






'''simple docstring'''
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        __SCREAMING_SNAKE_CASE (     lowerCamelCase			):




 def        __magic_name__		( self		:							int )		->  Union[str, Any]:
       SCREAMING_SNAKE_CASE__       :			str													=pa.array(TypedSequence([1, 2, 3] ) )
       self.assertEqual(arr.type   , pa.intaa() )




 def        __magic_name__		( self		:							List[Any] )		->  List[Any]:
       with self.assertRaises(__lowercase ):
             SCREAMING_SNAKE_CASE__       :			Optional[Any]													=pa.array(TypedSequence([1, 2, 3] )   , type=pa.intaa() )




 def        __magic_name__		( self		:							Any )		->  Union[str, Any]:
       with self.assertRaises(__lowercase ):
             SCREAMING_SNAKE_CASE__       :			Dict													=pa.array(TypedSequence([1, 2, 3]   , try_type=Value('''bool''' )   , type=Value('''int64''' ) ) )




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




 def        __magic_name__		( self		:							Union[str, Any] )		->  str:
       with self.assertRaises((TypeError, pa.lib.ArrowInvalid) ):
             SCREAMING_SNAKE_CASE__       :			Tuple													=pa.array(TypedSequence(['''foo''', '''bar''']   , type=Value('''int64''' ) ) )




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




 def        __magic_name__		( self		:							List[Any] )		->  Union[str, Any]:
       SCREAMING_SNAKE_CASE__       :			str													=pa.array(TypedSequence(['''foo''', '''bar''']   , try_type=Value('''int64''' ) ) )
       self.assertEqual(arr.type   , pa.string() )




 def        __magic_name__		( self		:							Tuple )		->  Optional[int]:
       SCREAMING_SNAKE_CASE__       :			Any													=pa.array(TypedSequence([[[1, 2, 3]]]   , type=ArrayaD((1, 3)   , '''int64''' ) ) )
       self.assertEqual(arr.type   , ArrayaDExtensionType((1, 3)   , '''int64''' ) )




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




 def        __magic_name__		( self		:							int )		->  List[str]:
       SCREAMING_SNAKE_CASE__       :			Union[str, Any]													=pa.array(TypedSequence([[[1, 2, 3]]]   , try_type=ArrayaD((1, 3)   , '''int64''' ) ) )
       self.assertEqual(arr.type   , ArrayaDExtensionType((1, 3)   , '''int64''' ) )




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




 @require_pil
 def        __magic_name__		( self		:							int )		->  List[str]:
       import PIL.Image

       SCREAMING_SNAKE_CASE__       :			str													=PIL.Image.fromarray(np.arange(10   , dtype=np.uinta ).reshape(2   , 5 ) )
       with patch(
           '''datasets.arrow_writer.cast_to_python_objects'''   , side_effect=__lowercase ) as mock_cast_to_python_objects:
             SCREAMING_SNAKE_CASE__       :			List[Any]													=pa.array(TypedSequence([{'''path''': None, '''bytes''': B'''image_bytes'''}, pil_image]   , type=Image() ) )
             SCREAMING_SNAKE_CASE__						,		SCREAMING_SNAKE_CASE__       :			List[Any]													=mock_cast_to_python_objects.call_args_list[-1]
             self.assertIn('''optimize_list_casting'''   , __lowercase )
             self.assertFalse(kwargs['''optimize_list_casting'''] )





def 	_a(					UpperCamelCase__			:  Tuple,		UpperCamelCase__			:  int							):




      '''simple docstring'''






      SCREAMING_SNAKE_CASE__       :			Any													=pa.BufferReader(UpperCamelCase__							) if isinstance(UpperCamelCase__,		pa.Buffer							) else pa.memory_map(UpperCamelCase__							)
      SCREAMING_SNAKE_CASE__       :			List[Any]													=pa.ipc.open_stream(UpperCamelCase__							)
      SCREAMING_SNAKE_CASE__       :			pa.Table													=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(					UpperCamelCase__			:  Any,		UpperCamelCase__			:  int							):




      '''simple docstring'''






