fastcrud 0.22.3

FastCRUD is a Python package for FastAPI, offering robust async CRUD operations and flexible endpoint creation utilities.

Powerful CRUD methods and automatic endpoint creation for FastAPI.

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FastCRUD is a Python package for FastAPI, offering robust async CRUD operations and flexible endpoint creation utilities, streamlined through advanced features like auto-detected join conditions, dynamic sorting, and offset and cursor pagination.

Documentation: benavlabs.github.io/fastcrud

Discord Community: Join our Discord server

Also take a look at CRUDAdmin - Modern admin interface for FastAPI

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Features

• ⚡️ Fully Async: Leverages Python's async capabilities for non-blocking database operations.
• 📚 SQLAlchemy 2.0: Works with the latest SQLAlchemy version for robust database interactions.
• 🦾 Powerful CRUD Functionality: Full suite of efficient CRUD operations with support for joins.
• ⚙️ Dynamic Query Building: Supports building complex queries dynamically, including filtering, sorting, and pagination.
• 🤝 Advanced Join Operations: Facilitates performing SQL joins with other models with automatic join condition detection.
• 📖 Built-in Offset Pagination: Comes with ready-to-use offset pagination.
• ➤ Cursor-based Pagination: Implements efficient pagination for large datasets, ideal for infinite scrolling interfaces.
• 🤸‍♂️ Modular and Extensible: Designed for easy extension and customization to fit your requirements.
• 🛣️ Auto-generated Endpoints: Streamlines the process of adding CRUD endpoints with custom dependencies and configurations.
• 🤖 Bundled Library Skill: Ships with a Library Skill so AI coding tools (Claude Code, Cursor, Copilot, …) know how to use FastCRUD correctly — including N+1 avoidance and when to drop to raw SQLAlchemy.

Requirements

Before installing FastCRUD, ensure you have the following prerequisites:

• Python: Version 3.10 or newer.
• FastAPI: FastCRUD is built to work with FastAPI, so having FastAPI in your project is essential.
• SQLAlchemy: Version 2.0.21 or newer. FastCRUD uses SQLAlchemy for database operations.
• Pydantic: Version 2.4.1 or newer. FastCRUD leverages Pydantic models for data validation and serialization.
• SQLAlchemy-Utils: Optional, but recommended for additional SQLAlchemy utilities.

⚠️ Warning: If you are using a non-native column type (such as those from sqlalchemy-utils) in your models, you may encounter a NotImplementedError. In such cases, you need to add a python_type attribute to your column type. For more details and a discussion on this issue, see this pull request.

Installing

To install, just run:

pip install fastcrud

Or, if using UV:

uv add fastcrud

For AI Coding Agents

FastCRUD ships with a bundled Library Skill at fastcrud/.agents/skills/fastcrud/SKILL.md, following the Agent Skills standard.

To make it available to your coding agent, run library-skills from your project directory after fastcrud is installed:

# In any project that has fastcrud installed
uvx library-skills              # for Codex, Cursor, Copilot, OpenCode, etc.
uvx library-skills --claude     # for Claude Code (uses .claude/skills instead)

This symlinks the bundled skill into .agents/skills/ (or .claude/skills/ for Claude Code). Re-run after upgrading FastCRUD to pick up skill changes.

The skill teaches agents:

• The canonical setup pattern (model → schemas → crud_router)
• How to pick the right method (and avoid N+1 when fetching related data)
• The limit=None footgun and the three-tier pagination default
• When NOT to use FastCRUD — aggregates, CTEs, GROUP BY projections, bulk writes belong to raw SQLAlchemy
• Return-value semantics, the filter operator syntax (__gte, __in, __ilike, …), soft delete, joined-table inheritance gotchas

Reference deep-dives live under fastcrud/.agents/skills/fastcrud/references/ for methods, filters, joins, pagination, and endpoints.

Usage

FastCRUD offers two primary ways to use its functionalities:

1. By using crud_router for automatic endpoint creation.
2. By integrating FastCRUD directly into your FastAPI endpoints for more control.

