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Add Type Hints to Function Parameters and Return in Python
Add type hints to function parameters and return values in Python for clearer, more maintainable code using the typing module.
from typing import List, Optional, Dict
def average(numbers: List[float]) -> float:
return sum(numbers) / len(numbers)
def full_name(first: str, last: Optional[str] = "") -> str:
return f"{first} {last}".strip()
def build_user(name: str, age: int, email: Optional[str] = None) -> Dict[str, object]:
us…How to Validate Function Arguments in Python
Shows how to manually check argument types and values in a Python function, raising clear TypeError and ValueError messages.
def calculate_area(length: float, width: float) -> float:
"""Calculate the area of a rectangle with manual type validation."""
if not isinstance(length, (int, float)) or isinstance(length, bool):
raise TypeError(f"length must be a number, got {type(length).__name__}")
if not isinstance(width, (int,…How to Return Success or Error as a Tuple in Python (Result Type Pattern)
Use a (bool, value) tuple as a lightweight Result type to return either a successful result or a descriptive error message from a Python function.
def divide(dividend: float, divisor: float) -> tuple[bool, float | str]:
"""Return (True, result) on success, (False, error_message) on failure."""
if divisor == 0:
return False, "Error: Division by zero"
return True, dividend / divisor
if __name__ == "__main__":
# Success case
success, r…How to Use Optional Return in Python Instead of Raising Exceptions
A Python function returns None for missing dictionary keys instead of raising KeyError, enabling graceful lookup handling with type hints.
from typing import Optional
def find_user(users: dict, user_id: int) -> Optional[dict]:
"""
Look up a user by ID. Returns the user dict if found,
otherwise returns None instead of raising KeyError.
"""
return users.get(user_id)
def main() -> None:
users = {
1: {"name": "Alice", "ema…Dataclass with Type Hints Fields in Python
Create a data class with typed fields and default values, then instantiate and inspect it.
from dataclasses import dataclass
@dataclass
class Person:
name: str
age: int
email: str = "unknown@example.com"
is_active: bool = True
if __name__ == "__main__":
person = Person(name="Alice", age=30)
print(person)
print(f"Name: {person.name}, Age: {person.age}, Email: {person.email}, A…Design Data Helpers with Python TypedDict and Literal
Use TypedDict, Literal, and Union to define typed data shapes and parse values in Python.
from typing import TypedDict, Literal, Optional, Union, List
class User(TypedDict):
name: str
age: int
role: Literal["admin", "user", "guest"]
def describeUser(data: User) -> str:
return f"{data['name']} ({data['age']}) — {data['role']}"
def parse_value(item: Union[int, str, None]) -> str:
if it…Format Data with Type Hints in Python
Build a validated person dict with modern type hints and optional list handling.
from typing import Any, Dict, List, Optional, Union
JsonValue = Union[str, int, float, bool, None, List["JsonValue"], Dict[str, "JsonValue"]]
def format_person(name: str, age: int, hobbies: Optional[List[str]] = None) -> Dict[str, Any]:
"""Build a person dict with validated typing."""
if not name or age < 0:…How to Convert Strings to Types in Python Using TypeVar
A beginner-friendly helper that converts a string to int, float, bool, or str with type hints and graceful failure handling.
from typing import TypeVar, Optional
T = TypeVar("T")
def convert_data(value: str, target_type: type[T]) -> Optional[T]:
"""Convert string value to target type; return None on failure."""
try:
if target_type is int:
return int(value)
elif target_type is float:
return f…How to Filter Data in Python with Type Hints
A reusable filter_data helper uses optional predicates and numeric bounds with modern Python type hints.
from typing import Iterable, TypeVar, Callable, Any
T = TypeVar("T")
def filter_data(
items: Iterable[T],
predicate: Callable[[T], bool] | None = None,
*,
min_value: float | None = None,
max_value: float | None = None,
) -> list[T]:
"""Filter items by predicate and/or numeric bounds."""
r…How to Group Data by Key in Python with Type Hints
Group a list of dictionaries by a specified key using a typed helper function and print a summary of each group.
from typing import Any, Dict, List, TypeVar, Union
T = TypeVar("T")
def group_by(data: List[Dict[str, Any]], key: str) -> Dict[Any, List[Dict[str, Any]]]:
"""Group a list of dictionaries by a given key."""
