





import enum
import os
from hashlib import shaaaa
from typing import Optional

from .. import config
from .logging import get_logger


SCREAMING_SNAKE_CASE__							:      Dict         =    get_logger(__name__)







class 	__lowerCAmelCase      (       enum.Enum	):
   _UpperCamelCase			:    Tuple  		=					"""all_checks"""
   _UpperCamelCase			:    Optional[int]  		=					"""basic_checks"""
   _UpperCamelCase			:    str  		=					"""no_checks"""







class 	__lowerCAmelCase      (       __a	):
   pass







class 	__lowerCAmelCase      (       __a	):
   pass







class 	__lowerCAmelCase      (       __a	):
   pass







class 	__lowerCAmelCase      (       __a	):
   pass







def    _A	(   lowerCamelCase				,			lowerCamelCase				,			lowerCamelCase=None ):
   if expected_checksums is None:
      logger.info("Unable to verify checksums." )
      return
   if len(set(lowerCamelCase ) - set(lowerCamelCase ) ) > 0:
      raise ExpectedMoreDownloadedFiles(str(set(lowerCamelCase ) - set(lowerCamelCase ) ) )
   if len(set(lowerCamelCase ) - set(lowerCamelCase ) ) > 0:
      raise UnexpectedDownloadedFile(str(set(lowerCamelCase ) - set(lowerCamelCase ) ) )
   a__						:    str   		=	[url for url in expected_checksums if expected_checksums[url] != recorded_checksums[url]]
   a__						:    str   		=	" for " + verification_name if verification_name is not None else ""
   if len(lowerCamelCase ) > 0:
      raise NonMatchingChecksumError(
          F"""Checksums didn\'t match{for_verification_name}:\n"""
          F"""{bad_urls}\n"""
          "Set `verification_mode='no_checks'` to skip checksums verification and ignore this error" )
   logger.info("All the checksums matched successfully" + for_verification_name )







class 	__lowerCAmelCase      (       __a	):
   pass







class 	__lowerCAmelCase      (       __a	):
   pass







class 	__lowerCAmelCase      (       __a	):
   pass







class 	__lowerCAmelCase      (       __a	):
   pass







def    _A	(   lowerCamelCase				,			lowerCamelCase ):
   if expected_splits is None:
      logger.info("Unable to verify splits sizes." )
      return
   if len(set(lowerCamelCase ) - set(lowerCamelCase ) ) > 0:
      raise ExpectedMoreSplits(str(set(lowerCamelCase ) - set(lowerCamelCase ) ) )
   if len(set(lowerCamelCase ) - set(lowerCamelCase ) ) > 0:
      raise UnexpectedSplits(str(set(lowerCamelCase ) - set(lowerCamelCase ) ) )
   a__						:    Any   		=	[
       {"expected": expected_splits[name], "recorded": recorded_splits[name]}
       for name in expected_splits
       if expected_splits[name].num_examples != recorded_splits[name].num_examples
   ]
   if len(lowerCamelCase ) > 0:
      raise NonMatchingSplitsSizesError(str(lowerCamelCase ) )
   logger.info("All the splits matched successfully." )






def    _A	(   lowerCamelCase				,			lowerCamelCase = True ):
   if record_checksum:
      a__						:    List[Any]   		=	shaaaa()
      with open(lowerCamelCase				,			"rb" ) as f:
         for chunk in iter(lambda: f.read(1 << 20 )				,			b"" ):
            m.update(lowerCamelCase )
         a__						:    str   		=	m.hexdigest()
   else:
      a__						:    Union[str, Any]   		=	None
   return {"num_bytes": os.path.getsize(lowerCamelCase ), "checksum": checksum}






def    _A	(   lowerCamelCase ):
   if dataset_size and config.IN_MEMORY_MAX_SIZE:
      return dataset_size < config.IN_MEMORY_MAX_SIZE
   else:
      return False



"""simple docstring"""






import os
from tempfile import TemporaryDirectory
from unittest import TestCase

import pytest
from absl.testing import parameterized

from datasets import config
from datasets.arrow_reader import HF_GCP_BASE_URL
from datasets.builder import DatasetBuilder
from datasets.dataset_dict import IterableDatasetDict
from datasets.iterable_dataset import IterableDataset
from datasets.load import dataset_module_factory, import_main_class
from datasets.utils.file_utils import cached_path


