random.seed(0) effect ： Make random data predictable , As long as seed It's worth the same , The random numbers generated later are the same .
random.seed() Commonly known as random number seed . Do not seed random numbers , The data you get from every random sampling is different . Set random number seed , It can ensure that the results of each sampling are the same . and random.seed() The numbers in parentheses , Equivalent to a key , Corresponding to a door , The same value can make the sampling results consistent .
From the picture above ：
If we set the same seed value , You can get the same random number ;
If not set seed, Then the value obtained each time is different ;
therefore , When faced with a random program , As long as our operating environment is consistent （ Ensure that the pseudo-random number generator is the same ）, And if the random seeds we set are the same , Then we can reproduce the results .
Reference resources ：
python in random.seed（） What is it for ？
np.random.seed(0) The role of ： Make random data predictable .
python3 in seed Function usage
