

import os
import textwrap

import pyarrow as pa
import pytest

from datasets import ClassLabel, Features, Image
from datasets.packaged_modules.csv.csv import Csv

from ..utils import require_pil

@pytest.fixture
def      snake_case__      (   SCREAMING_SNAKE_CASE_		:   List[str]      ):



     '''simple docstring'''





     lowercase__   :       str				=	tmp_path / 'file.csv'
     lowercase__   :       Optional[int]				=	textwrap.dedent(
         '\\n        header1,header2\n        1,2\n        10,20\n        '      )
     with open(SCREAMING_SNAKE_CASE_     ,					'w'      ) as f:
          f.write(SCREAMING_SNAKE_CASE_      )
     return str(SCREAMING_SNAKE_CASE_      )

@pytest.fixture
def      snake_case__      (   SCREAMING_SNAKE_CASE_		:   Dict      ):



     '''simple docstring'''





     lowercase__   :       Optional[int]				=	tmp_path / 'malformed_file.csv'
     lowercase__   :       Any				=	textwrap.dedent(
         '\\n        header1,header2\n        1,2\n        10,20,\n        '      )
     with open(SCREAMING_SNAKE_CASE_     ,					'w'      ) as f:
          f.write(SCREAMING_SNAKE_CASE_      )
     return str(SCREAMING_SNAKE_CASE_      )

@pytest.fixture
def      snake_case__      (   SCREAMING_SNAKE_CASE_		:   Optional[Any]     ,					SCREAMING_SNAKE_CASE_		:   str      ):



     '''simple docstring'''





     lowercase__   :       List[str]				=	tmp_path / 'csv_with_image.csv'
     lowercase__   :       str				=	textwrap.dedent(
         f"""\
        image
        {image_file}
        """      )
     with open(SCREAMING_SNAKE_CASE_     ,					'w'      ) as f:
          f.write(SCREAMING_SNAKE_CASE_      )
     return str(SCREAMING_SNAKE_CASE_      )

@pytest.fixture
def      snake_case__      (   SCREAMING_SNAKE_CASE_		:   List[Any]      ):



     '''simple docstring'''





     lowercase__   :       Optional[Any]				=	tmp_path / 'csv_with_label.csv'
     lowercase__   :       Dict				=	textwrap.dedent(
         '\\n        label\n        good\n        bad\n        good\n        '      )
     with open(SCREAMING_SNAKE_CASE_     ,					'w'      ) as f:
          f.write(SCREAMING_SNAKE_CASE_      )
     return str(SCREAMING_SNAKE_CASE_      )

@pytest.fixture
def      snake_case__      (   SCREAMING_SNAKE_CASE_		:   int      ):



     '''simple docstring'''





     lowercase__   :       int				=	tmp_path / 'csv_with_int_list.csv'
     lowercase__   :       Optional[int]				=	textwrap.dedent(
         '\\n        int_list\n        1 2 3\n        4 5 6\n        7 8 9\n        '      )
     with open(SCREAMING_SNAKE_CASE_     ,					'w'      ) as f:
          f.write(SCREAMING_SNAKE_CASE_      )
     return str(SCREAMING_SNAKE_CASE_      )

def      snake_case__      (   SCREAMING_SNAKE_CASE_		:   int     ,					SCREAMING_SNAKE_CASE_		:   Union[str, Any]     ,					SCREAMING_SNAKE_CASE_		:   Union[str, Any]      ):



     '''simple docstring'''





     lowercase__   :       int				=	Csv()
     lowercase__   :       List[Any]				=	csv._generate_tables([[csv_file, malformed_csv_file]]      )
     with pytest.raises(SCREAMING_SNAKE_CASE_     ,					match='Error tokenizing data'      ):
          for _ in generator:
               pass
     assert any(
         record.levelname == 'ERROR'
         and 'Failed to read file' in record.message
         and os.path.basename(SCREAMING_SNAKE_CASE_      ) in record.message
         for record in caplog.records      )

