Type Hints and Static Typing

May 30, 2026 | 5 min read

Why Type Hints Help

Type annotations give the compiler more information to generate efficient machine code. Typed variables can avoid generic Python object boxing.

Basic Type Hints

def process(data: list[int]) -> int:
    total: int = 0
    for x in data:
        total += x
    return total

Supported Type Constructs

int, float, bool, str
list[T], dict[K, V], tuple[T, ...]
Optional[T], Union[T, U]

Type Stability

The compiler generates specialised code for the first observed type. If a variable later changes type, it may deoptimise:

# Good: x stays int
x: int = 0
for i in range(1000):
    x += i

# Slower: type changes
x = 0
for i in range(1000):
    if i == 500:
        x = 1.5  # deoptimisation point

Limitations

Generic classes with custom type parameters may be treated as object.
Recursive type aliases are not fully resolved.