





"""simple docstring"""





import json
import os
from pathlib import Path

import pytest

from datasets.download.download_config import DownloadConfig
from datasets.download.download_manager import DownloadManager
from datasets.utils.file_utils import hash_url_to_filename


SCREAMING_SNAKE_CASE__					=   "http://www.mocksite.com/file1.txt"
SCREAMING_SNAKE_CASE__					=   "\"text\": [\"foo\", \"foo\"]"
SCREAMING_SNAKE_CASE__					=   "6d8ce9aa78a471c7477201efbeabd3bb01ac2e7d100a6dc024ba1608361f90a8"

class 		lowercase					:
      _SCREAMING_SNAKE_CASE					=      200
      _SCREAMING_SNAKE_CASE					=      {'Content-Length': '100'}
      _SCREAMING_SNAKE_CASE					=      {}





      def     _snake_case			(       self      ,						**lowercase )		->     List[str]:
            return [bytes(lowercase      ,						"""utf-8""" )]







def 			UpperCAmelCase__							(  *SCREAMING_SNAKE_CASE     :						Any							,						**SCREAMING_SNAKE_CASE     :						List[str]			):







      '''simple docstring'''




      return MockResponse()


@pytest.mark.parametrize("""urls_type"""							,						[str, list, dict]			)
def 			UpperCAmelCase__							(  SCREAMING_SNAKE_CASE     :						Tuple							,						SCREAMING_SNAKE_CASE     :						Tuple							,						SCREAMING_SNAKE_CASE     :						Optional[Any]			):







      '''simple docstring'''




      import requests

      monkeypatch.setattr(SCREAMING_SNAKE_CASE							,						"""request"""							,						SCREAMING_SNAKE_CASE			)

      lowerCAmelCase  						=       URL
      if issubclass(SCREAMING_SNAKE_CASE							,						SCREAMING_SNAKE_CASE			):
            lowerCAmelCase  						=       url
      elif issubclass(SCREAMING_SNAKE_CASE							,						SCREAMING_SNAKE_CASE			):
            lowerCAmelCase  						=       [url]
      elif issubclass(SCREAMING_SNAKE_CASE							,						SCREAMING_SNAKE_CASE			):
            lowerCAmelCase  						=       {"""train""": url}
      lowerCAmelCase  						=       """dummy"""
      lowerCAmelCase  						=       """downloads"""
      lowerCAmelCase  						=       tmp_path
      lowerCAmelCase  						=       DownloadConfig(
          cache_dir=os.path.join(SCREAMING_SNAKE_CASE							,						SCREAMING_SNAKE_CASE			)							,						use_etag=SCREAMING_SNAKE_CASE							,						)
      lowerCAmelCase  						=       DownloadManager(dataset_name=SCREAMING_SNAKE_CASE							,						download_config=SCREAMING_SNAKE_CASE			)
      lowerCAmelCase  						=       dl_manager.download(SCREAMING_SNAKE_CASE			)
      lowerCAmelCase  						=       urls
      for downloaded_paths in [downloaded_paths]:
            if isinstance(SCREAMING_SNAKE_CASE							,						SCREAMING_SNAKE_CASE			):
                  lowerCAmelCase  						=       [downloaded_paths]
                  lowerCAmelCase  						=       [urls]
            elif isinstance(SCREAMING_SNAKE_CASE							,						SCREAMING_SNAKE_CASE			):
                  assert "train" in downloaded_paths.keys()
                  lowerCAmelCase  						=       downloaded_paths.values()
                  lowerCAmelCase  						=       urls.values()
            assert downloaded_paths
            for downloaded_path, input_url in zip(SCREAMING_SNAKE_CASE							,						SCREAMING_SNAKE_CASE			):
                  assert downloaded_path == dl_manager.downloaded_paths[input_url]
                  lowerCAmelCase  						=       Path(SCREAMING_SNAKE_CASE			)
                  lowerCAmelCase  						=       downloaded_path.parts
                  assert parts[-1] == HASH
                  assert parts[-2] == cache_subdir
                  assert downloaded_path.exists()
                  lowerCAmelCase  						=       downloaded_path.read_text()
                  assert content == CONTENT
                  lowerCAmelCase  						=       downloaded_path.with_suffix(""".json"""			)
                  assert metadata_downloaded_path.exists()
                  lowerCAmelCase  						=       json.loads(metadata_downloaded_path.read_text()			)
                  assert metadata_content == {"url": URL, "etag": None}


