himangSharatun

class MassUpdateWorker
  include Sneakers::Worker

  QUEUE_NAME = MassUpdatePublisher::QUEUE_NAME
  from_queue QUEUE_NAME, arguments: { 'x-dead-letter-exchange': "#{QUEUE_NAME}-retry" }

  def work(msg)
    data = ActiveSupport::JSON.decode(msg)
    data["mutations"].each do |mutation |
      update_balance(mutation.to_h)

himangSharatun

# config/initializers/sneakers.rb
require 'sneakers'
require 'sneakers/handlers/maxretry'

module Connection
  def self.sneakers
    @_sneakers ||= begin
      Bunny.new(
        addresses: ENV['BUNNY_AMQP_ADDRESSES']&.split(','),
        username:  ENV['BUNNY_AMQP_USER'],

himangSharatun

class MassUpdatePublisher
  QUEUE_NAME = 'user.mass_update_using_csv'.freeze

  def initialize(mutations)
    @mutations = mutations
  end

  def publish(options = {})
    channel = RabbitQueueService.connection.create_channel
    exchange = channel.exchange(

himangSharatun

class RabbitQueueService
  def self.logger
    Rails.logger.tagged('bunny') do
      @@_logger ||= Rails.logger
    end
  end

  def self.connection
    @@_connection ||= begin
      instance = Bunny.new(

himangSharatun

sudo apt-get update
sudo apt-get install apt-transport-https ca-certificates curl software-properties-common
curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo apt-key add -
sudo apt-key fingerprint 0EBFCD88
sudo add-apt-repository "deb [arch=amd64] https://download.docker.com/linux/ubuntu $(lsb_release -cs) stable"

sudo apt-get update
sudo apt-get install docker-ce

himangSharatun

version: '2'
services:
  rabbitmq:
    image: rabbitmq:alpine
    ports:
      - 5672:5672
      - 15672:15672

himangSharatun

class UserController < ApplicationController
  def index
    @user = User.all
    render json: @user, each_serializer: UserSerializer
  end

  def mass_update

    update_using_csv(params[:csv])

himangSharatun

from gensim.models import Word2Vec
import re
import pickle
import numpy as np

def tokenize(sentence):
    remove_dots = re.sub("[.]", "", sentence.lower())
    return re.findall("[A-Za-z]{2,}", remove_dots)

def w2v_tfidf(sentence, w2v_model, tfidf_model):

himangSharatun

from gensim.models import Word2Vec
import re

def tokenize(sentence):
    remove_dots = re.sub("[.]", "", sentence.lower())
    return re.findall("[A-Za-z]{2,}", remove_dots)

def w2v_average(sentence, w2v_model):
    words = tokenize(sentence.lower())
    sum_w2v = 0

himangSharatun

import pandas as pd
from gensim.models import Word2Vec
import logging
import re

# Diplay log
logging.basicConfig(format='%(asctime)s : %(levelname)s : %(message)s', level=logging.INFO)

# Load data
data = pd.read_csv('training-data.csv', header=None)