matheus-rossi

import string, yaml

def load_yaml(file_path: str, context: dict = None):
    def string_constructor(loader, node):
        t = string.Template(node.value)
        value = t.substitute(context)
        return value
    
    l = yaml.SafeLoader
    l.add_constructor('tag:yaml.org,2002:str', string_constructor)

matheus-rossi

import sys

# List comprehension
list_comprehension = [i for i in range(10_000_000)]
print(f"List comprehension memory: {sys.getsizeof(list_comprehension) / (1024 * 1024)} MB")

# Yield generator
def generator():
    for i in range(10_000_000):
        yield i

matheus-rossi

from pyspark.sql import SparkSession

spark = (
  SparkSession
  .builder
  .appName("spark_parameterized_queries") 
  .getOrCreate()
)

##### Criando dois datasets de teste #####

matheus-rossi

apiVersion: v2
name: datahub-prerequisites
description: A Helm chart for packages that Datahub depends on
type: application
# This is the chart version. This version number should be incremented each time you make changes
# to the chart and its templates, including the app version.
version: 0.0.14
dependencies:
  - name: elasticsearch
    version: 7.17.3

matheus-rossi

const configPossibilities = [ [ 1 ], [ 1, 2 ], [ 1, 2, 3, 4 ] ] 

const configPossibilities2 = {
 ID_LINHA: [ 1 ],
 ID_IMPLEMENTO: [ 1 , 2 ],
 ID_COMPOSICAO: [ 1 , 2 , 3 , 4 ]
} 

const desiredResult = [
  [1, 1, 1 ],

matheus-rossi

// Somando valores de arrays (.reduce)
const numeros2 = [1, 2, 3]

function soma (x, y) {
  return x + y
}

const somaDosNumeros2 = numeros2.reduce(soma)
console.log(somaDosNumeros2) // 6

matheus-rossi

// Objeto Inicial
const refeicaoArray = [
  { id: 1, descricao: 'Café da Manhã', calorias: 420 },
  { id: 2, descricao: 'Almoço', calorias: 580 }
]

// Removendo item no array refeicoes (.filter)
function filtro (refeicao) {
  if (refeicao.id === 2) {
    return true

matheus-rossi

// array inicial
const refeicaoArray = [
  { id: 1, descricao: 'Café da Manhã', calorias: 420 },
  { id: 2, descricao: 'Almoço', calorias: 580 }
]

const novaRefeicao = {
  id: 3,
  descricao: 'Café da Tarde',
  calorias: 280

matheus-rossi

// Atualizando item no array (.map)
const numeros = [1, 2, 3]

function dobrar (num) {
  return num * 2
}

const dobrarEs6 = num => num *2

const numerosVezesDois = numeros.map(dobrarEs6)

matheus-rossi

// Arrays Iniciais
const refeicaoArray = [
  { id: 1, descricao: 'Café da Manhã', calorias: 420 },
  { id: 2, descricao: 'Almoço', calorias: 580 }
]

const novaRefeicao = {
  id: 3,
  descricao: 'Café da Tarde',
  calorias: 280