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Python Developer

  • 63 installs
  • Updated January 1, 1970
  • dengineproblem/agents-monorepo

Acts as a Python developer agent that writes, refactors, and debugs Python code so a solo builder can implement backend logic, scripts, and services.

About

A Python developer agent skill that writes, refactors, and debugs Python code for backend services, APIs, and automation scripts. A solo builder reaches for it whenever a task calls for hands-on Python implementation and they want an assistant fluent in idiomatic Python patterns and tooling.

  • Writes and refactors Python
  • Debugs and tests Python code
  • Builds scripts and services

Python Developer by the numbers

  • 63 all-time installs (skills.sh)
  • Ranked #134 of 290 Python skills by installs in the Skillselion catalog
  • Data as of Jul 29, 2026 (Skillselion catalog sync)
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Listed on Skillselion
Installs63
Last updatedJanuary 1, 1970
Repositorydengineproblem/agents-monorepo

What it does

Acts as a Python developer agent that writes, refactors, and debugs Python code so a solo builder can implement backend logic, scripts, and services.

Who is it for?

builders implementing Python backends and scripts

Skip if: non-Python stacks

Files

SKILL.mdMarkdownGitHub ↗

Python Developer Expert

Expert in modern Python development, type hints, and clean architecture.

Core Principles

  • Type hints for all function signatures
  • PEP 8 compliance
  • Idiomatic, Pythonic code
  • Comprehensive docstrings

Modern Python (3.10+)

Type Hints

from typing import Optional, Union
from collections.abc import Sequence

# Union types (3.10+)
def process(value: int | str | None) -> str:
    if value is None:
        return "empty"
    return str(value)

# Generic types
def first_item[T](items: Sequence[T]) -> T | None:
    return items[0] if items else None

Pattern Matching

def handle_response(response: dict) -> str:
    match response:
        case {"status": "success", "data": data}:
            return f"Success: {data}"
        case {"status": "error", "message": msg}:
            return f"Error: {msg}"
        case {"status": status}:
            return f"Unknown status: {status}"
        case _:
            return "Invalid response"

Dataclasses

from dataclasses import dataclass, field
from datetime import datetime

@dataclass
class User:
    id: int
    email: str
    name: str
    created_at: datetime = field(default_factory=datetime.now)
    tags: list[str] = field(default_factory=list)

    def __post_init__(self):
        self.email = self.email.lower()

Async Programming

import asyncio
import aiohttp
from typing import Any

async def fetch_url(session: aiohttp.ClientSession, url: str) -> dict[str, Any]:
    async with session.get(url) as response:
        return await response.json()

async def fetch_all(urls: list[str]) -> list[dict[str, Any]]:
    async with aiohttp.ClientSession() as session:
        tasks = [fetch_url(session, url) for url in urls]
        return await asyncio.gather(*tasks)

# Async generator
async def stream_data(source):
    async for item in source:
        yield process(item)

Context Managers

from contextlib import contextmanager, asynccontextmanager
from typing import Generator

@contextmanager
def managed_resource(name: str) -> Generator[Resource, None, None]:
    resource = acquire_resource(name)
    try:
        yield resource
    finally:
        resource.release()

@asynccontextmanager
async def async_db_session():
    session = await create_session()
    try:
        yield session
        await session.commit()
    except Exception:
        await session.rollback()
        raise
    finally:
        await session.close()

Error Handling

class ApplicationError(Exception):
    """Base exception for application errors."""
    def __init__(self, message: str, code: str, details: dict | None = None):
        super().__init__(message)
        self.code = code
        self.details = details or {}

class ValidationError(ApplicationError):
    """Raised when validation fails."""
    def __init__(self, field: str, message: str):
        super().__init__(message, "VALIDATION_ERROR", {"field": field})

# Usage
def validate_user(data: dict) -> User:
    if not data.get("email"):
        raise ValidationError("email", "Email is required")
    if "@" not in data["email"]:
        raise ValidationError("email", "Invalid email format")
    return User(**data)

Project Structure

project/
├── src/
│   └── package_name/
│       ├── __init__.py
│       ├── main.py
│       ├── models/
│       ├── services/
│       └── utils/
├── tests/
│   ├── conftest.py
│   ├── unit/
│   └── integration/
├── pyproject.toml
└── README.md

pyproject.toml

[project]
name = "my-package"
version = "0.1.0"
requires-python = ">=3.11"
dependencies = [
    "fastapi>=0.100.0",
    "pydantic>=2.0.0",
]

[project.optional-dependencies]
dev = [
    "pytest>=7.0.0",
    "pytest-asyncio>=0.21.0",
    "mypy>=1.0.0",
    "ruff>=0.1.0",
]

[tool.ruff]
line-length = 88
select = ["E", "F", "I", "N", "W"]

[tool.mypy]
strict = true
python_version = "3.11"

[tool.pytest.ini_options]
asyncio_mode = "auto"

Testing with Pytest

import pytest
from unittest.mock import AsyncMock, patch

@pytest.fixture
def user_data():
    return {"id": 1, "email": "test@example.com", "name": "Test"}

@pytest.fixture
async def db_session():
    session = await create_test_session()
    yield session
    await session.rollback()

class TestUserService:
    async def test_create_user(self, db_session, user_data):
        service = UserService(db_session)
        user = await service.create(user_data)
        assert user.email == user_data["email"]

    async def test_create_user_duplicate_email(self, db_session, user_data):
        service = UserService(db_session)
        await service.create(user_data)
        with pytest.raises(ValidationError):
            await service.create(user_data)

    @patch("services.user.send_email", new_callable=AsyncMock)
    async def test_send_welcome_email(self, mock_send, db_session):
        service = UserService(db_session)
        await service.send_welcome(user_id=1)
        mock_send.assert_called_once()

FastAPI Example

from fastapi import FastAPI, HTTPException, Depends
from pydantic import BaseModel, EmailStr

app = FastAPI()

class UserCreate(BaseModel):
    email: EmailStr
    name: str

class UserResponse(BaseModel):
    id: int
    email: str
    name: str

@app.post("/users", response_model=UserResponse)
async def create_user(
    data: UserCreate,
    service: UserService = Depends(get_user_service)
) -> UserResponse:
    try:
        user = await service.create(data.model_dump())
        return UserResponse.model_validate(user)
    except ValidationError as e:
        raise HTTPException(status_code=400, detail=str(e))

Лучшие практики

1. Type hints everywhere — типизация улучшает читаемость и IDE support 2. Dataclasses/Pydantic — для структурированных данных 3. Context managers — для управления ресурсами 4. Async when needed — для I/O-bound операций 5. Pytest fixtures — для переиспользования тестовой логики 6. Ruff + MyPy — для линтинга и проверки типов

Related skills

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