How to use python list efficiently
By manhnv, at: Feb. 24, 2025, 10:37 a.m.
Estimated Reading Time: __READING_TIME__ minutes


Using Python lists efficiently involves understanding their strengths and limitations, as well as employing best practices.
Here are some tips to help you use Python lists more effectively:
1. Understand List Operations
- Appending Items: Use
append()
to add items to the end of the list. This operation is efficient (O(1) amortized time complexity).
- Inserting Items: Inserting items at the beginning or middle of the list can be inefficient (O(n) time complexity) because it requires shifting elements.
- Accessing Items: Accessing items by index is efficient (O(1) time complexity).
- Slicing: Slicing creates a new list, which can be inefficient for large lists.
2. Use List Comprehensions
List comprehensions are a concise and efficient way to create lists. They are generally faster than using loops.
squares = [x**2 for x in range(10)]
3. Avoid Unnecessary Copies
Creating copies of lists can be memory-intensive. Use slicing or the copy
module judiciously.
copy_of_list = original_list[:]
# or
import copy
copy_of_list = copy.deepcopy(original_list)
4. Use deque
for Frequent Insertions/Deletions
If you need to frequently insert or delete items from both ends of a list, consider using collections.deque
, which is optimized for these operations.
from collections import deque
d = deque() d.append(1) d.appendleft(2)
5. Preallocate List Size
If you know the size of the list in advance, preallocating it can be more efficient.
my_list = ["a"] * 1000
6. Use extend()
for Adding Multiple Items
Instead of using multiple append()
calls, use extend()
to add multiple items at once.
my_list.extend([1, 2, 3])
7. Avoid Using Lists for Large Numeric Data
For large numeric data, consider using NumPy arrays, which are more memory-efficient and provide faster operations.
import numpy as np array = np.array([1, 2, 3, 4, 5])
8. Use join()
for String Concatenation
When concatenating strings, use join()
instead of the +
operator for better performance.
result = ''.join(list_of_strings)
9. Use Built-in Functions
Leverage built-in functions like sum()
, min()
, max()
, and sorted()
for common operations.
total = sum(my_list) sorted_list = sorted(my_list)
10. Profile Your Code
Use profiling tools like cProfile
to identify bottlenecks in your code and optimize list operations accordingly.
import cProfile
cProfile.run('your_function()')
Example of Efficient List Usage
# Efficiently creating a list of squares
squares = [x**2 for x in range(1000)]
# Efficiently adding multiple items
squares.extend([1000**2, 1001**2, 1002**2])
# Efficiently accessing items
for i in range(10):
print(squares[i])
# Efficiently concatenating strings
strings = ['a', 'b', 'c']
result = ''.join(strings)
By following these best practices, you can use Python lists more efficiently and improve the performance of your programs.
Challenging Exercises
-
Find the Longest Palindromic Sublist: Write a program to find the longest palindromic sublist within a given list.
- Example: For the list
[2, 1, 3, 1, 2, 5, 1, 3, 1]
, the longest palindromic sublist is[1, 3, 1, 2, 1, 3, 1]
.
- Example: For the list
-
Subset Sum Problem: Write a program to determine if there is a subset of a given list that sums to a specified value.
- Example: For the list
[3, 34, 4, 12, 5, 2]
and sum9
, the subsets[4, 5]
and[4, 2, 3]
both sum to 9.
- Example: For the list
-
Find the K-th Smallest Element: Write a program to find the k-th smallest element in an unsorted list.
- Example: For the list
[7, 10, 4, 3, 20, 15]
andk = 3
, the 3rd smallest element is7
.
- Example: For the list
-
Sliding Window Maximum: Write a program to find the maximum value in each sliding window of size
k
in a given list.- Example: For the list
[1, 3, -1, -3, 5, 3, 6, 7]
andk = 3
, the maximum values are[3, 3, 5, 5, 6, 7]
.
- Example: For the list
-
Find All Anagrams in a List: Write a program to find all anagrams in a list of strings.
- Example: For the list
["listen", "silent", "enlist", "google", "gooegl"]
, the anagrams are["listen", "silent", "enlist"]
and["google", "gooegl"]
.
- Example: For the list
-
Merge K Sorted Lists: Write a program to merge
k
sorted lists into one sorted list.- Example: For the lists
[[1, 4, 5], [1, 3, 4], [2, 6]]
, the merged list is[1, 1, 2, 3, 4, 4, 5, 6]
.
- Example: For the lists
-
Find the Median of Two Sorted Lists: Write a program to find the median of two sorted lists.
- Example: For the lists
[1, 3]
and[2]
, the median is2.0
. For the lists[1, 2]
and[3, 4]
, the median is2.5
.
- Example: For the lists
-
Find the Shortest Unsorted Subarray: Write a program to find the shortest subarray that needs to be sorted to make the entire list sorted.
- Example: For the list
[2, 6, 4, 8, 10, 9, 15]
, the shortest unsorted subarray is[6, 4, 8, 10, 9]
.
- Example: For the list
-
Find the Majority Element II: Write a program to find all elements that appear more than
n/3
times in a list.- Example: For the list
[3, 2, 3]
, the majority elements are[3]
. For the list[1, 1, 1, 3, 3, 2, 2, 2]
, the majority elements are[1, 2]
.
- Example: For the list
-
Find the Minimum Number of Jumps: Write a program to find the minimum number of jumps required to reach the end of a list, where each element represents the maximum number of steps that can be jumped.
- Example: For the list
[2, 3, 1, 1, 4]
, the minimum number of jumps is2
(jump from index 0 to 1, then from index 1 to 4).
- Example: For the list