Automated summary
This skill provides guidelines and patterns for writing idiomatic Python code, emphasizing the standard library, type hints, protocols, and flat control flow.
Strengths
- Promotes use of standard library and minimal dependencies.
- Enforces strict type hints with Python 3.14, improving robustness.
- Provides concrete patterns like protocols and pattern matching.
- Reduces complexity with flat control flow and guard clauses.
Limitations
- May be too prescriptive for cases requiring dynamic flexibility.
- Assumes Python 3.14+ and is not suited for legacy codebases.
- Does not cover all Python development aspects (e.g., async, performance).
When writing new Python projects or refactoring to modern, typed practices.
For projects requiring compatibility with Python <3.14 or using heavily dynamic patterns.
Security analysis
SafeThe skill provides guidance on writing Python code and does not instruct any destructive or exfiltrating actions. Allowed tools (Read, Bash, Grep, Glob) are standard for code development and carry minimal inherent risk when used as directed.
No concerns found
How this analysis is madeExamples
Refactor this Python function to use guard clauses and type hints, avoiding nested conditionals.Create a Python service class that uses a Protocol for its dependency, and implement a concrete class satisfying that protocol.Rewrite this event handler to use Python pattern matching instead of if-elif chains.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
-
Stdlib and Mature Libraries First
- Always prefer Python stdlib solutions
- External deps only when stdlib insufficient
- Prefer dataclasses over attrs, pathlib over os.path
-
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. UseType | Noneinstead (e.g.,str | None).
-
Protocol Over ABC
- Protocol for implicit interface satisfaction
- ABC only when runtime isinstance() needed
- Protocols are more flexible and Pythonic
-
Flat Control Flow
- Guard clauses with early returns
- Pattern matching to flatten conditionals
- Maximum 2 levels of nesting
-
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
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Claude Code
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