Jim Michael

Jim Michael


Puppeteer Tutorial - Getting Started using Puppeteer

Browser developer tools provide an amazing array of options for delving under the hood of websites and web apps. These capabilities can be further enhanced and automated by third-party tools. In this article, we’ll look at Puppeteer, a Node-based library for use with Chrome/Chromium.

The puppeteer website describes Puppeteer as

a Node library which provides a high-level API to control Chrome or Chromium over the DevTools Protocol. Puppeteer runs headless by default, but can be configured to run full (non-headless) Chrome or Chromium.

Puppeteer is made by the team behind Google Chrome, so you can be pretty sure it will be well maintained. It lets us perform common actions on the Chromium browser, programmatically through JavaScript, via a simple and easy-to-use API.

With Puppeteer, you can:

  • scrape websites
  • generate screenshots of websites including SVG and Canvas
  • create PDFs of websites
  • crawl an SPA (single-page application)
  • access web pages and extract information using the standard DOM API
  • generate pre-rendered content — that is, server-side rendering
  • automate form submission
  • automate performance analysis
  • automate UI testing like Cypress
  • test chrome extensions

Puppeteer does nothing new that Selenium, PhantomJS (which is now deprecated), and the like do, but it provides a simple and easy-to-use API and provides a great abstraction so we don’t have to worry about the nitty-gritty details when dealing with it.

It’s also actively maintained so we get all the new features of ECMAScript as Chromium supports it.


For this tutorial, you need a basic knowledge of JavaScript, ES6+ and Node.js.

You must also have installed the latest version of Node.js.

We’ll be using yarn throughout this tutorial. If you don’t have yarn already installed, install it from here.

To make sure we’re on the same page, these are the versions used in this tutorial:

  • Node 12.12.0
  • yarn 1.19.1
  • puppeteer 2.0.0


To use Puppeteer in your project, run the following command in the terminal:

$ yarn add puppeteer

Note: when you install Puppeteer, it downloads a recent version of Chromium (~170MB macOS, ~282MB Linux, ~280MB Win) that is guaranteed to work with the API. To skip the download, see Environment variables.

If you don’t need to download Chromium, then you can install puppeteer-core:

$ yarn add puppeteer-core

puppeteer-core is intended to be a lightweight version of Puppeteer for launching an existing browser installation or for connecting to a remote one. Be sure that the version of puppeteer-core you install is compatible with the browser you intend to connect to.

Note: puppeteer-core is only published from version 1.7.0.


Puppeteer requires at least Node v6.4.0, but we’re going to use async/await, which is only supported in Node v7.6.0 or greater, so make sure to update your Node.js to the latest version to get all the goodies.

Let’s dive into some practical examples using Puppeteer. In this tutorial, we’ll be:

  1. generating a screenshot of Unsplash using Puppeteer
  2. creating a PDF of Hacker News using Puppeteer
  3. signing in to Facebook using Puppeteer

1. Generate a Screenshot of Unsplash using Puppeteer

It’s really easy to do this with Puppeteer. Go ahead and create a screenshot.js file in the root of your project. Then paste in the following code:

const puppeteer = require('puppeteer')

const main = async () => {
  const browser = await puppeteer.launch()
  const page = await browser.newPage()
  await page.goto('https://unsplash.com')
  await page.screenshot({ path: 'unsplash.png' })

  await browser.close()


Firstly, we require the puppeteer package. Then we call the launch method on it that initializes the instance. This method is asynchronous as it returns a Promise. So we await for it to get the browser instance.

Then we call newPage on it and go to Unsplash and take a screenshot of it and save the screenshot as unsplash.png.

Now go ahead and run the above code in the terminal by typing:

$ node screenshot

Unsplash - 800px x 600px resolution

Now after 5–10 seconds you’ll see an unsplash.png file in your project that contains the screenshot of Unsplash. Notice that the viewport is set to 800px x 600px as Puppeteer sets this as the initial page size, which defines the screenshot size. The page size can be customized with Page.setViewport().

