lowercase_								= input_paths[compression_format]
  if input_path is None:
    lowercase_								= F'''for \'{compression_format}\' compression_format, '''
    if compression_format == "7z":
      reason += require_pyazr.kwargs["reason"]
    elif compression_format == "lz4":
      reason += require_lza.kwargs["reason"]
    elif compression_format == "zstd":
      reason += require_zstandard.kwargs["reason"]
    pytest.skip(_lowercase							)
  lowercase_								= Extractor.infer_extractor_format(_lowercase							)
  assert extractor_format is not None
  lowercase_								= tmp_path / ("extracted" if is_archive else "extracted.txt")
  Extractor.extract(_lowercase ,  _lowercase ,  _lowercase							)
  if is_archive:
    assert output_path.is_dir()
    for file_path in output_path.iterdir():
      assert file_path.name == text_file.name
      lowercase_								= file_path.read_text(encoding="""utf-8"""							)
  else:
    lowercase_								= output_path.read_text(encoding="""utf-8"""							)
  lowercase_								= text_file.read_text(encoding="""utf-8"""							)
  assert extracted_file_content == expected_file_content


@pytest.fixture
def 			_SCREAMING_SNAKE_CASE						(__lowerCAmelCase ,  __lowerCAmelCase							) ->						Dict:







  '''simple docstring'''


  import tarfile

  lowercase_								= tmp_path / "data_dot_dot"
  directory.mkdir()
  lowercase_								= directory / "tar_file_with_dot_dot.tar"
  with tarfile.TarFile(_lowercase ,  """w"""							) as f:
    f.add(_lowercase ,  arcname=os.path.join("""..""" ,  text_file.name							)							)
  return path


@pytest.fixture
def 			_SCREAMING_SNAKE_CASE						(__lowerCAmelCase							) ->						Optional[Any]:







  '''simple docstring'''


  import tarfile

  lowercase_								= tmp_path / "data_sym_link"
  directory.mkdir()
  lowercase_								= directory / "tar_file_with_sym_link.tar"
  os.symlink("""..""" ,  directory / """subdir""" ,  target_is_directory=_lowercase							)
  with tarfile.TarFile(_lowercase ,  """w"""							) as f:
    f.add(str(directory / """subdir"""							) ,  arcname="""subdir"""							)  # str required by os.readlink on Windows and Python < 3.8
  return path


@pytest.mark.parametrize(
    """insecure_tar_file, error_log""" ,  [("""tar_file_with_dot_dot""", """illegal path"""), ("""tar_file_with_sym_link""", """Symlink""")] ,  )
def 			_SCREAMING_SNAKE_CASE						(__lowerCAmelCase ,  __lowerCAmelCase ,  __lowerCAmelCase ,  __lowerCAmelCase ,  __lowerCAmelCase ,  __lowerCAmelCase							) ->						Optional[Any]:







  '''simple docstring'''


  lowercase_								= {
      "tar_file_with_dot_dot": tar_file_with_dot_dot,
      "tar_file_with_sym_link": tar_file_with_sym_link,
  }
  lowercase_								= insecure_tar_files[insecure_tar_file]
  lowercase_								= tmp_path / "extracted"
  TarExtractor.extract(_lowercase ,  _lowercase							)
  assert caplog.text
  for record in caplog.records:
    assert record.levelname == "ERROR"
    assert error_log in record.msg


def 			_SCREAMING_SNAKE_CASE						(__lowerCAmelCase							) ->						List[str]:







  '''simple docstring'''


  lowercase_								= tmpdir / "not_a_zip_file"
  # From: https://github.com/python/cpython/pull/5053
  lowercase_								= (
      B"\x89PNG\r\n\x1a\n\x00\x00\x00\rIHDR\x00\x00\x00\x01\x00\x00"
      B"\x00\x02\x08\x06\x00\x00\x00\x99\x81\xb6'\x00\x00\x00\x15I"
      B"DATx\x01\x01\n\x00\xf5\xff\x00PK\x05\x06\x00PK\x06\x06\x07"
      B"\xac\x01N\xc6|a\r\x00\x00\x00\x00IEND\xaeB`\x82"
  )
  with not_a_zip_file.open("""wb"""							) as f:
    f.write(_lowercase							)
  assert zipfile.is_zipfile(str(_lowercase							)							)  # is a false positive for `zipfile`
  assert not ZipExtractor.is_extractable(_lowercase							)  # but we're right






"""simple docstring"""
from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


UpperCAmelCase						:		Union[str, Any]			= {
    "configuration_longformer": [
        "LONGFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "LongformerConfig",
        "LongformerOnnxConfig",
    ],
    "tokenization_longformer": ["LongformerTokenizer"],
}

try:
       if not is_tokenizers_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       UpperCAmelCase						:		List[Any]			= ["LongformerTokenizerFast"]

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       UpperCAmelCase						:		Tuple			= [
           "LONGFORMER_PRETRAINED_MODEL_ARCHIVE_LIST",
           "LongformerForMaskedLM",
           "LongformerForMultipleChoice",
           "LongformerForQuestionAnswering",
           "LongformerForSequenceClassification",
           "LongformerForTokenClassification",
           "LongformerModel",
           "LongformerPreTrainedModel",
           "LongformerSelfAttention",
       ]

try:
       if not is_tf_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       UpperCAmelCase						:		List[Any]			= [
           "TF_LONGFORMER_PRETRAINED_MODEL_ARCHIVE_LIST",
           "TFLongformerForMaskedLM",
           "TFLongformerForMultipleChoice",
           "TFLongformerForQuestionAnswering",
           "TFLongformerForSequenceClassification",
           "TFLongformerForTokenClassification",
           "TFLongformerModel",
           "TFLongformerPreTrainedModel",
           "TFLongformerSelfAttention",
       ]


if TYPE_CHECKING:
       from .configuration_longformer import (
           LONGFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
           LongformerConfig,
           LongformerOnnxConfig,
       )
       from .tokenization_longformer import LongformerTokenizer

       try:
              if not is_tokenizers_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .tokenization_longformer_fast import LongformerTokenizerFast

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_longformer import (
                  LONGFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
                  LongformerForMaskedLM,
                  LongformerForMultipleChoice,
                  LongformerForQuestionAnswering,
                  LongformerForSequenceClassification,
                  LongformerForTokenClassification,
                  LongformerModel,
                  LongformerPreTrainedModel,
                  LongformerSelfAttention,
              )

       try:
              if not is_tf_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_tf_longformer import (
                  TF_LONGFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
                  TFLongformerForMaskedLM,
                  TFLongformerForMultipleChoice,
                  TFLongformerForQuestionAnswering,
                  TFLongformerForSequenceClassification,
                  TFLongformerForTokenClassification,
                  TFLongformerModel,
                  TFLongformerPreTrainedModel,
                  TFLongformerSelfAttention,
              )

else:
       import sys

       UpperCAmelCase						:		Optional[Any]			= _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)

