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How to develop crawler in go language

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2023-12-13 15:02:521152browse

The steps for crawler development using go language are as follows: 1. Select the appropriate library, such as GoQuery, Colly, PuerkitoBio and Gocolly, etc.; 2. Select the appropriate library and obtain the returned response data; 3. Parse HTML , extract the required information from the web page; 4. Concurrent processing, greatly improving crawling efficiency; 5. Data storage and processing; 6. Scheduled tasks; 7. Anti-crawler processing.

How to develop crawler in go language

The operating system for this tutorial: Windows 10 system, Go version 1.21, DELL G3 computer.

Go language has a strong performance in crawler development, mainly relying on its concurrency features and lightweight goroutine mechanism. The following are the main steps and common tools for crawler development in Go language:

1. Choose the appropriate library:

Go language has many mature web crawler libraries , such as GoQuery, Colly, PuerkitoBio and Gocolly, etc. These libraries provide convenient APIs and rich functions to help developers quickly build crawler programs.

2. Send HTTP requests:

In Go language, you can use the net/http package in the standard library to send HTTP requests. You can easily send requests to the target website through methods such as http.Get or http.Post and obtain the returned response data.

3. Parse HTML:

Choosing the appropriate HTML parsing library can help us extract the required information from the web page. The more commonly used libraries include GoQuery and PuertokitoBio/goquery, which provide syntax similar to jQuery, which can easily parse and filter HTML elements.

4. Concurrent processing:

Using the goroutine mechanism of the Go language, concurrent crawling can be easily realized. By starting multiple concurrent goroutines to handle multiple crawling tasks at the same time, crawling efficiency can be greatly improved.

5. Data storage and processing:

The obtained data can be stored in memory or written to persistent storage media such as files and databases. In the Go language, you can choose to use built-in data structures and file operation functions, or you can combine it with third-party libraries for data storage and processing.

6. Scheduled tasks:

In crawler development, scheduled tasks are often required, such as regularly crawling and updating websites. You can use the Time package of Go language to implement scheduling and execution of scheduled tasks.

7. Anti-crawler processing:

When developing crawlers, you need to note that the website may set anti-crawler strategies, such as detecting access frequency, setting verification codes, etc. Developers can circumvent anti-crawler strategies by properly setting user agent information and limiting request frequency.

The following is a simple example to demonstrate the basic process of crawler development using Go language and goquery library:

package main
import (
"fmt"
"log"
"strings"
"github.com/PuerkitoBio/goquery"
)
func main() {
url := "https://example.com"
doc, err := goquery.NewDocument(url)
if err != nil {
log.Fatal(err)
}
doc.Find("a").Each(func(i int, s *goquery.Selection) {
href, _ := s.Attr("href")
text := strings.TrimSpace(s.Text())
fmt.Printf("Link %d: %s - %s\n", i, text, href)
})
}

In this example, we first imported the goquery library, and then used NewDocument Method to obtain the content of the specified web page. Next, use the Find and Each methods to traverse all links in the web page and output the link text and URL.

It should be noted that when conducting actual crawler development, we also need to pay attention to legality, privacy, terms of service and other related issues to ensure that our crawler behavior complies with legal and ethical norms. At the same time, you also need to pay attention to the ethical use of web crawlers. When crawling content, you must follow the robots.txt rules of the website, respect the wishes of the website owner, and avoid unnecessary pressure on the website.

In actual crawler development, it is necessary to select appropriate strategies and tools based on specific tasks and the characteristics of the target website, while maintaining continuous learning and practice to improve the efficiency and stability of the crawler.

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