Let’s change the viewport to be 1920px x 1080px. Insert the following code before the goto method:

await page.setViewport({
  width: 1920,
  height: 1080,
  deviceScaleFactor: 1,

Now go ahead and also change the filename from unsplash.png to unsplash2.png in the screenshot method like so:

await page.screenshot({ path: 'unsplash2.png' })

The whole screenshot.js file should now look like this:

const puppeteer = require('puppeteer')

const main = async () => {
  const browser = await puppeteer.launch()
  const page = await browser.newPage()
  await page.setViewport({
    width: 1920,
    height: 1080,
    deviceScaleFactor: 1,
  await page.goto('https://unsplash.com')
  await page.screenshot({ path: 'unsplash2.png' })

  await browser.close()


Unsplash - 1920px x 1080px

2. Create PDF of Hacker News using Puppeteer

Now create a file named pdf.js and paste the following code into it:

const puppeteer = require('puppeteer')

const main = async () => {
  const browser = await puppeteer.launch()
  const page = await browser.newPage()
  await page.goto('https://news.ycombinator.com', { waitUntil: 'networkidle2' })
  await page.pdf({ path: 'hn.pdf', format: 'A4' })

  await browser.close()


We’ve only changed two lines from the screenshot code.

Firstly, we’ve replaced the URL with Hacker News and then added networkidle2:

await page.goto('https://news.ycombinator.com', { waitUntil: 'networkidle2' })

networkidle2 comes in handy for pages that do long polling or any other side activity and considers navigation to be finished when there are no more than two network connections for at least 500ms.

Then we called the pdf method to create a PDf and called it hn.pdf and we formatted it to be A4 size:

await page.pdf({ path: 'hn.pdf', format: 'A4' })

That’s it. We can now run the file to generate a PDF of Hacker News. Let’s go ahead and run the following command in the terminal:

$ node pdf

This will generate a PDF file called hn.pdf in the root directory of the project in A4 size.

3. Sign In to Facebook Using Puppeteer

Create a new file called signin.js with the following code:

const puppeteer = require('puppeteer')

const SECRET_EMAIL = 'example@gmail.com'
const SECRET_PASSWORD = 'secretpass123'

const main = async () => {
  const browser = await puppeteer.launch({
    headless: false,
  const page = await browser.newPage()
  await page.goto('https://facebook.com', { waitUntil: 'networkidle2' })
  await page.waitForSelector('#login_form')
  await page.type('input#email', SECRET_EMAIL)
  await page.type('input#pass', SECRET_PASSWORD)
  await page.click('#loginbutton')
  // await browser.close()


We’ve created two variables, SECRET_EMAIL and SECRET_PASSWORD, which should be replaced by your email and password of Facebook.

We then launch the browser and set headless mode to false to launch a full version of Chromium browser.

Then we go to Facebook and wait until everything is loaded.

On Facebook, there’s a #login_form selector that can be accessed via DevTools. This selector contains the login form, so we wait for it using waitForSelector method.

Then we have to type our email and password, so we grab the selectors input#email and input#pass from DevTools and pass in our SECRET_EMAIL and SECRET_PASSWORD.

After that, we click the #loginbutton to log in to Facebook.

The last line is commented out so that we see the whole process of typing email and password and clicking the login button.

Go ahead and run the code by typing the following in the terminal:

$ node signin

This will launch a whole Chromium browser and then log in to Facebook.


In this tutorial, we made a project that creates a screenshot of any given page within a specified viewport. We also built a project where we can create a PDF of any website. We then programmatically managed to sign in to Facebook.

Puppeteer recently released version 2, and it’s a nice piece of software to automate trivial tasks with a simple and easy-to-use API.

You can learn more about Puppeteer on its official website. The docs are very good, with tons of examples, and everything is well documented.

Now go ahead and automate boring tasks in your day-to-day life with Puppeteer.

#Puppeteer #javascript

What is GEEK

Buddha Community

Puppeteer Tutorial - Getting Started using Puppeteer
Willie  Beier

Willie Beier


Tutorial: Getting Started with R and RStudio

In this tutorial we’ll learn how to begin programming with R using RStudio. We’ll install R, and RStudio RStudio, an extremely popular development environment for R. We’ll learn the key RStudio features in order to start programming in R on our own.

If you already know how to use RStudio and want to learn some tips, tricks, and shortcuts, check out this Dataquest blog post.

