
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		(      lowerCAmelCase     ):
    def       _SCREAMING_SNAKE_CASE       (  self      ):



           '''simple docstring'''







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



           '''simple docstring'''







           with self.assertRaises(snake_case      ):
                  lowercase							:     Dict       	=      pa.array(TypedSequence([1, 2, 3]      )		,type=pa.intaa()      )
    def       _SCREAMING_SNAKE_CASE       (  self      ):



           '''simple docstring'''







           with self.assertRaises(snake_case      ):
                  lowercase							:     Tuple       	=      pa.array(TypedSequence([1, 2, 3]		,try_type=Value("""bool"""      )		,type=Value("""int64"""      )      )      )
    def       _SCREAMING_SNAKE_CASE       (  self      ):



           '''simple docstring'''







           lowercase							:     Optional[int]       	=      pa.array(TypedSequence([1, 2, 3]		,type=Value("""int32"""      )      )      )
           self.assertEqual(arr.type		,pa.intaa()      )
    def       _SCREAMING_SNAKE_CASE       (  self      ):



           '''simple docstring'''







           with self.assertRaises((TypeError, pa.lib.ArrowInvalid)      ):
                  lowercase							:     str       	=      pa.array(TypedSequence(["""foo""", """bar"""]		,type=Value("""int64"""      )      )      )
    def       _SCREAMING_SNAKE_CASE       (  self      ):



           '''simple docstring'''







           lowercase							:     str       	=      pa.array(TypedSequence([1, 2, 3]		,try_type=Value("""int32"""      )      )      )
           self.assertEqual(arr.type		,pa.intaa()      )
    def       _SCREAMING_SNAKE_CASE       (  self      ):



           '''simple docstring'''







           lowercase							:     str       	=      pa.array(TypedSequence(["""foo""", """bar"""]		,try_type=Value("""int64"""      )      )      )
           self.assertEqual(arr.type		,pa.string()      )
    def       _SCREAMING_SNAKE_CASE       (  self      ):



           '''simple docstring'''







           lowercase							:     Optional[Any]       	=      pa.array(TypedSequence([[[1, 2, 3]]]		,type=ArrayaD((1, 3)		,"""int64"""      )      )      )
           self.assertEqual(arr.type		,ArrayaDExtensionType((1, 3)		,"""int64"""      )      )
    def       _SCREAMING_SNAKE_CASE       (  self      ):



           '''simple docstring'''







           with self.assertRaises((TypeError, pa.lib.ArrowInvalid)      ):
                  lowercase							:     Dict       	=      pa.array(TypedSequence(["""foo""", """bar"""]		,type=ArrayaD((1, 3)		,"""int64"""      )      )      )
    def       _SCREAMING_SNAKE_CASE       (  self      ):



           '''simple docstring'''







           lowercase							:     Union[str, Any]       	=      pa.array(TypedSequence([[[1, 2, 3]]]		,try_type=ArrayaD((1, 3)		,"""int64"""      )      )      )
           self.assertEqual(arr.type		,ArrayaDExtensionType((1, 3)		,"""int64"""      )      )
    def       _SCREAMING_SNAKE_CASE       (  self      ):



           '''simple docstring'''







           lowercase							:     int       	=      pa.array(TypedSequence(["""foo""", """bar"""]		,try_type=ArrayaD((1, 3)		,"""int64"""      )      )      )
           self.assertEqual(arr.type		,pa.string()      )
    @require_pil
    def       _SCREAMING_SNAKE_CASE       (  self      ):



           '''simple docstring'''







           import PIL.Image

           lowercase							:     Dict       	=      PIL.Image.fromarray(np.arange(10		,dtype=np.uinta      ).reshape(2		,5      )      )
           with patch(
               """datasets.arrow_writer.cast_to_python_objects"""		,side_effect=snake_case      ) as mock_cast_to_python_objects:
                  lowercase							:     int       	=      pa.array(TypedSequence([{"""path""": None, """bytes""": b"""image_bytes"""}, pil_image]		,type=Image()      )      )
                  lowercase	,			lowercase							:     Optional[int]       	=      mock_cast_to_python_objects.call_args_list[-1]
                  self.assertIn("""optimize_list_casting"""		,snake_case      )
                  self.assertFalse(kwargs["""optimize_list_casting"""]      )







