You can modularize your project, with frameworks for example. And you can test individually each part of your project.

Thank you. It can be useful to show its integration into Xcode templates by @Apple!

Hello. What you need currently exists only on macOS with Xcode by using Create ML framework. You can find documentation here - https://developer.apple.com/documentation/createml/creating_a_model_from_tabular_data. You can't use Create ML framework today in your apps. Only available into scripts and playgrounds. But you can easily create Core ML models on servers using Turi Create - https://github.com/apple/turicreate. It works fine with Tabular data - https://apple.github.io/turicreate/docs/userguide/sframe/tabular-data.html. My suggestion if you want to ensure privacy for your users: use encryption with server (end-to-end encryption is the best) upload real data with a UUID and append fake data with random UUID (ie. 1 good sample, 3 fake samples) store the "good" UUID locally download results later by sending UUID (ie. 1 good UUID, 3 fake UUID) server will return good result + random results use local UUID to identify good result. If your model is public and can be used by any user, you can use distribute it by using model deployment - https://developer.apple.com/videos/play/wwdc2020/10152/ presented this year. And, once Create ML will be available for apps, you will be able to make it available for your users.

You can show this post for more informations: Using Core Data with SwiftUI App Protocol - https://developer.apple.com/forums/thread/650876.

Found the solution myself. sourceEntityVersionHash and destinationEntityVersionHash are required on NSEntityMapping.

It's now possible with write(_:toBufferCallback:) - https://developer.apple.com/documentation/avfaudio/avspeechsynthesizer/3141659-write