Table of Contents

#data science tutorials #beginner #r tutorial #r tutorials #rstats #tutorial #tutorials

Marcus  Flatley

Marcus Flatley


Getting Started with R Markdown — Guide and Cheatsheet

In this blog post, we’ll look at how to use R Markdown. By the end, you’ll have the skills you need to produce a document or presentation using R Mardown, from scratch!

We’ll show you how to convert the default R Markdown document into a useful reference guide of your own. We encourage you to follow along by building out your own R Markdown guide, but if you prefer to just read along, that works, too!

R Markdown is an open-source tool for producing reproducible reports in R. It enables you to keep all of your code, results, plots, and writing in one place. R Markdown is particularly useful when you are producing a document for an audience that is interested in the results from your analysis, but not your code.

R Markdown is powerful because it can be used for data analysis and data science, collaborating with others, and communicating results to decision makers. With R Markdown, you have the option to export your work to numerous formats including PDF, Microsoft Word, a slideshow, or an HTML document for use in a website.

r markdown tips, tricks, and shortcuts

Turn your data analysis into pretty documents with R Markdown.

We’ll use the RStudio integrated development environment (IDE) to produce our R Markdown reference guide. If you’d like to learn more about RStudio, check out our list of 23 awesome RStudio tips and tricks!

Here at Dataquest, we love using R Markdown for coding in R and authoring content. In fact, we wrote this blog post in R Markdown! Also, learners on the Dataquest platform use R Markdown for completing their R projects.

We included fully-reproducible code examples in this blog post. When you’ve mastered the content in this post, check out our other blog post on R Markdown tips, tricks, and shortcuts.

Okay, let’s get started with building our very own R Markdown reference document!

R Markdown Guide and Cheatsheet: Quick Navigation

1. Install R Markdown

R Markdown is a free, open source tool that is installed like any other R package. Use the following command to install R Markdown:


Now that R Markdown is installed, open a new R Markdown file in RStudio by navigating to File > New File > R Markdown…. R Markdown files have the file extension “.Rmd”.

2. Default Output Format

When you open a new R Markdown file in RStudio, a pop-up window appears that prompts you to select output format to use for the document.

New Document

The default output format is HTML. With HTML, you can easily view it in a web browser.

We recommend selecting the default HTML setting for now — it can save you time! Why? Because compiling an HTML document is generally faster than generating a PDF or other format. When you near a finished product, you change the output to the format of your choosing and then make the final touches.

One final thing to note is that the title you give your document in the pop-up above is not the file name! Navigate to File > Save As.. to name, and save, the document.

#data science tutorials #beginner #r #r markdown #r tutorial #r tutorials #rstats #rstudio #tutorial #tutorials

Why Use WordPress? What Can You Do With WordPress?

Can you use WordPress for anything other than blogging? To your surprise, yes. WordPress is more than just a blogging tool, and it has helped thousands of websites and web applications to thrive. The use of WordPress powers around 40% of online projects, and today in our blog, we would visit some amazing uses of WordPress other than blogging.
What Is The Use Of WordPress?

WordPress is the most popular website platform in the world. It is the first choice of businesses that want to set a feature-rich and dynamic Content Management System. So, if you ask what WordPress is used for, the answer is – everything. It is a super-flexible, feature-rich and secure platform that offers everything to build unique websites and applications. Let’s start knowing them:

1. Multiple Websites Under A Single Installation
WordPress Multisite allows you to develop multiple sites from a single WordPress installation. You can download WordPress and start building websites you want to launch under a single server. Literally speaking, you can handle hundreds of sites from one single dashboard, which now needs applause.
It is a highly efficient platform that allows you to easily run several websites under the same login credentials. One of the best things about WordPress is the themes it has to offer. You can simply download them and plugin for various sites and save space on sites without losing their speed.

2. WordPress Social Network
WordPress can be used for high-end projects such as Social Media Network. If you don’t have the money and patience to hire a coder and invest months in building a feature-rich social media site, go for WordPress. It is one of the most amazing uses of WordPress. Its stunning CMS is unbeatable. And you can build sites as good as Facebook or Reddit etc. It can just make the process a lot easier.
To set up a social media network, you would have to download a WordPress Plugin called BuddyPress. It would allow you to connect a community page with ease and would provide all the necessary features of a community or social media. It has direct messaging, activity stream, user groups, extended profiles, and so much more. You just have to download and configure it.
If BuddyPress doesn’t meet all your needs, don’t give up on your dreams. You can try out WP Symposium or PeepSo. There are also several themes you can use to build a social network.