grouped: Dict[Any, List[Dict[str, Any]]] = {}
for item in data:
value = item.get(key)
…How to Parse Data with Type Hints in Python
A beginner-friendly helper that parses simple dictionary- or list-like strings into typed Python structures using modern typing annotations.
from typing import Any, Dict, List, Union
def parse_data(raw: str) -> Union[Dict[str, Any], List[Any], str]:
"""Parse a simple string into structured data using type hints."""
cleaned = raw.strip()
if not cleaned:
return {}
if cleaned.startswith("{") and cleaned.endswith("}"):
…How to Use Basic Type Hints (int, str) for Return Values in Python
Declare a simple function with int and str type hints and a typed return value in Python.
def greet(name: str, age: int) -> str:
return f"{name} is {age} years old."
if __name__ == "__main__":
print(greet("Alice", 30))How to Use Literal Type Hints in Python
Use typing.Literal to restrict a function parameter to specific allowed string values and get static type checking.
from typing import Literal
def get_status_message(status: Literal["active", "inactive", "pending"]) -> str:
"""Return a message based on the status value."""
if status == "active":
return "Account is active"
elif status == "inactive":
return "Account is inactive"
else:
return "…How to Use Python Type Hints for Beginners
Build a data helper module with basic type hints — Union, Optional, List, Dict, Any, and TypeVar — to make your code clearer and safer.
from typing import Any, Union, Optional, List, Dict, Tuple, Callable, TypeVar
T = TypeVar("T")
def describe(value: Any) -> str:
"""Return a human-readable description of the value's type."""
if isinstance(value, list):
return f"list of {len(value)} items"
elif isinstance(value, dict):
ret…How to Use TypedDict for Data Validation in Python
Define a TypedDict schema and validate raw dictionary input with type hints for safer, more readable data handling.
from typing import Any, Dict, List, Optional, Union, TypedDict, Literal
class Product(TypedDict):
product_id: int
name: str
price: Union[int, float]
in_stock: bool
tags: Optional[List[str]]
def validate_product(data: Dict[str, Any]) -> Product:
product_id: int = int(data["product_id"])
na…How to Use TypedDict for Structured Dict Typing in Python
Define and use TypedDict to add type hints to dictionaries, improving code clarity and enabling static type checking in your Python projects.
from typing import TypedDict
class User(TypedDict):
name: str
age: int
email: str
def greet(user: User) -> str:
return f"Hello {user['name']}, age {user['age']}, contact {user['email']}"
if __name__ == "__main__":
alice: User = {"name": "Alice", "age": 30, "email": "alice@example.com"}
pr…How to Use Union Type Hints in Python
This code demonstrates how to use Union type hints to specify that a parameter can accept multiple types (int, float, str) and handle them accordingly.
from typing import Union
def process_value(value: Union[int, float, str]) -> str:
if isinstance(value, (int, float)):
return f"Number: {value * 2}"
return f"String: {value.upper()}"
if __name__ == "__main__":
print(process_value(10))
print(process_value(3.14))
print(process_value("hello"))How to Validate Data in Python with Typing Hints
Build a runtime validation helper that checks values against Python type hints like Optional, list, and basic types.
from typing import Any, Optional, Union, TypeVar, get_origin, get_args
T = TypeVar("T")
def validate(value: Any, expected_type: type) -> Optional[str]:
"""Returns an error message if value doesn't match expected_type, else None."""
# Handle Optional[...] types
origin = get_origin(expected_type)
if or…How to Validate Dataclass Fields with Python Type Hints
A beginner-friendly helper that checks if instance attributes match their declared type hints using dataclasses and get_type_hints.
from typing import Any, TypeVar, get_type_hints
from dataclasses import dataclass
T = TypeVar("T")
@dataclass
class User:
name: str
age: int
email: str
def validate_fields(obj: Any) -> dict[str, bool]:
"""Check if object attributes match declared type hints."""
hints = get_type_hints(obj.__class…NamedTuple typed record in Python
Define a lightweight immutable record with type hints using typing.NamedTuple; access fields by name and unpack like a tuple.
from typing import NamedTuple
class Point(NamedTuple):
x: float
y: float
label: str = "origin"
if __name__ == "__main__":
p = Point(3.5, -2.0, "A")
print(p)
print(f"x={p.x}, y={p.y}, label={p.label}")
print("is tuple:", isinstance(p, tuple))
q = Point(1.0, 1.0)
print(q)
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