that it uses mathematical process to generate random numbers the numbers are called pseudorandom numbers becausecoming from mathematical processthey are not truly randomthoughfor all intents and purposesthey appear random anyone who knows the process can recreate the numbers this is good for scientific and mathematical applicationswhere you want to be able to recreate the same random numbers for testing purposesbut it is not suitable for cryptographywhere you need to generate truly random numbers seeds for mathematical and scientific applicationsyou may want to reproduce the same random numbers each time you run your programin order to test your work with the same data you can do this by specifying the seed examples are shown belowrandom seed( print("seed :"[random randint( , for in range( )]random seed( print("seed :"[random randint( , for in range( )]random seed( print("seed :",[random randint( , for in range( )]seed [ seed [ seed [ the seed can be any integer if we just use random seed()then the seed will be more or less randomly selected based off of the system clock the random function most of the functions in the random module are based off of the random functionwhich uses the mersenne twister to generate random numbers between and mathematical transformations are then used on the result of random to get some of the more interesting random number functions other functions in the random module the random module contains functions that return random numbers from various distributionslike the gaussian or exponential distributions for instanceto generate gaussian (normalrandom variableuse the gauss function here are some examplesrandom gauss( , [round(random gauss( , ), for in range( ) [ the first argument of gauss is the mean and the second is the standard deviation if you're not familiar with normal random variablesthey are the standard bell curve things like heights and sat scores and many other real-life things approximately fit this distribution in the example abovethe random numbers generated are centered around numbers closer to are more likely to be generated than numbers farther away