def 						_snake_case(  SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__				) ->    str:
       lowercase							:     Union[str, Any]       	=      pa.BufferReader(SCREAMING_SNAKE_CASE__				) if isinstance(SCREAMING_SNAKE_CASE__					,	pa.Buffer				) else pa.memory_map(SCREAMING_SNAKE_CASE__				)
       lowercase							:     Any       	=      pa.ipc.open_stream(SCREAMING_SNAKE_CASE__				)
       lowercase							:     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, 10]				)
@pytest.mark.parametrize(
    """fields"""					,	[None, {"""col_1""": pa.string(), """col_2""": pa.intaa()}, {"""col_1""": pa.string(), """col_2""": pa.intaa()}]				)
def 						_snake_case(  SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__				) ->    Optional[int]:
       lowercase							:     int       	=      pa.BufferOutputStream()
       lowercase							:     Optional[int]       	=      pa.schema(SCREAMING_SNAKE_CASE__				) if fields else None
       with ArrowWriter(stream=SCREAMING_SNAKE_CASE__					,	schema=SCREAMING_SNAKE_CASE__					,	writer_batch_size=SCREAMING_SNAKE_CASE__				) as writer:
              writer.write({"""col_1""": """foo""", """col_2""": 1}				)
              writer.write({"""col_1""": """bar""", """col_2""": 2}				)
              lowercase	,			lowercase							:     Dict       	=      writer.finalize()
       assert num_examples == 2
       assert num_bytes > 0
       if not fields:
              lowercase							:     Optional[int]       	=      {"""col_1""": pa.string(), """col_2""": pa.intaa()}
       assert writer._schema == pa.schema(SCREAMING_SNAKE_CASE__					,	metadata=writer._schema.metadata				)
       _check_output(output.getvalue()					,	expected_num_chunks=num_examples if writer_batch_size == 1 else 1				)







def 						_snake_case(  ) ->    Dict:
       lowercase							:     Union[str, Any]       	=      pa.BufferOutputStream()
       lowercase							:     List[str]       	=      Features({"""labels""": ClassLabel(names=["""neg""", """pos"""]				)}				)
       with ArrowWriter(stream=SCREAMING_SNAKE_CASE__					,	features=SCREAMING_SNAKE_CASE__				) as writer:
              writer.write({"""labels""": 0}				)
              writer.write({"""labels""": 1}				)
              lowercase	,			lowercase							:     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
       lowercase							:     List[Any]       	=      pa.BufferReader(output.getvalue()				)
       lowercase							:     Any       	=      pa.ipc.open_stream(SCREAMING_SNAKE_CASE__				)
       lowercase							:     pa.Table       	=      f.read_all()
       lowercase							:     List[str]       	=      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(SCREAMING_SNAKE_CASE__				)







@pytest.mark.parametrize("""writer_batch_size"""					,	[None, 1, 10]				)
def 						_snake_case(  SCREAMING_SNAKE_CASE__				) ->    List[str]:
       lowercase							:     Dict       	=      pa.BufferOutputStream()
       with ArrowWriter(
           stream=SCREAMING_SNAKE_CASE__					,	writer_batch_size=SCREAMING_SNAKE_CASE__					,	hash_salt="""split_name"""					,	check_duplicates=SCREAMING_SNAKE_CASE__					,	) as writer:
              with pytest.raises(SCREAMING_SNAKE_CASE__				):
                     writer.write({"""col_1""": """foo""", """col_2""": 1}					,	key=[1, 2]				)
                     lowercase	,			lowercase							:     Optional[Any]       	=      writer.finalize()







@pytest.mark.parametrize("""writer_batch_size"""					,	[None, 2, 10]				)
def 						_snake_case(  SCREAMING_SNAKE_CASE__				) ->    Any:
       lowercase							:     List[Any]       	=      pa.BufferOutputStream()
       with ArrowWriter(
           stream=SCREAMING_SNAKE_CASE__					,	writer_batch_size=SCREAMING_SNAKE_CASE__					,	hash_salt="""split_name"""					,	check_duplicates=SCREAMING_SNAKE_CASE__					,	) as writer:
              with pytest.raises(SCREAMING_SNAKE_CASE__				):
                     writer.write({"""col_1""": """foo""", """col_2""": 1}					,	key=10				)
                     writer.write({"""col_1""": """bar""", """col_2""": 2}					,	key=10				)
                     lowercase	,			lowercase							:     Dict       	=      writer.finalize()







