writing-python

name	writing-python
description	Idiomatic Python 3.14+ development. Use when writing Python code, CLI tools, scripts, or services. Emphasizes stdlib, type hints, uv/ruff toolchain, and minimal dependencies.
allowed-tools	Read, Bash, Grep, Glob

Python Development (3.14+)

Core Philosophy

1. Stdlib and Mature Libraries First

   • Always prefer Python stdlib solutions
   • External deps only when stdlib insufficient
   • Prefer dataclasses over attrs, pathlib over os.path

2. Type Hints Everywhere (No Any)

   • Python 3.14 has lazy annotations by default
   • Use Protocol for structural typing (duck typing)
   • Avoid Any—use concrete types or generics
   • NEVER use typing.Optional. Use Type | None instead (e.g., str | None).

3. Protocol Over ABC

   • Protocol for implicit interface satisfaction
   • ABC only when runtime isinstance() needed
   • Protocols are more flexible and Pythonic

4. Flat Control Flow

   • Guard clauses with early returns
   • Pattern matching to flatten conditionals
   • Maximum 2 levels of nesting

5. Explicit Error Handling

   • Custom exception hierarchy for domain errors
   • Raise early, handle at boundaries
   • except ValueError | TypeError: (no parens)

Quick Patterns

Protocol-Based Dependency Injection

from typing import Protocol

# Protocol at consumer (like Go interfaces)
class UserStore(Protocol):
    def get(self, id: str) -> User | None: ...
    def save(self, user: User) -> None: ...

class UserService:
    def __init__(self, store: UserStore):
        self.store = store  # accepts any matching impl

Flat Control Flow (No Nesting)

# GOOD: guard clauses, early returns
def process(user: User | None) -> Result:
    if user is None:
        raise ValueError("user required")
    if not user.email:
        raise ValueError("email required")
    if not is_valid_email(user.email):
        raise ValueError("invalid email")
    return do_work(user)  # happy path at end

# BAD: nested conditions
def process(user: User | None) -> Result:
    if user is not None:
        if user.email:
            if is_valid_email(user.email):
                return do_work(user)
    raise ValueError("invalid")

Pattern Matching

# Flatten complex conditionals with match
match event:
    case {"type": "click", "x": x, "y": y}:
        handle_click(x, y)
    case {"type": "key", "code": code}:
        handle_key(code)
    case _:
        raise ValueError(f"Unknown event: {event}")

Type Hints (No Any)

# GOOD: concrete types
def process_users(users: list[User], limit: int | None = None) -> list[Result]:
    ...

# GOOD: generics when needed
from typing import TypeVar
T = TypeVar("T")
def first(items: list[T]) -> T | None:
    return items[0] if items else None

# BAD: unnecessary Any
def process(data: Any) -> Any:  # Don't do this
    ...

Error Handling

# except without parens (3.14)
except ValueError | TypeError:
    handle_error()

# Custom exceptions
class NotFoundError(AppError):
    def __init__(self, resource: str, id: str):
        self.resource = resource
        self.id = id
        super().__init__(f"{resource} not found: {id}")

Python 3.14 Features

• Deferred annotations: No from __future__ import annotations
• Template strings (t""): t"Hello {name}" returns Template
• except without parens: except ValueError | TypeError:
• concurrent.interpreters: True parallelism
• compression.zstd: Zstandard in stdlib
• Free-threaded build: No GIL (opt-in)

References

• PATTERNS.md - Code patterns and style
• CLI.md - CLI application patterns
• TESTING.md - Testing with pytest

Tooling

uv sync                    # Install deps
ruff check --fix .         # Lint and autofix
ruff format .              # Format
pytest -v                  # Test
mypy .                     # Type check