





import copy
import os
import tempfile
from unittest import TestCase
from unittest.mock import patch

import numpy as np
import pyarrow as pa
import pyarrow.parquet as pq
import pytest

from datasets.arrow_writer import ArrowWriter, OptimizedTypedSequence, ParquetWriter, TypedSequence
from datasets.features import ArrayaD, ClassLabel, Features, Image, Value
from datasets.features.features import ArrayaDExtensionType, cast_to_python_objects
from datasets.keyhash import DuplicatedKeysError, InvalidKeyError

from .utils import require_pil
class        snake_case_		(			_UpperCAmelCase):







		def 			__lowercase   (		self   )				->   str:
				_SCREAMING_SNAKE_CASE   : str								=pa.array(TypedSequence([1, 2, 3]   )   )
				self.assertEqual(arr.type			,     pa.intaa()   )







		def 			__lowercase   (		self   )				->   List[str]:






				with self.assertRaises(__UpperCamelCase   ):
						_SCREAMING_SNAKE_CASE   : Any								=pa.array(TypedSequence([1, 2, 3]   )			,     type=pa.intaa()   )







		def 			__lowercase   (		self   )				->   Tuple:






				with self.assertRaises(__UpperCamelCase   ):
						_SCREAMING_SNAKE_CASE   : Optional[int]								=pa.array(TypedSequence([1, 2, 3]			,     try_type=Value('''bool'''   )			,     type=Value('''int64'''   )   )   )







		def 			__lowercase   (		self   )				->   Dict:
				_SCREAMING_SNAKE_CASE   : Union[str, Any]								=pa.array(TypedSequence([1, 2, 3]			,     type=Value('''int32'''   )   )   )
				self.assertEqual(arr.type			,     pa.intaa()   )







		def 			__lowercase   (		self   )				->   Dict:






				with self.assertRaises((TypeError, pa.lib.ArrowInvalid)   ):
						_SCREAMING_SNAKE_CASE   : Optional[Any]								=pa.array(TypedSequence(['''foo''', '''bar''']			,     type=Value('''int64'''   )   )   )







		def 			__lowercase   (		self   )				->   str:
				_SCREAMING_SNAKE_CASE   : List[str]								=pa.array(TypedSequence([1, 2, 3]			,     try_type=Value('''int32'''   )   )   )
				self.assertEqual(arr.type			,     pa.intaa()   )







		def 			__lowercase   (		self   )				->   Any:
				_SCREAMING_SNAKE_CASE   : Dict								=pa.array(TypedSequence(['''foo''', '''bar''']			,     try_type=Value('''int64'''   )   )   )
				self.assertEqual(arr.type			,     pa.string()   )







		def 			__lowercase   (		self   )				->   List[Any]:
				_SCREAMING_SNAKE_CASE   : List[Any]								=pa.array(TypedSequence([[[1, 2, 3]]]			,     type=ArrayaD((1, 3)			,     '''int64'''   )   )   )
				self.assertEqual(arr.type			,     ArrayaDExtensionType((1, 3)			,     '''int64'''   )   )







		def 			__lowercase   (		self   )				->   Optional[Any]:






				with self.assertRaises((TypeError, pa.lib.ArrowInvalid)   ):
						_SCREAMING_SNAKE_CASE   : Union[str, Any]								=pa.array(TypedSequence(['''foo''', '''bar''']			,     type=ArrayaD((1, 3)			,     '''int64'''   )   )   )







		def 			__lowercase   (		self   )				->   int:
				_SCREAMING_SNAKE_CASE   : int								=pa.array(TypedSequence([[[1, 2, 3]]]			,     try_type=ArrayaD((1, 3)			,     '''int64'''   )   )   )
				self.assertEqual(arr.type			,     ArrayaDExtensionType((1, 3)			,     '''int64'''   )   )







		def 			__lowercase   (		self   )				->   Dict:
				_SCREAMING_SNAKE_CASE   : Dict								=pa.array(TypedSequence(['''foo''', '''bar''']			,     try_type=ArrayaD((1, 3)			,     '''int64'''   )   )   )
				self.assertEqual(arr.type			,     pa.string()   )







