





"""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    _SCREAMING_SNAKE_CASE	(			_lowercase		:					List[str]					, _lowercase		:					Any					, _lowercase		:					Union[str, Any]					, _lowercase		:					List[str]					, _lowercase		:					Union[str, Any]					, _lowercase		:					Tuple					, _lowercase		:					Dict					, _lowercase		:					Optional[int]					, _lowercase		:					List[str]					, _lowercase		:					Union[str, Any]					, _lowercase		:					str					, _lowercase		:					int					, )				->str:






	'''simple docstring'''






	a   :	Optional[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),
	}
	a, a   :	int			=       input_paths_and_base_extractors[compression_format]
	if input_path is None:
		a   :	List[str]			=       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      )
	a   :	Dict			=       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
			a   :	List[Any]			=       file_path.read_text(encoding="utf-8"      )
	else:
		a   :	Optional[Any]			=       output_path.read_text(encoding="utf-8"      )
	a   :	Optional[int]			=       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	(			_lowercase		:					Union[str, Any]					, _lowercase		:					Optional[Any]					, _lowercase		:					str					, _lowercase		:					Dict					, _lowercase		:					Union[str, Any]					, _lowercase		:					List[Any]					, _lowercase		:					str					, _lowercase		:					Any					, _lowercase		:					Optional[int]					, _lowercase		:					Any					, _lowercase		:					List[Any]					, _lowercase		:					Optional[int]					, )				->Union[str, Any]:






	'''simple docstring'''






	a   :	str			=       {
	    "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,
	}
	a   :	List[Any]			=       input_paths[compression_format]
	if input_path is None:
		a   :	List[str]			=       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      )
	a   :	str			=       Extractor.infer_extractor_format(_lowercase      )
	assert extractor_format is not None
	a   :	Dict			=       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
			a   :	Optional[int]			=       file_path.read_text(encoding="utf-8"      )
	else:
		a   :	Optional[int]			=       output_path.read_text(encoding="utf-8"      )
	a   :	List[str]			=       text_file.read_text(encoding="utf-8"      )
	assert extracted_file_content == expected_file_content






@pytest.fixture
def    _SCREAMING_SNAKE_CASE	(			_lowercase		:					Tuple					, _lowercase		:					Optional[Any]      )				->Dict:






	'''simple docstring'''






	import tarfile

	a   :	int			=       tmp_path / "data_dot_dot"
	directory.mkdir()
	a   :	Optional[Any]			=       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	(			_lowercase		:					List[str]      )				->Optional[Any]:






	'''simple docstring'''






	import tarfile

	a   :	Dict			=       tmp_path / "data_sym_link"
	directory.mkdir()
	a   :	str			=       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	(			_lowercase		:					Any					, _lowercase		:					List[str]					, _lowercase		:					int					, _lowercase		:					int					, _lowercase		:					str					, _lowercase		:					int      )				->Optional[Any]:






	'''simple docstring'''






	a   :	Any			=       {
	    "tar_file_with_dot_dot": tar_file_with_dot_dot,
	    "tar_file_with_sym_link": tar_file_with_sym_link,
	}
	a   :	List[str]			=       insecure_tar_files[insecure_tar_file]
	a   :	str			=       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	(			_lowercase		:					Tuple      )				->List[str]:






	'''simple docstring'''






	a   :	List[Any]			=       tmpdir / "not_a_zip_file"
	# From: https://github.com/python/cpython/pull/5053
	a   :	Any			=       (
	    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"""




import multiprocessing
import time

from arguments import PretokenizationArguments
from datasets import load_dataset

from transformers import AutoTokenizer, HfArgumentParser






def    _SCREAMING_SNAKE_CASE	(			_lowercase		:					List[str]      )				->int:






	'''simple docstring'''






	a   :	int			=       {}
	a   :	Union[str, Any]			=       tokenizer(example["content"]					, truncation=_lowercase      )["input_ids"]
	a   :	Any			=       len(example["content"]      ) / len(output["input_ids"]      )
	return output


a		:				int  			=    HfArgumentParser(PretokenizationArguments)
a		:				Optional[int]  			=    parser.parse_args()
if args.num_workers is None:
		a		:				Tuple  			=    multiprocessing.cpu_count()
a		:				Optional[int]  			=    AutoTokenizer.from_pretrained(args.tokenizer_dir)

a		:				Dict  			=    time.time()
a		:				Tuple  			=    load_dataset(args.dataset_name, split='''train''')
print(F'''Dataset loaded in {time.time()-t_start:.2f}s''')

a		:				Dict  			=    time.time()
a		:				Tuple  			=    ds.map(
    tokenize,
    num_proc=args.num_workers,
    remove_columns=[
        '''repo_name''',
        '''path''',
        '''copies''',
        '''size''',
        '''content''',
        '''license''',
        '''hash''',
        '''line_mean''',
        '''line_max''',
        '''alpha_frac''',
        '''autogenerated''',
    ],
)
print(F'''Dataset tokenized in {time.time()-t_start:.2f}s''')

a		:				Tuple  			=    time.time()
ds.push_to_hub(args.tokenized_data_repo)







print(F'''Data pushed to the hub in {time.time()-t_start:.2f}s''')


