Python random.sample() Function: Usage and Examples

Sample unique positions without replacement from a population.

What It Does and Why It Matters

random.sample(population, k) returns a new list containing k distinct selected positions. It raises ValueError when k exceeds the population size. Repeated equal values in the source can still appear in the result when they occur in different positions.

Use counts= for repeated items represented by a compact population.

Pseudorandom examples are suitable for simulation and tests. Use secrets instead for tokens, passwords and authentication.

Step-by-Step Example

Start with the complete example below. Read the inputs and predict what the final print statement will show before you run it.

import random
number_generator = random.Random(34)
selected_numbers = number_generator.sample(range(1, 31), k=5)
print(len(selected_numbers))
print(len(set(selected_numbers)) == 5)

How the Code Works

The imports make these standard-library tools available: random.
The name number_generator receives the value of random.Random(34). Changing this input lets you explore a different case.
The print calls display the results. Compare these results with the method’s documented return type and the input used.
The dedicated Random instance isolates the generator state from unrelated random calls. A fixed seed is useful here for repeatable demonstrations but must not be reused to generate secrets.

Expected output:

5
True

Each displayed line comes from the corresponding calculation or check. The output helps verify the return values before you adapt the example to your own input.

What to Notice

Pay attention to the accepted input types, the returned value and the boundary behavior. Predict what changes if you replace the example input with an empty, zero, negative or missing value, where that value is meaningful for this operation.

If the task uses a library function, inspect its documented exceptions and return type before reusing it inside a larger function.

Where You Would Use This

Use this in calculations, data summaries, simulations or validation when the numerical assumptions match the task. Check input domains, units and precision before interpreting a result. A single example output does not prove a statistical conclusion.

Practice Exercise

Select three distinct contest winners from a list of ten unique participants.

Before running your edited example, write down the result you expect. Then test at least one valid boundary or deliberately invalid value, using appropriate exception handling where necessary.

Reference: official Python documentation for the complete API contract and version notes.

Common Beginner Mistakes

Requesting more elements than are available or assuming equal-valued source entries cannot repeat.
Overlooking the documented condition: it raises ValueError when k exceeds the population size.

Key Takeaways

Sample unique positions without replacement from a population.
random.sample(population, k) returns a new list containing k distinct selected positions.
Select three distinct contest winners from a list of ten unique participants.
Pseudorandom examples are suitable for simulation and tests. Use secrets instead for tokens, passwords and authentication.