
Python Best Practices
- 1.9k installs
- 52 repo stars
- Updated June 24, 2026
- 0xbigboss/claude-code
python-best-practices is an agent skill for Use when reading or writing Python files (.py, pyproject.toml, requirements.txt).
About
Use when reading or writing Python files py pyproject toml requirements txt The python-best-practices skill documents workflows and patterns from the repository SKILL md name python-best-practices description Use when reading or writing Python files py pyproject toml requirements txt 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 python 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 python 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 primi.
- Python Best Practices
- Frozen dataclasses are immutable - no accidental mutation
- Type checker prevents passing OrderId here
- Accepts any object with a read() method - no inheritance required
- `ty` - fastest, good for CI and large codebases (early stage, rapidly evolving)
Python Best Practices by the numbers
- 1,901 all-time installs (skills.sh)
- +35 installs in the week ending Aug 5, 2026 (Skillselion tracking)
- Ranked #401 of 2,153 Testing & QA skills by installs in the Skillselion catalog
- Security screen: MEDIUM risk (skills.sh audit)
- Data as of Aug 5, 2026 (Skillselion catalog sync)
python-best-practices capabilities & compatibility
- Capabilities
- python best practices · frozen dataclasses are immutable no accidental · type checker prevents passing orderid here · accepts any object with a read() method no inh · `ty` fastest, good for ci and large codebases
- Use cases
- documentation
What python-best-practices says it does
--- name: python-best-practices description: Use when reading or writing Python files (.py, pyproject.toml, requirements.txt).
--- # 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.
npx skills add https://github.com/0xbigboss/claude-code --skill python-best-practicesAdd your badge
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| Installs | 1.9k |
|---|---|
| repo stars | ★ 52 |
| Security audit | 2 / 3 scanners passed |
| Last updated | June 24, 2026 |
| Repository | 0xbigboss/claude-code ↗ |
What problem does python-best-practices solve for developers using the documented workflows?
Use when reading or writing Python files (.py, pyproject.toml, requirements.txt).
Who is it for?
Developers working with python-best-practices patterns described in the skill documentation.
Skip if: Skip when docs are empty or the task is outside the skill documented scope.
When should I use this skill?
Use when reading or writing Python files (.py, pyproject.toml, requirements.txt).
What you get
Grounded guidance and workflows from SKILL.md for python-best-practices.
- Typed Python modules
- Immutable domain models
Files
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 mutationDiscriminated 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 errStructured 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 widgetOptional: 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
Related skills
How it compares
Use python-best-practices for core Python typing and idioms; pair with framework-specific skills when the task is routing, ORM design, or deployment rather than language style.
FAQ
Who is Python Best Practices for?
Developers and software engineers working with python-best-practices patterns from the skill documentation.
When should I use Python Best Practices?
Use when reading or writing Python files (.py, pyproject.toml, requirements.txt).
Is Python Best Practices safe to install?
Review the Security Audits panel on this page before installing in production.