@pytest.mark.parametrize("""writer_batch_size"""					,	[None, 2, 10]				)
def 						_snake_case(  SCREAMING_SNAKE_CASE__				) ->    Dict:
       lowercase							:     str       	=      pa.BufferOutputStream()
       with ArrowWriter(
           stream=SCREAMING_SNAKE_CASE__					,	writer_batch_size=SCREAMING_SNAKE_CASE__					,	hash_salt="""split_name"""					,	check_duplicates=SCREAMING_SNAKE_CASE__					,	) as writer:
              writer.write({"""col_1""": """foo""", """col_2""": 1}					,	key=1				)
              writer.write({"""col_1""": """bar""", """col_2""": 2}					,	key=2				)
              lowercase	,			lowercase							:     Optional[int]       	=      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, 10]				)
@pytest.mark.parametrize(
    """fields"""					,	[None, {"""col_1""": pa.string(), """col_2""": pa.intaa()}, {"""col_1""": pa.string(), """col_2""": pa.intaa()}]				)
def 						_snake_case(  SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__				) ->    Dict:
       lowercase							:     Union[str, Any]       	=      pa.BufferOutputStream()
       lowercase							:     Tuple       	=      pa.schema(SCREAMING_SNAKE_CASE__				) if fields else None
       with ArrowWriter(stream=SCREAMING_SNAKE_CASE__					,	schema=SCREAMING_SNAKE_CASE__					,	writer_batch_size=SCREAMING_SNAKE_CASE__				) as writer:
              writer.write_batch({"""col_1""": ["""foo""", """bar"""], """col_2""": [1, 2]}				)
              writer.write_batch({"""col_1""": [], """col_2""": []}				)
              lowercase	,			lowercase							:     str       	=      writer.finalize()
       assert num_examples == 2
       assert num_bytes > 0
       if not fields:
              lowercase							:     Union[str, Any]       	=      {"""col_1""": pa.string(), """col_2""": pa.intaa()}
       assert writer._schema == pa.schema(SCREAMING_SNAKE_CASE__					,	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, 10]				)
@pytest.mark.parametrize(
    """fields"""					,	[None, {"""col_1""": pa.string(), """col_2""": pa.intaa()}, {"""col_1""": pa.string(), """col_2""": pa.intaa()}]				)
def 						_snake_case(  SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__				) ->    str:
       lowercase							:     Tuple       	=      pa.BufferOutputStream()
       lowercase							:     List[str]       	=      pa.schema(SCREAMING_SNAKE_CASE__				) if fields else None
       with ArrowWriter(stream=SCREAMING_SNAKE_CASE__					,	schema=SCREAMING_SNAKE_CASE__					,	writer_batch_size=SCREAMING_SNAKE_CASE__				) as writer:
              writer.write_table(pa.Table.from_pydict({"""col_1""": ["""foo""", """bar"""], """col_2""": [1, 2]}				)				)
              lowercase	,			lowercase							:     str       	=      writer.finalize()
       assert num_examples == 2
       assert num_bytes > 0
       if not fields:
              lowercase							:     Union[str, Any]       	=      {"""col_1""": pa.string(), """col_2""": pa.intaa()}
       assert writer._schema == pa.schema(SCREAMING_SNAKE_CASE__					,	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, 10]				)
@pytest.mark.parametrize(
    """fields"""					,	[None, {"""col_1""": pa.string(), """col_2""": pa.intaa()}, {"""col_1""": pa.string(), """col_2""": pa.intaa()}]				)
def 						_snake_case(  SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__				) ->    int:
       lowercase							:     List[str]       	=      pa.BufferOutputStream()
       lowercase							:     List[Any]       	=      pa.schema(SCREAMING_SNAKE_CASE__				) if fields else None
       with ArrowWriter(stream=SCREAMING_SNAKE_CASE__					,	schema=SCREAMING_SNAKE_CASE__					,	writer_batch_size=SCREAMING_SNAKE_CASE__				) 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]}				)				)
              lowercase	,			lowercase							:     Optional[int]       	=      writer.finalize()
       assert num_examples == 2
       assert num_bytes > 0
       if not fields:
              lowercase							:     str       	=      {"""col_1""": pa.string(), """col_2""": pa.intaa()}
       assert writer._schema == pa.schema(SCREAMING_SNAKE_CASE__					,	metadata=writer._schema.metadata				)
       _check_output(output.getvalue()					,	expected_num_chunks=num_examples if writer_batch_size == 1 else 1				)







