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dataflowkitvscolly

BSD-3-Clause 4 3 641
Feb 09 2017 2024-04-04(a day ago)
22,036 5 181 Apache-2.0
v2.1.0(3 years ago) May 14 2018

Dataflow kit ("DFK") is a Web Scraping framework for Gophers. It extracts data from web pages, following the specified CSS Selectors. You can use it in many ways for data mining, data processing or archiving.

Web-scraping pipeline consists of 3 general components:

  • Downloading an HTML web-page. (Fetch Service)
  • Parsing an HTML page and retrieving data we're interested in (Parse Service)
  • Encoding parsed data to CSV, MS Excel, JSON, JSON Lines or XML format.

For fetching dataflowkit has several types of page fetchers:

  • Base fetcher uses standard golang http client to fetch pages as is. It works faster than Chrome fetcher. But Base fetcher cannot render dynamic javascript driven web pages.
  • Chrome fetcher is intended for rendering dynamic javascript based content. It sends requests to Chrome running in headless mode.

For parsing dataflowkit extracts data from downloaded web page following the rules listed in configuration JSON file. Extracted data is returned in CSV, MS Excel, JSON or XML format.

Some dataflowkit features:

  • Scraping of JavaScript generated pages;
  • Data extraction from paginated websites;
  • Processing infinite scrolled pages.
  • S—Āraping of websites behind login form;
  • Cookies and sessions handling;
  • Following links and detailed pages processing;
  • Managing delays between requests per domain;
  • Following robots.txt directives;
  • Saving intermediate data in Diskv or Mongodb. Storage interface is flexible enough to add more storage types easily;
  • Encode results to CSV, MS Excel, JSON(Lines), XML formats;
  • Dataflow kit is fast. It takes about 4-6 seconds to fetch and then parse 50 pages.
  • Dataflow kit is suitable to process quite large volumes of data. Our tests show the time needed to parse appr. 4 millions of pages is about 7 hours.

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.

Highlights


popularcss-selectorsxpath-selectorscommunity-toolsoutput-pipelinesmiddlewaresasyncproductionlarge-scale

Example Use


Dataflowkit uses JSON configuration like:
{
  "name": "collection",
  "request": {
      "url": "https://example.com"
  },
  "fields": [
      {
          "name": "Title",
          "selector": ".product-container a",
          "extractor": {
              "types": [
                  "text",
                  "href"
              ],
              "filters": [
                  "trim",
                  "lowerCase"
              ],
              "params": {
                  "includeIfEmpty": false
              }
          }
      },
      {
          "name": "Image",
          "selector": "#product-container img",
          "extractor": {
              "types": [
                  "alt",
                  "src",
                  "width",
                  "height"
              ],
              "filters": [
                  "trim",
                  "upperCase"
              ]
          }
      },
      {
          "name": "Buyinfo",
          "selector": ".buy-info",
          "extractor": {
              "types": [
                  "text"
              ],
              "params": {
                  "includeIfEmpty": false
              }
          }
      }
  ],
  "paginator": {
      "selector": ".next",
      "attr": "href",
      "maxPages": 3
  },
  "format": "json",
  "fetcherType": "chrome",
  "paginateResults": false
}
which is then ingested through CLI command.
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/")
}

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