Handlebars Pagination Integration Pattern for Large Dataset Queries

Goal

Determine the optimal pattern for integrating Handlebars templates with paginated data from large datasets, ensuring efficient rendering and proper data flow between the application and template layer.

Constraints and Uncertainty

Handlebars is a logic-less templating language that processes pre-fetched data passed through its context. The engine provides no native mechanisms for data fetching, slicing, or pagination control. The {{#each}} helper iterates over arrays but cannot query external sources or implement offset/limit logic. This creates a gap between the need to display large datasets efficiently and Handlebars' limited data manipulation capabilities.

The core question centers on how to structure the data preparation layer when using Handlebars alongside modern data fetching libraries like fetch or Apollo, particularly when implementing server-side or client-side pagination for datasets that exceed practical rendering limits.

Questions

1. What established patterns exist for integrating Handlebars templates with paginated data from REST or GraphQL APIs without embedding data logic in templates?
2. How should the application layer structure and pass paginated data to Handlebars to maintain separation of concerns while supporting efficient rendering of large datasets?