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Why might seed data used for automated testing differ in purpose from seed data used to bootstrap a fresh production environment?
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Why might seed data used for automated testing differ in purpose from seed data used to bootstrap a fresh production environment?
What is a common way seed scripts generate realistic-looking fake data (names, addresses, emails) for development/testing purposes, rather than using static hardcoded values?
What is a general difference in intent between "seed data" and "fixture data," two related but sometimes distinct terms used across different tools/ecosystems?
What is a reasonable general principle for deciding how much seed data is "enough" for a given development or testing purpose?
Why might a team prefer to define seed data in code (a script using the application's own models/ORM) rather than as a raw SQL dump or static file?
Why might a seed script be organized to respect foreign key/relationship dependencies (seeding parent records before their dependent child records)?
Why does seeding matter for demonstrating a product (a demo/sales environment) with realistic-looking sample data, as opposed to an empty database?
What is a reasonable approach for handling seed data that needs to represent a range of different states (e.g. users in various subscription tiers, or orders in various fulfillment statuses) to properly exercise an application during development?
What is a key difference between seed data and a database migration, even though both are often run as part of setting up an environment?
Why might a team deliberately avoid seeding sensitive-looking but fake data (like realistic-looking fake credit card numbers or fake personal information) carelessly, even in a non-production development database?
What is a practical reason a team might want their seed script to be re-runnable to reset a development database back to a known clean state?
What is a common use case for seed data in a local development environment?