himlohiya

sudo apt-get install python3-pip
sudo pip3 install awscli

function install_kops {
    if [ -z $(which kops) ]
       then
           curl -LO https://github.com/kubernetes/kops/releases/download/$(curl -s https://api.github.com/repos/kubernetes/kops/releases/latest | grep tag_name | cut -d '"' -f 4)/kops-linux-amd64
           chmod +x kops-linux-amd64
           mv kops-linux-amd64 /usr/local/bin/kops
       else

himlohiya

resource "aws_route53_zone" "newtech-academy" {
   name = "newtech.academy"
}
resource "aws_route53_record" "server1-record" {
   zone_id = "${aws_route53_zone.newtech-academy.zone_id}"
   name = "server1.newtech.academy"
   type = "A"
   ttl = "300"
   records = ["104.236.247.8"]
}

himlohiya

variable "AWS_ACCESS_KEY" {}
variable "AWS_SECRET_KEY" {}

variable "AWS_REGION" {
  default = "eu-west-1"
}

variable "AMIS" {
  type = "map"  
  default = {

himlohiya

resource "aws_instance" "example" {
  ami           = "${lookup(var.AMIS, var.AWS_REGION)}"
  instance_type = "t2.micro"

  # the VPC subnet
  subnet_id = "${aws_subnet.main-public-1.id}"

  # the security group
  vpc_security_group_ids = ["${aws_security_group.allow-ssh.id}"]

himlohiya

resource "aws_key_pair" "mykeypair" {
  key_name = "mykeypair"
  public_key = "${file("${var.PATH_TO_PUBLIC_KEY}")}"
}

himlohiya

provider "aws" { 
    region = "${var.AWS_REGION}"
    access_key = "${var.AWS_ACCESS_KEY}"
    secret_key = "${var.AWS_SECRET_KEY}"
}

himlohiya

data "aws_ip_ranges" "european_ec2" {
  regions = [
      "eu-west-1",
      "eu-central-1"
  ]
  services = [
      "ec2"
  ]
}

himlohiya

# nat gw
resource "aws_eip" "nat" {
  vpc      = true
}
resource "aws_nat_gateway" "nat-gw" {
  allocation_id = "${aws_eip.nat.id}"
  subnet_id = "${aws_subnet.main-public-1.id}"
  depends_on = ["aws_internet_gateway.main-gw"]
}

himlohiya

# Internet VPC
resource "aws_vpc" "main" {
    cidr_block = "10.0.0.0/16"
    instance_tenancy = "default"
    enable_dns_support = "true"
    enable_dns_hostnames = "true"
    enable_classiclink = "false"
    tags {
        Name = "main"
    }

himlohiya

from textblob import TextBlob

# compute sentiment scores (polarity) and labels
sentiment_scores_tb = [round(TextBlob(article).sentiment.polarity, 3) for article in news_df['clean_text']]
sentiment_category_tb = ['positive' if score > 0 
                             else 'negative' if score < 0 
                                 else 'neutral' 
                                     for score in sentiment_scores_tb]