Python Type Hints: Write Better Code with Type Annotations

Type hints make your Python code more readable, maintainable, and catch bugs before runtime. Here's a practical guide to using them effectively.

Complete Code Example

from typing import List, Dict, Optional, Union, Tuple, Any
from typing import Callable, Generator, TypeVar
from dataclasses import dataclass

# Basic type hints
def greet(name: str, times: int = 1) -> str:
    return f"Hello, {name}! " * times

# Collections
def process_items(items: List[int]) -> Dict[str, int]:
    return {"sum": sum(items), "count": len(items)}

# Optional (can be None)
def find_user(user_id: int) -> Optional[str]:
    users = {1: "Alice", 2: "Bob"}
    return users.get(user_id)  # Returns str or None

# Union (multiple types)
def parse_value(v: Union[str, int, float]) -> float:
    return float(v)

# Generic TypeVar
T = TypeVar("T")
def first_item(items: List[T]) -> Optional[T]:
    return items[0] if items else None

# Callable
def apply(func: Callable[[int], int], value: int) -> int:
    return func(value)

result = apply(lambda x: x * 2, 5)  # 10

# Dataclass with types
@dataclass
class User:
    name: str
    age: int
    email: Optional[str] = None
    tags: List[str] = None

    def __post_init__(self):
        if self.tags is None:
            self.tags = []

user = User("Alice", 30, "[e-mail]")
print(user)  # User(name='Alice', age=30, ...)

💡 Pro Tips

• Run mypy to catch type errors before runtime: pip install mypy
• Type hints don't affect runtime performance
• Start adding type hints to function signatures first

Why This Matters

Understanding these Python features will help you write more:

• ✅ Readable and maintainable code
• ✅ Memory-efficient applications
• ✅ Pythonic, idiomatic solutions

Summary

Mastering Python's built-in features is key to becoming a better developer. Practice these examples in your own projects, and you'll quickly see the benefits.

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