I personnaly prefer to use docker-compose to run a Fastapi image as well as a Postgres database next to it. Simply clone the repo and call docker-compose up to launch everything.įirst things first, we need something to test ! We'll create a small project with an endpoint to create an "Item" with a title and a description and store it in the database. The code presented in this article is fully available on Github. That's what we'll be covering in this article ! But if like me, you come from Django, you might still struggle to configure everything so that each test works in isolation, and leaves the database as it was before running.
FASTAPI SQLITE HOW TO
There is a guide to help you set it up, and a tutorial wich gives some indications on how to go about testing it. SQLAlchemy is the one documented by Fast API.
FASTAPI SQLITE INSTALL
You'll have to choose and install an ORM. For example, if you want to use a relational database, However it does mean that you have to set up yourself some things that usually comes out of the box in other frameworks. Everything else is up to you which allows you to tailor you architecture to perfectly fit your needs.
FASTAPI SQLITE FULL
INFO: Application startup complete.If you haven't heard of it yet, FastAPI is a micro-framewok that allows developers to make full use of modern Python."Micro" here, means that rather than trying to cover every use case, it focuses on doing a single thing extremely well: giving you the tools to build a fast (duh) API. INFO: Will watch for changes in these directories: INFO: Uvicorn running on (Press CTRL+C to quit) INFO: Started reloader process INFO: Started server process INFO: Waiting for application startup. Put all that code in a file called main.py.
Now we are ready to run the FastAPI application. In future examples later we will use a FastAPI Dependency to get the session, being able to share it with other dependencies and being able to replace it during testing. In this simple example, we just create the new sessions manually in the path operation functions. In some isolated cases, we would want to have new sessions inside, so, more than one session per request.īut we would never want to share the same session among different requests. We should normally have one session per request in most of the cases.
Remember that we should use a SQLModel session per each group of operations and if we need other unrelated operations we should use a different session? When a client sends a request to the path /heroes/ with a GET HTTP operation, we run this function that gets the heroes from the database and returns them. get ( "/heroes/" ) def read_heroes (): with Session ( engine ) as session : heroes = session. post ( "/heroes/" ) def create_hero ( hero : Hero ): with Session ( engine ) as session : session. on_event ( "startup" ) def on_startup (): create_db_and_tables (). Test Applications with FastAPI and SQLModelĪlternatives, Inspiration and Comparisonsįrom typing import Optional from fastapi import FastAPI from sqlmodel import Field, Session, SQLModel, create_engine, select class Hero ( SQLModel, table = True ): id : Optional = Field ( default = None, primary_key = True ) name : str = Field ( index = True ) secret_name : str age : Optional = Field ( default = None, index = True ) sqlite_file_name = "database.db" sqlite_url = f "sqlite:/// engine = create_engine ( sqlite_url, echo = True, connect_args = connect_args ) def create_db_and_tables (): SQLModel. Read Heroes with Limit and Offset with FastAPIįastAPI Path Operations for Teams - Other Models
FASTAPI SQLITE UPDATE
Update and Remove Many-to-Many Relationships Create a Table with SQLModel - Use the EngineĪutomatic IDs, None Defaults, and Refreshing DataĬreate Data with Many-to-Many Relationships
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