
import pyarrow.parquet as pq
import pytest

from datasets import Audio, Dataset, DatasetDict, Features, NamedSplit, Sequence, Value, config
from datasets.features.image import Image
from datasets.io.parquet import ParquetDatasetReader, ParquetDatasetWriter, get_writer_batch_size

from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases

def 		UpperCamelCase	(      lowercase_ , lowercase_   )		->	List[str]:


  '''simple docstring'''






  assert isinstance(lowercase_ , lowercase_   )
  assert dataset.num_rows == 4
  assert dataset.num_columns == 3
  assert dataset.column_names == ["col_1", "col_2", "col_3"]
  for feature, expected_dtype in expected_features.items():
    assert dataset.features[feature].dtype == expected_dtype

@pytest.mark.parametrize("""keep_in_memory""" , [False, True]   )
def 		UpperCamelCase	(      lowercase_ , lowercase_ , lowercase_   )		->	int:


  '''simple docstring'''






  lowercase__  :   int    		=      tmp_path / """cache"""
  lowercase__  :   List[str]    		=      {"""col_1""": """string""", """col_2""": """int64""", """col_3""": """float64"""}
  with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
    lowercase__  :   Optional[Any]    		=      ParquetDatasetReader(lowercase_ , cache_dir=lowercase_ , keep_in_memory=lowercase_   ).read()
  _check_parquet_dataset(lowercase_ , lowercase_   )

@pytest.mark.parametrize(
    """features""" , [
        None,
        {"""col_1""": """string""", """col_2""": """int64""", """col_3""": """float64"""},
        {"""col_1""": """string""", """col_2""": """string""", """col_3""": """string"""},
        {"""col_1""": """int32""", """col_2""": """int32""", """col_3""": """int32"""},
        {"""col_1""": """float32""", """col_2""": """float32""", """col_3""": """float32"""},
    ] , )
def 		UpperCamelCase	(      lowercase_ , lowercase_ , lowercase_   )		->	Tuple:


  '''simple docstring'''






  lowercase__  :   Union[str, Any]    		=      tmp_path / """cache"""
  lowercase__  :   Any    		=      {"""col_1""": """string""", """col_2""": """int64""", """col_3""": """float64"""}
  lowercase__  :   Optional[Any]    		=      features.copy() if features else default_expected_features
  lowercase__  :   int    		=      (
      Features({feature: Value(lowercase_   ) for feature, dtype in features.items()}   ) if features is not None else None
  )
  lowercase__  :   Dict    		=      ParquetDatasetReader(lowercase_ , features=lowercase_ , cache_dir=lowercase_   ).read()
  _check_parquet_dataset(lowercase_ , lowercase_   )

@pytest.mark.parametrize("""split""" , [None, NamedSplit("""train"""   ), """train""", """test"""]   )
def 		UpperCamelCase	(      lowercase_ , lowercase_ , lowercase_   )		->	Any:


  '''simple docstring'''






  lowercase__  :   Optional[int]    		=      tmp_path / """cache"""
  lowercase__  :   Dict    		=      {"""col_1""": """string""", """col_2""": """int64""", """col_3""": """float64"""}
  lowercase__  :   Optional[Any]    		=      ParquetDatasetReader(lowercase_ , cache_dir=lowercase_ , split=lowercase_   ).read()
  _check_parquet_dataset(lowercase_ , lowercase_   )
  assert dataset.split == split if split else "train"

@pytest.mark.parametrize("""path_type""" , [str, list]   )
def 		UpperCamelCase	(      lowercase_ , lowercase_ , lowercase_   )		->	int:


  '''simple docstring'''






  if issubclass(lowercase_ , lowercase_   ):
    lowercase__  :   Optional[Any]    		=      parquet_path
  elif issubclass(lowercase_ , lowercase_   ):
    lowercase__  :   Optional[Any]    		=      [parquet_path]
  lowercase__  :   int    		=      tmp_path / """cache"""
  lowercase__  :   str    		=      {"""col_1""": """string""", """col_2""": """int64""", """col_3""": """float64"""}
  lowercase__  :   Optional[int]    		=      ParquetDatasetReader(lowercase_ , cache_dir=lowercase_   ).read()
  _check_parquet_dataset(lowercase_ , lowercase_   )

def 		UpperCamelCase	(      lowercase_ , lowercase_ , lowercase_=("train",)   )		->	List[Any]:


  '''simple docstring'''






  assert isinstance(lowercase_ , lowercase_   )
  for split in splits:
    lowercase__  :   Union[str, Any]    		=      dataset_dict[split]
    assert dataset.num_rows == 4
    assert dataset.num_columns == 3
    assert dataset.column_names == ["col_1", "col_2", "col_3"]
    for feature, expected_dtype in expected_features.items():
      assert dataset.features[feature].dtype == expected_dtype

@pytest.mark.parametrize("""keep_in_memory""" , [False, True]   )
def 		UpperCamelCase	(      lowercase_ , lowercase_ , lowercase_   )		->	str:


