Understand your Mac and iPhone more deeply by tracing the evolution of Mac OS X from prelease to Swift. John Siracusa delivers the details.
You've got two main options:
(by @andrestaltz)
If you prefer to watch video tutorials with live-coding, then check out this series I recorded with the same contents as in this article: Egghead.io - Introduction to Reactive Programming.
eXtreme Go Horse (XGH) Process | |
Source: http://gohorseprocess.wordpress.com | |
1. I think therefore it's not XGH. | |
In XGH you don't think, you do the first thing that comes to your mind. There's not a second option as the first one is faster. | |
2. There are 3 ways of solving a problem: the right way, the wrong way and the XGH way which is exactly like the wrong one but faster. | |
XGH is faster than any development process you know (see Axiom 14). |
The following are examples of the four types rate limiters discussed in the accompanying blog post. In the examples below I've used pseudocode-like Ruby, so if you're unfamiliar with Ruby you should be able to easily translate this approach to other languages. Complete examples in Ruby are also provided later in this gist.
In most cases you'll want all these examples to be classes, but I've used simple functions here to keep the code samples brief.
This uses a basic token bucket algorithm and relies on the fact that Redis scripts execute atomically. No other operations can run between fetching the count and writing the new count.
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,
// Just before switching jobs: | |
// Add one of these. | |
// Preferably into the same commit where you do a large merge. | |
// | |
// This started as a tweet with a joke of "C++ pro-tip: #define private public", | |
// and then it quickly escalated into more and more evil suggestions. | |
// I've tried to capture interesting suggestions here. | |
// | |
// Contributors: @r2d2rigo, @joeldevahl, @msinilo, @_Humus_, | |
// @YuriyODonnell, @rygorous, @cmuratori, @mike_acton, @grumpygiant, |
The libdispatch is one of the most misused API due to the way it was presented to us when it was introduced and for many years after that, and due to the confusing documentation and API. This page is a compilation of important things to know if you're going to use this library. Many references are available at the end of this document pointing to comments from Apple's very own libdispatch maintainer (Pierre Habouzit).
My take-aways are:
You should create very few, long-lived, well-defined queues. These queues should be seen as execution contexts in your program (gui, background work, ...) that benefit from executing in parallel. An important thing to note is that if these queues are all active at once, you will get as many threads running. In most apps, you probably do not need to create more than 3 or 4 queues.
Go serial first, and as you find performance bottle necks, measure why, and if concurrency helps, apply with care, always validating under system pressure. Reuse
Also see the original Pieter Noordhuis's guide
You need: