Kedro Babysit
kedro-org/kedro
Run Kedro's local lint / format / type-check / tests on changed files (uses the project's pre-commit hooks, ruff, mypy, pytest, lint-imports, detect-secrets, Make targets — in the right venv), or…
Pythonic idiomlar, PEP 8 standartları, type hint'ler ve sağlam, verimli ve bakımı kolay Python uygulamaları oluşturmak için en iyi uygulamalar.
$ npx skills add affaan-m/ECC --skill python-patterns -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install affaan-m/ECC python-patterns --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/affaan-m/ECC.git skills-src && mkdir -p .claude/skills && cp -r skills-src/docs/tr/skills/python-patterns .claude/skills/python-patterns && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "python-patterns" agent skill from https://github.com/affaan-m/ECC/tree/main/docs/tr/skills/python-patterns into .claude/skills/python-patterns/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "python-patterns", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/affaan-m/ECC/tree/main/docs/tr/skills/python-patternsType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add affaan-m/ECC --skill python-patterns -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install affaan-m/ECC python-patterns --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/affaan-m/ECC.git skills-src && mkdir -p .agents/skills && cp -r skills-src/docs/tr/skills/python-patterns .agents/skills/python-patterns && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "python-patterns" agent skill from https://github.com/affaan-m/ECC/tree/main/docs/tr/skills/python-patterns into .agents/skills/python-patterns/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "python-patterns", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add affaan-m/ECC --skill python-patterns -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install affaan-m/ECC python-patterns --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/affaan-m/ECC.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/docs/tr/skills/python-patterns .cursor/skills/python-patterns && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "python-patterns" agent skill from https://github.com/affaan-m/ECC/tree/main/docs/tr/skills/python-patterns into .cursor/skills/python-patterns/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "python-patterns", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/affaan-m/ECC.git --path docs/tr/skills/python-patterns--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add affaan-m/ECC --skill python-patterns -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install affaan-m/ECC python-patterns --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/affaan-m/ECC.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/docs/tr/skills/python-patterns .gemini/skills/python-patterns && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "python-patterns" agent skill from https://github.com/affaan-m/ECC/tree/main/docs/tr/skills/python-patterns into .gemini/skills/python-patterns/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "python-patterns", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install affaan-m/ECC python-patternsInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add affaan-m/ECC --skill python-patterns -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/affaan-m/ECC.git skills-src && mkdir -p .github/skills && cp -r skills-src/docs/tr/skills/python-patterns .github/skills/python-patterns && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "python-patterns" agent skill from https://github.com/affaan-m/ECC/tree/main/docs/tr/skills/python-patterns into .github/skills/python-patterns/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "python-patterns", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add affaan-m/ECC --skill python-patterns -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install affaan-m/ECC python-patterns --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/affaan-m/ECC.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/docs/tr/skills/python-patterns .opencode/skills/python-patterns && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "python-patterns" agent skill from https://github.com/affaan-m/ECC/tree/main/docs/tr/skills/python-patterns into .opencode/skills/python-patterns/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "python-patterns", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
python-patternsPythonic idiomlar, PEP 8 standartları, type hint'ler ve sağlam, verimli ve bakımı kolay Python uygulamaları oluşturmak için en iyi uygulamalar.
Python Patterns is an agent skill from affaan-m/ECC. Pythonic idiomlar, PEP 8 standartları, type hint'ler ve sağlam, verimli ve bakımı kolay Python uygulamaları oluşturmak için en iyi uygulamalar.
Its SKILL.md is about 4.3k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Development, covering Type safety. It works with Python. The repository describes itself as: The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond. The licence is MIT.
3 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit ef648e0. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Shell commands in SKILL.md call:
blackruffmypypytestFrom the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Python Patterns loads about 4.3k tokens when it runs. Until then it costs about 40 tokens; SKILL.md has 285 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from affaan-m/ECC at commit ef648e0, republished under its MIT licence (© affaan-m). 285 words, ~4,257 tokens.
