Juan Manuel Garcia jmg

## FireBaseAuthGuard.tsx
import { useEffect, useState } from "react";
import { getAuth } from "@firebase/auth";
import Router from "next/router";

const auth = getAuth()

export const AuthGuard = ({ children, redirectUrl }: any) => {

    const [isLoading, setIsLoading] = useState(true);
    const [isAuthenticated, setIsAuthenticated] = useState(false);

## child.html
<!DOCTYPE html>
<html>
<head>
    <title>Child Window</title>

    <script type="text/javascript">

        //esta funcion escucha eventos desde parent.html para recibir los datos del archivo
        window.addEventListener('message', function(e) {


## parent.html
<!DOCTYPE html>
<html>
<head>
    <title>Parent Window</title>
</head>
<body>

    <div>
        <input onchange="readFileContent(this)" type="file" id="input-file">
    </div>

## buildFormulaWithTrendAndSeason.R
buildFormula <- function(dataset, LTerms, useTrend=FALSE, useSeason=FALSE) {

  lLen <- length(LTerms)

  for (i in 1:lLen)
    assign(paste("fact", i, sep=""), L(dataset, LTerms[i]))

  factors = array()
  for (i in 1:lLen)
    factors[i] <- paste("fact",  i , sep="")

## build_formula.R
buildFormula <- function(dataset, terms_array) {
  for (i in 1:length(terms_array))
    assign(paste("fact", i, sep=""), L(dataset, terms_array[i]))

  factors = array()
  for (i in 1:length(terms_array))
    factors[i] <- paste("fact", i, sep="")

  form = as.formula(paste("dataset~", paste(factors, collapse="+")))
  return(form)

## black_jack.py
import random
import time


class Card(object):

    def __init__(self, number, kind):

        self.number = number
        self.kind = kind

## quantreg_forecast_example.R
library(quantreg)

airq <- airquality
#fit the quantile regression with Ozone formula
fit <- rq(Ozone ~ ., data=airquality)

#create a new dataframe with the values to forecast the Ozone
newdata <- data.frame(Solar.R=201:203, Wind=8:10, Temp=82:84, Month=9, Day=20:22)
#newdata is the parameter to tell the predict function to use the values for making the forecast
fore <- predict(fit, newdata=newdata)

## get_all_sum_combinations.py
import itertools

def get_all_sum_combinations(elements):
    """
        Gets all the combinations of the sum of a list of elements.
    """
    combinations = []
    for i in range(1, len(elements) + 1):
        for subset in itertools.combinations(elements, r=i):
            result = sum(subset)

## carrusel.html
<!DOCTYPE html>
<html lang="en">
<head>
    <title>Carrusel Ejemplo</title>
    <meta charset="utf-8">
    <meta name="viewport" content="width=device-width, initial-scale=1">

    <!-- Archivos de bootstrap -->
    <link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/3.3.7/css/bootstrap.min.css">
    <script src="https://ajax.googleapis.com/ajax/libs/jquery/3.1.1/jquery.min.js"></script>

## celery_check_db_connection.py
from django.db import connection
from functools import wraps
def check_db_connection(f):
    @wraps(f)
    def inner(*args, **kargs):
        try:
            connection.connection.ping()
        except:
            connection.close()
        return f(*args, **kargs)
	import { useEffect, useState } from "react";
	import { getAuth } from "@firebase/auth";
	import Router from "next/router";

	const auth = getAuth()

	export const AuthGuard = ({ children, redirectUrl }: any) => {

	const [isLoading, setIsLoading] = useState(true);
	const [isAuthenticated, setIsAuthenticated] = useState(false);
	<!DOCTYPE html>
	<html>
	<head>
	<title>Child Window</title>

	<script type="text/javascript">

	//esta funcion escucha eventos desde parent.html para recibir los datos del archivo
	window.addEventListener('message', function(e) {
	buildFormula <- function(dataset, LTerms, useTrend=FALSE, useSeason=FALSE) {

	lLen <- length(LTerms)

	for (i in 1:lLen)
	assign(paste("fact", i, sep=""), L(dataset, LTerms[i]))

	factors = array()
	for (i in 1:lLen)
	factors[i] <- paste("fact", i , sep="")
	buildFormula <- function(dataset, terms_array) {
	for (i in 1:length(terms_array))
	assign(paste("fact", i, sep=""), L(dataset, terms_array[i]))

	factors = array()
	for (i in 1:length(terms_array))
	factors[i] <- paste("fact", i, sep="")

	form = as.formula(paste("dataset~", paste(factors, collapse="+")))
	return(form)
	import random
	import time


	class Card(object):

	def __init__(self, number, kind):

	self.number = number
	self.kind = kind
	library(quantreg)

	airq <- airquality
	#fit the quantile regression with Ozone formula
	fit <- rq(Ozone ~ ., data=airquality)

	#create a new dataframe with the values to forecast the Ozone
	newdata <- data.frame(Solar.R=201:203, Wind=8:10, Temp=82:84, Month=9, Day=20:22)
	#newdata is the parameter to tell the predict function to use the values for making the forecast
	fore <- predict(fit, newdata=newdata)
	import itertools

	def get_all_sum_combinations(elements):
	"""
	Gets all the combinations of the sum of a list of elements.
	"""
	combinations = []
	for i in range(1, len(elements) + 1):
	for subset in itertools.combinations(elements, r=i):
	result = sum(subset)
	<!DOCTYPE html>
	<html lang="en">
	<head>
	<title>Carrusel Ejemplo</title>
	<meta charset="utf-8">
	<meta name="viewport" content="width=device-width, initial-scale=1">

	<!-- Archivos de bootstrap -->
	<link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/3.3.7/css/bootstrap.min.css">
	<script src="https://ajax.googleapis.com/ajax/libs/jquery/3.1.1/jquery.min.js"></script>
	from django.db import connection
	from functools import wraps
	def check_db_connection(f):
	@wraps(f)
	def inner(args, *kargs):
	try:
	connection.connection.ping()
	except:
	connection.close()
	return f(args, *kargs)