The `random`

library in Python provides functions and classes for generating random numbers and data.

`random()`

: Generating a random floating-point number between 0 and 1.

`random_num = random.random()`

`randint()`

: Generating a random integer within a specified range.

`import random `

random_int = random.randint(start, end)

`uniform()`

: Generating a random floating-point number within a specified range.

`import random `

random_float = random.uniform(start, end)

`choice():`

Selecting a random item from a sequence (list, tuple, string, etc.).

`import random `

random_item = random.choice(sequence)

`shuffle():`

Shuffling the elements of a list randomly. It change the list. It is an inplace operation. You cannot assign it a new variable.

`import random `

random.shuffle(my_list)

`sample(population,k):`

Chooses k unique random elements from a population sequence or set.

- Returns a new list containing elements from the population while leaving the original population unchanged.
- To choose a sample from a range of integers, use range() for the population argument. This is especially fast and space efficient for sampling from a large population: sample(range(10000000), 60)

`import random `

random_sample = random.sample(population, k)

`randrange():`

Generating a random integer from a range with a specified step.

`import random `

random_num = random.randrange(start, stop, step)

`seed()`

Setting a seed value to ensure reproducibility of random results.

`import random `

random.seed(seed_value)

`random.seed()`

(Module-Level Seed): Setting the seed value for the entire `random`

module.

`import random `

random.seed(seed_value)