Below are examples demonstrating both approaches:

Using crud_router for Automatic Endpoint Creation

Here's a quick example to get you started:

Define Your Model and Schema

models.py

from sqlalchemy import Column, Integer, String
from sqlalchemy.orm import DeclarativeBase

class Base(DeclarativeBase):
    pass

class Item(Base):
    __tablename__ = 'items'
    id = Column(Integer, primary_key=True)
    name = Column(String)
    description = Column(String)

schemas.py

from pydantic import BaseModel

class ItemCreateSchema(BaseModel):
    name: str
    description: str

class ItemUpdateSchema(BaseModel):
    name: str
    description: str

Set Up FastAPI and FastCRUD

main.py

from typing import AsyncGenerator

from fastapi import FastAPI
from fastcrud import FastCRUD, crud_router
from sqlalchemy.ext.asyncio import AsyncSession, create_async_engine
from sqlalchemy.orm import sessionmaker

from yourapp.models import Base, Item
from yourapp.schemas import ItemCreateSchema, ItemUpdateSchema

# Database setup (Async SQLAlchemy)
DATABASE_URL = "sqlite+aiosqlite:///./test.db"
engine = create_async_engine(DATABASE_URL, echo=True)
async_session = sessionmaker(engine, class_=AsyncSession, expire_on_commit=False)

# Database session dependency
async def get_session() -> AsyncGenerator[AsyncSession, None]:
    async with async_session() as session:
        yield session

# Create tables before the app start
async def lifespan(app: FastAPI):
    async with engine.begin() as conn:
        await conn.run_sync(Base.metadata.create_all)
    yield

# FastAPI app
app = FastAPI(lifespan=lifespan)

# CRUD router setup
item_router = crud_router(
    session=get_session,
    model=Item,
    create_schema=ItemCreateSchema,
    update_schema=ItemUpdateSchema,
    path="/items",
    tags=["Items"],
)

app.include_router(item_router)

Using FastCRUD in User-Defined FastAPI Endpoints

For more control over your endpoints, you can use FastCRUD directly within your custom FastAPI route functions. Here's an example:

main.py

from typing import AsyncGenerator

from fastapi import FastAPI, Depends, HTTPException
from sqlalchemy.ext.asyncio import AsyncSession, create_async_engine
from sqlalchemy.orm import sessionmaker
from fastcrud import FastCRUD

from models import Base, Item
from schemas import ItemCreateSchema, ItemUpdateSchema

# Database setup (Async SQLAlchemy)
DATABASE_URL = "sqlite+aiosqlite:///./test.db"
engine = create_async_engine(DATABASE_URL, echo=True)
async_session = sessionmaker(engine, class_=AsyncSession, expire_on_commit=False)

# Database session dependency
async def get_session() -> AsyncGenerator[AsyncSession, None]:
    async with async_session() as session:
        yield session

# Create tables before the app start
async def lifespan(app: FastAPI):
    async with engine.begin() as conn:
        await conn.run_sync(Base.metadata.create_all)
    yield

# FastAPI app
app = FastAPI(lifespan=lifespan)

# Instantiate FastCRUD with your model
item_crud = FastCRUD(Item)

@app.post("/custom/items/")
async def create_item(
    item_data: ItemCreateSchema, db: AsyncSession = Depends(get_session)
):
    return await item_crud.create(db, item_data)

@app.get("/custom/items/{item_id}")
async def read_item(item_id: int, db: AsyncSession = Depends(get_session)):
    item = await item_crud.get(db, id=item_id)
    if not item:
        raise HTTPException(status_code=404, detail="Item not found")
    return item

# You can add more routes for update and delete operations in a similar fashion

In this example, we define custom endpoints for creating and reading items using FastCRUD directly, providing more flexibility in how the endpoints are structured and how the responses are handled.

To read more detailed descriptions, go to the documentation.

🧠 DeepWiki Docs: deepwiki.com/benavlabs/FastAPI-boilerplate

Showcase

Browse our showcase to see projects and tutorials built with FastCRUD:

• 🚀 Applications: Web apps and services powered by FastCRUD
• 📖 Open Source: Libraries and tools built with FastCRUD
• 📝 Tutorials: Learn how to build with FastCRUD

Featured Projects

• FastAPI Boilerplate: Extendable async API using FastAPI, Pydantic V2, SQLAlchemy 2.0 and PostgreSQL
• Email Assistant API: Personalized email writing assistant using OpenAI
• SQLModel Boilerplate: Async API boilerplate using FastAPI, SQLModel and PostgreSQL

Share Your Project

Built something with FastCRUD? We'd love to feature it! Submit your project through our showcase submission process.

References

• This project was heavily inspired by CRUDBase in FastAPI Microservices by @kludex.
• Thanks @ada0l for the PyPI package name!

Similar Projects

• flask-muck - "I'd love something like this for flask" There you have it
• FastAPI CRUD Router - Supports multiple ORMs, but currently unmantained
• FastAPI Quick CRUD - Same purpose, but only for SQLAlchemy 1.4

License

MIT

Contact

Benav Labs – benav.io github.com/benavlabs

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