      SCREAMING_SNAKE_CASE__       :			Any													=pa.BufferOutputStream()
      SCREAMING_SNAKE_CASE__       :			int													=pa.schema(UpperCamelCase__							) if fields else None
      with ArrowWriter(stream=UpperCamelCase__,		schema=UpperCamelCase__,		writer_batch_size=UpperCamelCase__							) as writer:
            writer.write({'''col_1''': '''foo''', '''col_2''': 1}							)
            writer.write({'''col_1''': '''bar''', '''col_2''': 2}							)
            SCREAMING_SNAKE_CASE__						,		SCREAMING_SNAKE_CASE__       :			Optional[int]													=writer.finalize()
      assert num_examples == 2
      assert num_bytes > 0
      if not fields:
            SCREAMING_SNAKE_CASE__       :			Dict													={'''col_1''': pa.string(), '''col_2''': pa.intaa()}
      assert writer._schema == pa.schema(UpperCamelCase__,		metadata=writer._schema.metadata							)
      _check_output(output.getvalue(),		expected_num_chunks=num_examples if writer_batch_size == 1 else 1							)





def 	_a(					):




      '''simple docstring'''






      SCREAMING_SNAKE_CASE__       :			str													=pa.BufferOutputStream()
      SCREAMING_SNAKE_CASE__       :			str													=Features({'''labels''': ClassLabel(names=['''neg''', '''pos''']							)}							)
      with ArrowWriter(stream=UpperCamelCase__,		features=UpperCamelCase__							) as writer:
            writer.write({'''labels''': 0}							)
            writer.write({'''labels''': 1}							)
            SCREAMING_SNAKE_CASE__						,		SCREAMING_SNAKE_CASE__       :			List[str]													=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__       :			Union[str, Any]													=pa.BufferReader(output.getvalue()							)
      SCREAMING_SNAKE_CASE__       :			Optional[Any]													=pa.ipc.open_stream(UpperCamelCase__							)
      SCREAMING_SNAKE_CASE__       :			pa.Table													=f.read_all()
      SCREAMING_SNAKE_CASE__       :			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(UpperCamelCase__							)





@pytest.mark.parametrize('''writer_batch_size''',		[None, 1, 1_0]							)
def 	_a(					UpperCamelCase__			:  Optional[Any]							):




      '''simple docstring'''






      SCREAMING_SNAKE_CASE__       :			int													=pa.BufferOutputStream()
      with ArrowWriter(
          stream=UpperCamelCase__,		writer_batch_size=UpperCamelCase__,		hash_salt='''split_name''',		check_duplicates=UpperCamelCase__,		) as writer:
            with pytest.raises(UpperCamelCase__							):
                  writer.write({'''col_1''': '''foo''', '''col_2''': 1},		key=[1, 2]							)
                  SCREAMING_SNAKE_CASE__						,		SCREAMING_SNAKE_CASE__       :			str													=writer.finalize()





@pytest.mark.parametrize('''writer_batch_size''',		[None, 2, 1_0]							)
def 	_a(					UpperCamelCase__			:  int							):




      '''simple docstring'''






      SCREAMING_SNAKE_CASE__       :			str													=pa.BufferOutputStream()
      with ArrowWriter(
          stream=UpperCamelCase__,		writer_batch_size=UpperCamelCase__,		hash_salt='''split_name''',		check_duplicates=UpperCamelCase__,		) as writer:
            with pytest.raises(UpperCamelCase__							):
                  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__       :			Optional[Any]													=writer.finalize()





@pytest.mark.parametrize('''writer_batch_size''',		[None, 2, 1_0]							)
def 	_a(					UpperCamelCase__			:  Union[str, Any]							):




      '''simple docstring'''






      SCREAMING_SNAKE_CASE__       :			Optional[Any]													=pa.BufferOutputStream()
      with ArrowWriter(
          stream=UpperCamelCase__,		writer_batch_size=UpperCamelCase__,		hash_salt='''split_name''',		check_duplicates=UpperCamelCase__,		) 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__       :			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(					UpperCamelCase__			:  Union[str, Any],		UpperCamelCase__			:  Optional[int]							):




      '''simple docstring'''






      SCREAMING_SNAKE_CASE__       :			Tuple													=pa.BufferOutputStream()
      SCREAMING_SNAKE_CASE__       :			int													=pa.schema(UpperCamelCase__							) if fields else None
      with ArrowWriter(stream=UpperCamelCase__,		schema=UpperCamelCase__,		writer_batch_size=UpperCamelCase__							) 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__       :			Dict													=writer.finalize()
      assert num_examples == 2
      assert num_bytes > 0
      if not fields:
            SCREAMING_SNAKE_CASE__       :			str													={'''col_1''': pa.string(), '''col_2''': pa.intaa()}
      assert writer._schema == pa.schema(UpperCamelCase__,		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(					UpperCamelCase__			:  Union[str, Any],		UpperCamelCase__			:  int							):




