How can I use regular expressions in Pholcus for data extraction?

Pholcus is a distributed, high-concurrency, and powerful web crawler software written in Go. It's primarily used for web scraping, which includes data extraction tasks. Regular expressions (regex) are a powerful tool for extracting specific data from text, which can be particularly useful in web scraping to parse and capture information from web page content.

To use regular expressions in Pholcus for data extraction, you will typically follow these steps:

1. Define the regular expression pattern that matches the data you want to extract.
2. Use the regex pattern within the context of Pholcus' scraping functions to extract the matched data from the web page content.

Here's a simple example of how you might use regular expressions in Pholcus:

package main

import (
    "github.com/henrylee2cn/pholcus/app"
    "github.com/henrylee2cn/pholcus/app/spider"
    "github.com/henrylee2cn/pholcus/common/goquery" // HTML parsing library
    "github.com/henrylee2cn/pholcus/logs"           // Information output
    "regexp"
)

func main() {
    app.NewSpider(
        spider.NewSpider("ExampleSpider", "Example description").
            AddRequest("http://example.com", "html").
            AddPipeline(func(dataCell *spider.Context) {
                // Get the raw HTML content
                html := dataCell.GetText()

                // Define a regular expression to find all instances of a pattern
                // For example, extract all email addresses
                re := regexp.MustCompile(`[a-z0-9._%+\-]+@[a-z0-9.\-]+\.[a-z]{2,4}`)

                // Find all matches
                matches := re.FindAllString(html, -1)

                // Iterate over all matches and process them
                for _, match := range matches {
                    logs.Log.Informational("Found email: %s", match)
                    // You can now use the extracted data as needed
                    // e.g., save to file, database, etc.
                }
            }),
    ).Run()
}

In this example:

• We use the regexp package to utilize regular expressions in Go.
• We define a regular expression pattern that matches email addresses with regexp.MustCompile().
• We use re.FindAllString() to find all matches of the regular expression in the HTML content.
• We iterate over the matches and perform actions with the extracted data, such as logging the information using logs.Log.Informational().

Remember to adjust the regular expression pattern to match the specific data you are trying to extract. Also, be sure that your use of regular expressions and web scraping complies with the website's terms of service and any applicable laws regarding data privacy and intellectual property.

It's worth noting that while regular expressions can be powerful, they are not always the best tool for parsing HTML due to the complex and often irregular structure of HTML documents. For more robust and maintainable web scraping, you might want to use a parsing library like Goquery, which is designed to work with HTML and provides a jQuery-like syntax for selecting elements from the DOM.