Python for C++ Developers: Learn Python Using What You Already Know

C++ vs Python, side by side

Each pair below does the same job. Start with the code you know, then see how Python expresses it.

Static vs dynamic typing

int count = 3;
count = "three";   // compile error

std::string name = "Ada";

count = 3
count = "three"    # allowed

name: str = "Ada"

C++ fixes each variable's type at compile time. In Python a name can be rebound to a value of any type, and types are checked only when the line runs. Type hints such as name: str are read by tools like mypy, not enforced at runtime, and integers never overflow.

Memory, pointers and references

int value = 10;
int* ptr = &value;
*ptr = 20;

void bump(int& n) { n += 1; }

a = [1, 2]
b = a
b.append(3)
print(a)  # [1, 2, 3]

Python has no pointers or manual memory management: every name is a reference to an object, and objects are freed when nothing refers to them. b = a copies the reference, not the list. Integers and strings are immutable, so n += 1 inside a function rebinds a local name instead of changing the caller's value.

std::vector vs list

std::vector<int> nums = {1, 2, 3};
nums.push_back(4);
// holds only ints, stored side by side

nums = [1, 2, 3]
nums.append(4)
mixed = [1, "two", 3.0]

std::vector stores values of one type side by side in memory. A Python list stores references to objects, so it can hold mixed types, which is flexible but heavier and slower for large amounts of numeric data. Use the array module or NumPy for compact numeric storage.

Loops and STL algorithms

std::vector<int> evens;
for (int n : nums) {
    if (n % 2 == 0) evens.push_back(n);
}
int total = std::accumulate(nums.begin(), nums.end(), 0);
std::sort(nums.begin(), nums.end());

evens = [n for n in nums if n % 2 == 0]
total = sum(nums)
nums.sort()

Most STL algorithms become comprehensions or built-ins such as sum, min, max, any and all, and you pass the collection itself instead of an iterator pair. nums.sort() sorts in place, while sorted(nums) returns a new list.