3. Create A Forum For Your Brand’s Community
Communities are very important for your business. They help you stay in constant connection with your users and consumers. And allow you to turn them into a loyal customer base. Meanwhile, there are many good technologies that can be used for building a community page – the good old WordPress is still the best.
It is the best community development technology. If you want to build your online community, you need to consider all the amazing features you get with WordPress. Plugins such as BB Press is an open-source, template-driven PHP/ MySQL forum software. It is very simple and doesn’t hamper the experience of the website.
Other tools such as wpFoRo and Asgaros Forum are equally good for creating a community blog. They are lightweight tools that are easy to manage and integrate with your WordPress site easily. However, there is only one tiny problem; you need to have some technical knowledge to build a WordPress Community blog page.

4. Shortcodes
Since we gave you a problem in the previous section, we would also give you a perfect solution for it. You might not know to code, but you have shortcodes. Shortcodes help you execute functions without having to code. It is an easy way to build an amazing website, add new features, customize plugins easily. They are short lines of code, and rather than memorizing multiple lines; you can have zero technical knowledge and start building a feature-rich website or application.
There are also plugins like Shortcoder, Shortcodes Ultimate, and the Basics available on WordPress that can be used, and you would not even have to remember the shortcodes.

5. Build Online Stores
If you still think about why to use WordPress, use it to build an online store. You can start selling your goods online and start selling. It is an affordable technology that helps you build a feature-rich eCommerce store with WordPress.
WooCommerce is an extension of WordPress and is one of the most used eCommerce solutions. WooCommerce holds a 28% share of the global market and is one of the best ways to set up an online store. It allows you to build user-friendly and professional online stores and has thousands of free and paid extensions. Moreover as an open-source platform, and you don’t have to pay for the license.
Apart from WooCommerce, there are Easy Digital Downloads, iThemes Exchange, Shopify eCommerce plugin, and so much more available.

6. Security Features
WordPress takes security very seriously. It offers tons of external solutions that help you in safeguarding your WordPress site. While there is no way to ensure 100% security, it provides regular updates with security patches and provides several plugins to help with backups, two-factor authorization, and more.
By choosing hosting providers like WP Engine, you can improve the security of the website. It helps in threat detection, manage patching and updates, and internal security audits for the customers, and so much more.

Read More

#use of wordpress #use wordpress for business website #use wordpress for website #what is use of wordpress #why use wordpress #why use wordpress to build a website

Tutorial: Loading and Cleaning Data with R and the tidyverse

1. Characteristics of Clean Data and Messy Data

What exactly is clean data? Clean data is accurate, complete, and in a format that is ready to analyze. Characteristics of clean data include data that are:

  • Free of duplicate rows/values
  • Error-free (e.g. free of misspellings)
  • Relevant (e.g. free of special characters)
  • The appropriate data type for analysis
  • Free of outliers (or only contain outliers have been identified/understood), and
  • Follows a “tidy data” structure

Common symptoms of messy data include data that contain:

  • Special characters (e.g. commas in numeric values)
  • Numeric values stored as text/character data types
  • Duplicate rows
  • Misspellings
  • Inaccuracies
  • White space
  • Missing data
  • Zeros instead of null values

2. Motivation

In this blog post, we will work with five property-sales datasets that are publicly available on the New York City Department of Finance Rolling Sales Data website. We encourage you to download the datasets and follow along! Each file contains one year of real estate sales data for one of New York City’s five boroughs. We will work with the following Microsoft Excel files:

  • rollingsales_bronx.xls
  • rollingsales_brooklyn.xls
  • rollingsales_manhattan.xls
  • rollingsales_queens.xls
  • rollingsales_statenisland.xls

As we work through this blog post, imagine that you are helping a friend launch their home-inspection business in New York City. You offer to help them by analyzing the data to better understand the real-estate market. But you realize that before you can analyze the data in R, you will need to diagnose and clean it first. And before you can diagnose the data, you will need to load it into R!

3. Load Data into R with readxl

Benefits of using tidyverse tools are often evident in the data-loading process. In many cases, the tidyverse package readxl will clean some data for you as Microsoft Excel data is loaded into R. If you are working with CSV data, the tidyverse readr package function read_csv() is the function to use (we’ll cover that later).