@pytest.mark.parametrize("""paths_type"""							,						[str, list, dict]			)
def 			UpperCAmelCase__							(  SCREAMING_SNAKE_CASE     :						Optional[Any]							,						SCREAMING_SNAKE_CASE     :						List[str]							,						SCREAMING_SNAKE_CASE     :						Dict			):







      '''simple docstring'''




      lowerCAmelCase  						=       str(SCREAMING_SNAKE_CASE			)
      if issubclass(SCREAMING_SNAKE_CASE							,						SCREAMING_SNAKE_CASE			):
            lowerCAmelCase  						=       filename
      elif issubclass(SCREAMING_SNAKE_CASE							,						SCREAMING_SNAKE_CASE			):
            lowerCAmelCase  						=       [filename]
      elif issubclass(SCREAMING_SNAKE_CASE							,						SCREAMING_SNAKE_CASE			):
            lowerCAmelCase  						=       {"""train""": filename}
      lowerCAmelCase  						=       """dummy"""
      lowerCAmelCase  						=       xz_file.parent
      lowerCAmelCase  						=       """extracted"""
      lowerCAmelCase  						=       DownloadConfig(
          cache_dir=SCREAMING_SNAKE_CASE							,						use_etag=SCREAMING_SNAKE_CASE							,						)
      lowerCAmelCase  						=       DownloadManager(dataset_name=SCREAMING_SNAKE_CASE							,						download_config=SCREAMING_SNAKE_CASE			)
      lowerCAmelCase  						=       dl_manager.extract(SCREAMING_SNAKE_CASE			)
      lowerCAmelCase  						=       paths
      for extracted_paths in [extracted_paths]:
            if isinstance(SCREAMING_SNAKE_CASE							,						SCREAMING_SNAKE_CASE			):
                  lowerCAmelCase  						=       [extracted_paths]
                  lowerCAmelCase  						=       [paths]
            elif isinstance(SCREAMING_SNAKE_CASE							,						SCREAMING_SNAKE_CASE			):
                  assert "train" in extracted_paths.keys()
                  lowerCAmelCase  						=       extracted_paths.values()
                  lowerCAmelCase  						=       paths.values()
            assert extracted_paths
            for extracted_path, input_path in zip(SCREAMING_SNAKE_CASE							,						SCREAMING_SNAKE_CASE			):
                  assert extracted_path == dl_manager.extracted_paths[input_path]
                  lowerCAmelCase  						=       Path(SCREAMING_SNAKE_CASE			)
                  lowerCAmelCase  						=       extracted_path.parts
                  assert parts[-1] == hash_url_to_filename(SCREAMING_SNAKE_CASE							,						etag=SCREAMING_SNAKE_CASE			)
                  assert parts[-2] == extracted_subdir
                  assert extracted_path.exists()
                  lowerCAmelCase  						=       extracted_path.read_text()
                  lowerCAmelCase  						=       text_file.read_text()
                  assert extracted_file_content == expected_file_content


def 			UpperCAmelCase__							(  SCREAMING_SNAKE_CASE     :						Tuple							,						SCREAMING_SNAKE_CASE     :						Optional[int]			):







      '''simple docstring'''




      assert path.endswith(""".jsonl"""			)
      for num_items, line in enumerate(SCREAMING_SNAKE_CASE							,						start=1			):
            lowerCAmelCase  						=       json.loads(line.decode("""utf-8"""			)			)
            assert item.keys() == {"col_1", "col_2", "col_3"}
      assert num_items == 4


@pytest.mark.parametrize("""archive_jsonl"""							,						["""tar_jsonl_path""", """zip_jsonl_path"""]			)
def 			UpperCAmelCase__							(  SCREAMING_SNAKE_CASE     :						Any							,						SCREAMING_SNAKE_CASE     :						Union[str, Any]			):







