Link to more interesting example: keithgalli.github.io/web-scraping/webpage.html A Header. Some italicized text. See full list on wiseowl.co.uk.

If you’re here, you probably already know what web scraping is. But on the off chance that you just happened to stumble upon this article, let’s start with a quick refresher on web scraping, and then we’ll move on to goquery.

Web Scraping – a quick introduction

Web Scraping is the automated method of extracting human-readable data output from a website. The specific data is gathered and copied into a central local database for later retrieval or analysis. There is a built-in library in the Go language for scraping HTML web pages, but often there are some methods that are used by websites to prevent web scraping – because it could potentially cause a denial-of-service, incur bandwidth costs to yourself or the website provider, overload log files, or otherwise stress computing resources.

However, there are web scraping techniques like DOM parsing, computer vision and NLP to simulate human browsing on web page content.

GoQuery is a library created by Martin Angers and brings a syntax and a set of features similar to jQuery to the Go language.

jQuery is a fast, small, and feature-rich JavaScript library. It makes things like HTML document traversal and manipulation, event handling, animation, and Ajax much simpler with an easy-to-use API that works across a multitude of browsers.

GoQuery makes it easier to parse HTML websites than the default net/html package, using DOM (Document Object Model) parsing.

Installing goquery

Let’s download the package using “go get“.

A concise manual can be brought up by using the “go doc goquery” command.

GoLang Web Scraping using goquery

Create a new .go document in your preferred IDE or text editor. Mine’s titled “goquery_program.go”, and you may choose to do the same:

We’ll begin by importing json and goquery, along with ‘log‘ to log any errors. We create a struct called Article with the Title, URL, and Category as metadata of the article.

Within the function main(), dispatch a GET client request to the URL journaldev.com for scraping the html.

We have already fetched our full html source code from the website. We can dump it to our terminal using the “os” package.

This will output the whole html file along with all tags in the terminal. I’m working on Linux Ubuntu 20.04, so the output display may vary with system.

It also gave a secondary print statement along with a notification that the page was optimized by LiteSpeed Cache:

Number of bytes copied to STDOUT: 151402

Now, let’s store this response in a reader file using goquery:

Now we need to use the Find() function, which takes in a tag, and inputs that as an argument into Each(). The Each function is typically used with an argument i int, and the selection for the specified tag. On clicking “inspect” in the JournalDev website, I saw that my content was in <p> tags. So I defined my Find with only the name of the tag:

• The “fmt” library has been used to print the text.
• The “next” was just to check if the output was being received(like, for debugging) but I think it looks good with the final output.
• The “%d” and “%s” are string format specifiers for Printf.

Web Scraping Example Output

The best thing about coding is the satisfaction when your code outputs exactly what you need, and I think this was to my utmost satisfaction:

I tried to keep this article as generalised as possible when dealing with websites. This method should work for you no matter what website you’re trying to parse !

With that, I will leave you…until next time.

References

You probably know how to use basic functions in Excel. It’s easy to do things like sorting, applying filters, making charts, and outlining data with Excel. You even can perform advanced data analysis using pivot and regression models. It becomes an easy job when the live data turns into a structured format. The problem is, how can we extract scalable data and put it into Excel? This can be tedious if you doing it manually by typing, searching, copying and pasting repetitively. Instead, you can achieve automated data scraping from websites to excel.

In this article, I will introduce several ways to save your time and energy to scrape web data into Excel.

Disclaimer:

There many other ways to scrape from websites using programming languages like PHP, Python, Perl, Ruby and etc. Here we just talk about how to scrape data from websites into excel for non-coders.

Getting web data using Excel Web Queries

Except for transforming data from a web page manually by copying and pasting, Excel Web Queries is used to quickly retrieve data from a standard web page into an Excel worksheet. It can automatically detect tables embedded in the web page's HTML. Excel Web queries can also be used in situations where a standard ODBC(Open Database Connectivity) connection gets hard to create or maintain. You can directly scrape a table from any website using Excel Web Queries.

The process boils down to several simple steps (Check out this article):

1. Go to Data > Get External Data > From Web

2. A browser window named “New Web Query” will appear

3. In the address bar, write the web address

(picture from excel-university.com)

4. The page will load and will show yellow icons against data/tables.

5. Select the appropriate one

6. Press the Import button.

Now you have the web data scraped into the Excel Worksheet - perfectly arranged in rows and columns as you like.

Web Scraping With Python

Getting web data using Excel VBA

Web Scraping Software

Most of us would use formula's in Excel(e.g. =avg(...), =sum(...), =if(...), etc.) a lot, but less familiar with the built-in language - Visual Basic for Application a.k.a VBA. It’s commonly known as “Macros” and such Excel files are saved as a **.xlsm. Before using it, you need to first enable the Developer tab in the ribbon (right click File -> Customize Ribbon -> check Developer tab). Then set up your layout. In this developer interface, you can write VBA code attached to various events. Click HERE (https://msdn.microsoft.com/en-us/library/office/ee814737(v=office.14).aspx) to getting started with VBA in excel 2010.

Using Excel VBA is going to be a bit technical - this is not very friendly for non-programmers among us. VBA works by running macros, step-by-step procedures written in Excel Visual Basic. To scrape data from websites to Excel using VBA, we need to build or get some VBA script to send some requests to web pages and get returned data from these web pages. It’s common to use VBA with XMLHTTP and regular expressions to parse the web pages. For Windows, you can use VBA with WinHTTP or InternetExplorer to scrape data from websites to Excel.

With some patience and some practice, you would find it worthwhile to learn some Excel VBA code and some HTML knowledge to make your web scraping into Excel much easier and more efficient for automating the repetitive work. There’s a plentiful amount of material and forums for you to learn how to write VBA code.

Automated Web Scraping Tools

For someone who is looking for a quick tool to scrape data off pages to Excel and doesn’t want to set up the VBA code yourself, I strongly recommend automated web scraping tools like Octoparse to scrape data for your Excel Worksheet directly or via API. There is no need to learn to program. You can pick one of those web scraping freeware from the list, and get started with extracting data from websites immediately and exporting the scraped data into Excel. Different web scraping tool has its pros and cons and you can choose the perfect one to fit your needs. The below video shows how to leverage an automated web scraping tool to extract web data to excel efficiently.

Web Scraping Html Table

Check out this post and try out these TOP 30 free web scraping tools

Outsource Your Web Scraping Project

If time is your most valuable asset and you want to focus on your core businesses, outsourcing such complicated web scraping work to a proficient web scraping team that has experience and expertise would be the best option. It’s difficult to scrape data from websites due to the fact that the presence of anti-scraping bots will restrain the practice of web scraping. A proficient web scraping team would help you get data from websites in a proper way and deliver structured data to you in an Excel sheet, or in any format you need.

Read Latest Customer Stories: How Web Scraping Helps Business of All Sizes

Web Scraping Software Comparison

日本語記事：Webデータを活用！WebサイトからデータをExcelに取り込む方法
Webスクレイピングについての記事は 公式サイトでも読むことができます。
Artículo en español: Scraping de Datos del Sitio Web a Excel
También puede leer artículos de web scraping en el Website Oficial