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Generic Repository In Fastapi That Is Managing Relationships Part 1

Leo Migdal
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generic repository in fastapi that is managing relationships part 1

I decided to start sharing what I do with everyone. Let’s get started! In this tutorial, we will build a simple FastAPI application using the Generic Repository Pattern. The repository pattern helps us manage access to data in a centralized and reusable way, making it easy to interact with our database models. We will focus on a simple base code to demonstrate the repository functionality, and we'll also cover unit tests to verify everything works as expected. The Repository Pattern is a design pattern that abstracts the data access logic in your application.

Instead of directly interacting with your database in multiple places, you centralize the logic in a repository class, making it more manageable, reusable, and easier to test. First, let’s create a virtual environment to isolate our project dependencies: Create a requirements.txt file in the root of your project directory with the following content: There was an error while loading. Please reload this page. There was an error while loading.

Please reload this page. There was an error while loading. Please reload this page. I’d like to share a library I recently published: fastapi-repository. It’s a generic async repository implementation designed specifically for FastAPI projects using SQLAlchemy. The goal is to provide a clean, reusable, and extensible pattern for CRUD operations and complex queries, avoiding repetitive boilerplate in your FastAPI applications.

We know how to build a very simple API with FastAPI and we also know how to use the Repository Pattern to isolate repositories. Let's use them together to create an API with three endpoints to create a new book, get all books, and get one book given an id. For this test, we'll need to use a client to call the API endpoints, and for this reason, we need to add requests package to the requirements file: First step, we need to create a new test file: Let's start with the more simple test: getting all books. To do it, we add an initial test:

To create the first API endpoint, we need to add a new route to handle the GET requests. Here we can see how to use the dependency injection to load the in-memory repository to be used from the endpoint. This document explains the repository pattern implementation in the FastAPI starter project. The repository pattern provides a clean abstraction for data access operations, separating database interaction logic from business logic. This page covers the repository classes, their methods, how they interact with the database layer, and how they are used by service classes. For information about the overall database configuration and migrations, see Database Configuration.

The repository pattern serves as an intermediary between the data source (database) and the business logic layer. It provides a collection-like interface for accessing domain objects while encapsulating the database access logic. Sources: src/repositories/item.py1-78 src/repositories/user.py1-78 The codebase implements two main repository classes: Both repositories follow a similar pattern, providing CRUD operations for their respective entities. Defining objects using data schemas is very useful to do field validations and be consistent along the code.

Next step is to define a place where to store collections of objects, and this is done in repositories. The basics for the Repository Pattern are: With this pattern, the important part is not how we implement the repository. The important thing is that all repositories and the implementations respect the defined contract (interface) and all use the same methods. Then we can implement controllers that no longer depend on a specific repository implementation. Now all we have to do is set up a dependency injection framework to use the desired repository implementation.

The dependency injection framework manages the instances of the repository classes and "injects" them into the controller constructor. And simply by modifying these settings we could change our data access technology without touching a single line of code in your controller. And this is where unit testing comes in. Using this pattern allows us to isolate the different layers. Since the controller code is loosely coupled to the repository, all we have to do in unit tests is provide a mock implementation in the repository that allows you to define its behavior. This gives us the ability to unit test controller actions without relying on a database or whatever.

A generic repository class designed to simplify CRUD operations and querying with SQLAlchemy and FastAPI. It supports:

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