.claude/skills/python-patterns/SKILL.md (or your agent's skills folder).Sağlam, verimli ve bakımı kolay uygulamalar oluşturmak için idiomatic Python desenleri ve en iyi uygulamalar.
Python okunabilirliği önceliklendirir. Kod açık ve anlaşılması kolay olmalıdır.
# İyi: Açık ve okunabilir
def get_active_users(users: list[User]) -> list[User]:
"""Sağlanan listeden sadece aktif kullanıcıları döndür."""
return [user for user in users if user.is_active]
# Kötü: Zeki ama kafa karıştırıcı
def get_active_users(u):
return [x for x in u if x.a]Sihirden kaçının; kodunuzun ne yaptığı konusunda açık olun.
# İyi: Açık yapılandırma
import logging
logging.basicConfig(
level=logging.INFO,
format='%(asctime)s - %(name)s - %(levelname)s - %(message)s'
)
# Kötü: Gizli yan etkiler
import some_module
some_module.setup() # Bu ne yapıyor?Python, koşulları kontrol etmek yerine exception handling'i tercih eder.
# İyi: EAFP stili
def get_value(dictionary: dict, key: str, default_value: Any = None) -> Any:
try:
return dictionary[key]
except KeyError:
return default_value
# Kötü: LBYL (Atlamadan Önce Bak) stili
def get_value(dictionary: dict, key: str, default_value: Any = None) -> Any:
if key in dictionary:
return dictionary[key]
else:
return default_valuefrom typing import Optional, List, Dict, Any
def process_user(
user_id: str,
data: Dict[str, Any],
active: bool = True
) -> Optional[User]:
"""Bir kullanıcıyı işle ve güncellenmiş User'ı veya None döndür."""
if not active:
return None
return User(user_id, data)# Python 3.9+ - Built-in tipleri kullan
def process_items(items: list[str]) -> dict[str, int]:
return {item: len(item) for item in items}
# Python 3.8 ve öncesi - typing modülünü kullan
from typing import List, Dict
def process_items(items: List[str]) -> Dict[str, int]:
return {item: len(item) for item in items}from typing import TypeVar, Union
# Karmaşık tipler için type alias
JSON = Union[dict[str, Any], list[Any], str, int, float, bool, None]
def parse_json(data: str) -> JSON:
return json.loads(data)
# Generic tipler
T = TypeVar('T')
def first(items: list[T]) -> T | None:
"""İlk öğeyi döndür veya liste boşsa None döndür."""
return items[0] if items else Nonefrom typing import Protocol
class Renderable(Protocol):
def render(self) -> str:
"""Nesneyi string'e render et."""
def render_all(items: list[Renderable]) -> str:
"""Renderable protocol'ünü implement eden tüm öğeleri render et."""
return "\n".join(item.render() for item in items)# İyi: Spesifik exception'ları yakala
def load_config(path: str) -> Config:
try:
with open(path) as f:
return Config.from_json(f.read())
except FileNotFoundError as e:
raise ConfigError(f"Config file not found: {path}") from e
except json.JSONDecodeError as e:
raise ConfigError(f"Invalid JSON in config: {path}") from e
# Kötü: Bare except
def load_config(path: str) -> Config:
try:
with open(path) as f:
return Config.from_json(f.read())
except:
return None # Sessiz hata!def process_data(data: str) -> Result:
try:
parsed = json.loads(data)
except json.JSONDecodeError as e:
# Traceback'i korumak için exception'ları zincirleme
raise ValueError(f"Failed to parse data: {data}") from eclass AppError(Exception):
"""Tüm uygulama hataları için base exception."""
pass
class ValidationError(AppError):
"""Input validation başarısız olduğunda raise edilir."""
pass
class NotFoundError(AppError):
"""İstenen kaynak bulunamadığında raise edilir."""
