Downloading Images from a Website with Go and goquery

In this article, we will learn how to use Go and the goquery library to download all the images from a Wikipedia page.

—-

Overview

The goal is to extract the names, breed groups, local names, and image URLs for all dog breeds listed on this Wikipedia page. We will store the image URLs, download the images and save them to a local folder.

Here are the key steps we will cover:

Import required packages
Send HTTP request to fetch the Wikipedia page
Parse the page HTML using goquery
Find the table with dog breed data using a CSS selector
Iterate through the table rows
Extract data from each column
Download images and save locally
Print/process extracted data

Let's go through each of these steps in detail.

Imports

We need these packages:

import (
  "net/http"
  "github.com/PuerkitoBio/goquery"
  "os"
)

net/http - Sends HTTP requests

goquery - Scrapes HTML/XML

os - Provides OS functionality

Send HTTP Request

To download the web page:

url := "<https://commons.wikimedia.org/wiki/List_of_dog_breeds>"

client := &http.Client{}
req, _ := http.NewRequest("GET", url, nil)

req.Header.Set("User-Agent", "Mozilla/5.0")

resp, _ := client.Do(req)

defer resp.Body.Close()

We make a GET request and set a custom user-agent header.

Parse HTML

To parse the HTML:

doc, _ := goquery.NewDocumentFromReader(resp.Body)

The goquery document represents parsed HTML/XML.

Find Breed Table

We use a CSS selector to find the table element:

table := doc.Find("table.wikitable.sortable")

This selects the

tag with the required CSS classes.

Iterate Through Rows

We loop through the rows:

table.Find("tr").Each(func(i int, s *goquery.Selection) {

  // Extract data

})

We iterate through each

element within the table.

Extract Column Data

Inside the loop, we extract the column data:

cells := s.Find("td, th")

name := cells.Eq(0).Find("a").Text()
group := cells.Eq(1).Text()

localName := cells.Eq(2).Find("span").Text()
if localName == "" {
  localName = ""
}

img := cells.Eq(3).Find("img")
photograph, _ := img.Attr("src")

We use Text() for text and Attr() for attributes.

Download Images

To download and save images:

if photograph != "" {

  response, _ := http.Get(photograph)
  defer response.Body.Close()

  f, _ := os.Create("dog_images/" + name + ".jpg")
  defer f.Close()

  io.Copy(f, response.Body)

}

We make a new GET request for the image and save it to a file.

Store Extracted Data

We store the extracted data:

names = append(names, name)
groups = append(groups, group)
localNames = append(localNames, localName)
photographs = append(photographs, photograph)

The slices can then be processed as needed.

And that's it! Here is the full code:

// Imports
import (
  "net/http"
  "github.com/PuerkitoBio/goquery"
  "os"
  "io"
)

// Slices to store data
var names []string
var groups []string
var localNames []string
var photographs []string

// HTTP request
url := "<https://commons.wikimedia.org/wiki/List_of_dog_breeds>"

client := &http.Client{}
req, _ := http.NewRequest("GET", url, nil)

req.Header.Set("User-Agent", "Mozilla/5.0")

resp, _ := client.Do(req)

defer resp.Body.Close()

// Load HTML
doc, _ := goquery.NewDocumentFromReader(resp.Body)

// Find table
table := doc.Find("table.wikitable.sortable")

// Iterate rows
table.Find("tr").Each(func(i int, s *goquery.Selection) {

  // Get cells
  cells := s.Find("td, th")

  // Extract data
  name := cells.Eq(0).Find("a").Text()
  group := cells.Eq(1).Text()

  localName := cells.Eq(2).Find("span").Text()
  if localName == "" {
    localName = ""
  }

  img := cells.Eq(3).Find("img")
  photograph, _ := img.Attr("src")

  // Download image
  if photograph != "" {

    response, _ := http.Get(photograph)
    defer response.Body.Close()

    f, _ := os.Create("dog_images/" + name + ".jpg")
    defer f.Close()

    io.Copy(f, response.Body)

  }

  // Store data
  names = append(names, name)
  groups = append(groups, group)
  localNames = append(localName, localName)
  photographs = append(photographs, photograph)

})

This provides a complete Go solution using goquery to scrape data and images from HTML tables. The same approach can apply to many websites.

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