      '''simple docstring'''




      lowerCAmelCase  						=       request.getfixturevalue(SCREAMING_SNAKE_CASE			)
      lowerCAmelCase  						=       DownloadManager()
      for num_jsonl, (path, file) in enumerate(dl_manager.iter_archive(SCREAMING_SNAKE_CASE			)							,						start=1			):
            _test_jsonl(SCREAMING_SNAKE_CASE							,						SCREAMING_SNAKE_CASE			)
      assert num_jsonl == 2


@pytest.mark.parametrize("""archive_nested_jsonl"""							,						["""tar_nested_jsonl_path""", """zip_nested_jsonl_path"""]			)
def 			UpperCAmelCase__							(  SCREAMING_SNAKE_CASE     :						Dict							,						SCREAMING_SNAKE_CASE     :						Optional[int]			):







      '''simple docstring'''




      lowerCAmelCase  						=       request.getfixturevalue(SCREAMING_SNAKE_CASE			)
      lowerCAmelCase  						=       DownloadManager()
      for num_tar, (path, file) in enumerate(dl_manager.iter_archive(SCREAMING_SNAKE_CASE			)							,						start=1			):
            for num_jsonl, (subpath, subfile) in enumerate(dl_manager.iter_archive(SCREAMING_SNAKE_CASE			)							,						start=1			):
                  _test_jsonl(SCREAMING_SNAKE_CASE							,						SCREAMING_SNAKE_CASE			)
      assert num_tar == 1
      assert num_jsonl == 2






def 			UpperCAmelCase__							(  SCREAMING_SNAKE_CASE     :						Dict			):







      '''simple docstring'''




      lowerCAmelCase  						=       DownloadManager()
      for num_file, file in enumerate(dl_manager.iter_files(SCREAMING_SNAKE_CASE			)							,						start=1			):
            assert os.path.basename(SCREAMING_SNAKE_CASE			) == ("test.txt" if num_file == 1 else "train.txt")
      assert num_file == 2








from typing import TYPE_CHECKING

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


A     :	str    = {
    'configuration_blenderbot': [
        'BLENDERBOT_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'BlenderbotConfig',
        'BlenderbotOnnxConfig',
    ],
    'tokenization_blenderbot': ['BlenderbotTokenizer'],
}

try:
					if not is_tokenizers_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					A     :	Optional[Any]    = ['BlenderbotTokenizerFast']

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					A     :	Optional[Any]    = [
					    'BLENDERBOT_PRETRAINED_MODEL_ARCHIVE_LIST',
					    'BlenderbotForCausalLM',
					    'BlenderbotForConditionalGeneration',
					    'BlenderbotModel',
					    'BlenderbotPreTrainedModel',
					]


try:
					if not is_tf_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					A     :	Dict    = [
					    'TFBlenderbotForConditionalGeneration',
					    'TFBlenderbotModel',
					    'TFBlenderbotPreTrainedModel',
					]


try:
					if not is_flax_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					A     :	Dict    = [
					    'FlaxBlenderbotForConditionalGeneration',
					    'FlaxBlenderbotModel',
					    'FlaxBlenderbotPreTrainedModel',
					]


if TYPE_CHECKING:
					from .configuration_blenderbot import (
					    BLENDERBOT_PRETRAINED_CONFIG_ARCHIVE_MAP,
					    BlenderbotConfig,
					    BlenderbotOnnxConfig,
					)
					from .tokenization_blenderbot import BlenderbotTokenizer

					try:
										if not is_tokenizers_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .tokenization_blenderbot_fast import BlenderbotTokenizerFast

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_blenderbot import (
										    BLENDERBOT_PRETRAINED_MODEL_ARCHIVE_LIST,
										    BlenderbotForCausalLM,
										    BlenderbotForConditionalGeneration,
										    BlenderbotModel,
										    BlenderbotPreTrainedModel,
										)

					try:
										if not is_tf_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_tf_blenderbot import (
										    TFBlenderbotForConditionalGeneration,
										    TFBlenderbotModel,
										    TFBlenderbotPreTrainedModel,
										)

					try:
										if not is_flax_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_flax_blenderbot import (
										    FlaxBlenderbotForConditionalGeneration,
										    FlaxBlenderbotModel,
										    FlaxBlenderbotPreTrainedModel,
										)

else:
					import sys

					A     :	List[Any]    = _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)