RickCogley

[
  {
    "user": "85599",
    "content": {
      "type": "add_people",
      "message": [
        "Hideaki",
        "Ena",
        "Yoshi",
        "Yori",

RickCogley

Introduction

I had been considering, off and on, moving our Flowdock chat rooms to an open source equivalent, because I'm generally against the idea of having years of information and group knowledge, in a system that I don't control. It's not just Flowdock, but also Slack, Hipchat and so on.

There are a few OSS systems out there, often billed as "slack alternatives", including Mattermost and Rocket Chat. As I was searching, I learned about matrix.org in a forum post about such systems, liked its philosophy of trying to break down information siloes, so I thought I'd try it.

Per the site, Matrix is:

an open standard for decentralised communication, providing simple HTTP APIs and open source reference implementations for securely distributing and persisting JSON over an open federation of servers.

RickCogley

Markdown and reStructuredText

GitHub supports several lightweight markup languages for documentation; the most popular ones (generally, not just at GitHub) are Markdown and reStructuredText. Markdown is sometimes considered easier to use, and is often preferred when the purpose is simply to generate HTML. On the other hand, reStructuredText is more extensible and powerful, with native support (not just embedded HTML) for tables, as well as things like automatic generation of tables of contents.

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Rocket Chat Search Basics

Introduction

Rocket Chat search supports the use of "regular expressions", the benefits of which are great search flexibility and the ability to search chat entries in any language, even ones which are traditionally a challenge for search (e.g. "CJK" languages - Chinese, Japanese, Korean).

Basic Regex Examples

Regular expressions are a deep, but admittedly geeky topic. The flexibility of "regex" search increases as you learn more about how to write regex patterns, but if you learn just a couple of simple patterns, you can benefit right away.

Let's see a few simple examples that you can try.

RickCogley

[deoplete]   File "<frozen importlib._bootstrap_external>", line 388, in _check_name_wrapper
[deoplete]   File "<frozen importlib._bootstrap_external>", line 809, in load_module
[deoplete]   File "<frozen importlib._bootstrap_external>", line 668, in load_module
[deoplete]   File "<frozen importlib._bootstrap>", line 268, in _load_module_shim
[deoplete]   File "<frozen importlib._bootstrap>", line 693, in _load
[deoplete]   File "<frozen importlib._bootstrap>", line 673, in _load_unlocked
[deoplete]   File "<frozen importlib._bootstrap_external>", line 665, in exec_module
[deoplete]   File "<frozen importlib._bootstrap>", line 222, in _call_with_frames_removed
[deoplete] Traceback (most recent call last):
[deoplete] Traceback (most recent call last):

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Readme

This is a quick guide to setting up mirroring of your 1999 site, to other web servers to serve your static output files. It uses the lsyncd daemon. This works using the Ubuntu-based Amazon AMI image provided by Scripting as of 19 July 2016.

Forever

If you haven't already tried it, "forever" is easy to set up and use, and it daemonizes your 1999 storage.js script. Install via npm from your nodestorage folder:

 sudo npm install forever -g

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Current

I am using the fantastic jq to manipulate a REST API's json, into a csv for upsertting into another database system, via its API. Once in the target system, I'm doing some date math, including rounding time stamps to 30 min intervals to allow me to do group them, for standard deviation calculation. The problem is, there is a lot of data and the database chokes when it has to round every record and then do std dev calculations on each.

• Sample.json shows a small sample of what the input data looks like, but actually it's just stdout from the curl command in the shell script.
• example-initial.sh shows the important bit of the initial shell script, that uses curl to authenticate against the data location's API, and then use jq to add a couple of columns and export to csv. It works like a charm.
• ACME-X1-A.csv is an example of the output CSV file, that's then upsertted into the target db.

Goal

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5 entertaining things you can find with the GitHub Search API

Let's have some command-line fun with curl, [jq][1], and the [new GitHub Search API][2].

Today we're looking for:

• The hottest repositories created in the last week.
• The oldest user accounts with zero followers. (So sad.)
• Issue trends by language.
• Clojure projects defying convention.

RickCogley

How-to setup a simple git push deployment

These are my notes basically. At first i created this gist just as a reminder for myself. But feel free to use this for your project as a starting point. If you have questions you can find me on twitter @thomasf https://twitter.com/thomasf This is how i used it on a Debian Wheezy testing (https://www.debian.org/releases/testing/)

Discuss, ask questions, etc. here https://news.ycombinator.com/item?id=7445545

On the server (example.com)

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#!/usr/bin/env bash

# Colours picked from https://robinpowered.com/blog/best-practice-system-for-organizing-and-tagging-github-issues/

###
# Label definitions
###
declare -A LABELS

# Platform