_lowercase							=				[
    {'''dataset''': '''wikipedia''', '''config_name''': '''20220301.de'''},
    {'''dataset''': '''wikipedia''', '''config_name''': '''20220301.en'''},
    {'''dataset''': '''wikipedia''', '''config_name''': '''20220301.fr'''},
    {'''dataset''': '''wikipedia''', '''config_name''': '''20220301.frr'''},
    {'''dataset''': '''wikipedia''', '''config_name''': '''20220301.it'''},
    {'''dataset''': '''wikipedia''', '''config_name''': '''20220301.simple'''},
    {'''dataset''': '''snli''', '''config_name''': '''plain_text'''},
    {'''dataset''': '''eli5''', '''config_name''': '''LFQA_reddit'''},
    {'''dataset''': '''wiki40b''', '''config_name''': '''en'''},
    {'''dataset''': '''wiki_dpr''', '''config_name''': '''psgs_w100.nq.compressed'''},
    {'''dataset''': '''wiki_dpr''', '''config_name''': '''psgs_w100.nq.no_index'''},
    {'''dataset''': '''wiki_dpr''', '''config_name''': '''psgs_w100.multiset.no_index'''},
    {'''dataset''': '''natural_questions''', '''config_name''': '''default'''},
]



def      lowerCAmelCase__			(		__magic_name__=True      )						->int:
			if with_config:
						return [
						    {
						        "testcase_name": d["dataset"] + "/" + d["config_name"],
						        "dataset": d["dataset"],
						        "config_name": d["config_name"],
						    }
						    for d in DATASETS_ON_HF_GCP
						]
			else:
						return [
						    {"testcase_name": dataset, "dataset": dataset} for dataset in {d["dataset"] for d in DATASETS_ON_HF_GCP}
						]

@parameterized.named_parameters(list_datasets_on_hf_gcp_parameters(with_config=__a       )       )
class 					__a     ( __a       ):



							'''simple docstring'''







							_lowerCamelCase					:			int          =   None
							_lowerCamelCase					:			int          =   None
							def   SCREAMING_SNAKE_CASE						(     self  ,    _lowerCamelCase  ,    _lowerCamelCase       )			->							Optional[Any]:




										'''simple docstring'''
										with TemporaryDirectory() as tmp_dir:
													__lowercase       =       dataset_module_factory(_lowerCamelCase  ,    cache_dir=_lowerCamelCase       )

													__lowercase       =       import_main_class(dataset_module.module_path  ,    dataset=_lowerCamelCase       )

													__lowercase       =       builder_cls(
													    cache_dir=_lowerCamelCase  ,    config_name=_lowerCamelCase  ,    hash=dataset_module.hash  ,    )

													__lowercase       =       "/".join(
													    [
													        HF_GCP_BASE_URL,
													        builder_instance._relative_data_dir(with_hash=_lowerCamelCase       ).replace(os.sep  ,    "/"       ),
													        config.DATASET_INFO_FILENAME,
													    ]       )
													__lowercase       =       cached_path(_lowerCamelCase  ,    cache_dir=_lowerCamelCase       )
													self.assertTrue(os.path.exists(_lowerCamelCase       )       )





@pytest.mark.integration
def      lowerCAmelCase__			(		__magic_name__      )						->str:
			__lowercase       =       tmp_path_factory.mktemp("test_hf_gcp"      ) / "test_wikipedia_simple"
			__lowercase       =       dataset_module_factory("wikipedia"			,   cache_dir=__magic_name__      )
			__lowercase       =       import_main_class(dataset_module.module_path      )
			__lowercase       =       builder_cls(
			    cache_dir=__magic_name__			,   config_name="20220301.frr"			,   hash=dataset_module.hash			,   )
			# use the HF cloud storage, not the original download_and_prepare that uses apache-beam
			__lowercase       =       None
			builder_instance.download_and_prepare()
			__lowercase       =       builder_instance.as_dataset()
			assert ds







@pytest.mark.integration
def      lowerCAmelCase__			(		__magic_name__      )						->Any:
			__lowercase       =       dataset_module_factory("wikipedia"			,   cache_dir=__magic_name__      )
			__lowercase       =       import_main_class(dataset_module.module_path			,   dataset=__magic_name__      )
			__lowercase       =       builder_cls(
			    cache_dir=__magic_name__			,   config_name="20220301.frr"			,   hash=dataset_module.hash			,   )
			__lowercase       =       builder_instance.as_streaming_dataset()
			assert ds
			assert isinstance(__magic_name__			,   __magic_name__      )
			assert "train" in ds
			assert isinstance(ds["train"]			,   __magic_name__      )
			assert next(iter(ds["train"]      )      )





