




import json
import os
import tempfile

import datasets
from utils import generate_example_dataset, get_duration


_SCREAMING_SNAKE_CASE							:       Tuple						=			5_0000
_SCREAMING_SNAKE_CASE							:       Any						=			5000

_SCREAMING_SNAKE_CASE		, _SCREAMING_SNAKE_CASE							:       Any						=			os.path.split(__file__)
_SCREAMING_SNAKE_CASE							:       str						=			os.path.join(RESULTS_BASEPATH, "results", RESULTS_FILENAME.replace(".py", ".json"))


@get_duration
def 					UpperCamelCase_(     snake_case							:	Any							,    snake_case							:	Union[str, Any]					):

							'''simple docstring'''






							for i in range(lowercase__					):
														snake_case_      =				dataset[i]


@get_duration
def 					UpperCamelCase_(     snake_case							:	str							,    snake_case							:	int							,    snake_case							:	Union[str, Any]					):

							'''simple docstring'''






							for i in range(0							,    len(lowercase__					)							,    lowercase__					):
														snake_case_      =				dataset[i : i + batch_size]


@get_duration
def 					UpperCamelCase_(     snake_case							:	Union[str, Any]							,    snake_case							:	Optional[int]							,    snake_case							:	Any					):

							'''simple docstring'''






							with dataset.formatted_as(type=lowercase__					):
														for i in range(lowercase__					):
																					snake_case_      =				dataset[i]


@get_duration
def 					UpperCamelCase_(     snake_case							:	Optional[Any]							,    snake_case							:	Tuple							,    snake_case							:	List[Any]							,    snake_case							:	List[Any]					):

							'''simple docstring'''






							with dataset.formatted_as(type=lowercase__					):
														for i in range(0							,    lowercase__							,    lowercase__					):
																					snake_case_      =				dataset[i : i + batch_size]


def 					UpperCamelCase_(     ):

							'''simple docstring'''






							snake_case_      =				{'num examples': SPEED_TEST_N_EXAMPLES}
							snake_case_      =				[
							    (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}),
							]

							snake_case_      =				[
							    (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"					)
														snake_case_      =				datasets.Features(
														    {"list": datasets.Sequence(datasets.Value("float32"					)					), "numbers": datasets.Value("float32"					)}					)
														snake_case_      =				generate_example_dataset(
														    os.path.join(lowercase__							,    "dataset.arrow"					)							,    lowercase__							,    num_examples=lowercase__							,    seq_shapes={"list": (1_0_0,)}							,    )
														print("first set of iterations"					)
														for func, kwargs in functions:
																					print(func.__name__							,    str(lowercase__					)					)
																					snake_case_      =				func(lowercase__							,    **lowercase__					)

														print("shuffling dataset"					)
														snake_case_      =				dataset.shuffle()
														print("Second set of iterations (after shuffling"					)
														for func, kwargs in functions_shuffled:
																					print("shuffled "							,    func.__name__							,    str(lowercase__					)					)
																					snake_case_      =				func(
																					    lowercase__							,    **lowercase__					)

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


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










'''simple docstring'''





_SCREAMING_SNAKE_CASE							:       Optional[int]						=			"Alexander Joslin"

import operator as op

from .stack import Stack


def 					UpperCamelCase_(     snake_case							:	str					):

							'''simple docstring'''






							snake_case_      =				{"*": op.mul, "/": op.truediv, "+": op.add, "-": op.sub}

							snake_case_      =				Stack()
							snake_case_      =				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
																					snake_case_      =				operator_stack.peek()
																					operator_stack.pop()
																					snake_case_      =				operand_stack.peek()
																					operand_stack.pop()
																					snake_case_      =				operand_stack.peek()
																					operand_stack.pop()

																					snake_case_      =				operators[opr](snake_case							,    snake_case					)
																					operand_stack.push(snake_case					)

    # RULE 5
							return operand_stack.peek()


if __name__ == "__main__":
		_SCREAMING_SNAKE_CASE							:       List[Any]						=			"(5 + ((4 * 2) * (2 + 3)))"
		# answer = 45
		print(F"{equation} = {dijkstras_two_stack_algorithm(equation)}")




