
"""simple docstring"""
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    _lowerCAmelCase    (     lowerCamelCase__							:							int,						lowerCamelCase__							:							Any,						lowerCamelCase__							:							Union[str, Any],						lowerCamelCase__							:							List[str],						lowerCamelCase__							:							Optional[Any],						lowerCamelCase__							:							Optional[Any],						lowerCamelCase__							:							Tuple,						lowerCamelCase__							:							List[str],						lowerCamelCase__							:							Union[str, Any],						lowerCamelCase__							:							Tuple,						lowerCamelCase__							:							Optional[Any],						lowerCamelCase__							:							Any,						)  ->    int:
  _SCREAMING_SNAKE_CASE   :				List[Any]							    = {
      "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),
  }
  _SCREAMING_SNAKE_CASE    ,		_SCREAMING_SNAKE_CASE   :				Union[str, Any]							    = input_paths_and_base_extractors[compression_format]
  if input_path is None:
    _SCREAMING_SNAKE_CASE   :				List[Any]							    = 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(lowerCamelCase__				)
  assert base_extractor.is_extractable(lowerCamelCase__				)
  _SCREAMING_SNAKE_CASE   :				int							    = tmp_path / ("extracted" if is_archive else "extracted.txt")
  base_extractor.extract(lowerCamelCase__,						lowerCamelCase__				)
  if is_archive:
    assert output_path.is_dir()
    for file_path in output_path.iterdir():
      assert file_path.name == text_file.name
      _SCREAMING_SNAKE_CASE   :				int							    = file_path.read_text(encoding="utf-8"				)
  else:
    _SCREAMING_SNAKE_CASE   :				Any							    = output_path.read_text(encoding="utf-8"				)
  _SCREAMING_SNAKE_CASE   :				Optional[Any]							    = 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    _lowerCAmelCase    (     lowerCamelCase__							:							Tuple,						lowerCamelCase__							:							int,						lowerCamelCase__							:							List[Any],						lowerCamelCase__							:							List[Any],						lowerCamelCase__							:							List[Any],						lowerCamelCase__							:							Union[str, Any],						lowerCamelCase__							:							int,						lowerCamelCase__							:							Optional[Any],						lowerCamelCase__							:							Tuple,						lowerCamelCase__							:							int,						lowerCamelCase__							:							str,						lowerCamelCase__							:							Union[str, Any],						)  ->    Optional[int]:
  _SCREAMING_SNAKE_CASE   :				Dict							    = {
      "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,
  }
  _SCREAMING_SNAKE_CASE   :				str							    = input_paths[compression_format]
  if input_path is None:
    _SCREAMING_SNAKE_CASE   :				Optional[int]							    = 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(lowerCamelCase__				)
  _SCREAMING_SNAKE_CASE   :				str							    = Extractor.infer_extractor_format(lowerCamelCase__				)
  assert extractor_format is not None
  _SCREAMING_SNAKE_CASE   :				int							    = tmp_path / ("extracted" if is_archive else "extracted.txt")
  Extractor.extract(lowerCamelCase__,						lowerCamelCase__,						lowerCamelCase__				)
  if is_archive:
    assert output_path.is_dir()
    for file_path in output_path.iterdir():
      assert file_path.name == text_file.name
      _SCREAMING_SNAKE_CASE   :				Optional[Any]							    = file_path.read_text(encoding="utf-8"				)
  else:
    _SCREAMING_SNAKE_CASE   :				List[str]							    = output_path.read_text(encoding="utf-8"				)
  _SCREAMING_SNAKE_CASE   :				Optional[Any]							    = text_file.read_text(encoding="utf-8"				)
  assert extracted_file_content == expected_file_content





@pytest.fixture
def    _lowerCAmelCase    (     lowerCamelCase__							:							int,						lowerCamelCase__							:							str				)  ->    Union[str, Any]:
  import tarfile

  _SCREAMING_SNAKE_CASE   :				List[str]							    = tmp_path / "data_dot_dot"
  directory.mkdir()
  _SCREAMING_SNAKE_CASE   :				Union[str, Any]							    = directory / "tar_file_with_dot_dot.tar"
  with tarfile.TarFile(lowerCamelCase__,						"w"				) as f:
    f.add(lowerCamelCase__,						arcname=os.path.join("..",						text_file.name				)				)
  return path





@pytest.fixture
def    _lowerCAmelCase    (     lowerCamelCase__							:							Optional[int]				)  ->    Any:
  import tarfile

  _SCREAMING_SNAKE_CASE   :				Dict							    = tmp_path / "data_sym_link"
  directory.mkdir()
  _SCREAMING_SNAKE_CASE   :				Union[str, Any]							    = directory / "tar_file_with_sym_link.tar"
  os.symlink("..",						directory / "subdir",						target_is_directory=lowerCamelCase__				)
  with tarfile.TarFile(lowerCamelCase__,						"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    _lowerCAmelCase    (     lowerCamelCase__							:							Dict,						lowerCamelCase__							:							str,						lowerCamelCase__							:							int,						lowerCamelCase__							:							int,						lowerCamelCase__							:							str,						lowerCamelCase__							:							int				)  ->    Optional[Any]:
  _SCREAMING_SNAKE_CASE   :				str							    = {
      "tar_file_with_dot_dot": tar_file_with_dot_dot,
      "tar_file_with_sym_link": tar_file_with_sym_link,
  }
  _SCREAMING_SNAKE_CASE   :				int							    = insecure_tar_files[insecure_tar_file]
  _SCREAMING_SNAKE_CASE   :				List[Any]							    = tmp_path / "extracted"
  TarExtractor.extract(lowerCamelCase__,						lowerCamelCase__				)
  assert caplog.text
  for record in caplog.records:
    assert record.levelname == "ERROR"
    assert error_log in record.msg





