| random.betavariate() | Beta distribution |
| random.choice() | Return a random element from the non-empty sequence seq |
| random.expovariate() | Exponential distribution |
| random.gammavariate() | Gamma distribution |
| random.gauss() | Gaussian distribution |
| random.getrandbits() | Returns a Python integer with k random bits |
| random.getstate() | Return an object capturing the current internal state of the generator |
| random.lognormvariate() | Log normal distribution |
| random.normalvariate() | Normal distribution |
| random.paretovariate() | Pareto distribution |
| random.randint() | Return a random integer N such that a <= N <= b |
| random.random() | Return the next random floating point number in the range [0 |
| random.randrange() | Return a randomly selected element from range(start, stop, step) |
| random.sample() | Return a k length list of unique elements chosen from the population sequence or set |
| random.seed() | Initialize the random number generator |
| random.setstate() | state should have been obtained from a previous call to getstate(), and setstate() restores the internal state of the generator to what it was at the time getstate() was called |
| random.shuffle() | Shuffle the sequence x in place |
| random.triangular() | Return a random floating point number N such that low <= N <= high and with the specified mode between those bounds |
| random.uniform() | Return a random floating point number N such that a <= N <= b for a <= b and b <= N <= a for b < a |
| random.vonmisesvariate() | mu is the mean angle, expressed in radians between 0 and 2*pi, and kappa is the concentration parameter, which must be greater than or equal to zero |
| random.weibullvariate() | Weibull distribution |