In this video, we'll be learning how to add pagination to our FastAPI application. Right now, our app returns all posts at once, which doesn't scale well as data grows. We'll fix that by adding skip and limit query parameters to our API, using SQLAlchemy's offset and limit for efficient database queries, creating a paginated response schema with metadata like total count and whether more data is available, and wiring up a Load More button on the frontend to fetch additional pages from our API. This is an industry-standard pattern you'll encounter on nearly any list endpoint in a real-world API. Let's get started...

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#Python #FastAPI

Corey Schafer

Part 13 of a FastAPI tutorial series covers implementing pagination for a blog application. The tutorial walks through adding skip and limit query parameters with validation to the posts API endpoint, creating a PaginatedPostResponse schema with metadata (total, skip, limit, has_more), and using SQLAlchemy's offset/limit for database-level pagination. On the frontend, a hybrid approach is used: the first batch is server-side rendered via Jinja2, and subsequent batches are loaded dynamically via JavaScript with a 'Load More' button. The same pattern is applied to user-specific post pages. Key points include ordering results for consistent pagination, capping limit at 100 to prevent abuse, and manually serializing nested relationships when constructing response objects.

Python FastAPI Tutorial (Part 13): Pagination - Loading More Data with Query Parameters