Pros of FastAPI

• More comprehensive and general-purpose web framework
• Larger community and ecosystem, with more extensions and integrations
• Extensive documentation and tutorials for various use cases

Cons of FastAPI

• Requires more setup and configuration for user management features
• Less opinionated, which may lead to more decision-making for developers

Code Comparison

FastAPI (basic route):

from fastapi import FastAPI

app = FastAPI()

@app.get("/")
async def root():
    return {"message": "Hello World"}

FastAPI-Users (user registration):

from fastapi_users import FastAPIUsers

fastapi_users = FastAPIUsers(
    user_db,
    auth_backends,
    User,
    UserCreate,
    UserUpdate,
    UserDB,
)

app.include_router(
    fastapi_users.get_register_router(),
    prefix="/auth",
    tags=["auth"],
)

FastAPI-Users is a specialized extension built on top of FastAPI, focusing on user management features. It provides pre-built routes and functionality for user registration, authentication, and profile management. FastAPI, on the other hand, is a more general-purpose web framework that offers flexibility and performance for building various types of APIs.

While FastAPI requires more manual setup for user-related features, it allows for greater customization and control over the implementation. FastAPI-Users simplifies user management but may be less flexible for complex or unique user scenarios.

Pros of Pydantic

• More general-purpose data validation and settings management
• Extensive type hinting and IDE support
• Broader ecosystem and integration with many Python libraries

Cons of Pydantic

• Not specifically designed for user management in FastAPI
• Requires more custom code for user-related functionality
• Less out-of-the-box features for authentication and authorization

Code Comparison

Pydantic model example:

from pydantic import BaseModel, EmailStr

class User(BaseModel):
    id: int
    name: str
    email: EmailStr

FastAPI-Users model example:

from fastapi_users import models

class User(models.BaseUser):
    pass

FastAPI-Users provides a more opinionated and feature-rich user model out of the box, while Pydantic offers a flexible base for custom data models. FastAPI-Users is tailored for user management in FastAPI applications, including authentication and authorization features. Pydantic, on the other hand, is a general-purpose data validation library that can be used in various contexts beyond user management.

While Pydantic offers greater flexibility and wider applicability, FastAPI-Users provides a more streamlined experience for implementing user-related functionality in FastAPI projects. The choice between the two depends on the specific requirements of your project and the level of customization needed for user management.

Pros of Starlette

• Lightweight and flexible ASGI framework, providing a solid foundation for building web applications
• Excellent performance and low overhead, suitable for high-performance applications
• Extensive middleware support and WebSocket handling capabilities

Cons of Starlette

• Lacks built-in user authentication and management features
• Requires more manual setup and configuration for user-related functionality
• Less opinionated, which may lead to more boilerplate code for common tasks

Code Comparison

Starlette:

from starlette.applications import Starlette
from starlette.responses import JSONResponse
from starlette.routing import Route

async def homepage(request):
    return JSONResponse({"message": "Hello, World!"})

app = Starlette(routes=[Route("/", homepage)])

FastAPI-Users:

from fastapi import FastAPI
from fastapi_users import FastAPIUsers, models
from fastapi_users.authentication import JWTAuthentication

app = FastAPI()
fastapi_users = FastAPIUsers(
    user_model=models.BaseUser,
    auth_backends=[JWTAuthentication(secret="SECRET", lifetime_seconds=3600)],
)

app.include_router(fastapi_users.get_auth_router(), prefix="/auth/jwt", tags=["auth"])

While Starlette provides a lightweight foundation for building web applications, FastAPI-Users offers a more comprehensive solution for user management and authentication out of the box. Starlette requires more manual setup for user-related features, whereas FastAPI-Users provides pre-built components for common user management tasks.

Pros of SQLAlchemy

• More comprehensive and flexible ORM with support for multiple databases
• Mature project with extensive documentation and community support
• Powerful query construction and optimization capabilities

Cons of SQLAlchemy

• Steeper learning curve due to its extensive feature set
• Can be overkill for simple projects or those focused on FastAPI integration
• Requires more boilerplate code for basic operations

Code Comparison

SQLAlchemy:

from sqlalchemy import create_engine, Column, Integer, String
from sqlalchemy.ext.declarative import declarative_base

Base = declarative_base()

class User(Base):
    __tablename__ = 'users'
    id = Column(Integer, primary_key=True)
    name = Column(String)

FastAPI Users:

from fastapi_users.db import SQLAlchemyBaseUserTable
from sqlalchemy import Column, Integer, String

class User(SQLAlchemyBaseUserTable):
    name = Column(String)

SQLAlchemy provides a more flexible and powerful ORM solution, suitable for complex database operations across various database systems. It offers advanced querying capabilities and extensive customization options. However, it comes with a steeper learning curve and may require more setup code.

FastAPI Users, on the other hand, is specifically designed for FastAPI integration and provides a more streamlined approach to user management. It offers out-of-the-box authentication and authorization features, making it easier to implement user-related functionality in FastAPI applications. However, it may be less flexible for complex database operations outside of user management.

Pros of Kratos

• More comprehensive identity and user management system
• Language-agnostic, can be integrated with various tech stacks
• Supports advanced features like multi-factor authentication and account recovery

Cons of Kratos

• Steeper learning curve and more complex setup
• Requires additional infrastructure (separate service)
• May be overkill for smaller projects or simpler authentication needs

Code Comparison

FastAPI-Users:

from fastapi_users import FastAPIUsers

fastapi_users = FastAPIUsers(
    user_db,
    auth_backends,
    User,
    UserCreate,
    UserUpdate,
    UserDB,
)

app.include_router(
    fastapi_users.get_auth_router(auth_backends[0]),
    prefix="/auth/jwt",
    tags=["auth"],
)

Kratos:

version: v0.7.1-alpha.1

dsn: memory

serve:
  public:
    base_url: http://127.0.0.1:4433/
    cors:
      enabled: true
  admin:
    base_url: http://kratos:4434/

selfservice:
  strategies:
    password:
      enabled: true

FastAPI-Users is more tightly integrated with FastAPI and provides a simpler setup for basic authentication scenarios. Kratos offers a more robust and scalable solution but requires additional configuration and infrastructure. The choice between them depends on project requirements, scalability needs, and desired features.