FastAPI: Simple application structure from scratch

In this blog post, we will set up a simple FastAPI application from scratch. This can serve as a good starting point for small to medium projects.

Series Content 📖

• Part 1: Laying the foundation (this post)
• Part 2: Migrations
• Part 3: Dockerize

What will we cover in this post? 📝

• Generate a base project with Poetry.
• Install FastAPI, SQLAlchemy and other dependencies.
• Create the necessary files that will serve as the base of the application

Before getting started... ⚠️

I am going to make the following assumptions:

• that you have a basic understanding of Python and Python types;
• that you already have the below installed:
  • Python 3.6+ (I am using Python 3.8)
  • PostgreSQL; and
  • Poetry

Without further ado, let's get started 🙂

Create a base project with Poetry 🏃

Open up a terminal and enter the below command.

poetry new app

After running the above command a new directory called app has been created. Let's go ahead and cd into that directory now.

cd app

The directory structure should look like the below.

.
├── app
│   └── __init__.py
├── pyproject.toml
├── README.rst
└── tests
    ├── __init__.py
    └── test_app.py

Let's quickly go over what we have here.

The app directory is our main python package.

A directory with a __init__.py file in it is considered a package in Python. Any .py files we add to this directory will be considered modules of this package. Usually, this file is empty but in this case, Poetry has gone ahead and added __version__ = '0.1.0'.

The pyproject.toml file is where all our dependencies will be added to. Later on, when we start installing our dependencies you will notice a poetry.lock file will be created, more on that later.

The README file can be used to add details about the project or any useful instructions that will help other developers working on the project. Personally, I prefer writing documentation in Markdown over reStructuredText so I will go ahead and rename README.rst to README.md. Feel free to do the same or leave it as is.

mv README.rst README.md

Finally, we have our tests directory that contains all the unit tests.

Install FastAPI and other dependencies 📦

In this section, we will install only the required dependencies to get a basic CRUD ( Create, Read, Update, Delete) application going.

What we will be installing?

• FastAPI - this goes without saying 🙂
• SQLAlchemy Object Relational Mapper (ORM)
• psycopg2-binary PostgreSQL database adapter
• Uvicorn a lightning-fast ASGI server

poetry add fastapi sqlalchemy psycopg2-binary uvicorn

We will also install the following development dependencies, mainly to maintain code quality and for testing.

• pytest testing framework
• Mypy static type checker for Python
• sqlalchemy-stubs Mypy plug-in and type stubs for SQLAlchemy
• Flake8 for code linting
• autoflake removes unused imports and unused variables
• isort sort import statements
• black Python code formatter

poetry add -D mypy sqlalchemy-stubs flake8 autoflake isort black 

Note: We have not included pytest in the above command as it is usually installed by default when using Poetry to create a new project.

At this point, nothing has really changed in our directory structure but you will notice that the pyproject.toml file has been updated and a new poetry.lock file has been created. The poetry.lock file locks the installed dependencies to a specific version. This is in particular helpful when multiple developers are working on the same project, to ensure everyone is using the same versions of each package.

To recap our directory structure should look something like this now.

.
├── app
│   └── __init__.py
├── poetry.lock
├── pyproject.toml
├── README.md
└── tests
    ├── __init__.py
    └── test_app.py

Add project files 📄

In this section, we will start adding the files that will make up the base of our application.

The first file we will create is the main.py file, it will serve as the entry point to our application and house all our routes. Let's create this file now under the app package directory.

main.py

app/main.py

from fastapi import FastAPI

app = FastAPI()


@app.get("/")
def index():
    return {"message": "Hello world!"}

At this point, we actually have a basic application that we can run. If we switch back to our terminal and run the following commands.

poetry shell
uvicorn app.main:app

Tip: If you want the server to reload on file changes you can use the --reload flag, like so uvicorn app.main:app --reload

Now if we head over to a browser and hit http://127.0.0.1:8000 we will be greeted with {"message":"Hello world!"}. FastAPI also gives us API documentation out of the box so if you now navigate to http://127.0.0.1:8000/docs you will now see the Swagger UI. Pretty awesome, right! 🤘

We will come back later and update the main.py file but for now, let's hit Ctrl+C in the terminal to stop Uvicorn and continue adding the rest of our files.

Next, let's create the db.py under the same directory. This file will contain our database session and a base class that all models will extend from.

db.py

app/db.py

from typing import Any

from sqlalchemy import create_engine
from sqlalchemy.ext.declarative import as_declarative
from sqlalchemy.orm import sessionmaker

from .config import settings

engine = create_engine(settings.SQLALCHEMY_DATABASE_URI, pool_pre_ping=True)
SessionLocal = sessionmaker(autocommit=False, autoflush=False, bind=engine)


@as_declarative()
class Base:
    id: Any

Info: You can read more about the sessionmaker function here and as_declarative decorator here.