		@require_pil
		def 			__lowercase   (		self   )				->   Optional[Any]:
				import PIL.Image

				_SCREAMING_SNAKE_CASE   : int								=PIL.Image.fromarray(np.arange(1_0			,     dtype=np.uinta   ).reshape(2			,     5   )   )
				with patch(
				    '''datasets.arrow_writer.cast_to_python_objects'''			,     side_effect=__UpperCamelCase   ) as mock_cast_to_python_objects:
						_SCREAMING_SNAKE_CASE   : Tuple								=pa.array(TypedSequence([{'''path''': None, '''bytes''': B'''image_bytes'''}, pil_image]			,     type=Image()   )   )
						_SCREAMING_SNAKE_CASE		,   _SCREAMING_SNAKE_CASE   : Tuple								=mock_cast_to_python_objects.call_args_list[-1]
						self.assertIn('''optimize_list_casting'''			,     __UpperCamelCase   )
						self.assertFalse(kwargs['''optimize_list_casting''']   )


def 					A__	(       SCREAMING_SNAKE_CASE_							,       SCREAMING_SNAKE_CASE_		)   ->     Any:
		_SCREAMING_SNAKE_CASE   : Optional[Any]								=pa.BufferReader(_A		) if isinstance(_A							,       pa.Buffer		) else pa.memory_map(_A		)
		_SCREAMING_SNAKE_CASE   : Optional[int]								=pa.ipc.open_stream(_A		)
		_SCREAMING_SNAKE_CASE   : Optional[Any]								=f.read_all()
		assert len(pa_table.to_batches()		) == expected_num_chunks
		assert pa_table.to_pydict() == {"col_1": ["foo", "bar"], "col_2": [1, 2]}
		del pa_table


@pytest.mark.parametrize('''writer_batch_size'''							,       [None, 1, 1_0]		)
@pytest.mark.parametrize(
    '''fields'''							,       [None, {'''col_1''': pa.string(), '''col_2''': pa.intaa()}, {'''col_1''': pa.string(), '''col_2''': pa.intaa()}]		)
def 					A__	(       SCREAMING_SNAKE_CASE_							,       SCREAMING_SNAKE_CASE_		)   ->     Optional[Any]:
		_SCREAMING_SNAKE_CASE   : str								=pa.BufferOutputStream()
		_SCREAMING_SNAKE_CASE   : List[Any]								=pa.schema(_A		) if fields else None
		with ArrowWriter(stream=_A							,       schema=_A							,       writer_batch_size=_A		) as writer:
				writer.write({'''col_1''': '''foo''', '''col_2''': 1}		)
				writer.write({'''col_1''': '''bar''', '''col_2''': 2}		)
				_SCREAMING_SNAKE_CASE		,   _SCREAMING_SNAKE_CASE   : List[Any]								=writer.finalize()
		assert num_examples == 2
		assert num_bytes > 0
		if not fields:
				_SCREAMING_SNAKE_CASE   : Optional[int]								={'''col_1''': pa.string(), '''col_2''': pa.intaa()}
		assert writer._schema == pa.schema(_A							,       metadata=writer._schema.metadata		)
		_check_output(output.getvalue()							,       expected_num_chunks=num_examples if writer_batch_size == 1 else 1		)


