Python Random moduleThe Python Random module is a built-in module for generating random integers in Python. These are sort of fake random numbers which do not possess true randomness. We can therefore use this module to generate random numbers, display a random item for a list or string, and so on. Generate Random FloatsThe random.random() function gives a float number that ranges from 0.0 to 1.0. There are no parameters required for this function. random.random():- Returns The second random floating point value within [0.0 and 1) is returned. random.uniform(a, b):- Generates a random floating point R in which a <= R <= b if a <= b and b <= R <= a if b < a. random.expovariate(lambda):- Returns the random value according to exponential distribution. random.gauss(mu, sigma):- Returns the random value according to gaussian distribution. There are other distributions also, such as Gamma Distribution, Normal Distribution, etc. Code Output: 0.3232640977876686 Generate Random IntegersThe random.randint() function generates a random integer from the range of numbers supplied. Code Output: 215 Generate Random Numbers within a Defined RangeThe random.randrange() function selects an item randomly from the given range defined by the start, the stop, and the step parameters. By default, the start is set to 0. Likewise, the step is set to 1 by default. Code Output: 4 9 20 Select Random ElementsThe random.choice() function selects an item from a non-empty series at random. An IndexError is thrown when the parameter is an empty series. Code Output: M 765 54 Shuffle Elements RandomlyA general sequence, like integers or floating-point series, can be a group of things like a List / Set. The random module contains methods that we can use to add randomization to the series. The random.shuffle() function shuffles the entries in a list at random. Code Output: [23, 43, 86, 65, 34, 23] [65, 23, 86, 23, 34, 43] Random SeedWe normally use the time of the system to ensure that the software delivers a different output each time we execute it because pseudorandom synthesis is dependent on the preceding number. As a result, we employ seeds. We can specify a seed to have an initial number using Python's random.seed() function. This seed number determines a random number generator's outcome; therefore, if it stays the same, the outcome will continue to be the same. Code Output: Generating 5 random numbers: [29, 47, 44, 185, 87, 158] [29, 47, 44, 185, 87, 158] Various Functions of Random ModuleFollowing is the list of functions available in the random module.
We learned about various methods that Python's random module provides us with for dealing with Integers, floating-point numbers, and other sequences like Lists, tuples, etc. We also looked at how the seed affects the pseudo - random number pattern.
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