python随机数_Python随机数
python随机数
In this tutorial, we are going to learn about Python Random Number. In our previous tutorial, we learned about .
在本教程中，我们将学习Python随机数。 在上⼀教程中，我们了解了 。
Python随机数 (Python Random Number)
To work with python random number, we need to import Python’s random module at first. Python random module provides pseudo-randomness.
要使⽤python随机数，我们⾸先需要导⼊Python的random模块。 Python随机模块提供伪随机性。
Python random module uses Mersenne Twister as the core random generator. So, this module is completely unsuitable for cryptographic purposes for being deterministic. However, we can use Python’s random module for most of the cases because Python’s random module contains many well known random distributions.
Python随机模块使⽤Mersenne Twister作为核⼼随机⽣成器。 因此，该模块完全不适合⽤于确定性的加密⽬的。 但是，在⼤多数情况下，我们可以使⽤Python的随机模块，因为Python的随机模块包含许多众所周知的随机分布。
Python随机整数 (Python Random Integer)
In this section, we will be discussing about generation integer numbers randomly. We can use randint(a,b) function to get a random integer from range a to b. Again, we can get number from a sequence by using randrange(start, stop, step) function. Let’s see an example to get python random integer.
在本节中，我们将随机讨论⽣成整数。 我们可以使⽤randint(a,b)函数来获取范围从a到b的随机整数。 同样，我们可以使⽤randrange(start, stop, step)函数从序列中获取数字。 让我们看⼀个获取python随机整数的⽰例。
import random as rand
a = 10
b = 100
print('\na =', a, 'and b =', b)
print('printing number [', a, ', ', b, ') :', rand.randint(a,b))
start = 1
stop = 12
step = 2
print('\nsequence = [1, 3, 5, 7, 9, 11]')
print('printing one number from the sequence :', rand.randrange(start, stop, step))
For each run, the output will change. However, here given a sample output.
对于每次运⾏，输出都会改变。 但是，这⾥给出了⽰例输出。
Python随机浮动 (Python Random Float)
There are several functions that returns real number or float randomly. For example, random() function returns a real number from 0 to 1 (exclusive).
有⼏个函数可以返回实数或随机浮动。 例如， random()函数返回⼀个从0到1（不包括）的实数。
Again, uniform(a, b) functions return a real number from a to b. Moreover there are some random distributions also available in Python random module. We can also get real number from those distribution.
同样， uniform(a, b)函数将实数从a返回到b。 此外，Python随机模块中还提供了⼀些随机分布。 我们还可以从这些分布中获得实数。
We can get random numbers from exponential distribution by using expovariate(lambd) function.
我们可以使⽤expovariate（lambd）函数从指数分布中获得随机数。
import random as rand
print('Random number from 0 to 1 :', rand.random())
print('Uniform Distribution [1,5] :', rand.uniform(1, 5))
print('Gaussian Distribution mu=0, sigma=1 :', rand.gauss(0, 1))
print('Exponential Distribution lambda = 1/10 :', povariate(1/10))
The values in output will vary for each execution. You will get output like this.
输出中的值对于每次执⾏都会有所不同。 您将获得这样的输出。
Random number from 0 to 1 : 0.5311529501408693
Uniform Distribution [1,5] : 3.8716411264052546
Gaussian Distribution mu=0, sigma=1 : 0.8779046620056893
Exponential Distribution lambda = 1/10 : 1.4637113187536595
Python随机种⼦ (Python Random seed)
random pythonPython random number generation is based on the previous number, so using system time is a great way to ensure that every time our program runs, it generates different numbers.
Python随机数的⽣成基于先前的数字，因此使⽤系统时间是确保每次程序运⾏时都会⽣成不同数字的好⽅法。
We can use python random seed() function to set the initial value. Note that if our seed value doesn’t change in each execution, we will get same sequence of numbers. Below is a sample program to prove this theory about seed value.
我们可以使⽤python random seed（）函数来设置初始值。 请注意，如果我们的种⼦值在每次执⾏中都没有改变，我们将获得相同的数字序列。 下⾯是⼀个⽰例程序，⽤于证明有关种⼦价值的这⼀理论。
import random
random.seed(10)
print('1st random number = ', random.random())
print('2nd random number = ', random.random())
print('1st random int = ', random.randint(1, 100))
print('2nd random int = ', random.randint(1, 100))
# resetting the seed to first value
random.seed(10)
print('3rd random number = ', random.random())
print('4th random number = ', random.random())
print('3rd random int = ', random.randint(1, 100))
print('4th random int = ', random.randint(1, 100))
Below image shows the output produced by the python random seed example program. We will get the same sequence of random numbers for each run.
python random seed
下图显⽰了python随机种⼦⽰例程序产⽣的输出。 对于每次运⾏，我们将获得相同的随机数序列。
Python随机列表– choice（），shuffle（），sample（） (Python Random List – choice(), shuffle(), sample())
There are some functions to use randomness in a sequence. For example, using choice() function yo
u can get a random element from a sequence.
有⼀些函数可以在序列中使⽤随机性。 例如，使⽤choice()函数可以从序列中获取随机元素。
Again, using shuffle() function you can shuffle the elements in a sequence.
同样，使⽤shuffle()函数可以将序列中的元素随机播放。
Also, using sample() function you can get x number of elements from a sequence randomly. So, let’s see the following code for random list example.
另外，使⽤sample()函数可以从序列中随机获取x个元素。 因此，让我们看下⾯的随机列表⽰例代码。
import random as rand
# initialize sequences
string = "inconvenience"
l = [1, 2, 3, 4, 10, 15]
# get a single element randomly
print('Single character randomly chosen :', rand.choice(string))
print('one randomly chosen number :', rand.choice(l))
# get multiple element
print('Randomly chosen 4 character from string :', rand.sample(string, 4))
print('Randomly chosen 4 length list :', rand.sample(l, 4))
# shuffle the list
rand.shuffle(l)
print('list is shuffled :', l)  # print the list
You may get output like the following.
您可能会得到类似以下的输出。
Single character randomly chosen : i
one randomly chosen number : 10
Randomly chosen 4 character from string : ['e', 'c', 'n', 'n']
Randomly chosen 4 length list : [2, 10, 3, 15]
list is shuffled : [2, 4, 15, 3, 10, 1]
So, that’s all for python random number. To know more, see their .
所以，这就是python随机数的全部。 要了解更多信息，请参阅其 。
python随机数

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