      '''simple docstring'''






      SCREAMING_SNAKE_CASE__       :			Optional[Any]													=pa.BufferOutputStream()
      SCREAMING_SNAKE_CASE__       :			List[Any]													=pa.schema(UpperCamelCase__							) if fields else None
      with ArrowWriter(stream=UpperCamelCase__,		schema=UpperCamelCase__,		writer_batch_size=UpperCamelCase__							) as writer:
            writer.write_table(pa.Table.from_pydict({'''col_1''': ['''foo''', '''bar'''], '''col_2''': [1, 2]}							)							)
            SCREAMING_SNAKE_CASE__						,		SCREAMING_SNAKE_CASE__       :			Tuple													=writer.finalize()
      assert num_examples == 2
      assert num_bytes > 0
      if not fields:
            SCREAMING_SNAKE_CASE__       :			Union[str, Any]													={'''col_1''': pa.string(), '''col_2''': pa.intaa()}
      assert writer._schema == pa.schema(UpperCamelCase__,		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(					UpperCamelCase__			:  Optional[Any],		UpperCamelCase__			:  Optional[Any]							):




      '''simple docstring'''






      SCREAMING_SNAKE_CASE__       :			int													=pa.BufferOutputStream()
      SCREAMING_SNAKE_CASE__       :			List[Any]													=pa.schema(UpperCamelCase__							) if fields else None
      with ArrowWriter(stream=UpperCamelCase__,		schema=UpperCamelCase__,		writer_batch_size=UpperCamelCase__							) 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__       :			int													=writer.finalize()
      assert num_examples == 2
      assert num_bytes > 0
      if not fields:
            SCREAMING_SNAKE_CASE__       :			Dict													={'''col_1''': pa.string(), '''col_2''': pa.intaa()}
      assert writer._schema == pa.schema(UpperCamelCase__,		metadata=writer._schema.metadata							)
      _check_output(output.getvalue(),		expected_num_chunks=num_examples if writer_batch_size == 1 else 1							)





def 	_a(					):




      '''simple docstring'''






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





def 	_a(					UpperCamelCase__			:  Optional[int]							):




      '''simple docstring'''






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





def 	_a(					UpperCamelCase__			:  Optional[int],		UpperCamelCase__			:  Tuple							):




      '''simple docstring'''






      if isinstance(lst[0],		UpperCamelCase__							):
            change_first_primitive_element_in_list(lst[0],		UpperCamelCase__							)
      else:
            SCREAMING_SNAKE_CASE__       :			Dict													=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(					UpperCamelCase__			:  Optional[int],		UpperCamelCase__			:  Optional[Any],		UpperCamelCase__			:  Optional[Any]							):




      '''simple docstring'''






      SCREAMING_SNAKE_CASE__       :			int													=pa.array(TypedSequence(UpperCamelCase__,		optimized_int_type=UpperCamelCase__							)							)
      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(					UpperCamelCase__			:  int,		UpperCamelCase__			:  Tuple,		UpperCamelCase__			:  List[str]							):




      '''simple docstring'''






      SCREAMING_SNAKE_CASE__       :			Union[str, Any]													=pa.array(OptimizedTypedSequence(UpperCamelCase__,		col=UpperCamelCase__							)							)
      assert get_base_dtype(arr.type							) == expected_dtype

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





@pytest.mark.parametrize('''raise_exception''',		[False, True]							)
def 	_a(					UpperCamelCase__			:  int,		UpperCamelCase__			:  Any							):




      '''simple docstring'''






      SCREAMING_SNAKE_CASE__       :			Any													=str(tmp_path / '''dataset-train.arrow'''							)
      try:
            with ArrowWriter(path=UpperCamelCase__							) 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(					UpperCamelCase__			:  Any							):




      '''simple docstring'''






      SCREAMING_SNAKE_CASE__       :			List[Any]													='''mock://dataset-train.arrow'''
      with ArrowWriter(path=UpperCamelCase__,		storage_options=mockfs.storage_options							) as writer:
            assert isinstance(writer._fs,		type(UpperCamelCase__							)							)
            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__       :			Optional[Any]													=writer.finalize()
      assert num_examples == 2
      assert num_bytes > 0
      assert mockfs.exists(UpperCamelCase__							)





def 	_a(					):




