




from typing import List, Optional, TypeVar

from .arrow_dataset import Dataset, _concatenate_map_style_datasets, _interleave_map_style_datasets
from .dataset_dict import DatasetDict, IterableDatasetDict
from .info import DatasetInfo
from .iterable_dataset import IterableDataset, _concatenate_iterable_datasets, _interleave_iterable_datasets
from .splits import NamedSplit
from .utils import logging
from .utils.py_utils import Literal


UpperCAmelCase_		:					Any          =  logging.get_logger(__name__)


UpperCAmelCase_		:					Dict          =  TypeVar("DatasetType", Dataset, IterableDataset)




def 		lowerCAmelCase_ (						lowerCamelCase						,  lowerCamelCase = None						,  lowerCamelCase = None						,  lowerCamelCase = None						,  lowerCamelCase = None						,  lowerCamelCase = "first_exhausted"						,  ):
				from .arrow_dataset import Dataset
				from .iterable_dataset import IterableDataset

				if not datasets:
								raise ValueError("""Unable to interleave an empty list of datasets.""" )
				for i, dataset in enumerate(lowerCamelCase ):
								if not isinstance(lowerCamelCase						,  (Dataset, IterableDataset) ):
												if isinstance(lowerCamelCase						,  (DatasetDict, IterableDatasetDict) ):
																if not dataset:
																				raise ValueError(
																				    F"Expected a list of Dataset objects or a list of IterableDataset objects, but element at position {i} "
																				    """is an empty dataset dictionary.""" )
																raise ValueError(
																    F"Dataset at position {i} has at least one split: {list(lowerCamelCase )}\n"
																    F"Please pick one to interleave with the other datasets, for example: dataset['{next(iter(lowerCamelCase ) )}']" )
												raise ValueError(
												    F"Expected a list of Dataset objects or a list of IterableDataset objects, but element at position {i} is a {type(lowerCamelCase ).__name__}." )
								if i == 0:
												__magic_name__					,			__magic_name__						:						List[str]										=(
												    (Dataset, IterableDataset) if isinstance(lowerCamelCase						,  lowerCamelCase ) else (IterableDataset, Dataset)
												)
								elif not isinstance(lowerCamelCase						,  lowerCamelCase ):
												raise ValueError(
												    F"Unable to interleave a {dataset_type.__name__} (at position 0) with a {other_type.__name__} (at position {i}). Expected a list of Dataset objects or a list of IterableDataset objects." )
				if stopping_strategy not in ["first_exhausted", "all_exhausted"]:
								raise ValueError(F"{stopping_strategy} is not supported. Please enter a valid stopping_strategy." )
				if dataset_type is Dataset:
								return _interleave_map_style_datasets(
								    lowerCamelCase						,  lowerCamelCase						,  lowerCamelCase						,  info=lowerCamelCase						,  split=lowerCamelCase						,  stopping_strategy=lowerCamelCase )
				else:
								return _interleave_iterable_datasets(
								    lowerCamelCase						,  lowerCamelCase						,  lowerCamelCase						,  info=lowerCamelCase						,  split=lowerCamelCase						,  stopping_strategy=lowerCamelCase )




def 		lowerCAmelCase_ (						lowerCamelCase						,  lowerCamelCase = None						,  lowerCamelCase = None						,  lowerCamelCase = 0						,  ):

				if not dsets:
								raise ValueError("""Unable to concatenate an empty list of datasets.""" )
				for i, dataset in enumerate(lowerCamelCase ):
								if not isinstance(lowerCamelCase						,  (Dataset, IterableDataset) ):
												if isinstance(lowerCamelCase						,  (DatasetDict, IterableDatasetDict) ):
																if not dataset:
																				raise ValueError(
																				    F"Expected a list of Dataset objects or a list of IterableDataset objects, but element at position {i} "
																				    """is an empty dataset dictionary.""" )
																raise ValueError(
																    F"Dataset at position {i} has at least one split: {list(lowerCamelCase )}\n"
																    F"Please pick one to interleave with the other datasets, for example: dataset['{next(iter(lowerCamelCase ) )}']" )
												raise ValueError(
												    F"Expected a list of Dataset objects or a list of IterableDataset objects, but element at position {i} is a {type(lowerCamelCase ).__name__}." )
								if i == 0:
												__magic_name__					,			__magic_name__						:						List[Any]										=(
												    (Dataset, IterableDataset) if isinstance(lowerCamelCase						,  lowerCamelCase ) else (IterableDataset, Dataset)
												)
								elif not isinstance(lowerCamelCase						,  lowerCamelCase ):
												raise ValueError(
												    F"Unable to interleave a {dataset_type.__name__} (at position 0) with a {other_type.__name__} (at position {i}). Expected a list of Dataset objects or a list of IterableDataset objects." )
				if dataset_type is Dataset:
								return _concatenate_map_style_datasets(lowerCamelCase						,  info=lowerCamelCase						,  split=lowerCamelCase						,  axis=lowerCamelCase )
				else:
								return _concatenate_iterable_datasets(lowerCamelCase						,  info=lowerCamelCase						,  split=lowerCamelCase						,  axis=lowerCamelCase )






'''simple docstring'''
def      UpperCamelCase_				(      A__  ,      A__  ,      A__						):
	if len(A__						) != len(A__						):
		raise ValueError("""The length of profit and weight must be same."""						)
	if max_weight <= 0:
		raise ValueError("""max_weight must greater than zero."""						)
	if any(p < 0 for p in profit						):
		raise ValueError("""Profit can not be negative."""						)
	if any(w < 0 for w in weight						):
		raise ValueError("""Weight can not be negative."""						)

	# List created to store profit gained for the 1kg in case of each weight
	# respectively.  Calculate and append profit/weight for each element.
	a_      				=						[p / w for p, w in zip(A__  ,      A__						)]

	# Creating a copy of the list and sorting profit/weight in ascending order
	a_      				=						sorted(A__						)

	# declaring useful variables
	a_      				=						len(A__						)
	a_      				=						0
	a_      				=						0
	a_      				=						0

	# loop till the total weight do not reach max limit e.g. 15 kg and till i<length
	while limit <= max_weight and i < length:
		# flag value for encountered greatest element in sorted_profit_by_weight
		a_      				=						sorted_profit_by_weight[length - i - 1]
		a_      				=						profit_by_weight.index(A__						)
		a_      				=						-1

		# check if the weight encountered is less than the total weight
		# encountered before.
		if max_weight - limit >= weight[index]:
			limit += weight[index]
			# Adding profit gained for the given weight 1 ===
			# weight[index]/weight[index]
			gain += 1 * profit[index]
		else:
			# Since the weight encountered is greater than limit, therefore take the
			# required number of remaining kgs and calculate profit for it.
			# weight remaining / weight[index]
			gain += (max_weight - limit) / weight[index] * profit[index]
			break
		i += 1
	return gain


if __name__ == "__main__":
		print(
		    'Input profits, weights, and then max_weight (all positive ints) separated by '
		    'spaces.'
		)

		lowercase__											=[int(x) for x in input('Input profits separated by spaces: ').split()]
		lowercase__											=[int(x) for x in input('Input weights separated by spaces: ').split()]
		lowercase__											=int(input('Max weight allowed: '))

		# Function Call
		calc_profit(profit, weight, max_weight)
