Home Backend Development Golang Build high-performance concurrent crawlers using Go and Goroutines

Build high-performance concurrent crawlers using Go and Goroutines

Jul 21, 2023 pm 08:03 PM
go (programming language) goroutines (concurrent programming) Crawler (web crawling data)

Using Go and Goroutines to build high-performance concurrent crawlers

In today's Internet era, information is growing explosively, and a large amount of web content is available for us to browse. For developers, obtaining this information and conducting further analysis is an important task. And crawlers are the tools used to achieve this goal. This article will introduce how to use Go language and Goroutines to build high-performance concurrent crawlers.

Go language is an open source programming language developed by Google. It is known for its minimalist syntax and powerful performance. Goroutines are a lightweight thread in the Go language that can be used to implement concurrent operations.

Before we start writing the crawler, we need to prepare two necessary libraries: net/http and golang.org/x/net/html. The former is used to send HTTP requests and receive HTTP responses, and the latter is used to parse HTML documents.

The following is a simple example that demonstrates how to use Go and Goroutines to write a concurrent crawler:

package main

import (
    "fmt"
    "net/http"
    "golang.org/x/net/html"
)

func main() {
    urls := []string{
        "https://www.example.com/page1",
        "https://www.example.com/page2",
        "https://www.example.com/page3",
    }

    results := make(chan string)

    for _, url := range urls {
        go func(url string) {
            body, err := fetch(url)
            if err != nil {
                fmt.Println(err)
                return
            }

            links := extractLinks(body)
            for _, link := range links {
                results <- link
            }
        }(url)
    }

    for i := 0; i < len(urls); i++ {
        fmt.Println(<-results)
    }
}

func fetch(url string) (string, error) {
    resp, err := http.Get(url)
    if err != nil {
        return "", err
    }
    defer resp.Body.Close()

    body, err := ioutil.ReadAll(resp.Body)
    if err != nil {
        return "", err
    }

    return string(body), nil
}

func extractLinks(body string) []string {
    links := []string{}
    doc, err := html.Parse(strings.NewReader(body))
    if err != nil {
        return links
    }

    var extract func(*html.Node)
    extract = func(n *html.Node) {
        if n.Type == html.ElementNode && n.Data == "a" {
            for _, attr := range n.Attr {
                if attr.Key == "href" {
                    links = append(links, attr.Val)
                    break
                }
            }
        }

        for c := n.FirstChild; c != nil; c = c.NextSibling {
            extract(c)
        }
    }

    extract(doc)
    return links
}
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In the above code, we first define a urlsArray, which contains the URL of the web page we want to crawl. Then, we created a results channel to store the crawling results.

Next, we use a for loop to iterate over each URL in the urls array. In each loop, we use the go keyword to create a Goroutine to crawl the specified URL concurrently. In Goroutine, we first call the fetch function to send an HTTP request and get the response HTML content. After that, we call the extractLinks function based on the HTML content, extract the links in it, and send them to the results channel.

Finally, we use a for loop to receive the crawl results from the results channel and print them.

By using Goroutines, we can send multiple HTTP requests concurrently, thereby improving the performance of the crawler. In addition, IO-intensive operations such as HTTP requests and HTML parsing can be efficiently handled using Goroutines.

To sum up, this article introduces how to use Go language and Goroutines to build high-performance concurrent crawlers. By properly utilizing concurrency mechanisms, we can obtain and analyze information on the Internet more efficiently. I hope readers can understand and master how to use Go language to write high-performance concurrent crawlers through the content of this article.

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