Python
FastAPI SQLAlchemy Models
About
In this module, you’ll set up a local PostgreSQL database instance and connect it to your application. The focus is on creating a real SQLAlchemy model and seeding your database with initial data. By the end of this module, you’ll have a working database with seeded data that is ready to be integrated into your application. Adapting your API to use this database and model will be covered in a future part of this lecture series.
Content
| Lesson |
Est. Delivery Time |
Skills |
| Setup |
5 min |
Set up the development environment. |
| Concepts |
5 min |
Understand foundational concepts for SQLAlchemy and ORMs. |
| Connecting to the Database |
15 min |
Establish a connection between Python and a local PostgreSQL database. |
| Creating Models |
10 min |
Define database models to represent your application’s data structure. |
| Building a Seeding Module |
15 min |
Develop a Python module to populate the database with initial data. |
| Seeding the Database |
10 min |
Populate your PostgreSQL database with real data. |
| Total content |
60 min |
|
Level Up content
| Lesson |
Est. Delivery Time |
Skills |
| Database Troubleshooting |
10 min |
Debug and resolve common PostgreSQL configuration issues. |
| Total Level Up content |
~ 10 min |
|
References
📖 Reference Materials