def 					A__	(       )   ->     Union[str, Any]:
		_SCREAMING_SNAKE_CASE   : Dict								=pa.BufferOutputStream()
		_SCREAMING_SNAKE_CASE   : Dict								=Features({'''labels''': ClassLabel(names=['''neg''', '''pos''']		)}		)
		with ArrowWriter(stream=_A							,       features=_A		) as writer:
				writer.write({'''labels''': 0}		)
				writer.write({'''labels''': 1}		)
				_SCREAMING_SNAKE_CASE		,   _SCREAMING_SNAKE_CASE   : Optional[Any]								=writer.finalize()
		assert num_examples == 2
		assert num_bytes > 0
		assert writer._schema == features.arrow_schema
		assert writer._schema.metadata == features.arrow_schema.metadata
		_SCREAMING_SNAKE_CASE   : int								=pa.BufferReader(output.getvalue()		)
		_SCREAMING_SNAKE_CASE   : str								=pa.ipc.open_stream(_A		)
		_SCREAMING_SNAKE_CASE   : str								=f.read_all()
		_SCREAMING_SNAKE_CASE   : List[Any]								=pa_table.schema
		assert pa_table.num_rows == 2
		assert schema == features.arrow_schema
		assert schema.metadata == features.arrow_schema.metadata
		assert features == Features.from_arrow_schema(_A		)


@pytest.mark.parametrize('''writer_batch_size'''							,       [None, 1, 1_0]		)
def 					A__	(       SCREAMING_SNAKE_CASE_		)   ->     Optional[int]:
		_SCREAMING_SNAKE_CASE   : Union[str, Any]								=pa.BufferOutputStream()
		with ArrowWriter(
		    stream=_A							,       writer_batch_size=_A							,       hash_salt='''split_name'''							,       check_duplicates=_A							,       ) as writer:
				with pytest.raises(_A		):
						writer.write({'''col_1''': '''foo''', '''col_2''': 1}							,       key=[1, 2]		)
						_SCREAMING_SNAKE_CASE		,   _SCREAMING_SNAKE_CASE   : Any								=writer.finalize()


@pytest.mark.parametrize('''writer_batch_size'''							,       [None, 2, 1_0]		)
def 					A__	(       SCREAMING_SNAKE_CASE_		)   ->     List[Any]:
		_SCREAMING_SNAKE_CASE   : Optional[Any]								=pa.BufferOutputStream()
		with ArrowWriter(
		    stream=_A							,       writer_batch_size=_A							,       hash_salt='''split_name'''							,       check_duplicates=_A							,       ) as writer:
				with pytest.raises(_A		):
						writer.write({'''col_1''': '''foo''', '''col_2''': 1}							,       key=1_0		)
						writer.write({'''col_1''': '''bar''', '''col_2''': 2}							,       key=1_0		)
						_SCREAMING_SNAKE_CASE		,   _SCREAMING_SNAKE_CASE   : List[Any]								=writer.finalize()


@pytest.mark.parametrize('''writer_batch_size'''							,       [None, 2, 1_0]		)
def 					A__	(       SCREAMING_SNAKE_CASE_		)   ->     Tuple:
		_SCREAMING_SNAKE_CASE   : Dict								=pa.BufferOutputStream()
		with ArrowWriter(
		    stream=_A							,       writer_batch_size=_A							,       hash_salt='''split_name'''							,       check_duplicates=_A							,       ) as writer:
				writer.write({'''col_1''': '''foo''', '''col_2''': 1}							,       key=1		)
				writer.write({'''col_1''': '''bar''', '''col_2''': 2}							,       key=2		)
				_SCREAMING_SNAKE_CASE		,   _SCREAMING_SNAKE_CASE   : List[Any]								=writer.finalize()
		assert num_examples == 2
		assert num_bytes > 0
		_check_output(output.getvalue()							,       expected_num_chunks=num_examples if writer_batch_size == 1 else 1		)


