Advanced Lists

Nested lists, list manipulation, slicing, copying, and performance tips.

Overview

Master advanced list operations.

Nested Lists

# 2D matrix
matrix = [
    [1, 2, 3],
    [4, 5, 6],
    [7, 8, 9]
]

# Access element
print(matrix[1][2])  # 6

# Iterate through matrix
for row in matrix:
    for item in row:
        print(item, end=" ")
    print()

# Matrix transpose
transposed = list(zip(*matrix))
print(transposed)  # [(1, 4, 7), (2, 5, 8), (3, 6, 9)]

# 3D list
cube = [[[0 for _ in range(3)] for _ in range(3)] for _ in range(3)]

List Slicing

lst = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]

# Basic slicing
print(lst[2:5])    # [2, 3, 4]
print(lst[:4])     # [0, 1, 2, 3]
print(lst[6:])     # [6, 7, 8, 9]
print(lst[::2])    # [0, 2, 4, 6, 8] (every 2nd)
print(lst[::-1])   # [9, 8, 7, 6, 5, 4, 3, 2, 1, 0] (reverse)

# Advanced slicing
print(lst[1:8:2])  # [1, 3, 5, 7]
print(lst[8:1:-2]) # [8, 6, 4, 2]

# Slice assignment
lst[2:4] = [20, 30]
print(lst)  # [0, 1, 20, 30, 4, 5, 6, 7, 8, 9]

# Insert with slice
lst[2:2] = [10, 11]
print(lst)  # [0, 1, 10, 11, 20, 30, 4, 5, 6, 7, 8, 9]

List Copying

import copy

original = [1, 2, [3, 4]]

# Shallow copy (different methods)
copy1 = original.copy()
copy2 = original[:]
copy3 = list(original)

# Deep copy
copy4 = copy.deepcopy(original)

# Modify nested list
original[2][0] = 99

print(original)  # [1, 2, [99, 4]]
print(copy1)     # [1, 2, [99, 4]] (shallow - affected!)
print(copy4)     # [1, 2, [3, 4]] (deep - independent)

List Performance

import time

# Bad: O(n) for each append
lst = []
for i in range(100000):
    lst.append(i)  # O(1) amortized

# Good: Pre-allocate
lst = [None] * 100000
for i in range(100000):
    lst[i] = i  # O(1)

# Membership test
large_list = list(range(1000000))
start = time.time()
999999 in large_list  # O(n)
print(f"List: {time.time() - start:.4f}s")

large_set = set(range(1000000))
start = time.time()
999999 in large_set  # O(1)
print(f"Set: {time.time() - start:.6f}s")

Practice

Implement a matrix multiplication function.