Runtime Type Checking

Introduction

Runtime type checking libraries like typeguard and beartype enforce type annotations at runtime, catching type errors before they cause issues.

Typeguard Basic Usage

from typeguard import typechecked

@typechecked
def greet(name: str, age: int) -> str:
    return f"Hello {name}, you are {age}"

greet("Alice", 30)    # Works
greet("Bob", "thirty")  # TypeError!

Typeguard for Classes

from typeguard import typechecked

@typechecked
class Person:
    def __init__(self, name: str, age: int):
        self.name = name
        self.age = age
    
    def set_age(self, age: int):
        self.age = age

person = Person("Alice", 30)
person.set_age("thirty")  # TypeError!

Beartype Usage

from beartype import beartype

@beartype
def calculate(x: int, y: int) -> int:
    return x + y

@beartype
class Point:
    def __init__(self, x: float, y: float):
        self.x = x
        self.y = y

Configuration

from typeguard import install_import_hook

install_import_hook("mymodule")

# Or configure globally
from typeguard.config import CollectionCheckStrategy

CollectionCheckStrategy.ALL_ITEMS

Performance Considerations

# Use sparingly in production due to overhead

# For debugging/development
from typeguard import typechecked

# For production, consider:
# 1. Type checking only in tests
# 2. Using __debug__ guards
# 3. Using type annotations for documentation only

Custom Type Checkers

from typeguard import TypeHintTypeChecker

@TypeHintTypeChecker
class CustomValidator:
    pass

# Or register custom type checkers
from typeguard import add_type_checker

@add_type_checker
class Email(str):
    pass

Practice Problems

1. Add type checking to a function
2. Use beartype with custom types
3. Configure type checking for a module
4. Implement custom type validator
5. Compare performance with static typing