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This skill provides python database patterns with SQLAlchemy 2.0 guidance, enabling efficient modeling, querying, async usage, and migrations for robust apps.
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---
name: python-database-patterns
description: "SQLAlchemy and database patterns for Python. Triggers on: sqlalchemy, database, orm, migration, alembic, async database, connection pool, repository pattern, unit of work."
compatibility: "SQLAlchemy 2.0+, Python 3.10+. Async requires asyncpg (PostgreSQL) or aiosqlite."
allowed-tools: "Read Write Bash"
depends-on: [python-typing-patterns, python-async-patterns]
related-skills: [python-fastapi-patterns]
---
# 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-patterns` - Mapped types and annotations
- `python-async-patterns` - Async database sessions
**Related Skills:**
- `python-fastapi-patterns` - Dependency injection for DB sessions
- `python-pytest-patterns` - Database fixtures and testing
This skill covers SQLAlchemy 2.0 patterns and practical database architecture for Python applications. It focuses on declarative models, synchronous and asynchronous sessions, relationship mapping, common query idioms, and integration with frameworks like FastAPI. The intent is to help you apply repository and unit-of-work ideas, configure connection pools, and run migrations predictably.
I provide concise examples and patterns that show how to define DeclarativeBase models, map relationships, and run queries using the SQLAlchemy 2.0 style API. Both sync and async engines and session factories are demonstrated, with guidance for transaction handling, connection pool settings, and eager loading strategies. There are also integration snippets for FastAPI dependency injection and pointers to migration and pooling best practices.
Should I use async or sync SQLAlchemy?
Choose async when your application is IO-bound and already uses async frameworks like FastAPI or asyncio-based workers; use sync for simpler, blocking services or compatibility with libraries that are not async.
How do I avoid N+1 queries with relationships?
Use eager loading options such as selectinload or joinedload on your select statements to fetch related collections or objects in a single query pattern.