Reintroduce Goodness from Deleted Examples

[cefn]

For repo hygeine, (and given the complexity of tracking the removal of immer) #197 will be deleting...

Deleted Apps

• apps/nextjs-mornington - a progressive lauf tutorial based on Mornington Crescent

Deleted Modules

• modules/lauf-runner - an unnecessarily class-based remix of Redux Saga, using lauf and generators
• modules/lauf-runner-primitives - some classes to support lauf-runner store operations
• modules/lauf-runner-trial - utilities to run tests of generator-based sequences
• modules/draft/lauf-node-runner - some classes to support lauf-runner node io operations
• modules/draft/lauf-stopwatch - a drafted mechanism for being able to halt (and potentially time-travel) generators

However, after removing immer and 'demoting' it to a function call that wraps a read/write store, I should reintroduce the goodness of these examples and design approaches. In particular...

Mornington Tutorial Goodness

Mornington should be revisited using non-immer and non-react logic as a starting point. It should begin as a less-finite-state-machine problem (without having to e.g. transition through creating users as the first step). (We could probably get as far as time-travel app behaviours before e.g. adding store-react into the mix for JSX). Many of the same lessons should be transferred using the same explanatory examples, but maybe authored from scratch on read/write.

Lauf-Runner time-travel and FSM generator goodness

Lauf-runner should be revisited using non-class-based (just promise function call based) yielding. It will have no direct dependency on stores at that point - just allow slicing of time by the resolution of promises when your logic is written using the generator syntax. A focus will be wiring into the Redux in-browser time-travel UI, and presenting the 'branching' paths of alternative futures that you can go back and forward with, there. Of course, stores can be 'point-cut' at the transition points, allowing you to revisit prior moments, and replaying generators allows you to 'resume' from those moments, potentially.

Lauf Runner Trial goodness

Lauf-runner-trial should be revisited for wording and techniques around test-automation of generator-based sequences.