"""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


_a   :	Optional[Any] 					=     [
    {'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 							SCREAMING_SNAKE_CASE  (    _lowerCamelCase		: Dict=True			) ->   List[str]:
  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=SCREAMING_SNAKE_CASE_	)	)
class 		__A							(				SCREAMING_SNAKE_CASE_	):
     _UpperCamelCase							:    Tuple	      =	None
     _UpperCamelCase							:    Dict	      =	None






     def 					__A						(	self       ,  a__       ,  a__						):
       with TemporaryDirectory() as tmp_dir:
         _lowerCAmelCase		: int						    =  dataset_module_factory(a__       ,  cache_dir=a__						)

         _lowerCAmelCase		: Union[str, Any]						    =  import_main_class(dataset_module.module_path       ,  dataset=a__						)

         _lowerCAmelCase		: DatasetBuilder						    =  builder_cls(
             cache_dir=a__       ,  config_name=a__       ,  hash=dataset_module.hash       ,  )

         _lowerCAmelCase		: Any						    =  """/""".join(
             [
                 HF_GCP_BASE_URL,
                 builder_instance._relative_data_dir(with_hash=a__						).replace(os.sep       ,  """/"""						),
                 config.DATASET_INFO_FILENAME,
             ]						)
         _lowerCAmelCase		: Optional[Any]						    =  cached_path(a__       ,  cache_dir=a__						)
         self.assertTrue(os.path.exists(a__						)						)







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






@pytest.mark.integration
def 							SCREAMING_SNAKE_CASE  (    _lowerCamelCase		: List[Any]			) ->   Optional[int]:
  _lowerCAmelCase		: Optional[Any]						    =  dataset_module_factory("""wikipedia"""    ,cache_dir=_lowerCamelCase			)
  _lowerCAmelCase		: List[Any]						    =  import_main_class(dataset_module.module_path    ,dataset=_lowerCamelCase			)
  _lowerCAmelCase		: DatasetBuilder						    =  builder_cls(
      cache_dir=_lowerCamelCase    ,config_name="""20220301.frr"""    ,hash=dataset_module.hash    ,)
  _lowerCAmelCase		: List[str]						    =  builder_instance.as_streaming_dataset()
  assert ds
  assert isinstance(_lowerCamelCase    ,_lowerCamelCase			)
  assert "train" in ds
  assert isinstance(ds["""train"""]    ,_lowerCamelCase			)
  assert next(iter(ds["""train"""]			)			)





"""simple docstring"""




from __future__ import annotations

from collections import deque
from collections.abc import Sequence
from dataclasses import dataclass
from typing import Any
@dataclass
class 		__A							:
     _UpperCamelCase							:    int
     _UpperCamelCase							:    Node | None	      =	None
     _UpperCamelCase							:    Node | None	      =	None







def 							SCREAMING_SNAKE_CASE  (    ) ->   Node | None:
  _lowerCAmelCase		: Tuple						    =  Node(1			)
  _lowerCAmelCase		: int						    =  Node(2			)
  _lowerCAmelCase		: int						    =  Node(3			)
  _lowerCAmelCase		: Any						    =  Node(4			)
  _lowerCAmelCase		: Dict						    =  Node(5			)
  return tree





def 							SCREAMING_SNAKE_CASE  (    _lowerCamelCase		: Node | None			) ->   list[int]:
  return [root.data, *preorder(root.left			), *preorder(root.right			)] if root else []





def 							SCREAMING_SNAKE_CASE  (    _lowerCamelCase		: Node | None			) ->   list[int]:
  return postorder(root.left			) + postorder(root.right			) + [root.data] if root else []





def 							SCREAMING_SNAKE_CASE  (    _lowerCamelCase		: Node | None			) ->   list[int]:
  return [*inorder(root.left			), root.data, *inorder(root.right			)] if root else []





