10/6/2023 0 Comments Fastapi sqliteIt 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. json () assert data = assert data = user_idĪnd all the modifications we made in the database during the tests will be in the test.db database instead of the main sql_app.db.Welcome to the Ultimate FastAPI tutorial series. main import app, get_db SQLALCHEMY_DATABASE_URL = "sqlite://" engine = create_engine ( SQLALCHEMY_DATABASE_URL, connect_args = " ) assert response. We create a new file at sql_app/tests/test_sql_app.py.įrom fastapi.testclient import TestClient from sqlalchemy import create_engine from sqlalchemy.orm import sessionmaker from sqlalchemy.pool import StaticPool from. In this example we'll create a temporary database only for the tests. In the test, you could use a dependency override to return your custom database session instead of the one that would be used normally. Your normal dependency get_db() would return a database session. ![]() ![]() The only changes here are in the new testing file. Let's update the example from SQL (Relational) Databases to use a testing database.Īll the app code is the same, you can go back to that chapter check how it was. The main idea is exactly the same you saw in that previous chapter. You could want to set up a different database for testing, rollback the data after the tests, pre-fill it with some testing data, etc. You can use the same dependency overrides from Testing Dependencies with Overrides to alter a database for testing. The new docs will include Pydantic v2 and will use SQLModel (which is also based on SQLAlchemy) once it is updated to use Pydantic v2 as well. The current version assumes Pydantic v1, and SQLAlchemy versions less than 2.0.
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