@pytest.mark.parametrize('''writer_batch_size'''							,       [None, 1, 1_0]		)
@pytest.mark.parametrize(
    '''fields'''							,       [None, {'''col_1''': pa.string(), '''col_2''': pa.intaa()}, {'''col_1''': pa.string(), '''col_2''': pa.intaa()}]		)
def 					A__	(       SCREAMING_SNAKE_CASE_							,       SCREAMING_SNAKE_CASE_		)   ->     List[Any]:
		_SCREAMING_SNAKE_CASE   : Optional[int]								=pa.BufferOutputStream()
		_SCREAMING_SNAKE_CASE   : str								=pa.schema(_A		) if fields else None
		with ArrowWriter(stream=_A							,       schema=_A							,       writer_batch_size=_A		) as writer:
				writer.write_batch({'''col_1''': ['''foo''', '''bar'''], '''col_2''': [1, 2]}		)
				writer.write_batch({'''col_1''': [], '''col_2''': []}		)
				_SCREAMING_SNAKE_CASE		,   _SCREAMING_SNAKE_CASE   : Tuple								=writer.finalize()
		assert num_examples == 2
		assert num_bytes > 0
		if not fields:
				_SCREAMING_SNAKE_CASE   : List[Any]								={'''col_1''': pa.string(), '''col_2''': pa.intaa()}
		assert writer._schema == pa.schema(_A							,       metadata=writer._schema.metadata		)
		_check_output(output.getvalue()							,       expected_num_chunks=num_examples if writer_batch_size == 1 else 1		)


@pytest.mark.parametrize('''writer_batch_size'''							,       [None, 1, 1_0]		)
@pytest.mark.parametrize(
    '''fields'''							,       [None, {'''col_1''': pa.string(), '''col_2''': pa.intaa()}, {'''col_1''': pa.string(), '''col_2''': pa.intaa()}]		)
def 					A__	(       SCREAMING_SNAKE_CASE_							,       SCREAMING_SNAKE_CASE_		)   ->     Any:
		_SCREAMING_SNAKE_CASE   : Tuple								=pa.BufferOutputStream()
		_SCREAMING_SNAKE_CASE   : List[Any]								=pa.schema(_A		) if fields else None
		with ArrowWriter(stream=_A							,       schema=_A							,       writer_batch_size=_A		) as writer:
				writer.write_table(pa.Table.from_pydict({'''col_1''': ['''foo''', '''bar'''], '''col_2''': [1, 2]}		)		)
				_SCREAMING_SNAKE_CASE		,   _SCREAMING_SNAKE_CASE   : List[str]								=writer.finalize()
		assert num_examples == 2
		assert num_bytes > 0
		if not fields:
				_SCREAMING_SNAKE_CASE   : List[Any]								={'''col_1''': pa.string(), '''col_2''': pa.intaa()}
		assert writer._schema == pa.schema(_A							,       metadata=writer._schema.metadata		)
		_check_output(output.getvalue()							,       expected_num_chunks=num_examples if writer_batch_size == 1 else 1		)


@pytest.mark.parametrize('''writer_batch_size'''							,       [None, 1, 1_0]		)
@pytest.mark.parametrize(
    '''fields'''							,       [None, {'''col_1''': pa.string(), '''col_2''': pa.intaa()}, {'''col_1''': pa.string(), '''col_2''': pa.intaa()}]		)
def 					A__	(       SCREAMING_SNAKE_CASE_							,       SCREAMING_SNAKE_CASE_		)   ->     List[Any]:
		_SCREAMING_SNAKE_CASE   : Optional[Any]								=pa.BufferOutputStream()
		_SCREAMING_SNAKE_CASE   : Tuple								=pa.schema(_A		) if fields else None
		with ArrowWriter(stream=_A							,       schema=_A							,       writer_batch_size=_A		) as writer:
				writer.write_row(pa.Table.from_pydict({'''col_1''': ['''foo'''], '''col_2''': [1]}		)		)
				writer.write_row(pa.Table.from_pydict({'''col_1''': ['''bar'''], '''col_2''': [2]}		)		)
				_SCREAMING_SNAKE_CASE		,   _SCREAMING_SNAKE_CASE   : Optional[Any]								=writer.finalize()
		assert num_examples == 2
		assert num_bytes > 0
		if not fields:
				_SCREAMING_SNAKE_CASE   : int								={'''col_1''': pa.string(), '''col_2''': pa.intaa()}
		assert writer._schema == pa.schema(_A							,       metadata=writer._schema.metadata		)
		_check_output(output.getvalue()							,       expected_num_chunks=num_examples if writer_batch_size == 1 else 1		)


def 					A__	(       )   ->     str:

