Concurrency is a domain I have wanted to explore for a long time because the locks and the race conditions have always intimidated me. I recall somebody suggesting concurrency patterns in golang because they said "you share the data and not the variables".

Amused by that, I searched for "concurrency in golang" and bumped into this awesome slide by Rob Pike: https://talks.golang.org/2012/waza.slide#1 which does a great job of explaining channels, concurrency patterns and a mini-architecture of load-balancer (also explains the above one-liner).

Let's dig in:

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.

Go 泛型的草案截止今日已经基本定型了，与其他语言最大的不同应该就是 Go 的泛型利用 Interface 做 Constraint，可以说是与现有的 Interface 充分结合，之前的草案本来要引入新的关键字 contracts 在这次改动后被现有的 interface 代替，这使得 Interface 的概念更像 Rust 的 trait（实际上 Go 的泛型概念也与 Rust 相似），不过 Go 中实现 Interface 不需要显示声明，所以我想先谈一下 Interface 这个 Go 语言中最出色的“发明”。

Interface 实现了 Go 风格的 Duck typing。它实现的方法查表方式与其他语言有些不同，有方法的语言大概有两个阵营

1. C++ 和 Java 在编译时生成方法的静态方法表，比如 C++ 的 vtable
2. Js 和 Python 动态查询，并花式缓存