fappel

/**
 * RunInThread an other accompanying files are licensed under the MIT
 * license.  Copyright (C) Frank Appel 2016-2021. All rights reserved
 */
import java.lang.annotation.ElementType;
import java.lang.annotation.Retention;
import java.lang.annotation.RetentionPolicy;
import java.lang.annotation.Target;

irazasyed

#!/bin/sh

# PATH TO YOUR HOSTS FILE
ETC_HOSTS=/etc/hosts

# DEFAULT IP FOR HOSTNAME
IP="127.0.0.1"

# Hostname to add/remove.
HOSTNAME=$1

vidavidorra

Auto-deploying Doxygen documentation to gh-pages with Travis CI

This explains how to setup for GitHub projects which automatically generates Doxygen code documentation and publishes the documentation to the gh-pages branch using Travis CI. This way only the source files need to be pushed to GitHub and the gh-pages branch is automatically updated with the generated Doxygen documentation.

Sign up for Travis CI and add your project

Get an account at Travis CI. Turn on Travis for your repository in question, using the Travis control panel.

Create a clean gh-pages branch

To create a clean gh-pages branch, with no commit history, from the master branch enter the code below in the Git Shell. This will create a gh-pages branch with one file, the README.md in it. It doesn't really matter what file is uploaded in it since it will be overwritten when the automatically generated documentation is published to th

ptarjan

Scaling your API with rate limiters

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.

Request rate limiter

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.