		with tempfile.TemporaryDirectory() as tmp_dir:
				_SCREAMING_SNAKE_CASE   : Any								={'''col_1''': pa.string(), '''col_2''': pa.intaa()}
				_SCREAMING_SNAKE_CASE   : Optional[int]								=os.path.join(_A							,       '''test.arrow'''		)
				with ArrowWriter(path=_A							,       schema=pa.schema(_A		)		) as writer:
						writer.write_batch({'''col_1''': ['''foo''', '''bar'''], '''col_2''': [1, 2]}		)
						_SCREAMING_SNAKE_CASE		,   _SCREAMING_SNAKE_CASE   : List[Any]								=writer.finalize()
				assert num_examples == 2
				assert num_bytes > 0
				assert writer._schema == pa.schema(_A							,       metadata=writer._schema.metadata		)
				_check_output(_A							,       1		)


def 					A__	(       SCREAMING_SNAKE_CASE_		)   ->     int:

		if pa.types.is_list(_A		):
				return get_base_dtype(arr_type.value_type		)
		else:
				return arr_type


def 					A__	(       SCREAMING_SNAKE_CASE_							,       SCREAMING_SNAKE_CASE_		)   ->     Any:

		if isinstance(lst[0]							,       _A		):
				change_first_primitive_element_in_list(lst[0]							,       _A		)
		else:
				_SCREAMING_SNAKE_CASE   : Optional[int]								=value


@pytest.mark.parametrize('''optimized_int_type, expected_dtype'''							,       [(None, pa.intaa()), (Value('''int32'''		), pa.intaa())]		)
@pytest.mark.parametrize('''sequence'''							,       [[1, 2, 3], [[1, 2, 3]], [[[1, 2, 3]]]]		)
def 					A__	(       SCREAMING_SNAKE_CASE_							,       SCREAMING_SNAKE_CASE_							,       SCREAMING_SNAKE_CASE_		)   ->     Dict:
		_SCREAMING_SNAKE_CASE   : List[Any]								=pa.array(TypedSequence(_A							,       optimized_int_type=_A		)		)
		assert get_base_dtype(arr.type		) == expected_dtype


@pytest.mark.parametrize(
    '''col, expected_dtype'''							,       [
        ('''attention_mask''', pa.inta()),
        ('''special_tokens_mask''', pa.inta()),
        ('''token_type_ids''', pa.inta()),
        ('''input_ids''', pa.intaa()),
        ('''other''', pa.intaa()),
    ]							,       )
@pytest.mark.parametrize('''sequence'''							,       [[1, 2, 3], [[1, 2, 3]], [[[1, 2, 3]]]]		)
def 					A__	(       SCREAMING_SNAKE_CASE_							,       SCREAMING_SNAKE_CASE_							,       SCREAMING_SNAKE_CASE_		)   ->     str:
		_SCREAMING_SNAKE_CASE   : Tuple								=pa.array(OptimizedTypedSequence(_A							,       col=_A		)		)
		assert get_base_dtype(arr.type		) == expected_dtype

		# not in range
		if col != "other":
				# avoids errors due to in-place modifications
				_SCREAMING_SNAKE_CASE   : Optional[Any]								=copy.deepcopy(_A		)
				_SCREAMING_SNAKE_CASE   : Optional[Any]								=np.iinfo(expected_dtype.to_pandas_dtype()		).max + 1
				change_first_primitive_element_in_list(_A							,       _A		)
				_SCREAMING_SNAKE_CASE   : Union[str, Any]								=pa.array(OptimizedTypedSequence(_A							,       col=_A		)		)
				assert get_base_dtype(arr.type		) == pa.intaa()


