When building a Python backend, it is tempting to focus on endpoints first and leave database design until later. That can work for a small prototype, but unclear relationships and duplicated logic become harder to fix as features accumulate.
Before adding more endpoints, think about what information the application needs to store, how entities relate to each other, which fields must be unique, and which queries will be frequent. Keep database access organized, validate incoming data, and use migrations to manage schema changes.
For an AI-powered document application, for example, storing document metadata separately from processing logic can make the system easier to extend and maintain.
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*What's your preferred approach for Python database projects: SQL-first, an ORM-first workflow, or a combination of both?
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