![]() ![]() To start off, we will look at the ORM and Data Access Layers:įor now, let’s turn our attention to the new db directory. The overall diagram of what we’re working towards looks like this: ![]() Migrations as we update our database schemas. We’ll go through all of these additions in this post, and by the end you’ll understand howĪll the new modules work together to enable not just a one-time database integration, but also You’ll notice that there are a number of new directories compared to previous With very minor config modifications you can use the same approachįor other relational database management systems (RDBMS) such as PostgreSQL or MySQL. Minimal setup so it’s useful for learning. Our POST operations just updated data structures in memory. So far in the tutorial, we have not been able to persist data beyond a server restart since all Practical Section 1 - Setting Up Database Tables with SQLAlchemy In this tutorial, we will make use of both components, though you can adapt the approach not to use the ORM. ![]() ORM (Object Relational Mapper) - which is optional.Core - a fully featured SQL abstraction toolkit.SQLAlchemy is composed of two distinct components: SQLAlchemy’s expression language builds on this concept from its core. Rows can be selected from not only tables but also joins and other select statements any of these units canīe composed into a larger structure. SQLAlchemy considers the database to be a relational algebra engine, not just a collection of tables. It gives application developers easy ways to work with relational databases in their Python SQLAlchemy is one of the most widely used and highest quality Python third-party libraries. Theory Section 1 - Quick Introduction to SQLAlchemy (because you can’t easily spin it up and run it locally without all the parts). There are a lot of parts that all work together and therefore would be more confusing if presented in isolation We’ll cover quite a lot of ground in this post because This is the first of the intermediate-level posts. Post Contents Theory Section 1 - Quick Introduction to SQLAlchemy Practical Section 1 - Establishing our Database Tables and Connection Practical Section 2 - CRUD operations and DB schemas Practical Section 3 - Enabling Migrations with Alembic Practical Section 4 - Putting it all Together in Our Endpoints Flask Beginner Level Difficulty Part 1: Hello World Part 2: URL Path Parameters & Type Hints Part 3: Query Parameters Part 4: Pydantic Schemas & Data Validation Part 5: Basic Error Handling Part 6: Jinja Templates Part 6b: Basic FastAPI App Deployment on Linode Intermediate Level Difficulty Part 7: Setting up a Database with SQLAlchemy and its ORM Part 8: Production app structure and API versioning Part 9: Creating High Performance Asynchronous Logic via async def and await Part 10: Authentication via JWT Part 11: Dependency Injection and FastAPI Depends Part 12: Setting Up A React Frontend Part 13: Using Docker, Uvicorn and Gunicorn to Deploy Our App to Heroku Part 14: Using Docker and Uvicorn to Deploy Our App to IaaS (Coming soon) Part 15: Exploring the Open Source Starlette Toolbox - GraphQL (Coming soon) Part 16: Alternative Backend/Python Framework Comparisons (i.e. Project github repo directory for this part of the tutorial Tutorial Series Contents Optional Preamble: FastAPI vs. The series is designed to be followed in order, but if you already know FastAPI you can jump to the relevant part. Each post gradually adds more complex functionality, showcasing the capabilities of FastAPI, ending with a realistic, production-ready API. Tutorial where we will build a cooking recipe API. Welcome to the Ultimate FastAPI tutorial series. ![]()
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