def random_int_multiple_of_n(start, stop, n): return randint(start // n, stop // n) * n print(random_int_multiple_of_n(3, 30, 3)) # 👉️ 18 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 第一个示例使...
使用random.uniform()生成一定范围内的浮点数。 import random print("floating point within given range") print(random.uniform(10.5, 25.5)) random.triangular(低,高,模式) 1. 2. 3. 4. 该random.triangular()函数返回一个随机浮点数N,使得lower <= N <= upper 在这些边界之间具有指定的模式。 下限的...
Let’s think about a simple example where we have a set of numbers contained in a list,and we would like to pick one of those numbers uniformly at random. 在本例中,我们需要使用的函数是random.choice,在括号内,我们需要一个列表。 The function we need to use in this case is random.choice...
importrandomprint("Printing random number using random.random()")print(random.random()) 如您所见,我们得到了0.50。您可能会得到其他号码。 random()是random模块的最基本功能。 random模块的几乎所有功能都依赖于基本功能random()。 random()返回范围为[0.0,1.0)的下一个随机浮点数。 random模块功能 现在,让...
Python random intenger number: Generate random numbers using randint() and randrange(). Python random choice: Select a random item from any sequence such as list, tuple, set. Python random sample: Select multiple random items (k sized random samples) from a list or set. ...
import random def compareNum(num1, num2): #函数名首字母小写,其后每个单词的首字母大写 if(num1 > num2): return 1 elif(num1 == num2): return 0 else: return -1 num1 = random.randrange(1, 9, 2) #关于range模块的使用见下方
We have already seen the random module. 我们已经看到了随机模块。 We will be using that to simulate simple random processes,but we’ll also take a look at some other tools the Python has to generate random numbers. 我们将使用它来模拟简单的随机过程,但我们还将看看Python生成随机数的其他一些工具...
importstring,randomrandword=lambdan:"".join([random.choice(string.ascii_letters)foriinrange(n)])...
value=Random_single() if value==True: count+=1 return count # 计算女性高于男性概率 def Probability(n): count=Multiple_random(n) p=count*1.0/n return p probability=Probability(n) print '随机次数',n print '女性高于男性概率:',probability ...
import random # Fixed seed for repetitive results const_seed = 200 # Bounds of numbers n_min = 0 n_max = 2 # Final number of values n_numbers = 5 # Seed and retrieve the values random.seed(const_seed) numbers = [random.uniform(n_min, n_max) for i in range(0, n_numbers)] ...