from typing import TypeVar

from .arrow_dataset import Dataset, _split_by_node_map_style_dataset
from .iterable_dataset import IterableDataset, _split_by_node_iterable_dataset


UpperCamelCase    				=		TypeVar('''DatasetType''', Dataset, IterableDataset)

def      lowercase_							(     _lowerCamelCase				:			Any						,      _lowerCamelCase				:			int						,      _lowerCamelCase				:			Tuple):


    if isinstance(_SCREAMING_SNAKE_CASE						,      _SCREAMING_SNAKE_CASE):
        return _split_by_node_map_style_dataset(_SCREAMING_SNAKE_CASE						,      rank=_SCREAMING_SNAKE_CASE						,      world_size=_SCREAMING_SNAKE_CASE)
    else:
        return _split_by_node_iterable_dataset(_SCREAMING_SNAKE_CASE						,      rank=_SCREAMING_SNAKE_CASE						,      world_size=_SCREAMING_SNAKE_CASE)










"""simple docstring"""





def    a__       (       _SCREAMING_SNAKE_CASE	,						_SCREAMING_SNAKE_CASE     ):




		"""simple docstring"""


		UpperCamelCase =						sorted(_SCREAMING_SNAKE_CASE	,						key=lambda _SCREAMING_SNAKE_CASE     : value[2]	,						reverse=_SCREAMING_SNAKE_CASE     )

		# Create a list of size equal to the maximum deadline
		# and initialize it with -1
		UpperCamelCase =						max(_SCREAMING_SNAKE_CASE	,						key=lambda _SCREAMING_SNAKE_CASE     : value[1]     )[1]
		UpperCamelCase =						[-1] * max_deadline

		# Finding the maximum profit and the count of jobs
		UpperCamelCase =						0
		UpperCamelCase =						0
		for job in jobs:
				# Find a free time slot for this job
				# (Note that we start from the last possible slot)
				for i in range(job[1] - 1	,						-1	,						-1     ):
						if time_slots[i] == -1:
								UpperCamelCase =						job[0]
								count += 1
								max_profit += job[2]
								break
		return [count, max_profit]


if __name__ == "__main__":
						import doctest

						doctest.testmod()






