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geziyorvsdataflowkit

MPL-2.0 23 1 2,470
Jun 06 2019 2024-04-04(a day ago)
641 3 4 BSD-3-Clause
2024-04-04(a day ago) Feb 09 2017

Geziyor is a blazing fast web crawling and web scraping framework. It can be used to crawl websites and extract structured data from them. Geziyor is useful for a wide range of purposes such as data mining, monitoring and automated testing.

Features:

  • JS Rendering
  • 5.000+ Requests/Sec
  • Caching (Memory/Disk/LevelDB)
  • Automatic Data Exporting (JSON, CSV, or custom)
  • Metrics (Prometheus, Expvar, or custom)
  • Limit Concurrency (Global/Per Domain)
  • Request Delays (Constant/Randomized)
  • Cookies, Middlewares, robots.txt
  • Automatic response decoding to UTF-8
  • Proxy management (Single, Round-Robin, Custom)

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.

Example Use


// This example extracts all quotes from quotes.toscrape.com and exports to JSON file.
func main() {
    geziyor.NewGeziyor(&geziyor.Options{
        StartURLs: []string{"http://quotes.toscrape.com/"},
        ParseFunc: quotesParse,
        Exporters: []export.Exporter{&export.JSON{}},
    }).Start()
}

func quotesParse(g *geziyor.Geziyor, r *client.Response) {
    r.HTMLDoc.Find("div.quote").Each(func(i int, s *goquery.Selection) {
        g.Exports <- map[string]interface{}{
            "text":   s.Find("span.text").Text(),
            "author": s.Find("small.author").Text(),
        }
    })
    if href, ok := r.HTMLDoc.Find("li.next > a").Attr("href"); ok {
        g.Get(r.JoinURL(href), quotesParse)
    }
}
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.

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