The random module in Python provides various functions to generate random numbers and perform random operations. These functions are useful for tasks such as simulations, games, and testing. Below is a list of some commonly used functions in the random module, along with their descriptions and links to detailed guides for each function.
Python random Module Functions Table
| Function | Description |
|---|---|
| seed() | Initializes the random number generator. |
| getstate() | Returns an object capturing the current internal state of the generator. |
| setstate() | Restores the internal state of the generator from an object returned by getstate(). |
| randint() | Returns a random integer between the specified values, inclusive. |
| randrange() | Returns a randomly selected element from the specified range. |
| choice() | Returns a randomly selected element from a non-empty sequence. |
| choices() | Returns a list of randomly selected elements from a population, with optional weights. |
| shuffle() | Shuffles the sequence in place. |
| uniform() | Returns a random floating-point number between the specified values. |
| triangular() | Returns a random floating-point number between the specified values, with a specified mode between them. |
| betavariate() | Returns a random float based on the Beta distribution. |
| gammavariate() | Returns a random float based on the Gamma distribution. |
| lognormvariate() | Returns a random float based on a log-normal distribution. |
| normalvariate() | Returns a random float based on the normal (Gaussian) distribution. |
| vonmisesvariate() | Returns a random float based on the von Mises distribution. |
| paretovariate() | Returns a random float based on the Pareto distribution. |
| weibullvariate() | Returns a random float based on the Weibull distribution. |
For more detailed information on each function, refer to the official Python documentation.