Build a FastAPI & SQLAlchemy Project: A Step-by-Step Guide

Hey everyone! 👋 Ever wanted to build a powerful and efficient web application? Well, you’ve come to the right place! Today, we’re diving deep into the world of FastAPI and SQLAlchemy , two amazing tools that make building web APIs a total breeze. We’re going to create a complete project from scratch, so get ready to roll up your sleeves and get coding! This FastAPI SQLAlchemy project example is designed for you, whether you’re a seasoned pro or just starting out. We’ll break down everything, step-by-step, making sure you grasp the concepts and can apply them to your own projects. This guide will walk you through setting up your environment, creating models, and building API endpoints. Let’s get started, shall we?

Setting Up Your Development Environment

Before we jump into the code, let’s get our environment ready. We’ll be using Python, so make sure you have it installed. If you don’t, head over to the official Python website and grab the latest version. We’ll also be using a virtual environment to keep our project dependencies isolated. This is super important because it prevents conflicts between different projects. Let’s create a project directory, navigate into it, and set up our virtual environment. In your terminal, run the following commands:

mkdir fastapi-sqlalchemy-project
cd fastapi-sqlalchemy-project
python -m venv .venv

This creates a directory for your project, moves you into it, and sets up a virtual environment named .venv . Now, let’s activate the virtual environment:

• On Windows:

  .venv\Scripts\activate
  

• On macOS and Linux:

  source .venv/bin/activate
  

You should see (.venv) at the beginning of your terminal prompt, indicating that the virtual environment is active. Next, we need to install the necessary packages. We’ll be using FastAPI, SQLAlchemy, databases (an async database library compatible with SQLAlchemy), and a database driver like asyncpg (for PostgreSQL) or aiosqlite (for SQLite). Let’s install them using pip:

pip install fastapi sqlalchemy databases asyncpg

Now that our environment is set up and ready to go, we can finally begin with our FastAPI SQLAlchemy project example ! Ready to build something awesome? Let’s proceed to create our database models, which is the heart of our application’s data management. This will involve defining our data structures and their relationships using SQLAlchemy.

Why Virtual Environments Are Awesome

Virtual environments are your best friend when working on Python projects. They keep your project dependencies separate from your global Python installation, preventing all sorts of headaches. Imagine having different projects that need different versions of the same library. Without virtual environments, you’d be in dependency hell! Virtual environments isolate these dependencies, ensuring that each project has exactly what it needs, without messing with other projects on your system. This makes your projects more reliable and easier to manage.

Choosing Your Database

For this project, we’ll use PostgreSQL because of its robustness and performance. However, you can easily adapt this guide to use other databases like SQLite or MySQL. The key is to install the appropriate database driver for your chosen database. For example, if you want to use SQLite, you’d install aiosqlite instead of asyncpg . When choosing a database, consider factors like scalability, performance, and the complexity of your data. PostgreSQL is a great choice for most projects, especially those that will grow over time.

Creating Database Models with SQLAlchemy

Alright, let’s get down to the fun part: creating our database models using SQLAlchemy. This is where we define the structure of our data. We’ll create a simple model for a Todo item. This will include an id , a title , a description , and a completed status. We’ll use the declarative base provided by SQLAlchemy to define our model. Create a new file named models.py in your project directory. Inside models.py , add the following code:

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

Base = declarative_base()

class Todo(Base):
    __tablename__ = "todos"

    id = Column(Integer, primary_key=True, index=True)
    title = Column(String, index=True)
    description = Column(String)
    completed = Column(Boolean, default=False)

In this code, we import the necessary modules from SQLAlchemy. We define a Todo class that inherits from Base . The __tablename__ attribute specifies the name of the database table. Then, we define the columns for our Todo model, specifying their types and other attributes like primary_key and index . This is how we structure our data in the database. Now, let’s create a file named database.py to handle the database connection and session management. Inside database.py , add the following code:

from sqlalchemy import create_engine
from sqlalchemy.orm import sessionmaker

DATABASE_URL = "postgresql://user:password@host:port/database"

engine = create_engine(DATABASE_URL)
SessionLocal = sessionmaker(autocommit=False, autoflush=False, bind=engine)

Replace `