def    _lowerCAmelCase    (     lowerCamelCase__							:							int				)  ->    int:
  # We should have less false positives than zipfile.is_zipfile
  # We do that by checking only the magic number
  _SCREAMING_SNAKE_CASE   :				Optional[Any]							    = tmpdir / "not_a_zip_file"
  # From: https://github.com/python/cpython/pull/5053
  _SCREAMING_SNAKE_CASE   :				Dict							    = (
      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(lowerCamelCase__				)
  assert zipfile.is_zipfile(str(lowerCamelCase__				)				)  # is a false positive for `zipfile`
  assert not ZipExtractor.is_extractable(lowerCamelCase__				)  # but we're right





"""simple docstring"""
import itertools
from dataclasses import dataclass
from typing import List, Optional

import pyarrow as pa
import pyarrow.parquet as pq

import datasets
from datasets.table import table_cast


lowercase_       :						List[str]     					=	datasets.utils.logging.get_logger(__name__)
@dataclass
class 			UpperCamelCase      (							datasets.BuilderConfig  ):
     A__      =			10000
     A__      =			None
     A__      =			None
class 			UpperCamelCase      (							datasets.ArrowBasedBuilder  ):
     A__      =			ParquetConfig
     def 				__SCREAMING_SNAKE_CASE							(     self				):




       """simple docstring"""


       return datasets.DatasetInfo(features=self.config.features				)
     def 				__SCREAMING_SNAKE_CASE							(     self  ,     snake_case__				):




       """simple docstring"""


       if not self.config.data_files:
         raise ValueError(F'''At least one data file must be specified, but got data_files={self.config.data_files}'''				)
       _SCREAMING_SNAKE_CASE   :				List[Any]							    = dl_manager.download_and_extract(self.config.data_files				)
       if isinstance(snake_case__  ,     (str, list, tuple)				):
         _SCREAMING_SNAKE_CASE   :				int							    = data_files
         if isinstance(snake_case__  ,     snake_case__				):
           _SCREAMING_SNAKE_CASE   :				List[Any]							    = [files]
         # Use `dl_manager.iter_files` to skip hidden files in an extracted archive
         _SCREAMING_SNAKE_CASE   :				Optional[Any]							    = [dl_manager.iter_files(snake_case__				) for file in files]
         return [datasets.SplitGenerator(name=datasets.Split.TRAIN  ,     gen_kwargs={"files": files}				)]
       _SCREAMING_SNAKE_CASE   :				Tuple							    = []
       for split_name, files in data_files.items():
         if isinstance(snake_case__  ,     snake_case__				):
           _SCREAMING_SNAKE_CASE   :				Optional[int]							    = [files]
         # Use `dl_manager.iter_files` to skip hidden files in an extracted archive
         _SCREAMING_SNAKE_CASE   :				Tuple							    = [dl_manager.iter_files(snake_case__				) for file in files]
         # Infer features is they are stoed in the arrow schema
         if self.info.features is None:
           for file in itertools.chain.from_iterable(snake_case__				):
             with open(snake_case__  ,     "rb"				) as f:
               _SCREAMING_SNAKE_CASE   :				Optional[int]							    = datasets.Features.from_arrow_schema(pq.read_schema(snake_case__				)				)
             break
         splits.append(datasets.SplitGenerator(name=snake_case__  ,     gen_kwargs={"files": files}				)				)
       return splits
     def 				__SCREAMING_SNAKE_CASE							(     self  ,     snake_case__				):




       """simple docstring"""


       if self.info.features is not None:
         # more expensive cast to support nested features with keys in a different order
         # allows str <-> int/float or str to Audio for example
         _SCREAMING_SNAKE_CASE   :				Union[str, Any]							    = table_cast(snake_case__  ,     self.info.features.arrow_schema				)
       return pa_table




     def 				__SCREAMING_SNAKE_CASE							(     self  ,     snake_case__				):




       """simple docstring"""


       _SCREAMING_SNAKE_CASE   :				Any							    = self.info.features.arrow_schema if self.info.features is not None else None
       if self.info.features is not None and self.config.columns is not None:
         if sorted(field.name for field in schema				) != sorted(self.config.columns				):
           raise ValueError(
               F'''Tried to load parquet data with columns \'{self.config.columns}\' with mismatching features \'{self.info.features}\''''				)
       for file_idx, file in enumerate(itertools.chain.from_iterable(snake_case__				)				):
         with open(snake_case__  ,     "rb"				) as f:
           _SCREAMING_SNAKE_CASE   :				List[Any]							    = pq.ParquetFile(snake_case__				)
           try:
             for batch_idx, record_batch in enumerate(
                 parquet_file.iter_batches(batch_size=self.config.batch_size  ,     columns=self.config.columns				)				):
               _SCREAMING_SNAKE_CASE   :				int							    = pa.Table.from_batches([record_batch]				)
               # Uncomment for debugging (will print the Arrow table size and elements)
               # logger.warning(f"pa_table: {pa_table} num rows: {pa_table.num_rows}")
               # logger.warning('\n'.join(str(pa_table.slice(i, 1).to_pydict()) for i in range(pa_table.num_rows)))
               yield F'''{file_idx}_{batch_idx}''', self._cast_table(snake_case__				)
           except ValueError as e:
             logger.error(F'''Failed to read file \'{file}\' with error {type(snake_case__				)}: {e}'''				)
             raise



