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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
Source

Usage

$
✓ Installed sqlalchemy v1.0.0

Getting Started

  1. Install the skill using the command above
  2. Open your AI coding agent (Claude Code, Codex, Gemini CLI, or Cursor)
  3. Reference the skill in your prompt
  4. 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 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.

Information

Version
1.0.0
Author
terminal-skills
Category
Data & AI
License
Apache-2.0