sqlalchemy-2-0

Modern async ORM with type-safe models and efficient queries

242 stars

Best use case

sqlalchemy-2-0 is best used when you need a repeatable AI agent workflow instead of a one-off prompt. It is especially useful for teams working in multi. Modern async ORM with type-safe models and efficient queries

Modern async ORM with type-safe models and efficient queries

Users should expect a more consistent workflow output, faster repeated execution, and less time spent rewriting prompts from scratch.

Practical example

Example input

Use the "sqlalchemy-2-0" skill to help with this workflow task. Context: Modern async ORM with type-safe models and efficient queries

Example output

A structured workflow result with clearer steps, more consistent formatting, and an output that is easier to reuse in the next run.

When to use this skill

  • Use this skill when you want a reusable workflow rather than writing the same prompt again and again.

When not to use this skill

  • Do not use this when you only need a one-off answer and do not need a reusable workflow.
  • Do not use it if you cannot install or maintain the related files, repository context, or supporting tools.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/sqlalchemy-2-0/SKILL.md --create-dirs "https://raw.githubusercontent.com/aiskillstore/marketplace/main/skills/bossjones/sqlalchemy-2-0/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/sqlalchemy-2-0/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How sqlalchemy-2-0 Compares

Feature / Agentsqlalchemy-2-0Standard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Modern async ORM with type-safe models and efficient queries

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

# SQLAlchemy 2.0+ Skill

## Quick Start

### Basic Setup

```python
from sqlalchemy.ext.asyncio import AsyncAttrs, async_sessionmaker, create_async_engine, AsyncSession
from sqlalchemy.orm import DeclarativeBase, Mapped, mapped_column
import asyncio

# Base class for models
class Base(AsyncAttrs, DeclarativeBase):
    pass

# Async engine
engine = create_async_engine("postgresql+asyncpg://user:pass@localhost/db")

# Session factory
async_session = async_sessionmaker(engine, expire_on_commit=False)

# Example model
class User(Base):
    __tablename__ = "users"

    id: Mapped[int] = mapped_column(primary_key=True)
    name: Mapped[str] = mapped_column(String(50))
    email: Mapped[str] = mapped_column(String(100))
```

### Basic CRUD Operations

```python
async def create_user(name: str, email: str) -> User:
    async with async_session() as session:
        async with session.begin():
            user = User(name=name, email=email)
            session.add(user)
            await session.flush()  # Get the ID
            return user

async def get_user(user_id: int) -> User | None:
    async with async_session() as session:
        result = await session.execute(select(User).where(User.id == user_id))
        return result.scalar_one_or_none()

async def update_user_email(user_id: int, new_email: str) -> bool:
    async with async_session() as session:
        result = await session.execute(
            update(User).where(User.id == user_id).values(email=new_email)
        )
        await session.commit()
        return result.rowcount > 0
```

## Common Patterns

### Models

#### Annotated Type-Safe Models (Recommended)

```python
from typing_extensions import Annotated
from typing import List, Optional

# Reusable column types
intpk = Annotated[int, mapped_column(primary_key=True)]
str50 = Annotated[str, mapped_column(String(50))]
created_at = Annotated[datetime, mapped_column(insert_default=func.now())]

class Post(Base):
    __tablename__ = "posts"

    id: Mapped[intpk]
    title: Mapped[str50]
    content: Mapped[str] = mapped_column(Text)
    author_id: Mapped[int] = mapped_column(ForeignKey("users.id"))
    created: Mapped[created_at]

    # Relationships
    author: Mapped["User"] = relationship(back_populates="posts")
    tags: Mapped[List["Tag"]] = relationship(secondary="post_tags")
```

#### Classic Style Models

```python
class Post(Base):
    __tablename__ = "posts"

    id = mapped_column(Integer, primary_key=True)
    title = mapped_column(String(50))
    content = mapped_column(Text)
    author_id = mapped_column(ForeignKey("users.id"))

    author = relationship("User", back_populates="posts")
```

