python-patterns

A guide to Python programming patterns for organizing code, describing interfaces, handling resources, writing reusable functions, and using type hints.

In plain words
What is it for?
Use it when designing repositories, data objects, context managers, decorators, asynchronous code, and Python packages.
Why use it?
It helps make Python code easier to test, extend, and understand by using standard language features and clear structure.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/mturac/everything-openai-codex/python-patterns
Any agent
npx skills add mturac/everything-openai-codex --skill python-patterns
Clone the repo
git clone --depth 1 https://github.com/mturac/everything-openai-codex

Made for: Claude Code, Codex.

Per session 45 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,291 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00045 $0.02291
Opus 5 $0.00023 $0.01145
Sonnet 5 $0.00009 $0.00458
Haiku 4.5 $0.00005 $0.00229

Measured yesterday against content hash 663be94e40ce, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

python-patterns scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

Copies of this mod

3 near-identical copies found in the catalogue:

.kiro/skills/python-patterns/SKILL.md · 429 lines

How it starts

The opening of the file, as written. The whole thing — 429 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Python Patterns

This skill provides comprehensive Python patterns extending common design principles with Python-specific idioms.

Protocol (Duck Typing)

Use Protocol for structural subtyping (duck typing with type hints):

from typing import Protocol

class Repository(Protocol):
    def find_by_id(self, id: str) -> dict | None: ...
    def save(self, entity: dict) -> dict: ...

# Any class with these methods satisfies the protocol
class UserRepository:
    def find_by_id(self, id: str) -> dict | None:
        # implementation
        pass

    def save(self, entity: dict) -> dict:
        # implementation
        pass

def process_entity(repo: Repository, id: str) -> None:
    entity = repo.find_by_id(id)
    # ... process

Benefits:

  • Type safety without inheritance
  • Flexible, loosely coupled code
  • Easy testing and mocking

Dataclasses as DTOs

Use dataclass for data transfer objects and value objects:

from dataclasses import dataclass, field
from typing import Optional

@dataclass
class CreateUserRequest:
    name: str
    email: str
    age: Optional[int] = None
    tags: list[str] = field(default_factory=list)

@dataclass(frozen=True)
class User:
    """Immutable user entity"""
    id: str
    name: str
    email: str

Features:

  • Auto-generated __init__, __repr__, __eq__
  • frozen=True for immutability
  • field() for complex defaults
  • Type hints for validation

Context Managers

Use context managers (with statement) for resource management:

from contextlib import contextmanager
from typing import Generator

@contextmanager
def database_transaction(db) -> Generator[None, None, None]:
    """Context manager for database transactions"""
    try:
        yield
        db.commit()
    except Exception:
        db.rollback()
        raise

# Usage
with database_transaction(db):
    db.execute("INSERT INTO users ...")

Class-based context manager:

class FileProcessor:
    def __init__(self, filename: str):
        self.filename = filename
        self.file = None

    def __enter__(self):
        self.file = open(self.filename, 'r')
        return self.file

    def __exit__(self, exc_type, exc_val, exc_tb):
        if self.file:
            self.file.close()
        return False  # Don't suppress exceptions

Read the full file on GitHub · 429 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. yesterday First seen · 429 lines · 45 tokens per session scan A 663be94e40ce

Subscribe to this mod's changes

python-patterns is a skill published in the GitHub repository mturac/everything-openai-codex (89 stars, last pushed 8d ago), licensed MIT. It adds 45 tokens to every session and 2,291 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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