scalaz streams and how to think about streams
Update: I've created an electronic book to collect together scalaz-stream user notes: My scalaz-streams User Notes Working on data streaming (many problems can be cast as data streams) is hard. Controlling synchronous and asynchronous behaviors easily and simply requires frameworks and code that is often is uncommon to most programmers, and hence, its hard to write the code while still retaining simplicity. Scalaz Streams (labelled sstreams in this article) help you manage complexity by providing a few fundamental abstractions. But I found the abstractions hard to use at first because I was not use to thinking in a model that sstreams uses. sstreams casts the problem as a state machine. There are 3 states and a "driver" that iterates through the states. Each state carries with it enough information to move to the next state. Each state is a "one step process" and so all states derive from the Process trait. The level of abstraction is pretty high which