### Relationships

#### One-to-Many

```python
class User(Base):
    __tablename__ = "users"

    id: Mapped[int] = mapped_column(primary_key=True)
    posts: Mapped[List["Post"]] = relationship(
        back_populates="author",
        cascade="all, delete-orphan"
    )

class Post(Base):
    __tablename__ = "posts"

    id: Mapped[int] = mapped_column(primary_key=True)
    author_id: Mapped[int] = mapped_column(ForeignKey("users.id"))
    author: Mapped["User"] = relationship(back_populates="posts")
```

#### Many-to-Many

```python
association_table = Table(
    "post_tags",
    Base.metadata,
    Column("post_id", ForeignKey("posts.id"), primary_key=True),
    Column("tag_id", ForeignKey("tags.id"), primary_key=True)
)

class Post(Base):
    __tablename__ = "posts"

    id: Mapped[int] = mapped_column(primary_key=True)
    tags: Mapped[List["Tag"]] = relationship(
        secondary=association_table,
        back_populates="posts"
    )

class Tag(Base):
    __tablename__ = "tags"

    id: Mapped[int] = mapped_column(primary_key=True)
    name: Mapped[str] = mapped_column(String(50), unique=True)
    posts: Mapped[List["Post"]] = relationship(
        secondary=association_table,
        back_populates="tags"
    )
```

### Queries

#### Basic Select

```python
from sqlalchemy import select, and_, or_

# Get all users
async def get_all_users():
    async with async_session() as session:
        result = await session.execute(select(User))
        return result.scalars().all()

# Filter with conditions
async def get_users_by_name(name: str):
    async with async_session() as session:
        stmt = select(User).where(User.name.ilike(f"%{name}%"))
        result = await session.execute(stmt)
        return result.scalars().all()

# Complex conditions
async def search_users(name: str = None, email: str = None):
    async with async_session() as session:
        conditions = []
        if name:
            conditions.append(User.name.ilike(f"%{name}%"))
        if email:
            conditions.append(User.email.ilike(f"%{email}%"))

        if conditions:
            stmt = select(User).where(and_(*conditions))
        else:
            stmt = select(User)

        result = await session.execute(stmt)
        return result.scalars().all()
```

#### Relationship Loading

```python
from sqlalchemy.orm import selectinload, joinedload

# Eager load relationships
async def get_posts_with_author():
    async with async_session() as session:
        stmt = select(Post).options(selectinload(Post.author))
        result = await session.execute(stmt)
        return result.scalars().all()

# Joined loading for single relationships
async def get_post_with_tags(post_id: int):
    async with async_session() as session:
        stmt = select(Post).options(
            joinedload(Post.author),
            selectinload(Post.tags)
        ).where(Post.id == post_id)
        result = await session.execute(stmt)
        return result.scalar_one_or_none()
```

#### Pagination

```python
async def get_posts_paginated(page: int, size: int):
    async with async_session() as session:
        offset = (page - 1) * size
        stmt = select(Post).offset(offset).limit(size).order_by(Post.created.desc())
        result = await session.execute(stmt)
        return result.scalars().all()
```

#### Aggregations

```python
from sqlalchemy import func

async def get_user_post_count():
    async with async_session() as session:
        stmt = (
            select(User.name, func.count(Post.id).label("post_count"))
            .join(Post)
            .group_by(User.id, User.name)
            .order_by(func.count(Post.id).desc())
        )
        result = await session.execute(stmt)
        return result.all()
```

### Sessions Management

#### Context Manager Pattern

```python
async def create_post(title: str, content: str, author_id: int):
    async with async_session() as session:
        async with session.begin():
            post = Post(title=title, content=content, author_id=author_id)
            session.add(post)
            return post
```