def 						_snake_case(  ) ->    int:
       with tempfile.TemporaryDirectory() as tmp_dir:
              lowercase							:     Tuple       	=      {"""col_1""": pa.string(), """col_2""": pa.intaa()}
              lowercase							:     List[Any]       	=      os.path.join(SCREAMING_SNAKE_CASE__					,	"""test.arrow"""				)
              with ArrowWriter(path=SCREAMING_SNAKE_CASE__					,	schema=pa.schema(SCREAMING_SNAKE_CASE__				)				) as writer:
                     writer.write_batch({"""col_1""": ["""foo""", """bar"""], """col_2""": [1, 2]}				)
                     lowercase	,			lowercase							:     str       	=      writer.finalize()
              assert num_examples == 2
              assert num_bytes > 0
              assert writer._schema == pa.schema(SCREAMING_SNAKE_CASE__					,	metadata=writer._schema.metadata				)
              _check_output(SCREAMING_SNAKE_CASE__					,	1				)







def 						_snake_case(  SCREAMING_SNAKE_CASE__				) ->    Tuple:
       if pa.types.is_list(SCREAMING_SNAKE_CASE__				):
              return get_base_dtype(arr_type.value_type				)
       else:
              return arr_type







def 						_snake_case(  SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__				) ->    List[Any]:
       if isinstance(lst[0]					,	SCREAMING_SNAKE_CASE__				):
              change_first_primitive_element_in_list(lst[0]					,	SCREAMING_SNAKE_CASE__				)
       else:
              lowercase							:     Optional[Any]       	=      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 						_snake_case(  SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__				) ->    str:
       lowercase							:     List[str]       	=      pa.array(TypedSequence(SCREAMING_SNAKE_CASE__					,	optimized_int_type=SCREAMING_SNAKE_CASE__				)				)
       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 						_snake_case(  SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__				) ->    Dict:
       # in range
       lowercase							:     Dict       	=      pa.array(OptimizedTypedSequence(SCREAMING_SNAKE_CASE__					,	col=SCREAMING_SNAKE_CASE__				)				)
       assert get_base_dtype(arr.type				) == expected_dtype

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







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







def 						_snake_case(  SCREAMING_SNAKE_CASE__				) ->    Union[str, Any]:
       lowercase							:     str       	=      """mock://dataset-train.arrow"""
       with ArrowWriter(path=SCREAMING_SNAKE_CASE__					,	storage_options=mockfs.storage_options				) as writer:
              assert isinstance(writer._fs					,	type(SCREAMING_SNAKE_CASE__				)				)
              assert writer._fs.storage_options == mockfs.storage_options
              writer.write({"""col_1""": """foo""", """col_2""": 1}				)
              writer.write({"""col_1""": """bar""", """col_2""": 2}				)
              lowercase	,			lowercase							:     Optional[int]       	=      writer.finalize()
       assert num_examples == 2
       assert num_bytes > 0
       assert mockfs.exists(SCREAMING_SNAKE_CASE__				)







def 						_snake_case(  ) ->    Dict:
       lowercase							:     Any       	=      pa.BufferOutputStream()
       with ParquetWriter(stream=SCREAMING_SNAKE_CASE__				) as writer:
              writer.write({"""col_1""": """foo""", """col_2""": 1}				)
              writer.write({"""col_1""": """bar""", """col_2""": 2}				)
              lowercase	,			lowercase							:     List[str]       	=      writer.finalize()
       assert num_examples == 2
       assert num_bytes > 0
       lowercase							:     Union[str, Any]       	=      pa.BufferReader(output.getvalue()				)
       lowercase							:     pa.Table       	=      pq.read_table(SCREAMING_SNAKE_CASE__				)
       assert pa_table.to_pydict() == {"col_1": ["foo", "bar"], "col_2": [1, 2]}







