This project extends the previous academic database project by integrating it with PostgreSQL using Docker and implementing SQLAlchemy models. It includes data migration with Alembic and a Python script (seed.py
) for populating the database with random data using Faker. The project also features a my_select.py
file containing functions for executing specific SQL queries using SQLAlchemy sessions.
- SQLAlchemy Models:
- Models for students, groups, teachers, subjects, and grades tables.
- Database Migration:
- Alembic for managing database schema changes.
- Data Seeding:
seed.py
script to populate the database with random data (30-50 students, 3 groups, 5-8 subjects, 3-5 teachers, up to 20 grades per student).
- Custom Query Functions:
my_select.py
containing functionsselect_1
toselect_10
for specific database queries.
- Docker Integration:
- Instructions for setting up a PostgreSQL database in a Docker container.