Pagination & Filtering: Managing Large Datasets Efficiently with FastAPI

Why Pagination Matters Imagine an API returning 10,000 items at once. That's 10,000 database reads, massive memory usage, and a slow response every single time. Pagination solves this by slicing data into manageable chunks. The Endpoint @app.get("/items") def get_items( page: int = Query(default=1, ge=1), limit: int = Query(default=5, ge=1, le=20), category: Optional[str] = None, min_price: Optional[float] = None, max_price: Optional[float] = None ): How Pagination Works offset = (page - 1) * limit items = query.offset(offset).limit(limit).all() page=1, limit=5 → items 1-5 page=2, limit=5 → items 6-10 page=3, limit=5 → items 11-15 The offset tells the database where to start, limit tells it how many to return. Filtering The same endpoint handles filtering: ?category=electronics → only electronics ?min_price=100&max_price=500 → price range filter ?category=electronics&page=2&limit=5 → combined! The Metadata Response { "metadata": { "total": 12, "page": 2, "limit": 5, "total_pages": 3 },