python-database-ops
SQLAlchemy and database patterns for Python. Triggers on: sqlalchemy, database, orm, migration, alembic, async database, connection pool, repository pattern, unit of work.
Best use case
python-database-ops is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
SQLAlchemy and database patterns for Python. Triggers on: sqlalchemy, database, orm, migration, alembic, async database, connection pool, repository pattern, unit of work.
Teams using python-database-ops should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/python-database-ops/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How python-database-ops Compares
| Feature / Agent | python-database-ops | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
SQLAlchemy and database patterns for Python. Triggers on: sqlalchemy, database, orm, migration, alembic, async database, connection pool, repository pattern, unit of work.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Python Database Patterns
SQLAlchemy 2.0 and database best practices.
## SQLAlchemy 2.0 Basics
```python
from sqlalchemy import create_engine, select
from sqlalchemy.orm import DeclarativeBase, Mapped, mapped_column, Session
class Base(DeclarativeBase):
pass
class User(Base):
__tablename__ = "users"
id: Mapped[int] = mapped_column(primary_key=True)
name: Mapped[str] = mapped_column(String(100))
email: Mapped[str] = mapped_column(String(255), unique=True)
is_active: Mapped[bool] = mapped_column(default=True)
# Create engine and tables
engine = create_engine("postgresql://user:pass@localhost/db")
Base.metadata.create_all(engine)
# Query with 2.0 style
with Session(engine) as session:
stmt = select(User).where(User.is_active == True)
users = session.execute(stmt).scalars().all()
```
## Async SQLAlchemy
```python
from sqlalchemy.ext.asyncio import (
AsyncSession,
async_sessionmaker,
create_async_engine,
)
from sqlalchemy import select
# Async engine
engine = create_async_engine(
"postgresql+asyncpg://user:pass@localhost/db",
echo=False,
pool_size=5,
max_overflow=10,
)
# Session factory
async_session = async_sessionmaker(engine, expire_on_commit=False)
# Usage
async with async_session() as session:
result = await session.execute(select(User).where(User.id == 1))
user = result.scalar_one_or_none()
```
## Model Relationships
```python
from sqlalchemy import ForeignKey
from sqlalchemy.orm import relationship, Mapped, mapped_column
class User(Base):
__tablename__ = "users"
id: Mapped[int] = mapped_column(primary_key=True)
name: Mapped[str]
# One-to-many
posts: Mapped[list["Post"]] = relationship(back_populates="author")
class Post(Base):
__tablename__ = "posts"
id: Mapped[int] = mapped_column(primary_key=True)
title: Mapped[str]
author_id: Mapped[int] = mapped_column(ForeignKey("users.id"))
# Many-to-one
author: Mapped["User"] = relationship(back_populates="posts")
```
## Common Query Patterns
```python
from sqlalchemy import select, and_, or_, func
# Basic select
stmt = select(User).where(User.is_active == True)
# Multiple conditions
stmt = select(User).where(
and_(
User.is_active == True,
User.age >= 18
)
)
# OR conditions
stmt = select(User).where(
or_(User.role == "admin", User.role == "moderator")
)
# Ordering and limiting
stmt = select(User).order_by(User.created_at.desc()).limit(10)
# Aggregates
stmt = select(func.count(User.id)).where(User.is_active == True)
# Joins
stmt = select(User, Post).join(Post, User.id == Post.author_id)
# Eager loading
from sqlalchemy.orm import selectinload
stmt = select(User).options(selectinload(User.posts))
```
## FastAPI Integration
```python
from fastapi import Depends, FastAPI
from sqlalchemy.ext.asyncio import AsyncSession
from typing import Annotated
async def get_db() -> AsyncGenerator[AsyncSession, None]:
async with async_session() as session:
yield session
DB = Annotated[AsyncSession, Depends(get_db)]
@app.get("/users/{user_id}")
async def get_user(user_id: int, db: DB):
result = await db.execute(select(User).where(User.id == user_id))
user = result.scalar_one_or_none()
if not user:
raise HTTPException(status_code=404)
return user
```
## Quick Reference
| Operation | SQLAlchemy 2.0 Style |
|-----------|---------------------|
| Select all | `select(User)` |
| Filter | `.where(User.id == 1)` |
| First | `.scalar_one_or_none()` |
| All | `.scalars().all()` |
| Count | `select(func.count(User.id))` |
| Join | `.join(Post)` |
| Eager load | `.options(selectinload(User.posts))` |
## Additional Resources
- `./references/sqlalchemy-async.md` - Async patterns, session management
- `./references/connection-pooling.md` - Pool configuration, health checks
- `./references/transactions.md` - Transaction patterns, isolation levels
- `./references/migrations.md` - Alembic setup, migration strategies
## Assets
- `./assets/alembic.ini.template` - Alembic configuration template
---
## See Also
**Prerequisites:**
- `python-typing-ops` - Mapped types and annotations
- `python-async-ops` - Async database sessions
**Related Skills:**
- `python-fastapi-ops` - Dependency injection for DB sessions
- `python-pytest-ops` - Database fixtures and testingRelated Skills
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