I’ve been using CherryPyfor decades. And along comes Svelte…

Using Svelte with CherryPy is like combining any frontend framework with a backend framework. In this setup, Svelte is responsible for building the client-side user interface, while CherryPy is used for server-side processing, handling HTTP requests, and communicating with databases. Here’s a simple guide on how you might use these two together:

1. Separate Frontend and Backend Development: Generally, it’s a good idea to keep your frontend (Svelte) and backend (CherryPy) code separate. This makes it easier to manage both parts of your project.
2. API Design: Design your server-side endpoints in CherryPy. These endpoints should correspond to the different types of data your client might request. For example, if you have a blog, you might have endpoints to get all posts, get a single post, create a post, update a post, and delete a post. This is often done using REST or GraphQL.
3. Server-Side Logic: Implement the server-side logic in CherryPy. This involves processing requests, handling business logic, and communicating with databases.
4. Fetch API in Svelte: In your Svelte application, you can use the Fetch API to make HTTP requests to your CherryPy backend. This can be done directly in your Svelte components. Svelte’s reactivity features make it easy to update the UI when data changes.
5. Websockets: If your application needs real-time updates, you could use websockets. Both Svelte and CherryPy have support for this.
6. Build & Deployment: When you’re ready to deploy your app, you’ll need to compile your Svelte app to JavaScript, HTML, and CSS. These static files can then be served by CherryPy or any static file server. On the server side, you’ll need to deploy your CherryPy app to a server that supports Python.

Remember, both Svelte and CherryPy are flexible and can support a variety of architectures, so you may need to adjust this setup based on the needs of your project. Additionally, when developing applications, it’s important to consider factors like error handling, data validation, security, and performance optimization.