cdown

urlencode() {
    # urlencode <string>

    old_lc_collate=$LC_COLLATE
    LC_COLLATE=C

    local length="${#1}"
    for (( i = 0; i < length; i++ )); do
        local c="${1:$i:1}"
        case $c in

nuxlli

Sublime Text 2 - Useful Shortcuts

Tested in Mac OS X: super == command

Open/Goto

---

• super+t: go to file
• super+ctrl+p: go to project
• super+r: go to methods

jaydenseric

Video conversion with FFmpeg

Install

On mac:

1. Download the latest release.
2. Extract the binary and place it in /usr/local/bin.

Command basics

jgravois

Do I have a web server running?

---

having a web server turned on doesn't necessarily mean you are serving pages on the world wide web. its what allows you to load your own static files (.html, .js etc.) in a browser via http://.

if you're not sure whether or not you have a web server running, no problem! its easy to confirm.

what happens when you visit http://localhost/?

superfawkes

#!/bin/bash
#
# git-svn-diff originally by (http://mojodna.net/2009/02/24/my-work-git-workflow.html)
# modified by mike@mikepearce.net
# modified by aconway@[redacted] - handle diffs that introduce new files
# modified by superfawkes - correct whitespaces in aconway's patch for Crucible, handle whitespaces for BSD/OSX styled sed
#
# Generate an SVN-compatible diff against the tip of the tracking branch

# Get the tracking branch (if we're on a branch)

KodrAus

Profiling performance

Using perf:

$ perf record -g binary
$ perf script | stackcollapse-perf.pl | rust-unmangle | flamegraph.pl > flame.svg

NOTE: See @GabrielMajeri's comments below about the -g option.

ugik

# Build neural network
net = tflearn.input_data(shape=[None, 5])
net = tflearn.fully_connected(net, 32)
net = tflearn.fully_connected(net, 32)
net = tflearn.fully_connected(net, 2, activation='softmax')
net = tflearn.regression(net)

# Define model and setup tensorboard
model = tflearn.DNN(net, tensorboard_dir='tflearn_logs')
# Start training (apply gradient descent algorithm)

davidbgk

import http.server
import socketserver
from http import HTTPStatus


class Handler(http.server.SimpleHTTPRequestHandler):
    def do_GET(self):
        self.send_response(HTTPStatus.OK)
        self.end_headers()
        self.wfile.write(b'Hello world')

prideout

#!/usr/bin/env python3

import http.server
import socketserver

PORT = 8000

Handler = http.server.SimpleHTTPRequestHandler
Handler.extensions_map.update({
    '.wasm': 'application/wasm',

optozorax

#include <random>

double random(void) {
  static std::mt19937 generator(time(0));
  static std::uniform_real_distribution<double> distribution(0, 1);
  return distribution(generator);
}