Python: Repeat the same random numbers using seed
That means you should not use them for certain types of applications, e.g. encryption and that they are repeatable.
If you start from the same place in the series twice, then you get the exact same "random" numbers.
The way to set this beginning in the random module of python is to call the random.seed() function and give it an arbitrary number. e.g. 42 would be perfect.
Let's see this!
In this simple script we just load the random module and called the random.random() method.
import random print(random.random())
Every time we run this script we get a different number.
0.511318181959 0.771417342337 0.565304847619
This happens because when python loads the random module it calls the seed function with the current time. As that time always changes the casual viewer would see random numbers.
import random random.seed(42) print(random.random())
If we run this script several time we'll always get back the same "random" number.
0.639426798458 0.639426798458 0.639426798458
Why are repeatable "random" numbers a good thing?
You might ask. Well, they are good if you would like to make sure you can run the same sequence of events while they are (almost) randomly created. For example when you write some test code. With tests you usually want the process to be repeatable.
So if you have a function that uses random numbers to calculate something and for every call it will return a different result then it is hard to check if it works properly. If you fix the random numbers then you will be able to observe the same result twice.
Anyway, what happens if your code loads other modules that also use random numbers?
Here we have a main file:
import random import other #random.seed(42) def f(): print(random.random()) f() other.g()
That loads the other.py:
import random def g(): print(random.random())
If we run python main.py several time we'll get different number-pairs on every run:
0.864327113674 0.675706432586 0.221254773857 0.0473047970533 0.415061037659 0.718553482388
If we enable the call to random.seed(42) we get the same two numbers on every run:
0.639426798458 0.0250107552227 0.639426798458 0.0250107552227 0.639426798458 0.0250107552227
Published on 2019-01-14