

'''simple docstring'''
from unittest import TestCase

from datasets import Sequence, Value
from datasets.arrow_dataset import Dataset







class 							A__    (       A__  ):





  def 						A  (		self      :	Optional[Any] )	->    str:





       '''simple docstring'''






       return [
           {"col_1": 3, "col_2": "a"},
           {"col_1": 2, "col_2": "b"},
           {"col_1": 1, "col_2": "c"},
           {"col_1": 0, "col_2": "d"},
       ]





  def 						A  (		self      :	Any )	->    Tuple:





       '''simple docstring'''






       _SCREAMING_SNAKE_CASE							    ={'col_1': [3, 2, 1, 0], 'col_2': ['a', 'b', 'c', 'd']}
       return Dataset.from_dict(_a )





  def 						A  (		self      :	Union[str, Any] )	->    Tuple:





       '''simple docstring'''






       _SCREAMING_SNAKE_CASE							    =self._create_example_records()
       _SCREAMING_SNAKE_CASE							    =Dataset.from_list(_a )
       self.assertListEqual(dset.column_names							,					['col_1', 'col_2'] )
       for i, r in enumerate(_a ):
            self.assertDictEqual(_a							,					example_records[i] )





  def 						A  (		self      :	Union[str, Any] )	->    List[Any]:





       '''simple docstring'''






       _SCREAMING_SNAKE_CASE							    =self._create_example_records()
       _SCREAMING_SNAKE_CASE							    =Dataset.from_list(_a )
       _SCREAMING_SNAKE_CASE							    =Dataset.from_dict({k: [r[k] for r in example_records] for k in example_records[0]} )
       self.assertEqual(dset.info							,					dset_from_dict.info )





  def 						A  (		self      :	Any )	->    List[Any]:  # checks what happens with missing columns





       '''simple docstring'''






       _SCREAMING_SNAKE_CASE							    =[{'col_1': 1}, {'col_2': 'x'}]
       _SCREAMING_SNAKE_CASE							    =Dataset.from_list(_a )
       self.assertDictEqual(dset[0]							,					{'col_1': 1} )
       self.assertDictEqual(dset[1]							,					{'col_1': None} )  # NB: first record is used for columns





  def 						A  (		self      :	str )	->    int:  # checks if the type can be inferred from the second record





       '''simple docstring'''






       _SCREAMING_SNAKE_CASE							    =[{'col_1': []}, {'col_1': [1, 2]}]
       _SCREAMING_SNAKE_CASE							    =Dataset.from_list(_a )
       self.assertEqual(dset.info.features['col_1']							,					Sequence(Value('int64' ) ) )





  def 						A  (		self      :	Optional[Any] )	->    Tuple:





       '''simple docstring'''






       _SCREAMING_SNAKE_CASE							    =Dataset.from_list([] )
       self.assertEqual(len(_a )							,					0 )
       self.assertListEqual(dset.column_names							,					[] )






_lowerCamelCase	:		Optional[int]							       =   65521







def SCREAMING_SNAKE_CASE				(       lowercase_						)   ->       int:



       """simple docstring"""

       A__       =    1
       A__       =    0
       for plain_chr in plain_text:
              A__       =    (a + ord(lowercase_						)) % MOD_ADLER
              A__       =    (b + a) % MOD_ADLER
       return (b << 16) | a


