


from .number_theory.prime_numbers import next_prime






class        UpperCAmelCase__			:



    """simple docstring"""






    def __init__(     self   ,  A_   ,  A_ = None   ,  A_ = None   ,  )    ->			None:
         __UpperCamelCase       				=size_table
         __UpperCamelCase       				=[None] * self.size_table
         __UpperCamelCase       				=0.75 if lim_charge is None else lim_charge
         __UpperCamelCase       				=1 if charge_factor is None else charge_factor
         __UpperCamelCase       				=[]
         __UpperCamelCase       				={}






    def _a   (     self       )    ->			Optional[Any]:
         return self._keys






    def _a   (     self       )    ->			List[Any]:
         return sum(1 for slot in self.values if slot is not None       ) / (
             self.size_table * self.charge_factor
         )






    def _a   (     self   ,  A_       )    ->			List[Any]:
         return key % self.size_table






    def _a   (     self   ,  A_       )    ->			Optional[int]:
         print(f'step {step_ord}'       )
         print(list(range(len(self.values       )       )       )       )
         print(self.values       )






    def _a   (     self   ,  A_       )    ->			Tuple:
         __UpperCamelCase       				=1
         __UpperCamelCase       				=values
         for value in values:
              self.insert_data(A_       )
              self._step_by_step(A_       )
              i += 1






    def _a   (     self   ,  A_   ,  A_       )    ->			str:
         __UpperCamelCase       				=data
         __UpperCamelCase       				=data






    def _a   (     self   ,  A_   ,  A_=None       )    ->			Dict:
         __UpperCamelCase       				=self.hash_function(key + 1       )

         while self.values[new_key] is not None and self.values[new_key] != key:
              if self.values.count(A_       ) > 0:
                   __UpperCamelCase       				=self.hash_function(new_key + 1       )
              else:
                   __UpperCamelCase       				=None
                   break

         return new_key






    def _a   (     self       )    ->			List[str]:
         __UpperCamelCase       				=[value for value in self.values if value is not None]
         __UpperCamelCase       				=next_prime(self.size_table   ,  factor=2       )
         self._keys.clear()
         __UpperCamelCase       				=[None] * self.size_table  # hell's pointers D: don't DRY ;/
         for value in survivor_values:
              self.insert_data(A_       )






    def _a   (     self   ,  A_       )    ->			str:
         __UpperCamelCase       				=self.hash_function(A_       )

         if self.values[key] is None:
              self._set_value(A_   ,  A_       )

         elif self.values[key] == data:
              pass

         else:
              __UpperCamelCase       				=self._collision_resolution(A_   ,  A_       )
              if collision_resolution is not None:
                   self._set_value(A_   ,  A_       )
              else:
                   self.rehashing()
                   self.insert_data(A_       )









import json
import os
import tempfile

import datasets
from utils import generate_example_dataset, get_duration


_A									=		50_0000

_A			,	_A									=		os.path.split(__file__)
_A									=		os.path.join(RESULTS_BASEPATH, 'results', RESULTS_FILENAME.replace('.py', '.json'))

@get_duration
def 		_UpperCAmelCase							(     SCREAMING_SNAKE_CASE__     :   datasets.Dataset							):
     __UpperCamelCase       				=dataset.select(range(0     ,	len(SCREAMING_SNAKE_CASE__							)     ,	2							)							)

@get_duration
def 		_UpperCAmelCase							(     SCREAMING_SNAKE_CASE__     :   datasets.Dataset							):
     __UpperCamelCase       				=dataset.sort('numbers'							)

@get_duration
def 		_UpperCAmelCase							(     SCREAMING_SNAKE_CASE__     :   datasets.Dataset							):
     __UpperCamelCase       				=dataset.shuffle()

@get_duration
def 		_UpperCAmelCase							(     SCREAMING_SNAKE_CASE__     :   datasets.Dataset							):
     __UpperCamelCase       				=dataset.train_test_split(0.1							)

@get_duration
def 		_UpperCAmelCase							(     SCREAMING_SNAKE_CASE__     :   datasets.Dataset     ,	SCREAMING_SNAKE_CASE__     :   int=10							):
     for shard_id in range(SCREAMING_SNAKE_CASE__							):
          __UpperCamelCase       				=dataset.shard(SCREAMING_SNAKE_CASE__     ,	SCREAMING_SNAKE_CASE__							)

def 		_UpperCAmelCase							(     ):
     __UpperCamelCase       				={'num examples': SPEED_TEST_N_EXAMPLES}
     __UpperCamelCase       				=(select, sort, shuffle, train_test_split, shard)
     with tempfile.TemporaryDirectory() as tmp_dir:
          print('generating dataset'							)
          __UpperCamelCase       				=datasets.Features({'text': datasets.Value('string'							), 'numbers': datasets.Value('float32'							)}							)
          __UpperCamelCase       				=generate_example_dataset(
              os.path.join(SCREAMING_SNAKE_CASE__     ,	'dataset.arrow'							)     ,	SCREAMING_SNAKE_CASE__     ,	num_examples=SCREAMING_SNAKE_CASE__							)
          print('Functions'							)
          for func in functions:
               print(func.__name__							)
               __UpperCamelCase       				=func(SCREAMING_SNAKE_CASE__							)

     with open(SCREAMING_SNAKE_CASE__     ,	'wb'							) as f:
          f.write(json.dumps(SCREAMING_SNAKE_CASE__							).encode('utf-8'							)							)


if __name__ == "__main__":  # useful to run the profiler
   benchmark_indices_mapping()





