cobyism

Deploying a subfolder to GitHub Pages

Sometimes you want to have a subdirectory on the master branch be the root directory of a repository’s gh-pages branch. This is useful for things like sites developed with Yeoman, or if you have a Jekyll site contained in the master branch alongside the rest of your code.

For the sake of this example, let’s pretend the subfolder containing your site is named dist.

Step 1

Remove the dist directory from the project’s .gitignore file (it’s ignored by default by Yeoman).

dustinboston

// Usage: 
//
// 1. Put this in the file that gets first loaded by RequireJS
// 2. Once the page has loaded, type window.rtree.map() in the console
//    This will map all dependencies in the window.rtree.tree object
// 3. To generate UML call window.rtree.toUml(). The output can be used
//    here: http://yuml.me/diagram/scruffy/class/draw
requirejs.onResourceLoad = function (context, map, depMaps) {
  if (!window.rtree) {
    window.rtree = {};

veox

[
    {
        "constant": true,
        "inputs": [],
        "name": "name",
        "outputs": [
            {
                "name": "",
                "type": "string"
            }

vitorbritto

Remove MySQL completely

1. Open the Terminal

2. Use mysqldump to backup your databases

3. Check for MySQL processes with: ps -ax | grep mysql

4. Stop and kill any MySQL processes

5. Analyze MySQL on HomeBrew:

   brew remove mysql
   

john2x

Clojure Destructuring Tutorial and Cheat Sheet

(Related blog post)

Simply put, destructuring in Clojure is a way extract values from a datastructure and bind them to symbols, without having to explicitly traverse the datstructure. It allows for elegant and concise Clojure code.

Vectors and Sequences

iiLaurens

window.scrollTo(0, 0)
var bodyRect = document.body.getBoundingClientRect();

var items = Array.prototype.slice.call(
  document.querySelectorAll('*')
).map(function(element) {
  var rect=element.getBoundingClientRect();
  return {
    element: element,
    include: (element.tagName === "BUTTON" || element.tagName === "A" || (element.onclick != null) || window.getComputedStyle(element).cursor == "pointer"),

rtt

Tinder API documentation

Note: this was written in April/May 2014 and the API may has definitely changed since. I have nothing to do with Tinder, nor its API, and I do not offer any support for anything you may build on top of this. Proceed with caution

http://rsty.org/

I've sniffed most of the Tinder API to see how it works. You can use this to create bots (etc) very trivially. Some example python bot code is here -> https://gist.github.com/rtt/5a2e0cfa638c938cca59 (horribly quick and dirty, you've been warned!)

zed

/** Emulate `cmd1 | cmd2 | more` pipeline using recursion.

http://stackoverflow.com/questions/20434124/recursive-piping-in-unix-environment
*/
#include <signal.h>
#include <stdio.h>
#include <stdlib.h>

#include <unistd.h>

Rich-Harris

Edit — February 2019

This gist had a far larger impact than I imagined it would, and apparently people are still finding it, so a quick update:

• TC39 is currently moving forward with a slightly different version of TLA, referred to as 'variant B', in which a module with TLA doesn't block sibling execution. This vastly reduces the danger of parallelizable work happening in serial and thereby delaying startup, which was the concern that motivated me to write this gist
• In the wild, we're seeing (async main(){...}()) as a substitute for TLA. This completely eliminates the blocking problem (yay!) but it's less powerful, and harder to statically analyse (boo). In other words the lack of TLA is causing real problems
• Therefore, a version of TLA that solves the original issue is a valuable addition to the language, and I'm in full support of the current proposal, which you can read here.

I'll leave the rest of this document unedited, for archaeological

debasishg

General Background and Overview

1. Probabilistic Data Structures for Web Analytics and Data Mining : A great overview of the space of probabilistic data structures and how they are used in approximation algorithm implementation.
2. Models and Issues in Data Stream Systems
3. Philippe Flajolet’s contribution to streaming algorithms : A presentation by Jérémie Lumbroso that visits some of the hostorical perspectives and how it all began with Flajolet
4. Approximate Frequency Counts over Data Streams by Gurmeet Singh Manku & Rajeev Motwani : One of the early papers on the subject.
5. [Methods for Finding Frequent Items in Data Streams](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.187.9800&rep=rep1&t