A scalable and production ready boilerplate for FastAPI
- Project Overview
- Features
- Installation Guide
- Usage Guide
- Advanced Usage
- Contributing
- License
- Acknowledgements
This boilerplate follows a layered architecture that includes a model layer, a repository layer, a controller layer, and an API layer. Its directory structure is designed to isolate boilerplate code within the core directory, which requires minimal attention, thereby facilitating quick and easy feature development. The directory structure is also generally very predictable. The project's primary objective is to offer a production-ready boilerplate with a better developer experience and readily available features. It also has some widely used features like authentication, authorization, database migrations, type checking, etc which are discussed in detail in the Features section.
- Python 3.11+ support
- SQLAlchemy 2.0+ support
- Asynchoronous capabilities
- Database migrations using Alembic
- Basic Authentication using JWT
- Row Level Access Control for permissions
- Redis for caching
- Celery for background tasks
- Testing suite
- Type checking using mypy
- Dockerized database and redis
- Readily available CRUD operations
- Linting using pylint
- Formatting using black
You need following to run this project:
- Python 3.11
- Docker with Docker Compose
- Poetry
I use asdf to manage my python versions. You can use it too. However, it is only supported on Linux and macOS. For Windows, you can use something like pyenv.
Once you have installed the above and have cloned the repository, you can follow the following steps to get the project up and running:
- Create a virtual environment using poetry:
poetry shell- Install the dependencies:
poetry install- Run the database and redis containers:
docker-compose up -d-
Copy the
.env.examplefile to.envand update the values as per your needs. -
Run the migrations:
make migrate- Run the server:
make runThe server should now be running on http://localhost:8000 and the API documentation should be available at http://localhost:8000/docs.
The project is designed to be modular and scalable. There are 3 main directories in the project:
-
core: This directory contains the central part of this project. It contains most of the boiler plate code like security dependencies, database connections, configuration, middlewares etc. It also contains the base classes for the models, repositories, and controllers. Thecoredirectory is designed to be as minimal as possible and usually requires minimal attention. Overall, thecoredirectory is designed to be as generic as possible and can be used in any project. While building additional feature you may not need to modify this directory at all except for adding more controllers to theFactoryclass incore/factory.py. -
app: This directory contains the actual application code. It contains the models, repositories, controllers, and schemas for the application. This is the directory you will be spending most of your time in while building features. The directory has following sub-directories:modelsHere is where you add new tablesrepositoriesFor each model, you need to create a repository. This is where you add the CRUD operations for the model.controllersFor each logical unit of the application, you need to create a controller. This is where you add the business logic for the application.schemasThis is where you add the schemas for the application. The schemas are used for validation and serialization/deserialization of the data.
-
api: This directory contains the API layer of the application. It contains the API router, it is where you add the API endpoints.
The boilerplate contains a lot of features some of which are used in the application and some of which are not. The following sections describe the features in detail.
The migrations are handled by Alembic. The migrations are stored in the migrations directory. To create a new migration, you can run the following command:
make generate-migrationIt will ask you for a message for the migration. Once you enter the message, it will create a new migration file in the migrations directory. You can then run the migrations using the following command:
make migrateIf you need to downgrade the database or reset it. You can use make rollback and make reset-database respectively.
The authentication used is basic implementation of JWT with bearer token. When the bearer token is supplied in the Authorization header, the token is verified and the user is automatically authenticated by setting request.user.id using middleware. To use the user model in any endpoint you can use the get_current_user dependency. If for any endpoint you want to enforce authentication, you can use the AuthenticationRequired dependency. It will raise a HTTPException if the user is not authenticated.
