Architecture Patterns with Python

Validation Recap Validation means different things to different people When talking about validation, make sure you’re clear about what you’re validating. We find it useful to think about syntax, semantics, and pragmatics: the structure of messages, the meaningfulness of messages, and the business logic governing our response to messages. Validate at the edge when possible Validating required fields and the permissible ranges of numbers is boring, and we want to keep it out of our nice clean codebase. Handlers should always receive only valid messages. Only validate what you require Use the Tolerant Reader pattern: read only the fields your application needs and don’t overspecify their internal structure. Treating fields as opaque strings buys you a lot of flexibility. Spend time writing helpers for validation Having a nice declarative way to validate incoming messages and apply preconditions to your handlers will make your codebase much cleaner. It’s worth investing time to make boring code easy to maintain. Locate each of the three types of validation in the right place Validating syntax can happen on message classes, validating semantics can happen in the service layer or on the message bus, and validating pragmatics belongs in the domain model.