To use Go to write web crawlers and data extraction programs, you need to pay attention to four core links: sending requests, parsing HTML, extracting data, and dealing with anti-crawling strategies. 1. It is recommended to use net/http packages or third-party libraries such as colly and goquery when initiating HTTP requests. Pay attention to setting User-Agent and random delays. 2. Parsing HTML commonly used goquery (similar to jQuery syntax) or golang.org/x/net/html (standard library parser). 3. When extracting data, it is recommended to locate elements through class name or ID, and dynamic content can be processed by chromedp. 4. The anti-crawl response strategy includes using a proxy IP pool, setting reasonable request intervals, simulated login, and bypass detection using the Headless browser.

It is actually quite common to use Go for web crawlers and data extraction. Go has good performance and strong concurrency capabilities, which is very suitable for this type of task. If you already have a bit of Go, it is not difficult to write a crawler by hand.

However, before you start directly, you must first clarify several key points: sending requests, parsing HTML, extracting data, and processing anti-crawling. These links must be taken into account. Here are some of the parts you are most likely to care about.

How to initiate an HTTP request

The most common use of requests in Go is the built-in net/http package. It is stable enough, and it can also control timeouts with context to avoid being stuck.

Let's give a simple example:

 client := &http.Client{}
req, _ := http.NewRequest("GET", "https://example.com", nil)
resp, err := client.Do(req)
if err != nil {
    log.Fatal(err)
}
defer resp.Body.Close()

You can also use third-party libraries such as colly or goquery to package, which will be more convenient. However, it is recommended to be familiar with the native method first and then consider the encapsulation library.

Tips:

• Setting User-Agent is necessary, otherwise many websites will block the default Go request header.
• Adding a random delay (such as 1~3 seconds) can reduce the risk of blocked IP.

Parsing HTML and extracting data

After getting the response body, the next step is to parse the HTML and extract the content you need. Commonly used in Go are:

• goquery : a syntax similar to jQuery, suitable for pages with clear structure
• golang.org/x/net/html : Standard library-level parser, high efficiency but slightly complex API

Take goquery as an example:

 doc, err := goquery.NewDocumentFromReader(resp.Body)
if err != nil {
    log.Fatal(err)
}
doc.Find(".product-title").Each(func(i int, s *goquery.Selection) {
    title := s.Text()
    fmt.Println(title)
})

This method is simple and intuitive, suitable for data extraction of most static pages.

Notice:

• Try to use class names or IDs to locate elements, and do not rely on the tag nesting level, because the page structure is easy to change.
• If the page is loaded dynamically (such as React rendering), then you need to consider the Headless browser, such as using chromedp.

Anti-climbing and coping strategies

Many websites now have certain anti-crawling mechanisms, such as restricting access frequency, detecting request headers, verification codes, etc.

Common coping methods include:

• Use Proxy IP Pool Rotate IP Address
• Set a reasonable request interval, don't be too fast
• Simulate login user behavior with cookies login status
• For JS rendering content, you can consider using Go binding with chromedp or puppeteer

A simple usage of chromedp:

 ctx, cancel := chromedp.NewContext(context.Background())
defer cancel()

var res string
err = chromedp.Run(ctx,
    chromedp.Navigate("https://dynamic-site.com"),
    chromedp.Text(".content", &res),
)

Although this method is a little slower, it can bypass most of the problems of dynamic loading of JS.

Basically that's it. It is not difficult to write crawlers in Go. What you really need to pay attention to is the details: such as how to construct the request header, how to avoid detection, and how to extract data efficiently. You can start with small projects at the beginning, such as climbing a weather forecast or news title, and slowly adding concurrency, persistence, and proxy functions, so you can naturally get started.

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