prologic

Learn Go in ~5mins

This is inspired by A half-hour to learn Rust and Zig in 30 minutes.

Basics

Your first Go program as a classical "Hello World" is pretty simple:

First we create a workspace for our project:

apollo13

"""
License: MIT - https://opensource.org/licenses/MIT

ChromeLogger is a protocol which allows sending logging messages to the Browser.

This module implements simple support for Django. It consists of two components:

    * `LoggingMiddleware` which is responsible for sending all log messages
      associated with the request to the browser.
    * `ChromeLoggerHandler` a python logging handler which collects all messages.

mattiaslundberg

Ansible playbook to setup HTTPS using Let's encrypt on nginx.

The Ansible playbook installs everything needed to serve static files from a nginx server over HTTPS.
The server pass A rating on [SSL Labs](https://www.ssllabs.com/).

To use:
 1. Install [Ansible](https://www.ansible.com/)
 2. Setup an Ubuntu 16.04 server accessible over ssh
 3. Create `/etc/ansible/hosts` according to template below and change example.com to your domain
 4. Copy the rest of the files to an empty directory (`playbook.yml` in the root of that folder and the rest in the `templates` subfolder)

gilyes

Backup:
docker exec -t -u postgres your-db-container pg_dumpall -c > dump_`date +%d-%m-%Y"_"%H_%M_%S`.sql

Restore:
cat your_dump.sql | docker exec -i your-db-container psql -Upostgres

paulirish

What forces layout / reflow

All of the below properties or methods, when requested/called in JavaScript, will trigger the browser to synchronously calculate the style and layout*. This is also called reflow or layout thrashing, and is common performance bottleneck.

Generally, all APIs that synchronously provide layout metrics will trigger forced reflow / layout. Read on for additional cases and details.

Element APIs

Getting box metrics

• elem.offsetLeft, elem.offsetTop, elem.offsetWidth, elem.offsetHeight, elem.offsetParent

WayneSan

import jwt

from django.conf import settings
from django.contrib.auth.models import User

from rest_framework import exceptions
from rest_framework.authentication import TokenAuthentication


class JSONWebTokenAuthentication(TokenAuthentication):

jdkanani

data:text/html, <style type="text/css">.e{position:absolute;top:0;right:0;bottom:0;left:0;}</style><div class="e" id="editor"></div><script src="http://d1n0x3qji82z53.cloudfront.net/src-min-noconflict/ace.js" type="text/javascript" charset="utf-8"></script><script>var e=ace.edit("editor");e.setTheme("ace/theme/monokai");e.getSession().setMode("ace/mode/ruby");</script>
<!-- 
For other language: Instead of  `ace/mode/ruby`, Use

Markdown -> `ace/mode/markdown`
Python -> `ace/mode/python`
C/C++ -> `ace/mode/c_cpp`
Javscript -> `ace/mode/javascript`
Java -> `ace/mode/java`
Scala- -> `ace/mode/scala`

lecram

#! /usr/bin/env python

"""{escher} -- one-file key-value storage.

What?
  This is a toy application to manage persistent key-value string data.
  The file {escher} is *both* the application and its data.
  When you run any of the commands below, the file will be executed and,
  after data change, it will rewrite itself with updated data.
  You can copy the file with whatever name to create multiple datasets.

rgreenjr

-- show running queries (pre 9.2)
SELECT procpid, age(clock_timestamp(), query_start), usename, current_query 
FROM pg_stat_activity 
WHERE current_query != '<IDLE>' AND current_query NOT ILIKE '%pg_stat_activity%' 
ORDER BY query_start desc;

-- show running queries (9.2)
SELECT pid, age(clock_timestamp(), query_start), usename, query 
FROM pg_stat_activity 
WHERE query != '<IDLE>' AND query NOT ILIKE '%pg_stat_activity%' 

hellerbarde

Latency numbers every programmer should know

L1 cache reference ......................... 0.5 ns
Branch mispredict ............................ 5 ns
L2 cache reference ........................... 7 ns
Mutex lock/unlock ........................... 25 ns
Main memory reference ...................... 100 ns             
Compress 1K bytes with Zippy ............. 3,000 ns  =   3 µs
Send 2K bytes over 1 Gbps network ....... 20,000 ns  =  20 µs
SSD random read ........................ 150,000 ns  = 150 µs

Read 1 MB sequentially from memory ..... 250,000 ns = 250 µs