Difference Between List and Tuple in Python

Last Updated : 13 Mar, 2025

In Python, lists and tuples both store collections of data, but differ in mutability, performance and memory usage. Lists are mutable, allowing modifications, while tuples are immutable. Choosing between them depends on whether you need to modify the data or prioritize performance and memory efficiency.

Key Differences between List and Tuple

S.No	List	Tuple
1	Lists are mutable(can be modified).	Tuples are immutable(cannot be modified).
2	Iteration over lists is time-consuming.	Iterations over tuple is faster
3	Lists are better for performing operations, such as insertion and deletion.	Tuples are more suitable for accessing elements efficiently.
4	Lists consume more memory.	Tuples consumes less memory
5	Lists have several built-in methods.	Tuples have fewer built-in methods.
6	Lists are more prone to unexpected changes and errors.	Tuples, being immutable are less error prone.

Mutability Test: List vs Tuples

List are Mutable

Lists can be modified, meaning their elements can be changed, added or removed after creation.

Python

a = [1, 2, 4, 4, 3, 3, 3, 6, 5] # Modifying an element in the list `a` a[3] = 77 print(a)

Output

[1, 2, 4, 77, 3, 3, 3, 6, 5]

Explanation: Here, we modified the fourth element (index 3) from 4 to 77. Lists allow direct modification of their elements.

Tuples are Immutable

Tuples cannot be modified after creation. Any attempt to change an element will result in an error.

Python

b = (0, 1, 2, 3) # Attempting to modify a tuple b[0] = 4 print(b)

Hangup (SIGHUP)
Traceback (most recent call last):
  File "/home/guest/sandbox/Solution.py", line 4, in <module>
    b[0] = 4
    ~^^^
TypeError: 'tuple' object does not support item assignment

Explanation: Tuples do not support item assignment, making them immutable. This prevents unintended modifications.

Performance Comparison: Lists vs Tuples

Memory Efficiency Test

Since tuples are stored in a single memory block and do not require additional space for dynamic changes, they are more memory-efficient than lists.

Python

import sys  # Creating an empty list and tuple a = [] b = ()  # Assigning values a = ["Geeks", "For", "Geeks"] b = ("Geeks", "For", "Geeks")  # Checking memory usage print(sys.getsizeof(a)) print(sys.getsizeof(b))

Output

88 64

Explanation: This code shows that the list takes more memory than the tuple. Tuples, being immutable, require less overhead, making them a better choice for storing fixed data.

Iteration Speed Test

Tuples have a performance advantage in iterations because they are immutable and stored in a contiguous memory block, reducing overhead.

Python

import time  # Creating a large list and tuple a = list(range(100000001)) b = tuple(range(100000001))  # Timing tuple iteration start = time.time_ns() for i in range(len(b)):     x = b[i] end = time.time_ns() print(end - start)  # Timing list iteration start = time.time_ns() for i in range(len(a)):     x = a[i] end = time.time_ns() print(end - start)

Output

16649292352 
12447795073

Explanation: Tuples iterate faster than lists as they are stored in a single memory block, while lists need extra operations for dynamic resizing.

Operations - Lists vs Tuples

In Python, both lists and tuples support a range of operations, including indexing, slicing, concatenation, and more. However, there are some differences between the operations that are available for lists and tuples due to their mutability and immutability, respectively.

Indexing

Both lists and tuples allow you to access individual elements using their index, starting from 0.

Python

a = [1, 2, 3] # list b = (4, 5, 6) # tuple print(a[0]) print(b[1])

Output

1 5

Slicing

Both lists and tuples allow you to extract a subset of elements using slicing.

Python

a = [1, 2, 3, 4, 5] b = (6, 7, 8, 9, 10) print(a[1:3]) print(b[:3])

Output

[2, 3] (6, 7, 8)

Concatenation

Both lists and tuples can be concatenated using the "+" operator.

Python

# List Concatenation a = [1, 2, 3] b = [4, 5, 6] print(a + b)  # Tuple Concatenation a = (7, 8, 9) b = (10, 11, 12) print(a + b)

Output

[1, 2, 3, 4, 5, 6] (7, 8, 9, 10, 11, 12)

List-Specific operations

Only lists support operations that modify their contents:

Append: Adds an element at the end.
Extend: Merges another list.
Remove: Removes the first occurrence of a value.

Python

a = [1, 2, 3] a.append(4) a.extend([5, 6]) a.remove(2) print(a)

Output

[1, 3, 4, 5, 6]

Explanation: append(4) method adds the number 4 to the end of the list, making it [1, 2, 3, 4]. Next, the extend([5, 6]) method adds multiple elements [5, 6] to the list, updating it to [1, 2, 3, 4, 5, 6]. The remove(2) method then deletes the first occurrence of 2 from the list, resulting in [1, 3, 4, 5, 6]

When to Use Tuples Over Lists?

In Python, tuples and lists are both used to store collections of data, but they have some important differences. Here are some situations where you might want to use tuples instead of lists:

Immutability: Tuples are immutable, ensuring data integrity by preventing modifications. Ideal for constants, configurations, and fixed data.
Performance: Tuples are faster and more memory-efficient than lists as they are stored in a single block and don’t require extra space for modifications.
Memory Efficiency: Tuples use contiguous memory, while lists need extra space for dynamic resizing, making tuples a better choice for large, unchanging datasets.

Difference Between List and Tuple in Python

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Difference Between List and Tuple in Python

Key Differences between List and Tuple

Mutability Test: List vs Tuples

List are Mutable

Tuples are Immutable

Performance Comparison: Lists vs Tuples

Memory Efficiency Test

Iteration Speed Test

Operations - Lists vs Tuples

Indexing

Slicing

Concatenation

List-Specific operations

When to Use Tuples Over Lists?

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