python-best-practices▌
0xbigboss/claude-code · updated Apr 8, 2026
Type-first Python development using dataclasses, discriminated unions, NewType, and Protocol to make illegal states unrepresentable.
- ›Define data models and function signatures before implementation; use frozen dataclasses, Literal-based discriminated unions, and NewType for domain primitives to prevent invalid states at type-check time
- ›Leverage Protocol for structural typing, TypedDict for external data shapes, and exhaustive pattern matching with match statements to catch incomplete lo
Python Best Practices
Follows type-first, functional, and error handling patterns from CLAUDE.md. This skill covers language-specific idioms only.
Make Illegal States Unrepresentable
Use Python's type system to prevent invalid states at type-check time.
Frozen dataclasses for immutable domain models:
from dataclasses import dataclass
from datetime import datetime
@dataclass(frozen=True)
class User:
id: str
email: str
name: str
created_at: datetime
# Frozen dataclasses are immutable — no accidental mutation
Discriminated unions with Literal:
from dataclasses import dataclass
from typing import Literal
@dataclass
class Success:
status: Literal["success"] = "success"
data: str
@dataclass
class Failure:
status: Literal["error"] = "error"
error: Exception
RequestState = Success | Failure
def handle_state(state: RequestState) -> None:
match state:
case Success(data=data):
render(data)
case Failure(error=err):
show_error(err)
NewType for domain primitives:
from typing import NewType
UserId = NewType("UserId", str)
OrderId = NewType("OrderId", str)
def get_user(user_id: UserId) -> User:
# Type checker prevents passing OrderId here
...
Protocol for structural typing:
from typing import Protocol
class Readable(Protocol):
def read(self, n: int = -1) -> bytes: ...
def process_input(source: Readable) -> bytes:
# Accepts any object with a read() method — no inheritance required
return source.read()
Python-Specific Error Handling
Chain exceptions with from err to preserve the original traceback:
try:
data = json.loads(raw)
except json.JSONDecodeError as err:
raise ValueError(f"invalid JSON payload: {err}") from err
Structured Logging
Use a module-level logger with %s formatting (deferred string interpolation):
import logging
logger = logging.getLogger("myapp.widgets")
def create_widget(name: str) -> Widget:
logger.debug("creating widget: %s", name)
widget = Widget(name=name)
logger.debug("created widget id=%s", widget.id)
return widget
Optional: ty
For fast type checking, consider ty from Astral (creators of ruff and uv). Written in Rust, significantly faster than mypy or pyright.
uvx ty check # run directly, no install needed
uvx ty check src/ # check specific path
# pyproject.toml
[tool.ty]
python-version = "3.12"
When to choose:
ty— fastest, good for CI and large codebases (early stage, rapidly evolving)pyright— most complete type inference, VS Code integrationmypy— mature, extensive plugin ecosystem