diogoaurelio

import akka.actor.Actor
import akka.actor.Props
import akka.event.Logging
 
class DudeA extends Actor {
    val log = Logging(context.system, this)
     
    def receive = {
        case "hello" => sender() ! "Hallo, Grüß Dich!"
        case _ => log.info("Hmm...")

diogoaurelio

trait Actor {
    final def sender(): ActorRef = context.sender()
}

diogoaurelio

import urllib
import pg8000
import boto3
import os
import logging

IAM_ROLE = os.environ['IAM_ROLE']
DB_NAME = os.environ['DB_NAME']
DB_USER = os.environ['DB_USER']
DB_PORT = os.environ['DB_PORT']

diogoaurelio

module "redshift_loader_lambda" {

  source = "github.com/diogoaurelio/terraform-aws-lambda-module"
  version = "v0.0.1"

  aws_region     = "${var.aws_region}"
  environment    = "${var.environment}"
  project        = "${var.project}"

  lambda_unique_function_name = "${var.redshift_loader_lambda_unique_function_name}"

diogoaurelio

################################################################################
# Locals used for different Lambdas Environmental Variables
################################################################################

locals {

  redshift_loader_lambda_env_vars = {
    ENVIRONMENT = "${var.environment}"
    REGION      = "${var.aws_region}"
    IAM_ROLE    = "${var.redshift_data_loader_lambda_iam_role}"

diogoaurelio

################################################################################
# AWS Lambda IAM Policy document definitions
################################################################################

data "aws_iam_policy_document" "this" {
  statement {
    effect = "Allow"

    actions = [
      "s3:GetBucketLocation",

diogoaurelio

# Redshift - check currently running queries; useful for misbehaving queries;
SELECT
  userid
  , query
  , pid
  , starttime
  , left(text, 100) as query
FROM stv_inflight;

diogoaurelio

my_string = """
your string \n seperated \n by \n new \n lines.
"""
account_id = '12345678910'
region = 'eu-west-1'
parameter_name = 'some-secret-name'

key_id = 'your-key-id'

diogoaurelio

# create the general function
def _amount_spent(quantity: int, price: float) -> float:
    """
    Calculates the product between two variables
    :param quantity: (float/int)
    :param price: (float/int)
    :return:
            (float/int)
    """
    return quantity * price

diogoaurelio

from tests.test_utils.test_spark import spark_session
from pyspark.sql import DataFrame, Row, SparkSession
from pyspark.sql.functions import col

from src.job import amount_spent_udf


def test_amount_spent_udf(spark_session: SparkSession) -> None:
    input_df = spark_session.createDataFrame([
        Row(customer_name="Geoffrey", date="2016-04-22", category="Foo", product_name="Bar", quantity=1, price=2.00),