  '''simple docstring'''






  lowercase__  :   Tuple    		=      tmp_path / """cache"""
  lowercase__  :   Union[str, Any]    		=      {"""col_1""": """string""", """col_2""": """int64""", """col_3""": """float64"""}
  with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
    lowercase__  :   Any    		=      ParquetDatasetReader(
        {"""train""": parquet_path} , cache_dir=lowercase_ , keep_in_memory=lowercase_   ).read()
  _check_parquet_datasetdict(lowercase_ , lowercase_   )

@pytest.mark.parametrize(
    """features""" , [
        None,
        {"""col_1""": """string""", """col_2""": """int64""", """col_3""": """float64"""},
        {"""col_1""": """string""", """col_2""": """string""", """col_3""": """string"""},
        {"""col_1""": """int32""", """col_2""": """int32""", """col_3""": """int32"""},
        {"""col_1""": """float32""", """col_2""": """float32""", """col_3""": """float32"""},
    ] , )
def 		UpperCamelCase	(      lowercase_ , lowercase_ , lowercase_   )		->	List[Any]:


  '''simple docstring'''






  lowercase__  :   List[Any]    		=      tmp_path / """cache"""
  lowercase__  :   Optional[int]    		=      {"""col_1""": """string""", """col_2""": """int64""", """col_3""": """float64"""}
  lowercase__  :   Optional[int]    		=      features.copy() if features else default_expected_features
  lowercase__  :   str    		=      (
      Features({feature: Value(lowercase_   ) for feature, dtype in features.items()}   ) if features is not None else None
  )
  lowercase__  :   Any    		=      ParquetDatasetReader({"""train""": parquet_path} , features=lowercase_ , cache_dir=lowercase_   ).read()
  _check_parquet_datasetdict(lowercase_ , lowercase_   )

@pytest.mark.parametrize("""split""" , [None, NamedSplit("""train"""   ), """train""", """test"""]   )
def 		UpperCamelCase	(      lowercase_ , lowercase_ , lowercase_   )		->	Union[str, Any]:


  '''simple docstring'''






  if split:
    lowercase__  :   List[Any]    		=      {split: parquet_path}
  else:
    lowercase__  :   List[str]    		=      """train"""
    lowercase__  :   Optional[Any]    		=      {"""train""": parquet_path, """test""": parquet_path}
  lowercase__  :   int    		=      tmp_path / """cache"""
  lowercase__  :   Optional[Any]    		=      {"""col_1""": """string""", """col_2""": """int64""", """col_3""": """float64"""}
  lowercase__  :   Optional[Any]    		=      ParquetDatasetReader(lowercase_ , cache_dir=lowercase_   ).read()
  _check_parquet_datasetdict(lowercase_ , lowercase_ , splits=list(path.keys()   )   )
  assert all(dataset[split].split == split for split in path.keys()   )

def 		UpperCamelCase	(      lowercase_ , lowercase_   )		->	Optional[Any]:


  '''simple docstring'''






  lowercase__  :   Dict    		=      ParquetDatasetWriter(lowercase_ , tmp_path / """foo.parquet"""   )
  assert writer.write() > 0
  lowercase__  :   Tuple    		=      pq.ParquetFile(tmp_path / """foo.parquet"""   )
  lowercase__  :   List[Any]    		=      pf.read()
  assert dataset.data.table == output_table

def 		UpperCamelCase	(      lowercase_ , lowercase_   )		->	Union[str, Any]:


  '''simple docstring'''






  lowercase__  :   List[str]    		=      str(shared_datadir / """test_image_rgb.jpg"""   )
  lowercase__  :   str    		=      {"""image""": [image_path]}
  lowercase__  :   List[Any]    		=      Features({"""image""": Image()}   )
  lowercase__  :   Union[str, Any]    		=      Dataset.from_dict(lowercase_ , features=lowercase_   )
  lowercase__  :   Any    		=      ParquetDatasetWriter(lowercase_ , tmp_path / """foo.parquet"""   )
  assert writer.write() > 0

  lowercase__  :   Union[str, Any]    		=      Dataset.from_parquet(str(tmp_path / """foo.parquet"""   )   )
  assert dataset.features == reloaded_dataset.features

  lowercase__  :   Optional[int]    		=      ParquetDatasetReader(str(tmp_path / """foo.parquet"""   ) , streaming=lowercase_   ).read()
  assert dataset.features == reloaded_iterable_dataset.features



@pytest.mark.parametrize(
    """feature, expected""" , [
        (Features({"""foo""": Value("""int32"""   )}   ), None),
        (Features({"""image""": Image(), """foo""": Value("""int32"""   )}   ), config.PARQUET_ROW_GROUP_SIZE_FOR_IMAGE_DATASETS),
        (Features({"""nested""": Sequence(Audio()   )}   ), config.PARQUET_ROW_GROUP_SIZE_FOR_AUDIO_DATASETS),
    ] , )
def 		UpperCamelCase	(      lowercase_ , lowercase_   )		->	Optional[int]:


  '''simple docstring'''






  assert get_writer_batch_size(lowercase_   ) == expected








from __future__ import annotations

from collections.abc import Iterator
from typing import Any



class       _snake_case   :


 def __init__(					self					,  SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   lowercase__  :   Any    		=      data
   lowercase__  :   Node | None    		=      None



class       _snake_case   :


 def __init__(					self):


   '''simple docstring'''




   lowercase__  :   List[Any]    		=      None
   lowercase__  :   int    		=      None


 def __iter__(					self):


   '''simple docstring'''




   lowercase__  :   List[str]    		=      self.head
   while self.head:
     yield node.data
     lowercase__  :   str    		=      node.next
     if node == self.head:
       break


 def __len__(					self):


   '''simple docstring'''




   return sum(1 for _ in self)


 def __repr__(					self):


   '''simple docstring'''




   return "->".join(str(SCREAMING_SNAKE_CASE_) for item in iter(self))


 def      lowercase__     (					self					,  SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   self.insert_nth(len(self)					,  SCREAMING_SNAKE_CASE_)


 def      lowercase__     (					self					,  SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   self.insert_nth(0					,  SCREAMING_SNAKE_CASE_)


 def      lowercase__     (					self					,  SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   if index < 0 or index > len(self):
     raise IndexError("""list index out of range.""")
   lowercase__  :   Optional[int]    		=      Node(SCREAMING_SNAKE_CASE_)
   if self.head is None:
     lowercase__  :   Union[str, Any]    		=      new_node  # first node points itself
     lowercase__  :   Dict    		=      new_node
   elif index == 0:  # insert at head
     lowercase__  :   int    		=      self.head
     lowercase__  :   int    		=      new_node
   else:
     lowercase__  :   List[str]    		=      self.head
     for _ in range(index - 1):
       lowercase__  :   Union[str, Any]    		=      temp.next
     lowercase__  :   int    		=      temp.next
     lowercase__  :   Optional[Any]    		=      new_node
     if index == len(self) - 1:  # insert at tail
       lowercase__  :   Union[str, Any]    		=      new_node


 def      lowercase__     (					self):


   '''simple docstring'''




   return self.delete_nth(0)


 def      lowercase__     (					self):


   '''simple docstring'''




   return self.delete_nth(len(self) - 1)


 def      lowercase__     (					self					,  SCREAMING_SNAKE_CASE_ = 0):


   '''simple docstring'''




   if not 0 <= index < len(self):
     raise IndexError("""list index out of range.""")
   lowercase__  :   str    		=      self.head
   if self.head == self.tail:  # just one node
     lowercase__  :   List[Any]    		=      None
   elif index == 0:  # delete head node
     lowercase__  :   str    		=      self.tail.next.next
     lowercase__  :   List[Any]    		=      self.head.next
   else:
     lowercase__  :   Optional[int]    		=      self.head
     for _ in range(index - 1):
       lowercase__  :   List[Any]    		=      temp.next
     lowercase__  :   Optional[Any]    		=      temp.next
     lowercase__  :   Dict    		=      temp.next.next
     if index == len(self) - 1:  # delete at tail
       lowercase__  :   Tuple    		=      temp
   return delete_node.data



 def      lowercase__     (					self):


   '''simple docstring'''




   return len(self) == 0

def 		UpperCamelCase	(      )		->	None:


  '''simple docstring'''






  lowercase__  :   int    		=      CircularLinkedList()
  assert len(lowercase_   ) == 0
  assert circular_linked_list.is_empty() is True
  assert str(lowercase_   ) == ""

  try:
    circular_linked_list.delete_front()
    raise AssertionError  # This should not happen
  except IndexError:
    assert True  # This should happen

  try:
    circular_linked_list.delete_tail()
    raise AssertionError  # This should not happen
  except IndexError:
    assert True  # This should happen

  try:
    circular_linked_list.delete_nth(-1   )
    raise AssertionError
  except IndexError:
    assert True

  try:
    circular_linked_list.delete_nth(0   )
    raise AssertionError
  except IndexError:
    assert True

  assert circular_linked_list.is_empty() is True
  for i in range(5   ):
    assert len(lowercase_   ) == i
    circular_linked_list.insert_nth(lowercase_ , i + 1   )
  assert str(lowercase_   ) == "->".join(str(lowercase_   ) for i in range(1 , 6   )   )

  circular_linked_list.insert_tail(6   )
  assert str(lowercase_   ) == "->".join(str(lowercase_   ) for i in range(1 , 7   )   )
  circular_linked_list.insert_head(0   )
  assert str(lowercase_   ) == "->".join(str(lowercase_   ) for i in range(0 , 7   )   )

  assert circular_linked_list.delete_front() == 0
  assert circular_linked_list.delete_tail() == 6
  assert str(lowercase_   ) == "->".join(str(lowercase_   ) for i in range(1 , 6   )   )
  assert circular_linked_list.delete_nth(2   ) == 3

  circular_linked_list.insert_nth(2 , 3   )
  assert str(lowercase_   ) == "->".join(str(lowercase_   ) for i in range(1 , 6   )   )

  assert circular_linked_list.is_empty() is False


if __name__ == "__main__":
     import doctest

     doctest.testmod()






