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Agent Skill · 研究检索

sqlalchemy-2.0+(sqlalchemy 2 0 搜索)

sqlalchemy-2.0+ 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

sqlalchemy-2.0+ 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为权限未标注;许可证信息还不明确,暂无第三方扫描结果,按安装量在研究检索类的 73,675 个 Skill 里排第 20,563。

总安装 5,179周安装 173GitHub Stars 公开资料未说明下载 1,749核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:sqlalchemy-2.0+(sqlalchemy 2 0 搜索)
来源仓库:https://github.com/slanycukr/riot-api-project
仓库路径:skills/sqlalchemy-2.0+
安装命令:
npx skills add slanycukr/riot-api-project --skill "sqlalchemy-2.0+"
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

AgentSkills.tonpx skills
npx skills add slanycukr/riot-api-project --skill "sqlalchemy-2.0+"

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

sqlalchemy-2.0+ 用于 Python ORM 开发与数据库交互,支持现代异步查询和类型注解。它帮助 Agent 设计模型映射、编写会话管理和事务控制逻辑。

安装命令:npx skills add slanycukr/riot-api-project --skill "sqlalchemy-2.0+",需匹配数据库驱动版本。异步操作时应正确使用事件循环,避免阻塞主线程导致性能下降。迁移模型变更时应在测试环境验证外键约束和索引重建过程。

来源仓库内路径:skills/sqlalchemy-2.0+

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add slanycukr/riot-api-project --skill "sqlalchemy-2.0+";命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    权限没有明确标注,第一次使用时只给一个无关紧要的任务,观察它到底读了哪些文件和网络。

常见问题

6 条

sqlalchemy-2.0+ 怎么安装?

在终端执行 npx skills add slanycukr/riot-api-project --skill "sqlalchemy-2.0+"。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

sqlalchemy-2.0+ 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

sqlalchemy-2.0+ 需要什么权限?

权限级别没有明确标注。第一次使用时建议只给无关紧要的任务,观察它实际读写了哪些内容。

sqlalchemy-2.0+ 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

sqlalchemy-2.0+ 用的人多吗?

公开数据是累计安装 5,179 次,近一周安装 173 次,下载 1,749 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

sqlalchemy-2.0+ 安全吗?

没有查到第三方扫描结果,安全性无法从公开资料判断,安装前请自行审查源码、依赖和命令行为。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 没有第三方扫描结果,安全性只能靠自己读源码判断。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 要求有安全扫描结论才肯安装的团队。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
sqlalchemy-2.0+

sqlalchemy 2 0 搜索 · 本页

5,179—权限未标注未明确未收录

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

SQLAlchemy 2.0+ Skill

Quick Start

Basic Setup

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

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)
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
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
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
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
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
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
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
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
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)
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
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)
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
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
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

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()
# 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

pip install sqlalchemy[asyncio]  # Core SQLAlchemy
pip install asyncpg             # PostgreSQL async driver
# or
pip install aiosqlite           # SQLite async driver
# or
pip install 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:

# Generate migration
alembic revision --autogenerate -m "Add users table"

# Apply migrations
alembic upgrade head

平台分布

Codex

36.47%
按下载量换算638

Claude

31.99%
按下载量换算560

Cursor

19.53%
按下载量换算342

Gemini CLI

9.91%
按下载量换算173

安全审计

暂无安全审计结果可展示。

权限和风险

权限未标注

当前来源未能明确判断权限范围,默认进入异常复核队列。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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