Full-Stack FastAPI with PostgreSQL: A Comprehensive Guide

FastAPI is a modern, fast (high-performance) web framework for building APIs with Python 3.6+ based on standard Python type hints. It uses a Starlette web framework and Pydantic for data validation and Python type checking. PostgreSQL is a powerful open-source relational database system that provides a scalable and reliable platform for storing data in web applications. In this article, we’ll explore how to build a full-stack FastAPI application with PostgreSQL integration.

1. Environment Setup

Before we proceed, make sure you have Python and pip installed on your system. You’ll also need to install the required dependencies. Here’s a list of the dependencies we’ll be using in this tutorial:

• FastAPI
• SQLAlchemy
• Pydantic
• Uvicorn (for ASGI server)
• Poetry (for dependency management)

You can install these dependencies using pip or Poetry. Here’s an example command to install them using Poetry:

pipenv install

2. Setting up PostgreSQL Database

To set up PostgreSQL, you’ll need to install the PostgreSQL server on your system. You can follow the official PostgreSQL documentation for installation instructions.

Once you have PostgreSQL installed, you’ll need to create a database for your application. You can use the following command to create a new database:

CREATE DATABASE mydatabase;

Replace mydatabase with the desired name for your database.

3. Database Migration with SQLAlchemy

Now that you have the database set up, you’ll need to create the database schema using SQLAlchemy. First, make sure you have SQLAlchemy installed by running pip install sqlalchemy.

Next, you’ll need to create a SQLAlchemy engine that connects your application to the database. Here’s an example of how to create the engine:

from sqlalchemy import create_engine
engine = create_engine('postgresql://username:password@localhost/mydatabase')

Replace username, password, and localhost with your PostgreSQL credentials and database location.

Now that you have the engine set up, you can define your database models using SQLAlchemy ORM (Object Relational Mapping). For example, let’s create a simple User model:

from sqlalchemy import 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)
    email = Column(String)

In this example, we define a User model with three columns: id, name, and email. The __tablename__ attribute sets the name of the table in the database.

To create the database schema based on your models, you can use SQLAlchemy’s Base.metadata.create_all() method:

Base.metadata.create_all(engine)

This command will create the necessary tables in your PostgreSQL database.

4. Creating a FastAPI App

Now that you have the database set up, let’s move on to creating the FastAPI app. Make sure you have FastAPI installed by running pip install fastapi.

First, create a new file called main.py and import the necessary modules:

from fastapi import FastAPI
from sqlalchemy.orm import Session
from sqlalchemy import create_engine
from yourapp import models  # Import your model modules here

Replace yourapp with the name of the directory where you stored your model code.

Now, let’s create the FastAPI app instance:

app = FastAPI()

Next, you’ll need to set up the database session for interacting with the PostgreSQL database. You can use SQLAl