






import json
import os
import tempfile

import datasets
from utils import generate_example_dataset, get_duration


SCREAMING_SNAKE_CASE__      :			Dict							=		5_00_00
SCREAMING_SNAKE_CASE__      :			List[str]							=		50_00

SCREAMING_SNAKE_CASE__      :			Dict							=		os.path.split(__file__)
SCREAMING_SNAKE_CASE__      :			Tuple							=		os.path.join(RESULTS_BASEPATH, """results""", RESULTS_FILENAME.replace(""".py""", """.json"""))

@get_duration
def      __lowercase					( snake_case,  snake_case ):







    """simple docstring"""






    for i in range(snake_case ):
        __magic_name__		:Optional[Any]        =      dataset[i]

@get_duration
def      __lowercase					( snake_case,  snake_case,  snake_case ):







    """simple docstring"""






    for i in range(0,  len(snake_case ),  snake_case ):
        __magic_name__		:Any        =      dataset[i : i + batch_size]

@get_duration
def      __lowercase					( snake_case,  snake_case,  snake_case ):







    """simple docstring"""






    with dataset.formatted_as(type=snake_case ):
        for i in range(snake_case ):
            __magic_name__		:int        =      dataset[i]

@get_duration
def      __lowercase					( snake_case,  snake_case,  snake_case,  snake_case ):







    """simple docstring"""






    with dataset.formatted_as(type=snake_case ):
        for i in range(0,  snake_case,  snake_case ):
            __magic_name__		:List[str]        =      dataset[i : i + batch_size]

def      __lowercase					( ):







    """simple docstring"""






    __magic_name__		:Optional[int]        =      {'''num examples''': SPEED_TEST_N_EXAMPLES}
    __magic_name__		:List[str]        =      [
        (read, {'''length''': SMALL_TEST}),
        (read, {'''length''': SPEED_TEST_N_EXAMPLES}),
        (read_batch, {'''length''': SPEED_TEST_N_EXAMPLES, '''batch_size''': 1_0}),
        (read_batch, {'''length''': SPEED_TEST_N_EXAMPLES, '''batch_size''': 1_0_0}),
        (read_batch, {'''length''': SPEED_TEST_N_EXAMPLES, '''batch_size''': 1_0_0_0}),
        (read_formatted, {'''type''': '''numpy''', '''length''': SMALL_TEST}),
        (read_formatted, {'''type''': '''pandas''', '''length''': SMALL_TEST}),
        (read_formatted, {'''type''': '''torch''', '''length''': SMALL_TEST}),
        (read_formatted, {'''type''': '''tensorflow''', '''length''': SMALL_TEST}),
        (read_formatted_batch, {'''type''': '''numpy''', '''length''': SMALL_TEST, '''batch_size''': 1_0}),
        (read_formatted_batch, {'''type''': '''numpy''', '''length''': SMALL_TEST, '''batch_size''': 1_0_0_0}),
    ]

    __magic_name__		:Optional[Any]        =      [
        (read, {'''length''': SMALL_TEST}),
        (read, {'''length''': SPEED_TEST_N_EXAMPLES}),
        (read_batch, {'''length''': SPEED_TEST_N_EXAMPLES, '''batch_size''': 1_0}),
        (read_batch, {'''length''': SPEED_TEST_N_EXAMPLES, '''batch_size''': 1_0_0}),
        (read_batch, {'''length''': SPEED_TEST_N_EXAMPLES, '''batch_size''': 1_0_0_0}),
        (read_formatted, {'''type''': '''numpy''', '''length''': SMALL_TEST}),
        (read_formatted_batch, {'''type''': '''numpy''', '''length''': SMALL_TEST, '''batch_size''': 1_0}),
        (read_formatted_batch, {'''type''': '''numpy''', '''length''': SMALL_TEST, '''batch_size''': 1_0_0_0}),
    ]
    with tempfile.TemporaryDirectory() as tmp_dir:
        print('''generating dataset''' )
        __magic_name__		:str        =      datasets.Features(
            {'''list''': datasets.Sequence(datasets.Value('''float32''' ) ), '''numbers''': datasets.Value('''float32''' )} )
        __magic_name__		:List[str]        =      generate_example_dataset(
            os.path.join(snake_case,  '''dataset.arrow''' ),  snake_case,  num_examples=snake_case,  seq_shapes={'''list''': (1_0_0,)},  )
        print('''first set of iterations''' )
        for func, kwargs in functions:
            print(func.__name__,  str(snake_case ) )
            __magic_name__		:int        =      func(snake_case,  **snake_case )

        print('''shuffling dataset''' )
        __magic_name__		:int        =      dataset.shuffle()
        print('''Second set of iterations (after shuffling''' )
        for func, kwargs in functions_shuffled:
            print('''shuffled ''',  func.__name__,  str(snake_case ) )
            __magic_name__		:Optional[int]        =      func(
                snake_case,  **snake_case )

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


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














SCREAMING_SNAKE_CASE__      :			str							=		"""Alexander Joslin"""

import operator as op

from .stack import Stack

def      __lowercase					( snake_case ):







				"""simple docstring"""






				__magic_name__		:Optional[int]        =      {'''*''': op.mul, '''/''': op.truediv, '''+''': op.add, '''-''': op.sub}

				__magic_name__		:Stack[int]        =      Stack()
				__magic_name__		:Stack[str]        =      Stack()

				for i in equation:
								if i.isdigit():
												# RULE 1
												operand_stack.push(int(snake_case ) )
								elif i in operators:
												# RULE 2
												operator_stack.push(snake_case )
								elif i == ")":
												# RULE 4
												__magic_name__		:Optional[int]        =      operator_stack.peek()
												operator_stack.pop()
												__magic_name__		:List[str]        =      operand_stack.peek()
												operand_stack.pop()
												__magic_name__		:Optional[Any]        =      operand_stack.peek()
												operand_stack.pop()

												__magic_name__		:Optional[int]        =      operators[opr](snake_case,  snake_case )
												operand_stack.push(snake_case )

    # RULE 5
				return operand_stack.peek()


if __name__ == "__main__":
					SCREAMING_SNAKE_CASE__      :			Any							=		"""(5 + ((4 * 2) * (2 + 3)))"""
					# answer = 45
					print(f"{equation} = {dijkstras_two_stack_algorithm(equation)}")






