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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 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…How to Stream Tokens from a Mock LLM in Python
Simulate real-time LLM streaming by yielding tokens one at a time with a delay, making it easy to test streaming UIs.
import time
from typing import Generator
def stream_tokens(text: str, delay: float = 0.05) -> Generator[str, None, None]:
"""Simulate an LLM streaming tokens word by word."""
for word in text.split():
yield word
time.sleep(delay)
if __name__ == "__main__":
sample = "Hello world! This is…How to Parse and Extract Nested Data in Python
Load JSON files with Path and recursively extract values by key from nested Python structures using modern typing and standard library.
import json
from pathlib import Path
from typing import Any, Dict, List, Union
def load_data(filepath: Union[str, Path]) -> Union[Dict[str, Any], List[Any]]:
"""Load JSON data from a file with modern Path handling."""
path = Path(filepath)
if not path.exists():
raise FileNotFoundError(f"File not f…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 Merge TypedDicts in Python
Merge two TypedDict dictionaries with type-aware logic using NotRequired, **kwargs unpacking, and safe key updates.
from typing import TypedDict, NotRequired, merge # hypothetical
class User(TypedDict):
name: str
email: NotRequired[str]
age: NotRequired[int]
def merge_users(base: User, **overrides: User) -> User:
"""Merge two user dicts with typing-aware logic."""
result: User = dict(base)
for key, value …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 Sort Data in Python
Sort sequences with type-safe helpers that handle mixed data with a string fallback.
from typing import Any, TypeVar, Protocol, Sequence, Iterable
T = TypeVar("T")
Comparable = TypeVar("Comparable", bound="Comparable")
class Sortable(Protocol):
def __lt__(self, other: Any) -> bool: ...
S = TypeVar("S", bound=Sortable)
def sort_data(data: Sequence[S], *, reverse: bool = False) -> list[S]:
"…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 and Dataclasses in Python
Create typed data structures with TypedDict and dataclasses, then use them as helper functions for describing objects in a type-safe way.
from typing import TypedDict, NotRequired, Optional
from dataclasses import dataclass
class User(TypedDict):
name: str
age: NotRequired[int]
email: Optional[str]
@dataclass
class Product:
id: int
title: str
price: float = 0.0
def describe_user(user: User) -> str:
age = user.get("age",…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…How to use Optional type hint in Python
Use the Optional type hint to indicate a parameter can be a string or None, with an example function that handles both cases.
from typing import Optional
def greet(name: Optional[str]) -> str:
if name is None:
return "Hello, anonymous!"
else:
return f"Hello, {name}!"
if __name__ == "__main__":
print(greet("Alice"))
print(greet(None))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)
# …How to Mock Eventual Consistency UI Notes in Python
Simulates a UI note that shows local state until a pending server update is confirmed, mocking eventual consistency behavior in distributed systems.
class EventualConsistencyNote:
def __init__(self, entity_id, note):
self.entity_id = entity_id
self.note = note
self.confirmed = False
self.pending_updates = []
def add_pending_update(self, update):
self.pending_updates.append(update)
def confirm_update(self):
…How to Build a Mock TFX Pipeline in Python
Simulate a TFX-style ML pipeline with simple Python functions to understand component orchestration, data flow, and artifact passing.
# Mock TFX pipeline to illustrate component orchestration
def CsvExampleGen(data_path):
"""Mock component: Simulates reading CSV data."""
print(f"ExampleGen: Reading from {data_path}")
return {"records": 100, "name": "examples"}
def StatisticsGen(example_artifact):
"""Mock component: Simulates genera…How to Mock a Redis Session Store in Python
An in-memory RedisSessionStore class with TTL-based expiry, get/set/delete/exists methods, and JSON field support—perfect for testing and prototyping without a live Redis.
import time
import json
from collections import defaultdict
class RedisSessionStore:
"""In-memory mock of a Redis-backed session store."""
def __init__(self, ttl=3600):
self._data = defaultdict(dict)
self._expires = {}
self._ttl = ttl
def set(self, session_id, field, value):
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