pass
# Kullanım
def get_user(user_id: str) -> User:
user = db.find_user(user_id)
if not user:
raise NotFoundError(f"User not found: {user_id}")
return user# İyi: Context manager'ları kullanma
def process_file(path: str) -> str:
with open(path, 'r') as f:
return f.read()
# Kötü: Manuel kaynak yönetimi
def process_file(path: str) -> str:
f = open(path, 'r')
try:
return f.read()
finally:
f.close()from contextlib import contextmanager
@contextmanager
def timer(name: str):
"""Bir kod bloğunu zamanlamak için context manager."""
start = time.perf_counter()
yield
elapsed = time.perf_counter() - start
print(f"{name} took {elapsed:.4f} seconds")
# Kullanım
with timer("data processing"):
process_large_dataset()class DatabaseTransaction:
def __init__(self, connection):
self.connection = connection
def __enter__(self):
self.connection.begin_transaction()
return self
def __exit__(self, exc_type, exc_val, exc_tb):
if exc_type is None:
self.connection.commit()
else:
self.connection.rollback()
return False # Exception'ları suppress etme
# Kullanım
with DatabaseTransaction(conn):
user = conn.create_user(user_data)
conn.create_profile(user.id, profile_data)# İyi: Basit dönüşümler için list comprehension
names = [user.name for user in users if user.is_active]
# Kötü: Manuel döngü
names = []
for user in users:
if user.is_active:
names.append(user.name)
# Karmaşık comprehension'lar genişletilmelidir
# Kötü: Çok karmaşık
result = [x * 2 for x in items if x > 0 if x % 2 == 0]
# İyi: Bir generator fonksiyonu kullan
def filter_and_transform(items: Iterable[int]) -> list[int]:
result = []
for x in items:
if x > 0 and x % 2 == 0:
result.append(x * 2)
return result# İyi: Lazy evaluation için generator
total = sum(x * x for x in range(1_000_000))
# Kötü: Büyük ara liste oluşturur
total = sum([x * x for x in range(1_000_000)])def read_large_file(path: str) -> Iterator[str]:
"""Büyük bir dosyayı satır satır oku."""
with open(path) as f:
for line in f:
yield line.strip()
# Kullanım
for line in read_large_file("huge.txt"):
process(line)from dataclasses import dataclass, field
from datetime import datetime
@dataclass
class User:
"""Otomatik __init__, __repr__ ve __eq__ ile User entity."""
id: str
name: str
email: str
created_at: datetime = field(default_factory=datetime.now)
is_active: bool = True
# Kullanım
user = User(
id="123",
name="Alice",
email="alice@example.com"
)@dataclass
class User:
email: str
age: int
def __post_init__(self):
# Email formatını validate et
if "@" not in self.email:
raise ValueError(f"Invalid email: {self.email}")
# Yaş aralığını validate et
if self.age < 0 or self.age > 150:
raise ValueError(f"Invalid age: {self.age}")from typing import NamedTuple
class Point(NamedTuple):
"""Immutable 2D nokta."""
x: float
y: float
def distance(self, other: 'Point') -> float:
return ((self.x - other.x) ** 2 + (self.y - other.y) ** 2) ** 0.5
# Kullanım
p1 = Point(0, 0)
p2 = Point(3, 4)
print(p1.distance(p2)) # 5.0import functools
import time
def timer(func: Callable) -> Callable:
"""Fonksiyon yürütmesini zamanlamak için decorator."""
@functools.wraps(func)
def wrapper(*args, **kwargs):
start = time.perf_counter()
result = func(*args, **kwargs)
elapsed = time.perf_counter() - start
print(f"{func.__name__} took {elapsed:.4f}s")
return result
return wrapper
@timer
def slow_function():
time.sleep(1)
# slow_function() yazdırır: slow_function took 1.0012sdef repeat(times: int):
"""Bir fonksiyonu birden çok kez tekrarlamak için decorator."""
def decorator(func: Callable) -> Callable:
@functools.wraps(func)
def wrapper(*args, **kwargs):
results = []
for _ in range(times):
results.append(func(*args, **kwargs))
return results
return wrapper
return decorator
@repeat(times=3)
def greet(name: str) -> str:
return f"Hello, {name}!"