@pytest.mark.parametrize('''raise_exception'''							,       [False, True]		)
def 					A__	(       SCREAMING_SNAKE_CASE_							,       SCREAMING_SNAKE_CASE_		)   ->     Dict:
		_SCREAMING_SNAKE_CASE   : Optional[int]								=str(tmp_path / '''dataset-train.arrow'''		)
		try:
				with ArrowWriter(path=_A		) as writer:
						if raise_exception:
								raise pa.lib.ArrowInvalid()
						else:
								writer.stream.close()
		except pa.lib.ArrowInvalid:
				pass
		finally:
				assert writer.stream.closed


def 					A__	(       SCREAMING_SNAKE_CASE_		)   ->     Dict:
		_SCREAMING_SNAKE_CASE   : Any								='''mock://dataset-train.arrow'''
		with ArrowWriter(path=_A							,       storage_options=mockfs.storage_options		) as writer:
				assert isinstance(writer._fs							,       type(_A		)		)
				assert writer._fs.storage_options == mockfs.storage_options
				writer.write({'''col_1''': '''foo''', '''col_2''': 1}		)
				writer.write({'''col_1''': '''bar''', '''col_2''': 2}		)
				_SCREAMING_SNAKE_CASE		,   _SCREAMING_SNAKE_CASE   : int								=writer.finalize()
		assert num_examples == 2
		assert num_bytes > 0
		assert mockfs.exists(_A		)


def 					A__	(       )   ->     Dict:
		_SCREAMING_SNAKE_CASE   : int								=pa.BufferOutputStream()
		with ParquetWriter(stream=_A		) as writer:
				writer.write({'''col_1''': '''foo''', '''col_2''': 1}		)
				writer.write({'''col_1''': '''bar''', '''col_2''': 2}		)
				_SCREAMING_SNAKE_CASE		,   _SCREAMING_SNAKE_CASE   : List[str]								=writer.finalize()
		assert num_examples == 2
		assert num_bytes > 0
		_SCREAMING_SNAKE_CASE   : str								=pa.BufferReader(output.getvalue()		)
		_SCREAMING_SNAKE_CASE   : List[str]								=pq.read_table(_A		)
		assert pa_table.to_pydict() == {"col_1": ["foo", "bar"], "col_2": [1, 2]}


@require_pil
@pytest.mark.parametrize('''embed_local_files'''							,       [False, True]		)
def 					A__	(       SCREAMING_SNAKE_CASE_							,       SCREAMING_SNAKE_CASE_		)   ->     Any:
		import PIL.Image

		_SCREAMING_SNAKE_CASE   : Optional[int]								=str(tmp_path / '''test_image_rgb.jpg'''		)
		PIL.Image.fromarray(np.zeros((5, 5)							,       dtype=np.uinta		)		).save(_A							,       format='''png'''		)
		_SCREAMING_SNAKE_CASE   : List[Any]								=pa.BufferOutputStream()
		with ParquetWriter(
		    stream=_A							,       features=Features({'''image''': Image()}		)							,       embed_local_files=_A		) as writer:
				writer.write({'''image''': image_path}		)
				writer.finalize()
		_SCREAMING_SNAKE_CASE   : Union[str, Any]								=pa.BufferReader(output.getvalue()		)
		_SCREAMING_SNAKE_CASE   : Tuple								=pq.read_table(_A		)
		_SCREAMING_SNAKE_CASE   : Dict								=pa_table.to_pydict()
		if embed_local_files:
				assert isinstance(out['''image'''][0]['''path''']							,       _A		)
				with open(_A							,       '''rb'''		) as f:
						assert out["image"][0]["bytes"] == f.read()
		else:
				assert out["image"][0]["path"] == image_path
				assert out["image"][0]["bytes"] is None



def 					A__	(       )   ->     int:
		_SCREAMING_SNAKE_CASE   : List[Any]								=pa.schema([pa.field('''col_1'''							,       pa.string()							,       nullable=_A		)]		)
		_SCREAMING_SNAKE_CASE   : List[str]								=pa.BufferOutputStream()
		with ArrowWriter(stream=_A		) as writer:
				writer._build_writer(inferred_schema=_A		)
				assert writer._schema == pa.schema([pa.field('''col_1'''							,       pa.string()		)]		)








from __future__ import annotations

import queue
class        snake_case_		:







		def __init__(		self			,     __lowercase   )				->   int:
				lowerCamelCase   : int								=data
				lowerCamelCase   : str								=None
				lowerCamelCase   : Dict								=None


def 					A__	(       )   ->     TreeNode:
		print('''\n********Press N to stop entering at any point of time********\n'''		)
		lowerCamelCase   : Tuple								=input('''Enter the value of the root node: '''		).strip().lower()
		lowerCamelCase   : queue.Queue								=queue.Queue()
		lowerCamelCase   : Dict								=TreeNode(int(SCREAMING_SNAKE_CASE_		)		)
		q.put(SCREAMING_SNAKE_CASE_		)
		while not q.empty():
				lowerCamelCase   : Dict								=q.get()
				lowerCamelCase   : Optional[int]								=F"Enter the left node of {node_found.data}: "
				lowerCamelCase   : Tuple								=input(SCREAMING_SNAKE_CASE_		).strip().lower() or '''n'''
				if check == "n":
						return tree_node
				lowerCamelCase   : Union[str, Any]								=TreeNode(int(SCREAMING_SNAKE_CASE_		)		)
				lowerCamelCase   : Optional[Any]								=left_node
				q.put(SCREAMING_SNAKE_CASE_		)
				lowerCamelCase   : List[Any]								=F"Enter the right node of {node_found.data}: "
				lowerCamelCase   : int								=input(SCREAMING_SNAKE_CASE_		).strip().lower() or '''n'''
				if check == "n":
						return tree_node
				lowerCamelCase   : str								=TreeNode(int(SCREAMING_SNAKE_CASE_		)		)
				lowerCamelCase   : Optional[Any]								=right_node
				q.put(SCREAMING_SNAKE_CASE_		)
		raise


def 					A__	(       SCREAMING_SNAKE_CASE_		)   ->     None:
		if not isinstance(SCREAMING_SNAKE_CASE_							,       SCREAMING_SNAKE_CASE_		) or not node:
				return
		print(node.data							,       end=''','''		)
		pre_order(node.left		)
		pre_order(node.right		)


def 					A__	(       SCREAMING_SNAKE_CASE_		)   ->     None:
		if not isinstance(SCREAMING_SNAKE_CASE_							,       SCREAMING_SNAKE_CASE_		) or not node:
				return
		in_order(node.left		)
		print(node.data							,       end=''','''		)
		in_order(node.right		)


def 					A__	(       SCREAMING_SNAKE_CASE_		)   ->     None:
		if not isinstance(SCREAMING_SNAKE_CASE_							,       SCREAMING_SNAKE_CASE_		) or not node:
				return
		post_order(node.left		)
		post_order(node.right		)
		print(node.data							,       end=''','''		)


def 					A__	(       SCREAMING_SNAKE_CASE_		)   ->     None:
		if not isinstance(SCREAMING_SNAKE_CASE_							,       SCREAMING_SNAKE_CASE_		) or not node:
				return
		lowerCamelCase   : queue.Queue								=queue.Queue()
		q.put(SCREAMING_SNAKE_CASE_		)
		while not q.empty():
				lowerCamelCase   : Optional[int]								=q.get()
				print(node_dequeued.data							,       end=''','''		)
				if node_dequeued.left:
						q.put(node_dequeued.left		)
				if node_dequeued.right:
						q.put(node_dequeued.right		)


def 					A__	(       SCREAMING_SNAKE_CASE_		)   ->     None:
		if not isinstance(SCREAMING_SNAKE_CASE_							,       SCREAMING_SNAKE_CASE_		) or not node:
				return
		lowerCamelCase   : queue.Queue								=queue.Queue()
		q.put(SCREAMING_SNAKE_CASE_		)
		while not q.empty():
				lowerCamelCase   : Tuple								=[]
				while not q.empty():
						lowerCamelCase   : List[str]								=q.get()
						print(node_dequeued.data							,       end=''','''		)
						if node_dequeued.left:
								list_.append(node_dequeued.left		)
						if node_dequeued.right:
								list_.append(node_dequeued.right		)
				print()
				for node in list_:
						q.put(SCREAMING_SNAKE_CASE_		)