You may have noticed we import settings from config but we haven't actually created that file yet, so let's do so now.

config.py

app/config.py

from typing import Any, Dict, Optional

from pydantic import BaseSettings, PostgresDsn, validator


class Settings(BaseSettings):
    POSTGRES_SERVER: str
    POSTGRES_USER: str
    POSTGRES_PASSWORD: str
    POSTGRES_DB: str

    SQLALCHEMY_DATABASE_URI: Optional[PostgresDsn] = None

    @validator("SQLALCHEMY_DATABASE_URI", pre=True)
    def assemble_db_connection(cls, v: Optional[str], values: Dict[str, Any]) -> Any:
        if isinstance(v, str):
            return v
        return PostgresDsn.build(
            scheme="postgresql",
            user=values.get("POSTGRES_USER"),
            password=values.get("POSTGRES_PASSWORD"),
            host=values.get("POSTGRES_SERVER"),
            path=f"/{values.get('POSTGRES_DB') or  ''}",
        )

    class Config:
        case_sensitive = True
        env_file = ".env"


settings = Settings()

Info: When loading configurations from a .env file the python-dotenv package is required.

Here we are making use of Pydantic's settings management. By default, the BaseSettings class will try to read the environment variables set at system level using os.environ. However in our case instead we are specifying that we would like our environment variables to be read from a .env file. Pydantic relies on the python-dotenv package to achieve this, let's add it as a dependency now.

poetry add python-dotenv

And now we will create the .env file at the root of the project directory.

.env

.env

# PostgreSQL
POSTGRES_SERVER=localhost
POSTGRES_USER=postgres
POSTGRES_PASSWORD=password
POSTGRES_DB=app

Make sure to edit this file to reflect your set up.

.gitignore

Since the .env file can contain sensitive information we wouldn't want to commit this to version control. So now would probably be a good time to add a .gitignore file to our project. We will copy the Python .gitignore template provided by GitHub here.
.gitignore

wget https://raw.githubusercontent.com/github/gitignore/master/Python.gitignore
mv Python.gitignore .gitignore

Next, we will create a models.py and schemas.py file.

models.py

The models.py file will contain all our models that extend from the SQLAlchemy Base class we defined in db.py We will create that file now with an example User model.

app/models.py

from uuid import uuid4
from sqlalchemy import Column, String, Text
from sqlalchemy.dialects.postgresql import UUID

from .db import Base


class Post(Base):
    __tablename__ = "posts"

    id = Column(UUID(as_uuid=True), primary_key=True, index=True, default=uuid4)
    title = Column(String)
    body = Column(Text)

schemas.py

Let's create the schemas.py file now. This file will contain all our Pydantic models. Under the hood, FastAPI makes use of these models to validate the incoming request body, parse the response body and generate automatic docs for our API. Really cool, at least I think so! 👌

app/schemas.py

from typing import Optional

from pydantic import BaseModel, UUID4


# Shared properties
class PostBase(BaseModel):
    title: Optional[str] = None
    body: Optional[str] = None


# Properties to receive via API on creation
class PostCreate(PostBase):
    title: str
    body: str


# Properties to receive via API on update
class PostUpdate(PostBase):
    pass


class PostInDBBase(PostBase):
    id: Optional[UUID4] = None

    class Config:
        orm_mode = True


# Additional properties to return via API
class Post(PostInDBBase):
    pass


# Additional properties stored in DB
class PostInDB(PostInDBBase):
    pass

The final file we will create for now is the actions.py file. This file will contain all our use cases or actions that will be performed, such as CRUD operations.

actions.py

app/actions.py

from typing import Any, Dict, Generic, List, Optional, Type, TypeVar, Union

from fastapi.encoders import jsonable_encoder
from pydantic import UUID4, BaseModel
from sqlalchemy.orm import Session

from . import schemas
from .db import Base
from .models import Post

# Define custom types for SQLAlchemy model, and Pydantic schemas
ModelType = TypeVar("ModelType", bound=Base)
CreateSchemaType = TypeVar("CreateSchemaType", bound=BaseModel)
UpdateSchemaType = TypeVar("UpdateSchemaType", bound=BaseModel)


class BaseActions(Generic[ModelType, CreateSchemaType, UpdateSchemaType]):
    def __init__(self, model: Type[ModelType]):
        """Base class that can be extend by other action classes.
           Provides basic CRUD and listing operations.

