Database Seeding

Database seeding is the process of populating a database with initial data. This is particularly useful during development and testing phases to ensure your application has realistic data to work with, without having to manually create it.

Why Use Database Seeding?

Development: Provides a quick way to set up a development environment with sample data, allowing developers to immediately start working on features without worrying about data entry.
Testing: Ensures that your tests run against a consistent and representative dataset, making your tests more reliable and reproducible.
Demonstrations: Useful for populating a database for demonstrations or presentations of your application.

The `seed` Management Command

This project includes a powerful custom Django management command, seed, located at apps/core/management/commands/seed.py. This command allows you to easily populate your database with sample user data.

Usage

To use the seed command, you typically run it via python manage.py seed or poetry run seed.

python manage.py seed [options]

Available Options

The seed command supports the following arguments:

--users <count>: Specifies the number of fake users to create. If not provided, it defaults to 10 users.
- Example: python manage.py seed --users 50 (Creates 50 fake users)
--superuser: A flag that, when present, creates a superuser with predefined credentials (admin@admin.com / admin).
- Example: python manage.py seed --superuser (Creates an admin user)
--clean: A flag that, when present, deletes all existing non-superuser user data from the database before seeding. This is useful for starting with a fresh dataset.
- Example: python manage.py seed --clean (Deletes existing data before seeding)

Combined Examples

You can combine these options to achieve specific seeding scenarios:

Basic seeding with default options (creates 10 users):
```
python manage.py seed
```

Create specific number of users and a superuser:

python manage.py seed --users 20 --superuser

Clean existing data, create 50 users, and a superuser:

python manage.py seed --users 50 --superuser --clean

Implementation Details

The seed command uses the Faker library to generate realistic-looking fake data for user profiles. It also utilizes Django's transaction.atomic decorator to ensure that the seeding process is atomic; if any part of the seeding fails, the entire operation is rolled back, preventing partial data corruption.