#### Dependency Injection (FastAPI)

```python
from fastapi import Depends

async def get_db_session():
    async with async_session() as session:
        try:
            yield session
        finally:
            await session.close()

async def create_user_endpoint(
    user_data: UserCreate,
    session: AsyncSession = Depends(get_db_session)
):
    user = User(**user_data.dict())
    session.add(user)
    await session.commit()
    await session.refresh(user)
    return user
```

#### Scoped Sessions

```python
from sqlalchemy.ext.asyncio import async_scoped_session
import asyncio

# Create scoped session
async_session_scope = async_scoped_session(
    async_sessionmaker(engine, expire_on_commit=False),
    scopefunc=asyncio.current_task
)

# Use in application
async def some_function():
    session = async_session_scope()
    # Use session normally
    await session.commit()
```

### Advanced Patterns

#### Write-Only Relationships (Memory Efficient)

```python
from sqlalchemy.orm import WriteOnlyMapped

class User(Base):
    __tablename__ = "users"

    id: Mapped[int] = mapped_column(primary_key=True)
    posts: WriteOnlyMapped["Post"] = relationship()

async def get_user_posts(user_id: int):
    async with async_session() as session:
        user = await session.get(User, user_id)
        if user:
            # Explicit select for collection
            stmt = select(Post).where(Post.author_id == user_id)
            result = await session.execute(stmt)
            return result.scalars().all()
        return []
```

#### Custom Session Classes

```python
class AsyncSessionWithDefaults(AsyncSession):
    async def execute_with_defaults(self, statement, **kwargs):
        # Add default options
        return await self.execute(statement, **kwargs)

# Use custom session
async_session = async_sessionmaker(
    engine,
    class_=AsyncSessionWithDefaults,
    expire_on_commit=False
)
```

#### Connection Routing

```python
class RoutingSession(Session):
    def get_bind(self, mapper=None, clause=None, **kw):
        if mapper and issubclass(mapper.class_, ReadOnlyModel):
            return read_engine
        return write_engine

class AsyncRoutingSession(AsyncSession):
    sync_session_class = RoutingSession
```

### Raw SQL

```python
from sqlalchemy import text

async def run_raw_sql():
    async with async_session() as session:
        result = await session.execute(text("SELECT COUNT(*) FROM users"))
        count = result.scalar()
        return count

async def run_parameterized_query(user_id: int):
    async with async_session() as session:
        stmt = text("SELECT * FROM posts WHERE author_id = :user_id")
        result = await session.execute(stmt, {"user_id": user_id})
        return result.fetchall()
```

## Performance Tips

1. **Use selectinload for collections**: More efficient than lazy loading
2. **Batch operations**: Use `add_all()` for bulk inserts
3. **Connection pooling**: Configure pool size based on load
4. **Index columns**: Add indexes for frequently queried columns
5. **Use streaming**: For large result sets, use `stream()`

```python
# Streaming large results
async def process_all_users():
    async with async_session() as session:
        result = await session.stream(select(User))
        async for user in result.scalars():
            # Process user without loading all into memory
            await process_user(user)
```

## Requirements

```bash
uv add sqlalchemy[asyncio]  # Core SQLAlchemy
uv add asyncpg             # PostgreSQL async driver
# or
uv add aiosqlite           # SQLite async driver
# or
uv add aiomysql            # MySQL async driver
```

## Database URLs

- **PostgreSQL**: `postgresql+asyncpg://user:pass@localhost/db`
- **SQLite**: `sqlite+aiosqlite:///database.db`
- **MySQL**: `mysql+aiomysql://user:pass@localhost/db`

## Migration Integration

Use Alembic for database migrations:

```python
# Generate migration
uv run alembic revision --autogenerate -m "Add users table"

# Apply migrations
uv run alembic upgrade head
```

Related Skills

azure-quotas

242
from aiskillstore/marketplace

Check/manage Azure quotas and usage across providers. For deployment planning, capacity validation, region selection. WHEN: "check quotas", "service limits", "current usage", "request quota increase", "quota exceeded", "validate capacity", "regional availability", "provisioning limits", "vCPU limit", "how many vCPUs available in my subscription".

