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Design Patterns 90 XP · 10 min

Repository Pattern

Abstract data access behind an interface so your business logic never knows whether data comes from a database, cache, or API — and testing becomes a one-liner swap.

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Why this matters

When a service directly imports a database driver or fires raw SQL, the business rule and the storage plumbing are fused. You can't test the rule without a real database, you can't swap Postgres for Redis without rewriting the service, and every storage detail bleeds into the domain. The Repository pattern draws a clean line: define an interface that describes what the domain needs (find pending orders, save an order), then provide separate implementations for production storage and in-memory testing. The domain never imports a driver again.

The problem

Bad

The solution

Good

Testing becomes trivial

With a repository interface in place, a complete unit test for OrderService needs no database, no network, no docker-compose. Inject an InMemoryOrderRepository, seed it with test data, and verify results — the test runs in milliseconds and never flakes. In production, inject PostgresOrderRepository via your DI container. Same service, zero changes.

Key takeaway

Repository hides the plumbing. Your domain speaks to an interface — swapping Postgres for in-memory, Redis, or a remote API is a one-liner in the DI wiring, not a rewrite of business logic.

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