ferretvsgeziyor
Ferret is a web scraping system. It aims to simplify data extraction from the web for UI testing, machine learning, analytics and more. ferret allows users to focus on the data. It abstracts away the technical details and complexity of underlying technologies using its own declarative language. It is extremely portable, extensible, and fast.
Features
- Declarative language
- Support of both static and dynamic web pages
- Embeddable
- Extensible
Ferret is always implemented in Python through pyfer
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)
Example Use
// Example scraper for Google in Ferret:
LET google = DOCUMENT("https://www.google.com/", {
driver: "cdp",
userAgent: "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_14_6) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/76.0.3809.87 Safari/537.36"
})
HOVER(google, 'input[name="q"]')
WAIT(RAND(100))
INPUT(google, 'input[name="q"]', @criteria, 30)
WAIT(RAND(100))
CLICK(google, 'input[name="btnK"]')
WAITFOR EVENT "navigation" IN google
WAIT_ELEMENT(google, "#res")
LET results = ELEMENTS(google, X("//*[text() = 'Search Results']/following-sibling::*/*"))
FOR el IN results
RETURN {
title: INNER_TEXT(el, 'h3')?,
description: INNER_TEXT(el, X("//em/parent::*")),
url: ELEMENT(el, 'a')?.attributes.href
}
// 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)
}
}