@require_pil
def      snake_case__      (   SCREAMING_SNAKE_CASE_		:   Tuple      ):



     '''simple docstring'''





     with open(SCREAMING_SNAKE_CASE_     ,					encoding='utf-8'      ) as f:
          lowercase__   :       List[Any]				=	f.read().splitlines()[1]
     lowercase__   :       Tuple				=	Csv(encoding='utf-8'     ,					features=Features({'image': Image()}      )      )
     lowercase__   :       Optional[int]				=	csv._generate_tables([[csv_file_with_image]]      )
     lowercase__   :       Tuple				=	pa.concat_tables([table for _, table in generator]      )
     assert pa_table.schema.field('image'      ).type == Image()()
     lowercase__   :       Any				=	pa_table.to_pydict()['image']
     assert generated_content == [{"path": image_file, "bytes": None}]

def      snake_case__      (   SCREAMING_SNAKE_CASE_		:   List[Any]      ):



     '''simple docstring'''





     with open(SCREAMING_SNAKE_CASE_     ,					encoding='utf-8'      ) as f:
          lowercase__   :       Optional[Any]				=	f.read().splitlines()[1:]
     lowercase__   :       Dict				=	Csv(encoding='utf-8'     ,					features=Features({'label': ClassLabel(names=['good', 'bad']      )}      )      )
     lowercase__   :       Any				=	csv._generate_tables([[csv_file_with_label]]      )
     lowercase__   :       Dict				=	pa.concat_tables([table for _, table in generator]      )
     assert pa_table.schema.field('label'      ).type == ClassLabel(names=['good', 'bad']      )()
     lowercase__   :       Tuple				=	pa_table.to_pydict()['label']
     assert generated_content == [ClassLabel(names=['good', 'bad']      ).straint(SCREAMING_SNAKE_CASE_      ) for label in labels]

def      snake_case__      (   SCREAMING_SNAKE_CASE_		:   Dict      ):



     '''simple docstring'''





     lowercase__   :       List[Any]				=	Csv(encoding='utf-8'     ,					sep=','     ,					converters={'int_list': lambda SCREAMING_SNAKE_CASE_      : [int(SCREAMING_SNAKE_CASE_      ) for i in x.split()]}      )
     lowercase__   :       str				=	csv._generate_tables([[csv_file_with_int_list]]      )
     lowercase__   :       str				=	pa.concat_tables([table for _, table in generator]      )
     assert pa.types.is_list(pa_table.schema.field('int_list'      ).type      )
     lowercase__   :       int				=	pa_table.to_pydict()['int_list']
     assert generated_content == [[1, 2, 3], [4, 5, 6], [7, 8, 9]]




from __future__ import annotations


class 				SCREAMING_SNAKE_CASE__ :





    def __init__(				self						,       a						,       a):
         lowercase__				,			lowercase__   :       Dict				=	text, pattern
         lowercase__				,			lowercase__   :       Any				=	len(a), len(a)





    def 				snake_case_    (				self						,       a):

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





    def 				snake_case_    (				self						,       a):

         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 				snake_case_    (				self):
         # searches pattern in text and returns index positions
         lowercase__   :       Any				=	[]
         for i in range(self.textLen - self.patLen + 1):
              lowercase__   :       Optional[Any]				=	self.mismatch_in_text(a)
              if mismatch_index == -1:
                   positions.append(a)
              else:
                   lowercase__   :       Optional[int]				=	self.match_in_pattern(self.text[mismatch_index])
                   lowercase__   :       Optional[Any]				=	(
                       mismatch_index - match_index
                   )  # shifting index lgtm [py/multiple-definition]
         return positions



snake_case_        =			'''ABAABA'''
snake_case_        =			'''AB'''
snake_case_        =			BoyerMooreSearch(text, pattern)
snake_case_        =			bms.bad_character_heuristic()

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