def 							SCREAMING_SNAKE_CASE  (    _lowerCamelCase		: Node | None			) ->   int:
  return (max(height(root.left			)    ,height(root.right			)			) + 1) if root else 0





def 							SCREAMING_SNAKE_CASE  (    _lowerCamelCase		: Node | None			) ->   Sequence[Node | None]:
  _lowerCAmelCase		: list[Any]						    =  []

  if root is None:
    return output

  _lowerCAmelCase		: Union[str, Any]						    =  deque([root]			)

  while process_queue:
    _lowerCAmelCase		: Optional[Any]						    =  process_queue.popleft()
    output.append(node.data			)

    if node.left:
      process_queue.append(node.left			)
    if node.right:
      process_queue.append(node.right			)
  return output





def 							SCREAMING_SNAKE_CASE  (    _lowerCamelCase		: Node | None    ,_lowerCamelCase		: int			) ->   Sequence[Node | None]:
  _lowerCAmelCase		: list[Any]						    =  []

  def populate_output(_lowerCamelCase		: Node | None    ,_lowerCamelCase		: int			) -> None:
    if not root:
      return
    if level == 1:
      output.append(root.data			)
    elif level > 1:
      populate_output(root.left    ,level - 1			)
      populate_output(root.right    ,level - 1			)

  populate_output(_lowerCamelCase    ,_lowerCamelCase			)
  return output





def 							SCREAMING_SNAKE_CASE  (    _lowerCamelCase		: Node | None    ,_lowerCamelCase		: int			) ->   Sequence[Node | None]:
  _lowerCAmelCase		: list[Any]						    =  []

  def populate_output(_lowerCamelCase		: Node | None    ,_lowerCamelCase		: int			) -> None:
    if root is None:
      return
    if level == 1:
      output.append(root.data			)
    elif level > 1:
      populate_output(root.right    ,level - 1			)
      populate_output(root.left    ,level - 1			)

  populate_output(_lowerCamelCase    ,_lowerCamelCase			)
  return output





def 							SCREAMING_SNAKE_CASE  (    _lowerCamelCase		: Node | None			) ->   Sequence[Node | None] | list[Any]:
  if root is None:
    return []

  _lowerCAmelCase		: list[Sequence[Node | None]]						    =  []

  _lowerCAmelCase		: Tuple						    =  0
  _lowerCAmelCase		: Dict						    =  height(_lowerCamelCase			)

  for h in range(1    ,height_tree + 1			):
    if not flag:
      output.append(get_nodes_from_left_to_right(_lowerCamelCase    ,_lowerCamelCase			)			)
      _lowerCAmelCase		: Any						    =  1
    else:
      output.append(get_nodes_from_right_to_left(_lowerCamelCase    ,_lowerCamelCase			)			)
      _lowerCAmelCase		: Optional[int]						    =  0

  return output





def 							SCREAMING_SNAKE_CASE  (    ) ->   None:  # Main function for testing.
  _lowerCAmelCase		: int						    =  make_tree()
  print(f"In-order Traversal: {inorder(_lowerCamelCase			)}"			)
  print(f"Pre-order Traversal: {preorder(_lowerCamelCase			)}"			)
  print(f"Post-order Traversal: {postorder(_lowerCamelCase			)}"    ,"""\n"""			)

  print(f"Height of Tree: {height(_lowerCamelCase			)}"    ,"""\n"""			)

  print("""Complete Level Order Traversal: """			)
  print(level_order(_lowerCamelCase			)    ,"""\n"""			)

  print("""Level-wise order Traversal: """			)

  for level in range(1    ,height(_lowerCamelCase			) + 1			):
    print(f"Level {level}:"    ,get_nodes_from_left_to_right(_lowerCamelCase    ,level=_lowerCamelCase			)			)

  print("""\nZigZag order Traversal: """			)
  print(zigzag(_lowerCamelCase			)			)


if __name__ == "__main__":
     import doctest

     doctest.testmod()
     main()