# greet("Alice") döndürür ["Hello, Alice!", "Hello, Alice!", "Hello, Alice!"]class CountCalls:
"""Bir fonksiyonun kaç kez çağrıldığını sayan decorator."""
def __init__(self, func: Callable):
functools.update_wrapper(self, func)
self.func = func
self.count = 0
def __call__(self, *args, **kwargs):
self.count += 1
print(f"{self.func.__name__} has been called {self.count} times")
return self.func(*args, **kwargs)
@CountCalls
def process():
pass
# Her process() çağrısı çağrı sayısını yazdırırimport concurrent.futures
import threading
def fetch_url(url: str) -> str:
"""Bir URL fetch et (I/O-bound operasyon)."""
import urllib.request
with urllib.request.urlopen(url) as response:
return response.read().decode()
def fetch_all_urls(urls: list[str]) -> dict[str, str]:
"""Thread'ler kullanarak birden fazla URL'yi eşzamanlı fetch et."""
with concurrent.futures.ThreadPoolExecutor(max_workers=10) as executor:
future_to_url = {executor.submit(fetch_url, url): url for url in urls}
results = {}
for future in concurrent.futures.as_completed(future_to_url):
url = future_to_url[future]
try:
results[url] = future.result()
except Exception as e:
results[url] = f"Error: {e}"
return resultsdef process_data(data: list[int]) -> int:
"""CPU-yoğun hesaplama."""
return sum(x ** 2 for x in data)
def process_all(datasets: list[list[int]]) -> list[int]:
"""Birden fazla process kullanarak birden fazla dataset işle."""
with concurrent.futures.ProcessPoolExecutor() as executor:
results = list(executor.map(process_data, datasets))
return resultsimport asyncio
async def fetch_async(url: str) -> str:
"""Asenkron olarak bir URL fetch et."""
import aiohttp
async with aiohttp.ClientSession() as session:
async with session.get(url) as response:
return await response.text()
async def fetch_all(urls: list[str]) -> dict[str, str]:
"""Birden fazla URL'yi eşzamanlı fetch et."""
tasks = [fetch_async(url) for url in urls]
results = await asyncio.gather(*tasks, return_exceptions=True)
return dict(zip(urls, results))myproject/
├── src/
│ └── mypackage/
│ ├── __init__.py
│ ├── main.py
│ ├── api/
│ │ ├── __init__.py
│ │ └── routes.py
│ ├── models/
│ │ ├── __init__.py
│ │ └── user.py
│ └── utils/
│ ├── __init__.py
│ └── helpers.py
├── tests/
│ ├── __init__.py
│ ├── conftest.py
│ ├── test_api.py
│ └── test_models.py
├── pyproject.toml
├── README.md
└── .gitignore# İyi: Import sırası - stdlib, third-party, local
import os
import sys
from pathlib import Path
import requests
from fastapi import FastAPI
from mypackage.models import User
from mypackage.utils import format_name
# İyi: Otomatik import sıralama için isort kullanın
# pip install isort# mypackage/__init__.py
"""mypackage - Örnek bir Python paketi."""
__version__ = "1.0.0"
# Ana class/fonksiyonları paket seviyesinde export et
from mypackage.models import User, Post
from mypackage.utils import format_name
__all__ = ["User", "Post", "format_name"]# Kötü: Normal class __dict__ kullanır (daha fazla bellek)
class Point:
def __init__(self, x: float, y: float):
self.x = x
self.y = y
# İyi: __slots__ bellek kullanımını azaltır
class Point:
__slots__ = ['x', 'y']
def __init__(self, x: float, y: float):
self.x = x
self.y = y# Kötü: Bellekte tam liste döndürür
def read_lines(path: str) -> list[str]:
with open(path) as f:
return [line.strip() for line in f]
# İyi: Satırları birer birer yield eder
def read_lines(path: str) -> Iterator[str]:
with open(path) as f:
for line in f:
yield line.strip()# Kötü: String immutability nedeniyle O(n²)
result = ""
for item in items:
result += str(item)
# İyi: join kullanarak O(n)
result = "".join(str(item) for item in items)
# İyi: Oluşturma için StringIO kullanma
from io import StringIO
buffer = StringIO()
for item in items:
buffer.write(str(item))
result = buffer.getvalue()# Kod formatlama
black .
isort .
