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collyvsphoton

Apache-2.0 185 5 22,347
May 14 2018 v2.1.0(4 years ago)
10,575 3 52 MIT
Aug 24 2018 335 (month) 1.1.9(5 years ago)

Colly is a popular web scraping library for the Go programming language. It's designed to be fast and easy to use, and it provides a simple and flexible API for traversing and extracting information from websites.

Colly supports:

  • Concurrent scraping with a simple API
  • Automatic handling of cookies and sessions
  • Automatic handling of redirects
  • Support for parsing HTML and XML
  • Support for parsing JSON and binary data
  • Support for custom storage (e.g. scraping results to a database)
  • Simple JavaScript rendering with Colly's built-in rendering engine.

Colly also provides several optional features, such as support for user-agents, delay between requests, rate-limiting and proxy usage.

Colly's API is quite simple, and it is easy to get started with basic web scraping tasks. It's a good choice for scraping moderate to heavy sites, and it can be useful for a wide range of use cases, such as data mining, content extraction, and more.

Additionally, you can use it together with Goquery, a library that allow you to make jquery like queries on HTML documents and it is often used together with Colly to ease the way of parsing the HTML.

Photon is a Python library for web scraping. It is designed to be lightweight and fast, and can be used to extract data from websites and web pages. Photon can extract the following data while crawling:

  • URLs (in-scope & out-of-scope)
  • URLs with parameters (example.com/gallery.php?id=2)
  • Intel (emails, social media accounts, amazon buckets etc.)
  • Files (pdf, png, xml etc.)
  • Secret keys (auth/API keys & hashes)
  • JavaScript files & Endpoints present in them
  • Strings matching custom regex pattern
  • Subdomains & DNS related data

The extracted information is saved in an organized manner or can be exported as json.

Highlights


popularcss-selectorsxpath-selectorscommunity-toolsoutput-pipelinesmiddlewaresasyncproductionlarge-scale

Example Use


package main

import (
  "fmt"

  "github.com/gocolly/colly/v2"
)

func main() {
  // Instantiate default collector
  c := colly.NewCollector(
    // Visit only domains: hackerspaces.org, wiki.hackerspaces.org
    colly.AllowedDomains("hackerspaces.org", "wiki.hackerspaces.org"),
  )

  // On every a element which has href attribute call callback
  c.OnHTML("a[href]", func(e *colly.HTMLElement) {
    link := e.Attr("href")
    // Print link
    fmt.Printf("Link found: %q -> %s\n", e.Text, link)
    // Visit link found on page
    // Only those links are visited which are in AllowedDomains
    c.Visit(e.Request.AbsoluteURL(link))
  })

  // Before making a request print "Visiting ..."
  c.OnRequest(func(r *colly.Request) {
    fmt.Println("Visiting", r.URL.String())
  })

  // Start scraping on https://hackerspaces.org
  c.Visit("https://hackerspaces.org/")
}
from photon import Photon

#Create a new Photon instance
ph = Photon()

#Extract data from a specific element of the website
url = "https://www.example.com"
selector = "div.main"
data = ph.get_data(url, selector)

#Print the extracted data
print(data)


#Extract data from multiple websites asynchronously
urls = ["https://www.example1.com", "https://www.example2.com"]
data = ph.get_data_async(urls)

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