>
sqlalchemy
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.
#sqlalchemy#python#orm#database#async
terminal-skillsv1.0.0
Works with:claude-codeopenai-codexgemini-clicursor
Usage
$
✓ Installed sqlalchemy v1.0.0
Getting Started
- Install the skill using the command above
- Open your AI coding agent (Claude Code, Codex, Gemini CLI, or Cursor)
- Reference the skill in your prompt
- The AI will use the skill's capabilities automatically
Example Prompts
- "Analyze the sales data in revenue.csv and identify trends"
- "Create a visualization comparing Q1 vs Q2 performance metrics"
Documentation
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
Mappedtype hints (SQLAlchemy 2.0) — they provide IDE autocompletion and type safety. - Always use
selectinloadorjoinedloadfor relationships — prevents N+1 query problems. - Use
expire_on_commit=Falsefor 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.
Information
- Version
- 1.0.0
- Author
- terminal-skills
- Category
- Data & AI
- License
- Apache-2.0