DevOps & Infrastructure

raindrop-io

242
from aiskillstore/marketplace

Manage Raindrop.io bookmarks with AI assistance. Save and organize bookmarks, search your collection, manage reading lists, and organize research materials. Use when working with bookmarks, web research, reading lists, or when user mentions Raindrop.io.

Data & Research

zlibrary-to-notebooklm

242
from aiskillstore/marketplace

自动从 Z-Library 下载书籍并上传到 Google NotebookLM。支持 PDF/EPUB 格式,自动转换,一键创建知识库。

discover-skills

242
from aiskillstore/marketplace

当你发现当前可用的技能都不够合适(或用户明确要求你寻找技能)时使用。本技能会基于任务目标和约束,给出一份精简的候选技能清单,帮助你选出最适配当前任务的技能。

web-performance-seo

242
from aiskillstore/marketplace

Fix PageSpeed Insights/Lighthouse accessibility "!" errors caused by contrast audit failures (CSS filters, OKLCH/OKLAB, low opacity, gradient text, image backgrounds). Use for accessibility-driven SEO/performance debugging and remediation.

project-to-obsidian

242
from aiskillstore/marketplace

将代码项目转换为 Obsidian 知识库。当用户提到 obsidian、项目文档、知识库、分析项目、转换项目 时激活。 【激活后必须执行】: 1. 先完整阅读本 SKILL.md 文件 2. 理解 AI 写入规则(默认到 00_Inbox/AI/、追加式、统一 Schema) 3. 执行 STEP 0: 使用 AskUserQuestion 询问用户确认 4. 用户确认后才开始 STEP 1 项目扫描 5. 严格按 STEP 0 → 1 → 2 → 3 → 4 顺序执行 【禁止行为】: - 禁止不读 SKILL.md 就开始分析项目 - 禁止跳过 STEP 0 用户确认 - 禁止直接在 30_Resources 创建(先到 00_Inbox/AI/) - 禁止自作主张决定输出位置

obsidian-helper

242
from aiskillstore/marketplace

Obsidian 智能笔记助手。当用户提到 obsidian、日记、笔记、知识库、capture、review 时激活。 【激活后必须执行】: 1. 先完整阅读本 SKILL.md 文件 2. 理解 AI 写入三条硬规矩(00_Inbox/AI/、追加式、白名单字段) 3. 按 STEP 0 → STEP 1 → ... 顺序执行 4. 不要跳过任何步骤,不要自作主张 【禁止行为】: - 禁止不读 SKILL.md 就开始工作 - 禁止跳过用户确认步骤 - 禁止在非 00_Inbox/AI/ 位置创建新笔记(除非用户明确指定)

internationalizing-websites

242
from aiskillstore/marketplace

Adds multi-language support to Next.js websites with proper SEO configuration including hreflang tags, localized sitemaps, and language-specific content. Use when adding new languages, setting up i18n, optimizing for international SEO, or when user mentions localization, translation, multi-language, or specific languages like Japanese, Korean, Chinese.

google-official-seo-guide

242
from aiskillstore/marketplace

Official Google SEO guide covering search optimization, best practices, Search Console, crawling, indexing, and improving website search visibility based on official Google documentation

github-release-assistant

242
from aiskillstore/marketplace

Generate bilingual GitHub release documentation (README.md + README.zh.md) from repo metadata and user input, and guide release prep with git add/commit/push. Use when the user asks to write or polish README files, create bilingual docs, prepare a GitHub release, or mentions release assistant/README generation.

doc-sync-tool

242
from aiskillstore/marketplace

自动同步项目中的 Agents.md、claude.md 和 gemini.md 文件,保持内容一致性。支持自动监听和手动触发。

deploying-to-production

242
from aiskillstore/marketplace

Automate creating a GitHub repository and deploying a web project to Vercel. Use when the user asks to deploy a website/app to production, publish a project, or set up GitHub + Vercel deployment.