hkraji

### Ruby

## Breakpoint

# DEBUG SNIPPET >>> REMOVE <<<
require (RUBY_VERSION.match(/1\.8\..*/) ? 'ruby-debug' : 'debugger');Debugger.start; debugger


### System

hkraji

    require 'ostruct'
    
    def self.convert_data(elements)
      results = []

      if elements.is_a?(Array)
        elements.each do |el|
          results << deep_convert(el)
        end
      else

hkraji

git config --global core.autocrlf false

hkraji

module MethodLogger

  def self.extended(base)
    clazz_methods = base.methods(false)

    base.class_eval do
      clazz_methods.each do |method_name|
        original_method = method(method_name).unbind
        define_singleton_method(method_name) do |*args, &block|
          puts "$$---> #{base}##{method_name}(#{args.inspect})"

hkraji

require 'net/http'

# you can find CITY_ID here http://bulk.openweathermap.org/sample/city.list.json.gz
CITY_ID = 2172517

# options: metric / imperial
UNITS   = 'metric'

# create free account on open weather map to get API key
API_KEY = ENV['WEATHER_KEY']

hkraji

#!/usr/bin/env bash
#
# Usage:
#
# checkout BRANCH_NAME
#
# checkout master
# checkout hkraji/pr_work_in_progress
#

hkraji

require 'rake'
require 'ap'

namespace :gazzda_s3 do
  desc 'Upload images from directory to specified s3 bucket'
  task :upload, [:bucket] do |t, args|
    path_to_images = '/Users/haris/rails/scm_gazzda/image-files'
    bucket = args[:bucket]

    connection = Fog::Storage.new({ :provider => "AWS", :aws_access_key_id => ENV['AWS_KEY_ID'], :aws_secret_access_key => ENV['AWS_KEY_SECRET'], :region => 'eu-central-1' })

hkraji

files:
  /etc/nginx/conf.d/proxy.conf:
    content: |
      client_max_body_size 500M;
      server_names_hash_bucket_size 128;

      upstream backend {
        server unix:///var/run/puma/my_app.sock;
      }

hkraji

Intro

Following are some code samples from one of the features I've developed on my startup Vorta. Vorta is Supply Chain Software and it has a LOT of tables. To support that we've used datatables since it was best solution at the time on the frontend. Since we needed support for large, floating tables.

The following backend-only code uses DSL to define a table. By simply defining CustomerDatatable, you get a functional table with sorting, searching, toggling, and reordering capabilities without any custom code. While there are additional supporting classes, I've only included a few. Despite its complexity, this approach simplifies maintenance and accelerates new development by confining changes to _datatable files, thereby hiding much of the complexity.

Video

To visually see what I mean you can view this video