      '''simple docstring'''






      SCREAMING_SNAKE_CASE__       :			Optional[int]													=pa.BufferOutputStream()
      with ParquetWriter(stream=UpperCamelCase__							) as writer:
            writer.write({'''col_1''': '''foo''', '''col_2''': 1}							)
            writer.write({'''col_1''': '''bar''', '''col_2''': 2}							)
            SCREAMING_SNAKE_CASE__						,		SCREAMING_SNAKE_CASE__       :			Union[str, Any]													=writer.finalize()
      assert num_examples == 2
      assert num_bytes > 0
      SCREAMING_SNAKE_CASE__       :			Tuple													=pa.BufferReader(output.getvalue()							)
      SCREAMING_SNAKE_CASE__       :			pa.Table													=pq.read_table(UpperCamelCase__							)
      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(					UpperCamelCase__			:  List[Any],		UpperCamelCase__			:  List[Any]							):




      '''simple docstring'''






      import PIL.Image

      SCREAMING_SNAKE_CASE__       :			str													=str(tmp_path / '''test_image_rgb.jpg'''							)
      PIL.Image.fromarray(np.zeros((5, 5),		dtype=np.uinta							)							).save(UpperCamelCase__,		format='''png'''							)
      SCREAMING_SNAKE_CASE__       :			Optional[int]													=pa.BufferOutputStream()
      with ParquetWriter(
          stream=UpperCamelCase__,		features=Features({'''image''': Image()}							),		embed_local_files=UpperCamelCase__							) as writer:
            writer.write({'''image''': image_path}							)
            writer.finalize()
      SCREAMING_SNAKE_CASE__       :			List[str]													=pa.BufferReader(output.getvalue()							)
      SCREAMING_SNAKE_CASE__       :			pa.Table													=pq.read_table(UpperCamelCase__							)
      SCREAMING_SNAKE_CASE__       :			Optional[int]													=pa_table.to_pydict()
      if embed_local_files:
            assert isinstance(out['''image'''][0]['''path'''],		UpperCamelCase__							)
            with open(UpperCamelCase__,		'''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(					):




      '''simple docstring'''






      SCREAMING_SNAKE_CASE__       :			str													=pa.schema([pa.field('''col_1''',		pa.string(),		nullable=UpperCamelCase__							)]							)
      SCREAMING_SNAKE_CASE__       :			List[str]													=pa.BufferOutputStream()
      with ArrowWriter(stream=UpperCamelCase__							) as writer:
            writer._build_writer(inferred_schema=UpperCamelCase__							)
            assert writer._schema == pa.schema([pa.field('''col_1''',		pa.string()							)]							)







'''simple docstring'''
from __future__ import annotations





def 	_a(					UpperCamelCase__			:  List[str],		UpperCamelCase__			:  Union[str, Any],		UpperCamelCase__			:  int,		UpperCamelCase__			:  List[str]							):  # noqa: E741




      '''simple docstring'''






      while r - l > 1:
            SCREAMING_SNAKE_CASE__       :			List[str]													=(l + r) // 2
            if v[m] >= key:
                  SCREAMING_SNAKE_CASE__       :			Dict													=m
            else:
                  SCREAMING_SNAKE_CASE__       :			Any													=m  # noqa: E741
      return r





def 	_a(					UpperCamelCase__			:  list[int]							):




      '''simple docstring'''






      if len(UpperCamelCase__							) == 0:
            return 0

      SCREAMING_SNAKE_CASE__       :			List[Any]													=[0] * len(UpperCamelCase__							)
      SCREAMING_SNAKE_CASE__       :			Dict													=1

      SCREAMING_SNAKE_CASE__       :			Union[str, Any]													=v[0]

      for i in range(1,		len(UpperCamelCase__							)							):
            if v[i] < tail[0]:
                  SCREAMING_SNAKE_CASE__       :			List[Any]													=v[i]
            elif v[i] > tail[length - 1]:
                  SCREAMING_SNAKE_CASE__       :			int													=v[i]
                  length += 1
            else:
                  SCREAMING_SNAKE_CASE__       :			Union[str, Any]													=v[i]

      return length


if __name__ == "__main__":
  import doctest

  doctest.testmod()