# Linting
ruff check .
pylint mypackage/
# Type checking
mypy .
# Test
pytest --cov=mypackage --cov-report=html
# Güvenlik taraması
bandit -r .
# Dependency yönetimi
pip-audit
safety check[project]
name = "mypackage"
version = "1.0.0"
requires-python = ">=3.9"
dependencies = [
"requests>=2.31.0",
"pydantic>=2.0.0",
]
[project.optional-dependencies]
dev = [
"pytest>=7.4.0",
"pytest-cov>=4.1.0",
"black>=23.0.0",
"ruff>=0.1.0",
"mypy>=1.5.0",
]
[tool.black]
line-length = 88
target-version = ['py39']
[tool.ruff]
line-length = 88
select = ["E", "F", "I", "N", "W"]
[tool.mypy]
python_version = "3.9"
warn_return_any = true
warn_unused_configs = true
disallow_untyped_defs = true
[tool.pytest.ini_options]
testpaths = ["tests"]
addopts = "--cov=mypackage --cov-report=term-missing"| İfade | Açıklama |
|---|---|
| EAFP | Affederek Sormaktansa İzin İstemek Daha Kolay |
| Context manager'lar | Kaynak yönetimi için with kullan |
| List comprehension'lar | Basit dönüşümler için |
| Generator'lar | Lazy evaluation ve büyük dataset'ler için |
| Type hint'ler | Fonksiyon signature'larını annotate et |
| Dataclass'lar | Auto-generated metodlarla veri container'ları için |
__slots__ | Bellek optimizasyonu için |
| f-string'ler | String formatlama için (Python 3.6+) |
pathlib.Path | Path operasyonları için (Python 3.4+) |
enumerate | Döngülerde index-element çiftleri için |
# Kötü: Mutable default argümanlar
def append_to(item, items=[]):
items.append(item)
return items
# İyi: None kullan ve yeni liste oluştur
def append_to(item, items=None):
if items is None:
items = []
items.append(item)
return items
# Kötü: type() ile tip kontrolü
if type(obj) == list:
process(obj)
# İyi: isinstance kullan
if isinstance(obj, list):
process(obj)
# Kötü: None ile == ile karşılaştırma
if value == None:
process()
# İyi: is kullan
if value is None:
process()
# Kötü: from module import *
from os.path import *
# İyi: Açık import'lar
from os.path import join, exists
# Kötü: Bare except
try:
risky_operation()
except:
pass
# İyi: Spesifik exception
try:
risky_operation()
except SpecificError as e:
logger.error(f"Operation failed: {e}")Unutmayın: Python kodu okunabilir, açık ve en az sürpriz ilkesine uygun olmalıdır. Şüphe duyduğunuzda, açıklığı zekiceden öncelikli kılın.
© affaan-m, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in docs/tr/skills/python-patterns of affaan-m/ECC.
Open the folder on GitHubat commit ef648e0
We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in affaan-m/ECC, which our catalogue first saw on October 7, 2026.
Python Patterns next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Python Patterns this skillaffaan-m/ECC | 274k | 1 repos | ~4.3k | Automated safety check: Pass | MIT | |
| Kedro Babysitkedro-org/kedro | 11k | — | ~4k | Automated safety check: Pass | Custom licence | |
| Dignified Python Standardsdocling-project/docling | 68k | — | ~1.5k | Automated safety check: Pass | Apache-2.0 | |
| Rust Ffiariebovenberg/whenever | 2.4k | — | ~2.5k | Automated safety check: Pass | MIT | |
| Diataxis Docs Writercalf-ai/calfkit-sdk | 149 | 1 repos | ~3k | Automated safety check: Pass | Apache-2.0 | |
| Update Dependenciesalorence/django-modern-rpc | 111 | — | ~1.3k | Automated safety check: Pass | MIT |
kedro-org/kedro
Run Kedro's local lint / format / type-check / tests on changed files (uses the project's pre-commit hooks, ruff, mypy, pytest, lint-imports, detect-secrets, Make targets — in the right venv), or…
docling-project/docling
Applies opinionated production Python conventions chosen by the project's Python version: modern type syntax, pathlib, explicit checks and interface guidance.
