Generating Random Test Data for Django Models

[JoseStevens]

I'm building a Django app for sports analytics and need to generate random test data for my models to simulate user interactions and test my views and APIs. Specifically, I want to populate a Player model with ​random NBA player names, stats (e.g., points, rebounds), and other attributes to stress-test my database queries and API endpoints.

I’ve started with a simple approach using Python’s random module in a Django management command:

from django.core.management.base import BaseCommand
from myapp.models import Player
import random

class Command(BaseCommand):
    help = 'Generate random NBA player data'

    def handle(self, *args, **kwargs):
        players = ['LeBron James', 'Stephen Curry', 'Kevin Durant']
        for _ in range(100):
            Player.objects.create(
                name=random.choice(players),
                points=random.randint(0, 50),
                rebounds=random.randint(0, 20)
            )
        self.stdout.write(self.style.SUCCESS('Successfully generated test data'))

This works for a small list, but I’m looking for more scalable and realistic solutions, especially for generating diverse stats or integrating external data sources. For inspiration, I found a tool (​https://wputopia.com/tools/random-nba-player/) that generates random NBA player data, which got me thinking about integrating similar randomness into my Django app. Has anyone built a robust random data generator for Django models? Are there libraries or patterns (e.g., Faker) that you recommend for this? Any tips on optimizing performance for large datasets or ensuring data variety?

Thanks for any insights or code examples!

[Simon Charette]

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