def 					A__	(       SCREAMING_SNAKE_CASE_		)   ->     None:
		if not isinstance(SCREAMING_SNAKE_CASE_							,       SCREAMING_SNAKE_CASE_		) or not node:
				return
		lowerCamelCase   : list[TreeNode]								=[]
		lowerCamelCase   : Tuple								=node
		while n or stack:
				while n:  # start from root node, find its left child
						print(n.data							,       end=''','''		)
						stack.append(SCREAMING_SNAKE_CASE_		)
						lowerCamelCase   : Any								=n.left
				# end of while means current node doesn't have left child
				lowerCamelCase   : Tuple								=stack.pop()
				# start to traverse its right child
				lowerCamelCase   : Union[str, Any]								=n.right


def 					A__	(       SCREAMING_SNAKE_CASE_		)   ->     None:
		if not isinstance(SCREAMING_SNAKE_CASE_							,       SCREAMING_SNAKE_CASE_		) or not node:
				return
		lowerCamelCase   : list[TreeNode]								=[]
		lowerCamelCase   : List[Any]								=node
		while n or stack:
				while n:
						stack.append(SCREAMING_SNAKE_CASE_		)
						lowerCamelCase   : List[Any]								=n.left
				lowerCamelCase   : Dict								=stack.pop()
				print(n.data							,       end=''','''		)
				lowerCamelCase   : Union[str, Any]								=n.right


def 					A__	(       SCREAMING_SNAKE_CASE_		)   ->     None:
		if not isinstance(SCREAMING_SNAKE_CASE_							,       SCREAMING_SNAKE_CASE_		) or not node:
				return
		lowerCamelCase		,   lowerCamelCase   : Optional[int]								=[], []
		lowerCamelCase   : Dict								=node
		stacka.append(SCREAMING_SNAKE_CASE_		)
		while stacka:  # to find the reversed order of post order, store it in stack2
				lowerCamelCase   : int								=stacka.pop()
				if n.left:
						stacka.append(n.left		)
				if n.right:
						stacka.append(n.right		)
				stacka.append(SCREAMING_SNAKE_CASE_		)
		while stacka:  # pop up from stack2 will be the post order
				print(stacka.pop().data							,       end=''','''		)


def 					A__	(       SCREAMING_SNAKE_CASE_ = ""							,       SCREAMING_SNAKE_CASE_=5_0							,       SCREAMING_SNAKE_CASE_="*"		)   ->     str:
		if not s:
				return "\n" + width * char
		lowerCamelCase		,   lowerCamelCase   : Dict								=divmod(width - len(SCREAMING_SNAKE_CASE_		) - 2							,       2		)
		return F"{left * char} {s} {(left + extra) * char}"


if __name__ == "__main__":
				import doctest

				doctest.testmod()
				print(prompt('''Binary Tree Traversals'''))

				snake_case_							=			build_tree()
				print(prompt('''Pre Order Traversal'''))
				pre_order(node)
				print(prompt() + '''\n''')

				print(prompt('''In Order Traversal'''))
				in_order(node)
				print(prompt() + '''\n''')

				print(prompt('''Post Order Traversal'''))
				post_order(node)
				print(prompt() + '''\n''')

				print(prompt('''Level Order Traversal'''))
				level_order(node)
				print(prompt() + '''\n''')

				print(prompt('''Actual Level Order Traversal'''))
				level_order_actual(node)
				print('''*''' * 5_0 + '''\n''')

				print(prompt('''Pre Order Traversal - Iteration Version'''))
				pre_order_iter(node)
				print(prompt() + '''\n''')

				print(prompt('''In Order Traversal - Iteration Version'''))
				in_order_iter(node)
				print(prompt() + '''\n''')

				print(prompt('''Post Order Traversal - Iteration Version'''))
				post_order_iter(node)
				print(prompt())

