Of course! Shuffling a list in Python is a common task, and the primary way to do it is by using the random module.
Here's a complete guide covering the best methods, important distinctions, and examples.
The Main Method: random.shuffle()
This is the most direct and common way to shuffle a list in-place. This means it modifies the original list directly and does not return a new one.
How to Use It
- Import the
randommodule. - Call
random.shuffle(your_list).
Example
import random
# 1. Create a list
my_list = ['apple', 'banana', 'cherry', 'date', 'elderberry']
print(f"Original list: {my_list}")
# 2. Shuffle the list in-place
random.shuffle(my_list)
# 3. The original list is now modified
print(f"Shuffled list: {my_list}
Output (will be different each time):
Original list: ['apple', 'banana', 'cherry', 'date', 'elderberry']
Shuffled list: ['date', 'elderberry', 'apple', 'banana', 'cherry']Important: random.shuffle() vs. random.sample()
A common point of confusion is between shuffle() and sample(). It's crucial to understand the difference.
| Feature | random.shuffle() |
random.sample() |
|---|---|---|
| Purpose | Shuffles a list in-place. | Creates a new list with a specified number of unique items. |
| Return Value | None (it modifies the list directly). |
A new list containing the selected items. |
| Original List | Is modified. | Is not changed. |
| Common Use | When you want to randomize the order of an existing list. | When you want to pick a few random items from a list without changing it. |
Example of random.sample()
import random
my_list = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
# Get 3 unique random elements from the list
# The original list remains unchanged
random_elements = random.sample(my_list, 3)
print(f"Original list: {my_list}")
print(f"Randomly sampled elements: {random_elements}")
Output:
Original list: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
Randomly sampled elements: [8, 2, 5]How to Shuffle and Get a New List (Without Modifying the Original)
Sometimes you don't want to change your original list. The best way to do this is by creating a copy of the list and then shuffling the copy.
Method 1: Slicing (Most Pythonic)
This is the most common and readable way to create a copy.
import random
original_list = [1, 2, 3, 4, 5]
print(f"Original list: {original_list}")
# Create a copy using slicing [:] and shuffle the copy
shuffled_copy = original_list[:] # This is a shallow copy
random.shuffle(shuffled_copy)
print(f"Shuffled copy: {shuffled_copy}")
print(f"Original list (unchanged): {original_list}")
Output:
Original list: [1, 2, 3, 4, 5]
Shuffled copy: [3, 1, 5, 2, 4]
Original list (unchanged): [1, 2, 3, 4, 5]Method 2: The list() Constructor
You can also pass the original list to the list() constructor to make a copy.
import random
original_list = [1, 2, 3, 4, 5]
shuffled_copy = list(original_list) # Creates a new list
random.shuffle(shuffled_copy)
print(f"Shuffled copy: {shuffled_copy}")
print(f"Original list (unchanged): {original_list}")
Shuffling a List of Numbers (e.g., for a Deck of Cards)
If you need to generate a shuffled list of numbers, you can combine range() and sample().
import random
# Create a shuffled list of numbers from 0 to 51 (like a deck of cards)
shuffled_deck = random.sample(range(52), 52)
print(f"First 10 cards of the shuffled deck: {shuffled_deck[:10]}")
Output:
First 10 cards of the shuffled deck: [41, 18, 7, 29, 50, 12, 33, 4, 21, 0]Summary: Which Method to Use?
| Your Goal | Recommended Method | Why? |
|---|---|---|
| Shuffle an existing list permanently. | random.shuffle(my_list) |
It's the direct, in-place method designed for this exact purpose. |
| Get a shuffled version but keep the original. | shuffled_copy = my_list[:] then random.shuffle(shuffled_copy) |
This is clean, readable, and creates a new list to work with. |
| Pick a few random items from a list. | random.sample(my_list, k=3) |
It's the right tool for the job, designed for sampling without replacement. |
| Generate a shuffled list of numbers. | random.sample(range(n), n) |
Efficient and clear way to create a sequence of unique, shuffled numbers. |