@require_pil
@pytest.mark.parametrize("""embed_local_files"""					,	[False, True]				)
def 						_snake_case(  SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__				) ->    Union[str, Any]:
       import PIL.Image

       lowercase							:     str       	=      str(tmp_path / """test_image_rgb.jpg"""				)
       PIL.Image.fromarray(np.zeros((5, 5)					,	dtype=np.uinta				)				).save(SCREAMING_SNAKE_CASE__					,	format="""png"""				)
       lowercase							:     Tuple       	=      pa.BufferOutputStream()
       with ParquetWriter(
           stream=SCREAMING_SNAKE_CASE__					,	features=Features({"""image""": Image()}				)					,	embed_local_files=SCREAMING_SNAKE_CASE__				) as writer:
              writer.write({"""image""": image_path}				)
              writer.finalize()
       lowercase							:     int       	=      pa.BufferReader(output.getvalue()				)
       lowercase							:     pa.Table       	=      pq.read_table(SCREAMING_SNAKE_CASE__				)
       lowercase							:     int       	=      pa_table.to_pydict()
       if embed_local_files:
              assert isinstance(out["""image"""][0]["""path"""]					,	SCREAMING_SNAKE_CASE__				)
              with open(SCREAMING_SNAKE_CASE__					,	"""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 						_snake_case(  ) ->    str:
       lowercase							:     List[str]       	=      pa.schema([pa.field("""col_1"""					,	pa.string()					,	nullable=SCREAMING_SNAKE_CASE__				)]				)
       lowercase							:     Optional[int]       	=      pa.BufferOutputStream()
       with ArrowWriter(stream=SCREAMING_SNAKE_CASE__				) as writer:
              writer._build_writer(inferred_schema=SCREAMING_SNAKE_CASE__				)
              assert writer._schema == pa.schema([pa.field("""col_1"""					,	pa.string()				)]				)

from __future__ import annotations


class      lowerCamelCase    :
  """simple docstring"""







  def __init__(							self       :				Union[str, Any]     ,   __magic_name__       :				str     ,   __magic_name__       :				str      )     ->		Dict:
        SCREAMING_SNAKE_CASE_   ,       SCREAMING_SNAKE_CASE_      =     text, pattern
        SCREAMING_SNAKE_CASE_   ,       SCREAMING_SNAKE_CASE_      =     len(__magic_name__      ), len(__magic_name__      )







  def       __A   (							self       :				List[str]     ,   __magic_name__       :				str      )     ->		int:

        for i in range(self.patLen - 1     ,   -1     ,   -1      ):
              if char == self.pattern[i]:
                    return i
        return -1







  def       __A   (							self       :				Dict     ,   __magic_name__       :				int      )     ->		int:

        for i in range(self.patLen - 1     ,   -1     ,   -1      ):
              if self.pattern[i] != self.text[current_pos + i]:
                    return current_pos + i
        return -1







  def       __A   (							self       :				Tuple      )     ->		list[int]:
        # searches pattern in text and returns index positions
        SCREAMING_SNAKE_CASE_      =     []
        for i in range(self.textLen - self.patLen + 1      ):
              SCREAMING_SNAKE_CASE_      =     self.mismatch_in_text(__magic_name__      )
              if mismatch_index == -1:
                    positions.append(__magic_name__      )
              else:
                    SCREAMING_SNAKE_CASE_      =     self.match_in_pattern(self.text[mismatch_index]      )
                    SCREAMING_SNAKE_CASE_      =     (
                        mismatch_index - match_index
                    )  # shifting index lgtm [py/multiple-definition]
        return positions



A   :     Dict       =				"ABAABA"
A   :     Union[str, Any]       =				"AB"
A   :     str       =				BoyerMooreSearch(text, pattern)
A   :     Tuple       =				bms.bad_character_heuristic()

if len(positions) == 0:
      print("No match found")
else:
      print("Pattern found in following positions: ")
      print(positions)


