sqlalchemy
$
npx mdskill add TerminalSkills/skills/sqlalchemyUse SQLAlchemy to manage Python database interactions with async support
- Solve tasks like ORM setup, model definition, and async database queries
- Relies on SQLAlchemy 2.0, Alembic, and async drivers like asyncpg
- Analyzes user needs to recommend SQLAlchemy over Django ORM or other tools
- Returns Python code examples and configuration for database operations
SKILL.md
.github/skills/sqlalchemyView on GitHub ↗
---
name: sqlalchemy
description: >-
Work with databases in Python using SQLAlchemy. Use when a user asks to
set up a Python ORM, define database models, write async database queries,
manage migrations with Alembic, or choose between SQLAlchemy and Django ORM.
license: Apache-2.0
compatibility: 'Python 3.10+, PostgreSQL, MySQL, SQLite'
metadata:
author: terminal-skills
version: 1.0.0
category: data-ai
tags:
- sqlalchemy
- python
- orm
- database
- async
---
# SQLAlchemy
## Overview
SQLAlchemy is the standard Python ORM and SQL toolkit. Version 2.0 introduces a modern, type-friendly API with async support. Define models as Python classes, write queries with the builder pattern, and manage schema changes with Alembic migrations.
## Instructions
### Step 1: Async Setup
```python
# db.py — Async SQLAlchemy configuration
from sqlalchemy.ext.asyncio import create_async_engine, async_sessionmaker, AsyncSession
from sqlalchemy.orm import DeclarativeBase, Mapped, mapped_column, relationship
from sqlalchemy import String, ForeignKey, DateTime, func
from datetime import datetime
DATABASE_URL = "postgresql+asyncpg://user:pass@localhost:5432/myapp"
engine = create_async_engine(DATABASE_URL, echo=False, pool_size=20)
async_session_maker = async_sessionmaker(engine, expire_on_commit=False)
class Base(DeclarativeBase):
pass
```
### Step 2: Define Models
```python
# models.py — SQLAlchemy 2.0 models with type hints
from db import Base
from sqlalchemy import String, ForeignKey, DateTime, Integer, Text, Boolean, func
from sqlalchemy.orm import Mapped, mapped_column, relationship
from datetime import datetime
class User(Base):
__tablename__ = "users"
id: Mapped[str] = mapped_column(String(36), primary_key=True)
name: Mapped[str] = mapped_column(String(100))
email: Mapped[str] = mapped_column(String(255), unique=True, index=True)
role: Mapped[str] = mapped_column(String(20), default="member")
created_at: Mapped[datetime] = mapped_column(DateTime, server_default=func.now())
# Relationships
projects: Mapped[list["Project"]] = relationship(back_populates="owner", cascade="all, delete")
def __repr__(self) -> str:
return f"<User {self.email}>"
class Project(Base):
__tablename__ = "projects"
id: Mapped[str] = mapped_column(String(36), primary_key=True)
name: Mapped[str] = mapped_column(String(100))
description: Mapped[str | None] = mapped_column(Text)
status: Mapped[str] = mapped_column(String(20), default="active")
owner_id: Mapped[str] = mapped_column(ForeignKey("users.id"))
task_count: Mapped[int] = mapped_column(Integer, default=0)
created_at: Mapped[datetime] = mapped_column(DateTime, server_default=func.now())
owner: Mapped["User"] = relationship(back_populates="projects")
tasks: Mapped[list["Task"]] = relationship(back_populates="project", cascade="all, delete")
class Task(Base):
__tablename__ = "tasks"
id: Mapped[str] = mapped_column(String(36), primary_key=True)
title: Mapped[str] = mapped_column(String(200))
status: Mapped[str] = mapped_column(String(20), default="todo")
project_id: Mapped[str] = mapped_column(ForeignKey("projects.id"))
assignee_id: Mapped[str | None] = mapped_column(ForeignKey("users.id"))
project: Mapped["Project"] = relationship(back_populates="tasks")
```
### Step 3: Queries
```python
# queries.py — Async query examples
from sqlalchemy import select, func, and_
from sqlalchemy.orm import selectinload
async def get_user_projects(db: AsyncSession, user_id: str):
"""Fetch user's projects with task counts."""
result = await db.execute(
select(Project)
.where(Project.owner_id == user_id, Project.status == "active")
.options(selectinload(Project.tasks)) # eager load to avoid N+1
.order_by(Project.created_at.desc())
)
return result.scalars().all()
async def get_project_stats(db: AsyncSession, project_id: str):
"""Aggregate task statistics for a project."""
result = await db.execute(
select(
Task.status,
func.count(Task.id).label("count"),
)
.where(Task.project_id == project_id)
.group_by(Task.status)
)
return {row.status: row.count for row in result.all()}
async def search_tasks(db: AsyncSession, query: str, project_id: str):
"""Full-text search in task titles."""
result = await db.execute(
select(Task)
.where(
and_(
Task.project_id == project_id,
Task.title.ilike(f"%{query}%"),
)
)
.limit(20)
)
return result.scalars().all()
```
### Step 4: Alembic Migrations
```bash
# Initialize Alembic
pip install alembic
alembic init alembic
# Generate migration from model changes
alembic revision --autogenerate -m "add tasks table"
# Apply migrations
alembic upgrade head
# Rollback one step
alembic downgrade -1
```
## Guidelines
- Use `Mapped` type hints (SQLAlchemy 2.0) — they provide IDE autocompletion and type safety.
- Always use `selectinload` or `joinedload` for relationships — prevents N+1 query problems.
- Use `expire_on_commit=False` for async sessions — prevents lazy loading exceptions.
- Alembic autogenerate detects most schema changes, but review migrations before applying.
- For simple projects, consider SQLModel (FastAPI creator's library) — simpler API, same engine.
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