Moved to https://github.com/kbilsted/Functional-core-imperative-shell/blob/master/README.md
State machines are everywhere in interactive systems, but they're rarely defined clearly and explicitly. Given some big blob of code including implicit state machines, which transitions are possible and under what conditions? What effects take place on what transitions?
There are existing design patterns for state machines, but all the patterns I've seen complect side effects with the structure of the state machine itself. Instances of these patterns are difficult to test without mocking, and they end up with more dependencies. Worse, the classic patterns compose poorly: hierarchical state machines are typically not straightforward extensions. The functional programming world has solutions, but they don't transpose neatly enough to be broadly usable in mainstream languages.
Here I present a composable pattern for pure state machiness with effects,
- Introduction to Functional Programming Johannes Weiß - https://vimeo.com/100786088
- ReactiveCocoa at MobiDevDay Andrew Sardone - https://vimeo.com/65637501
- The Future Of ReactiveCocoa Justin Spahr-Summers - https://www.youtube.com/watch?v=ICNjRS2X8WM
- Enemy of the State Justin Spahr-Summers - https://www.youtube.com/watch?v=7AqXBuJOJkY
- WWDC 2014 Session 229 - Advanced iOS Application Architecture and Patterns Andy Matuschak - https://developer.apple.com/videos/play/wwdc2014/229/
- Functioning as a Functionalist Andy Matuschak - https://www.youtube.com/watch?v=rJosPrqBqrA
- Controlling Complexity in Swift Andy Matuschak - https://realm.io/news/andy-matuschak-controlling-complexity/
# Hello, and welcome to makefile basics. | |
# | |
# You will learn why `make` is so great, and why, despite its "weird" syntax, | |
# it is actually a highly expressive, efficient, and powerful way to build | |
# programs. | |
# | |
# Once you're done here, go to | |
# http://www.gnu.org/software/make/manual/make.html | |
# to learn SOOOO much more. |
class Graph: | |
def __init__(self): | |
self.nodes = set() | |
self.edges = defaultdict(list) | |
self.distances = {} | |
def add_node(self, value): | |
self.nodes.add(value) | |
def add_edge(self, from_node, to_node, distance): |
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