In today’s data-driven world, information is often scattered across the web. Sometimes, we need to gather data from websites for various purposes, such as research, analysis, or automation. Go, a powerful programming language, provides us with the tools to perform web scraping and data extraction efficiently.

In this blog post, we’ll explore a Go program that demonstrates web scraping and data extraction. This program is designed to extract fixture information for a sports league from a website. Specifically, we aim to find the date of the matches and the teams that are playing. Let’s dive into the code to understand how it accomplishes this task.

The Code

package main

import (

type fixtureResult struct {
	teams     []string
	matchDate []string

func main() {
	// Open and parse the HTML file
	file, err := os.Open("./2023-ligue1-fixtures.html")
	if err != nil {
		log.Fatalf("Error opening HTML file: %v", err)
	defer file.Close()

	doc, err := html.Parse(file)
	if err != nil {
		log.Fatalf("Error parsing HTML: %v", err)

	// Find and print contents of li.MatchCardsList_matchCard__DBsrE

func findAndPrintMatchCardContents(node *html.Node) {
	if node.Type == html.ElementNode && node.Data == "li" {
		for _, attr := range node.Attr {
			if attr.Key == "class" && attr.Val == "MatchCardsList_matchCard__DBsrE" {
				anchor := node.FirstChild
				for _, attr := range anchor.Attr {
					if attr.Key == "href" {
						// Extract fixture information

	// Recursively process child nodes
	for child := node.FirstChild; child != nil; child = child.NextSibling {

func getFixtureInfo(fixturePath string) {
	// Build the full URL
	link := fmt.Sprintf(``, fixturePath)
	resp, err := http.Get(link)
	if err != nil {
	defer resp.Body.Close()

	// Create a goquery document from the response body
	doc, err := goquery.NewDocumentFromReader(resp.Body)
	if err != nil {

	var date []string
	var teams []string

	// Find and extract the match date
	doc.Find(".MatchScore_numeric__ke8YT").Each(func(i int, s *goquery.Selection) {
		date = append(date, s.Text())

	// Find and extract the team names
	doc.Find(".MatchScoreTeam_name__zzQrD").Each(func(i int, s *goquery.Selection) {
		teams = append(teams, s.Text())

	// Create a fixtureResult struct to store the extracted data
	fixture := fixtureResult{
		teams:     teams,
		matchDate: date,

	// Print the extracted fixture information
	fmt.Printf("%+v\n", fixture)

How It Works

Now, let’s break down how this Go program accomplishes its goal:

  1. Opening and Parsing HTML: The program starts by opening an HTML file named 2023-xxxx-fixtures.html. It uses the os and packages to do this. The HTML content is loaded into a structured format for parsing.

  2. Searching for Match Cards: The findAndPrintMatchCardContents function is responsible for searching for specific HTML elements (li) with the class name MatchCardsList_matchCard__DBsrE. When a matching element is found, the program extracts the href attribute from the anchor element within that li. This href attribute contains a path to another web page with detailed fixture information.

  3. Fetching Detailed Fixture Information: The getFixtureInfo function constructs the full URL for the detailed fixture information, sends an HTTP GET request to that URL, and creates a goquery document from the response body. Using goquery simplifies HTML parsing and querying.

  4. Extracting Data: The program searches for HTML elements with class names MatchScore_numeric__ke8YT (which contains match dates) and MatchScoreTeam_name__zzQrD (which contains team names). It extracts this data and stores it in slices.

  5. Printing Results: Finally, the program creates a fixtureResult struct to store the extracted data and prints it in a structured format.

Ways to improve

A very powerful concept that is commonly used in golang is concurrency, currently my code retrieves data serially which can be slow depending on the volume of data. One way I can expand on this script is to retrieve fixture data using a group of workers dispatched in parallel.


This Go program showcases how to perform web scraping and data extraction efficiently. By leveraging Go’s powerful packages like, we can parse HTML, navigate complex structures, and extract valuable information from websites. Web scraping is a versatile technique with applications in various domains, from data analysis to automation. I might end up using this data to create an iOS app or something who knows?!?!?!?! See ya next time!