As we all know, machine scheduling is a very classical problem in computer science and has been studied for a very long history. Scheduling problems differ widely in the nature of the constraints that must be satisfied and the type of schedule desire
Consider a town where all the streets are one-way and each street leads from one intersection to another. It is also known that starting from an intersection and walking through town's streets you can never reach the same intersection i.e. the town's
# -*- coding: utf-8 -*- #使用迭代查找一个list中最小和最大值,并返回一个tuple #遍历list,找到最小值 def findMinAndMax(L): if L==[]: return(None, None) else: a=L[0] b=L[0] for num in L: if num<a: a=num for num in L: if num>b: b=num return (a,b) print(findMinAndMax([1,2,3,4,5,6]))
# -*- coding: utf-8 -*- # 请使用迭代查找一个list中最小和最大值,并返回一个tuple from collections import Iterable def findMinAndMax(L): if len(L) == 0: return (None,None) if isinstance(L,Iterable) == True: min = L[0] max = L[0] for x in L: if x > max: max = x if x < min:
请使用迭代查找一个list中最小和最大值,并返回一个tuple: 要注意返回的值的类型是不是tuple def findMinAndMax(L): min=0 max=0 if len(L)==0: return tuple([None,None]) else: for i in L: for j in L: if i>=j: i=j min=i #找出最小值 for i in L: for j in L: if i<=j: i=j max=i #找出最大值 return tuple([min