ariebovenberg/whenever
Instructions for using whenever's internal Rust FFI abstractions
calf-ai/calfkit-sdk
Write or improve software documentation using the Diátaxis framework — four documentation types (tutorials, how-to guides, reference, explanation), each serving a different user need.
alorence/django-modern-rpc
Routine update of all project dependencies — uv itself, uv.lock (all groups), tool versions pinned in GitHub workflows and .pre-commit-config.yaml (uv, ruff, mypy...), and SHA-pinned GitHub Actions.
withceleste/celeste-python
A skill your agent uses whenever writing, modifying, reviewing, or debugging code involving Celeste, celeste-ai, celeste-python, import celeste, src/celeste, or withceleste app integrations.
affaan-m/ECC
Audits your installed Claude skills and commands for quality, with a quick mode for recently changed skills and a full mode that evaluates all of them through subagents.
affaan-m/ECC
Ingest, index, search, edit, and monitor video and audio with the VideoDB Python SDK — upload from files, URLs, or RTSP feeds, build spoken and scene indexes with timestamped search and playable…
affaan-m/ECC
Scans installed skills for principles that recur across them and proposes rule-file changes: append, revise, add a section, create a file or leave as covered.
affaan-m/ECC
Builds DRAFT counterparty agreements from one markdown template and a small JSON spec per party, with clauses picked by the party's role.
affaan-m/ECC
Measures whether agents actually follow a skill, rule or agent definition by generating scenarios at three strictness levels and scoring tool-call traces.
affaan-m/ECC
Instinct-based learning system that observes sessions via hooks, creates atomic instincts with confidence scoring, and evolves them into skills/commands/agents.
Works with
Categories
Pythonic idiomlar, PEP 8 standartları, type hint'ler ve sağlam, verimli ve bakımı kolay Python uygulamaları oluşturmak için en iyi uygulamalar. Python Patterns is an agent skill from affaan-m/ECC. Pythonic idiomlar, PEP 8 standartları, type hint'ler ve sağlam, verimli ve bakımı kolay Python uygulamaları oluşturmak için en iyi uygulamalar.
Python Patterns fits situations like: tasks that involve Type safety.
Run `npx skills add affaan-m/ECC --skill python-patterns -a claude-code`. Or copy the skill folder (docs/tr/skills/python-patterns in affaan-m/ECC) into .claude/skills/python-patterns in your project. Claude Code loads it when a task matches its description.
Run `npx skills add affaan-m/ECC --skill python-patterns -a codex`. Or copy the skill folder (docs/tr/skills/python-patterns in affaan-m/ECC) into .agents/skills/python-patterns in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add affaan-m/ECC --skill python-patterns -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/python-patterns, .gemini/skills/python-patterns, .github/skills/python-patterns and .opencode/skills/python-patterns in your project.
Going by SKILL.md and its folder, Python Patterns needs the command-line tools its instructions call (black, ruff, mypy and pytest). Our summary lists: Python 3.
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Python Patterns is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 4.3k tokens (SKILL.md is roughly 17k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Python Patterns: Kedro Babysit (kedro-org/kedro, 11k stars), Dignified Python Standards (docling-project/docling, 68k stars), Rust Ffi (ariebovenberg/whenever, 2.4k stars) and Diataxis Docs Writer (calf-ai/calfkit-sdk, 149 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
affaan-m (a GitHub user) maintains it in affaan-m/ECC, which has 274,360 GitHub stars. The repository holds 657 skills in this directory. The repository was last updated on October 5, 2026.
Source: affaan-m/ECC on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.