The boilerplate contains a custom row level permissions management module. It is inspired by fastapi-permissions. It is located in core/security/access_control.py. You can use this to enforce different permissions for different models. The module operates based on Principals and permissions. Every user has their own set of principals which need to be set using a function. Check core/fastapi/dependencies/permissions.py for an example. The principals are then used to check the permissions for the user. The permissions need to be defined at the model level. Check app/models/user.py for an example. Then you can use the dependency directly in the route to raise a HTTPException if the user does not have the required permissions. Below is an incomplete example:
from fastapi import APIRouter, Depends
from core.security.access_control import AccessControl, UserPrincipal, RolePrincipal, Allow
from core.database import Base
class User(Base):
__tablename__ = "users"
id = Column(Integer, primary_key=True)
name = Column(String)
email = Column(String, unique=True)
password = Column(String)
role = Column(String)
def __acl__(self):
return [
(Allow, UserPrincipal(self.id), "view"),
(Allow, RolePrincipal("admin"), "delete"),
]
def get_user_principals(user: User = Depends(get_current_user)):
return [UserPrincipal(user.id)]
Permission = AccessControl(get_user_principals)
router = APIRouter()
@router.get("/users/{user_id}")
def get_user(user_id: int, user: User = get_user(user_id), assert_access = Permission("view")):
assert_access(user)
return userYou can directly use the Cache.cached decorator from core.cache. Example
from core.cache import Cache
@Cache.cached(prefix="user", ttl=60)
def get_user(user_id: int):
...The celery worker is already configured for the app. You can add your tasks in worker/ to run the celery worker, you can run the following command:
make celery-workerThe sessions are already handled by the middleware and get_session dependency which injected into the repositories through fastapi dependency injection inside the Factory class in core/factory.py. There is also Transactional decorator which can be used to wrap the functions which need to be executed in a transaction. Example:
@Transactional()
async def some_mutating_function():
...Note: The decorator already handles the commit and rollback of the transaction. You do not need to do it manually.
If for any case you need an isolated sessions you can use standalone_session decorator from core.database. Example:
@standalone_session
async def do_something():
...The boilerplate uses the repository pattern. Every model has a repository and all of them inherit base repository from core/repository. The repositories are located in app/repositories. The repositories are injected into the controllers inside the Factory class in core/factory/factory.py.py.
The base repository has the basic crud operations. All customer operations can be added to the specific repository. Example:
from core.repository import BaseRepository
from app.models.user import User
from sqlalchemy.sql.expression import select
class UserRepository(BaseRepository[User]):
async def get_by_email(self, email: str):
return await select(User).filter(User.email == email).gino.first()To facilitate easier access to queries with complex joins, the BaseRepository class has a _query function (along with other handy functions like _all() and _one_or_none()) which can be used to write compplex queries very easily. Example:
async def get_user_by_email_join_tasks(email: str):
query = await self._query(join_)
query = query.filter(User.email == email)
return await self._one_or_none(query)Note: For every join you want to make you need to create a function in the same repository with pattern _join_{name}. Example: _join_tasks for tasks. Example:
async def _join_tasks(self, query: Select) -> Select:
return query.options(joinedload(User.tasks))Kind of to repositories, every logical unit of the application has a controller. The controller also has a primary repository which is injected into it. The controllers are located in app/controllers.
These controllers contain all the business logic of the application. Check app/controllers/auth.py for an example.
The schemas are located in app/schemas. The schemas are used to validate the request body and response body. The schemas are also used to generate the OpenAPI documentation. The schemas are inherited from BaseModel from pydantic. The schemas are primarily isolated into requests and responses which are pretty self explainatory.
You can use make format to format the code using black and isort.
You can use make lint to lint the code using pylint.
The project contains tests for all endpoints, some of the logical components like JWTHander and AccessControl and an example of testing complex inner components like BaseRepository. The tests are located in tests/. You can run the tests using make test.
Contributions are higly welcome. Please open an issue or a PR if you want to contribute.
This project is licensed under the terms of the MIT license. See the LICENSE file.
- This project uses several components from teamhide/fastapi-boilerplate
- The row level access control is inspired by fastapi-permissions
- CRUD pattern is inspired by full-stack-fastapi-postgresql
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