
import json
import os
from dataclasses import dataclass

import numpy as np
import pyarrow as pa

import datasets
from utils import get_duration


_A       =					10_00_00_00_00_00
_A       =					1_00_00

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



def 		lowercase_     (  A__					,						A__						)				->				datasets.Dataset:
    """simple docstring"""

    snake_case						=   pa.Table.from_pydict({"col": [0] * chunk_size}						)
    snake_case						=   pa.concat_tables([table] * (num_examples // chunk_size)						)
    return datasets.Dataset(A__					,						fingerprint="table_100B"						)







@dataclass
class 	lowerCamelCase						:
     UpperCAmelCase__							:				int
     UpperCAmelCase__							:				int
     UpperCAmelCase__							:				int
     UpperCAmelCase__							:				int





     def 						UpperCAmelCase(self :       Optional[Any]  )		->		Any:
         snake_case						=   np.random.default_rng(self.seed  )
         snake_case						=   rng.integers(low=self.low							,       high=self.high							,       size=self.size  ).tolist()





     def __iter__(self :       Dict  )		->		Optional[Any]:
         return iter(self._sampled_values  )





     def __len__(self :       List[str]  )		->		str:
         return self.size



@get_duration
def 		lowercase_     (  A__						)				->				Optional[int]:
    """simple docstring"""

    snake_case						=   dataset[0]



@get_duration
def 		lowercase_     (  A__						)				->				Optional[Any]:
    """simple docstring"""

    snake_case						=   dataset[-1]



@get_duration
def 		lowercase_     (  A__						)				->				int:
    """simple docstring"""

    snake_case						=   dataset[range(len(A__						) // 2					,						len(A__						) // 2 + 1024						)]



@get_duration
def 		lowercase_     (  A__						)				->				Any:
    """simple docstring"""

    snake_case						=   dataset[RandIter(0					,						len(A__						)					,						1024					,						seed=42						)]



def 		lowercase_     (  )				->				int:
    """simple docstring"""

    snake_case						=   {"num examples": SPEED_TEST_N_EXAMPLES}
    snake_case						=   (get_first_row, get_last_row, get_batch_of_aaaa_rows, get_batch_of_aaaa_random_rows)
    print("generating dataset"						)
    snake_case						=   generate_100B_dataset(num_examples=A__					,						chunk_size=A__						)
    print("Functions"						)
    for func in functions:
        print(func.__name__						)
        snake_case						=   func(A__						)

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


if __name__ == "__main__":  # useful to run the profiler
   benchmark_table_100B()



_A       =					{
    "+": lambda x, y: x + y,
    "-": lambda x, y: x - y,
    "*": lambda x, y: x * y,
    "/": lambda x, y: x / y,
}



def 		lowercase_     (  A__						)				->				Union[str, Any]:
    """simple docstring"""

    return c.isdigit()



def 		lowercase_     (  A__						)				->				int:
    """simple docstring"""

    snake_case						=   []

    # iterate over the string in reverse order
    for c in expression.split()[::-1]:
        # push operand to stack
        if is_operand(A__						):
            stack.append(int(A__						)						)

        else:
            # pop values from stack can calculate the result
            # push the result onto the stack again
            snake_case						=   stack.pop()
            snake_case						=   stack.pop()
            stack.append(calc[c](A__					,						A__						)						)

    return stack.pop()


# Driver code
if __name__ == "__main__":
   _A       =					"+ 9 * 2 6"
   print(evaluate(test_expression))

   _A       =					"/ * 10 2 + 4 1 "
   print(evaluate(test_expression))