        :param model: The SQLAlchemy model
        :type model: Type[ModelType]
        """
        self.model = model

    def get_all(
        self, db: Session, *, skip: int = 0, limit: int = 100
    ) -> List[ModelType]:
        return db.query(self.model).offset(skip).limit(limit).all()

    def get(self, db: Session, id: UUID4) -> Optional[ModelType]:
        return db.query(self.model).filter(self.model.id == id).first()

    def create(self, db: Session, *, obj_in: CreateSchemaType) -> ModelType:
        obj_in_data = jsonable_encoder(obj_in)
        db_obj = self.model(**obj_in_data)  # type: ignore
        db.add(db_obj)
        db.commit()
        db.refresh(db_obj)
        return db_obj

    def update(
        self,
        db: Session,
        *,
        db_obj: ModelType,
        obj_in: Union[UpdateSchemaType, Dict[str, Any]]
    ) -> ModelType:
        obj_data = jsonable_encoder(db_obj)
        if isinstance(obj_in, dict):
            update_data = obj_in
        else:
            update_data = obj_in.dict(exclude_unset=True)
        for field in obj_data:
            if field in update_data:
                setattr(db_obj, field, update_data[field])
        db.add(db_obj)
        db.commit()
        db.refresh(db_obj)
        return db_obj

    def remove(self, db: Session, *, id: UUID4) -> ModelType:
        obj = db.query(self.model).get(id)
        db.delete(obj)
        db.commit()
        return obj


class PostActions(BaseActions[Post, schemas.PostCreate, schemas.PostUpdate]):
    """Post actions with basic CRUD operations"""

    pass


post = PostActions(Post)

Before going back and updating our main.py file, let's review our final directory structure.

.
├── app
│   ├── actions.py
│   ├── config.py
│   ├── __init__.py
│   ├── main.py
│   ├── models.py
│   └── schemas.py
├── poetry.lock
├── pyproject.toml
├── README.md
└── tests
    ├── __init__.py
    └── test_app.py

Let's update our main.py file now and connect all the dots.

Update main.py

app/main.py

from typing import Any, List

from fastapi import Depends, FastAPI, HTTPException
from pydantic import UUID4
from sqlalchemy.orm import Session
from starlette.status import HTTP_201_CREATED, HTTP_404_NOT_FOUND

from . import actions, models, schemas
from .db import SessionLocal, engine

# Create all tables in the database.
# Comment this out if you using migrations.
models.Base.metadata.create_all(bind=engine)

app = FastAPI()


# Dependency to get DB session.
def get_db():
    try:
        db = SessionLocal()
        yield db
    finally:
        db.close()


@app.get("/")
def index():
    return {"message": "Hello world!"}


@app.get("/posts", response_model=List[schemas.Post], tags=["posts"])
def list_posts(db: Session = Depends(get_db), skip: int = 0, limit: int = 100) -> Any:
    posts = actions.post.get_all(db=db, skip=skip, limit=limit)
    return posts


@app.post(
    "/posts", response_model=schemas.Post, status_code=HTTP_201_CREATED, tags=["posts"]
)
def create_post(*, db: Session = Depends(get_db), post_in: schemas.PostCreate) -> Any:
    post = actions.post.create(db=db, obj_in=post_in)
    return post


@app.put(
    "/posts/{id}",
    response_model=schemas.Post,
    responses={HTTP_404_NOT_FOUND: {"model": schemas.HTTPError}},
    tags=["posts"],
)
def update_post(
    *, db: Session = Depends(get_db), id: UUID4, post_in: schemas.PostUpdate,
) -> Any:
    post = actions.post.get(db=db, id=id)
    if not post:
        raise HTTPException(status_code=HTTP_404_NOT_FOUND, detail="Post not found")
    post = actions.post.update(db=db, db_obj=post, obj_in=post_in)
    return post


@app.get(
    "/posts/{id}",
    response_model=schemas.Post,
    responses={HTTP_404_NOT_FOUND: {"model": schemas.HTTPError}},
    tags=["posts"],
)
def get_post(*, db: Session = Depends(get_db), id: UUID4) -> Any:
    post = actions.post.get(db=db, id=id)
    if not post:
        raise HTTPException(status_code=HTTP_404_NOT_FOUND, detail="Post not found")
    return post


@app.delete(
    "/posts/{id}",
    response_model=schemas.Post,
    responses={HTTP_404_NOT_FOUND: {"model": schemas.HTTPError}},
    tags=["posts"],
)
def delete_post(*, db: Session = Depends(get_db), id: UUID4) -> Any:
    post = actions.post.get(db=db, id=id)
    if not post:
        raise HTTPException(status_code=HTTP_404_NOT_FOUND, detail="Post not found")
    post = actions.post.remove(db=db, id=id)
    return post

Finally, if we run the server again and hit http://127.0.0.1:8000/docs we now have a basic API that can perform CRUD operations on our Post entity. 🚀

uvicorn app.main:app

Conclusion 💡

If you have made it this far, well done! 👍

We created a simple application that can serve as a good starting point for small to medium projects. There are still a number of things we can include in this base project such as migrations or adding Docker to our stack. (Hint: we will cover this in future posts, stay tuned 😉)

The final code for this post can be found on GitHub.

If you enjoyed reading this article and would like to stay tuned for more, or just want to connect, follow me on twitter @alexvanzyl.