Let’s look at an example. Here’s how the Excel file for the Brooklyn borough looks:

The Brooklyn Excel file

Now let’s load the Brooklyn dataset into R from an Excel file. We’ll use the readxlpackage. We specify the function argument skip = 4 because the row that we want to use as the header (i.e. column names) is actually row 5. We can ignore the first four rows entirely and load the data into R beginning at row 5. Here’s the code:

library(readxl) # Load Excel files
brooklyn <- read_excel("rollingsales_brooklyn.xls", skip = 4)

Note we saved this dataset with the variable name brooklyn for future use.

4. View the Data with tidyr::glimpse()

The tidyverse offers a user-friendly way to view this data with the glimpse() function that is part of the tibble package. To use this package, we will need to load it for use in our current session. But rather than loading this package alone, we can load many of the tidyverse packages at one time. If you do not have the tidyverse collection of packages, install it on your machine using the following command in your R or R Studio session:


Once the package is installed, load it to memory:


Now that tidyverse is loaded into memory, take a “glimpse” of the Brooklyn dataset:

## Observations: 20,185
## Variables: 21
## $ BOROUGH <chr> "3", "3", "3", "3", "3", "3", "…
## $ `TAX CLASS AT PRESENT` <chr> "1", "1", "1", "1", "1", "1", "…
## $ BLOCK <dbl> 6359, 6360, 6364, 6367, 6371, 6…
## $ LOT <dbl> 70, 48, 74, 24, 19, 32, 65, 20,…
## $ `EASE-MENT` <lgl> NA, NA, NA, NA, NA, NA, NA, NA,…
## $ `BUILDING CLASS AT PRESENT` <chr> "S1", "A5", "A5", "A9", "A9", "…
## $ ADDRESS <chr> "8684 15TH AVENUE", "14 BAY 10T…
## $ `APARTMENT NUMBER` <chr> NA, NA, NA, NA, NA, NA, NA, NA,…
## $ `ZIP CODE` <dbl> 11228, 11228, 11214, 11214, 112…
## $ `RESIDENTIAL UNITS` <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1…
## $ `COMMERCIAL UNITS` <dbl> 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
## $ `TOTAL UNITS` <dbl> 2, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1…
## $ `LAND SQUARE FEET` <dbl> 1933, 2513, 2492, 1571, 2320, 3…
## $ `GROSS SQUARE FEET` <dbl> 4080, 1428, 972, 1456, 1566, 22…
## $ `YEAR BUILT` <dbl> 1930, 1930, 1950, 1935, 1930, 1…
## $ `TAX CLASS AT TIME OF SALE` <chr> "1", "1", "1", "1", "1", "1", "…
## $ `BUILDING CLASS AT TIME OF SALE` <chr> "S1", "A5", "A5", "A9", "A9", "…
## $ `SALE PRICE` <dbl> 1300000, 849000, 0, 830000, 0, …
## $ `SALE DATE` <dttm> 2020-04-28, 2020-03-18, 2019-0…

The glimpse() function provides a user-friendly way to view the column names and data types for all columns, or variables, in the data frame. With this function, we are also able to view the first few observations in the data frame. This data frame has 20,185 observations, or property sales records. And there are 21 variables, or columns.

#data science tutorials #beginner #r #r tutorial #r tutorials #rstats #tidyverse #tutorial #tutorials

Jeromy  Lowe

Jeromy Lowe


Data Visualization in R with ggplot2: A Beginner Tutorial

A famous general is thought to have said, “A good sketch is better than a long speech.” That advice may have come from the battlefield, but it’s applicable in lots of other areas — including data science. “Sketching” out our data by visualizing it using ggplot2 in R is more impactful than simply describing the trends we find.

This is why we visualize data. We visualize data because it’s easier to learn from something that we can see rather than read. And thankfully for data analysts and data scientists who use R, there’s a tidyverse package called ggplot2 that makes data visualization a snap!

In this blog post, we’ll learn how to take some data and produce a visualization using R. To work through it, it’s best if you already have an understanding of R programming syntax, but you don’t need to be an expert or have any prior experience working with ggplot2

#data science tutorials #beginner #ggplot2 #r #r tutorial #r tutorials #rstats #tutorial #tutorials