gocrawlvsralger
Gocrawl is a polite, slim and concurrent web crawler library written in Go. It is designed to be simple and easy to use, while still providing a high degree of flexibility and control over the crawling process.
One of the key features of Gocrawl is its politeness, which means that it obeys the website's robots.txt file and respects the crawl-delay specified in the file. It also takes into account the website's last modified date, if any, to avoid recrawling the same page. This helps to reduce the load on the website and prevent any potential legal issues. Gocrawl is also highly concurrent, which allows it to efficiently crawl large numbers of pages in parallel. This helps to speed up the crawling process and reduce the time required to complete the task.
The library also offers a high degree of flexibility in customizing the crawling process. It allows you to specify custom callbacks and handlers for handling different types of pages, such as error pages, redirects, and so on. This allows you to handle and process the pages as per your requirement. Additionally, Gocrawl provides various functionalities such as support for cookies, user-agent, auto-detection of links, and auto-detection of sitemaps.
ralger is a small web scraping framework for R based on rvest and xml2.
It's goal to simplify basic web scraping and it provides a convenient and easy to use API.
It offers functions for retrieving pages, parsing HTML using CSS selectors, automatic table parsing and auto link, title, image and paragraph extraction.
Example Use
// Only enqueue the root and paths beginning with an "a"
var rxOk = regexp.MustCompile(`http://duckduckgo\.com(/a.*)?$`)
// Create the Extender implementation, based on the gocrawl-provided DefaultExtender,
// because we don't want/need to override all methods.
type ExampleExtender struct {
gocrawl.DefaultExtender // Will use the default implementation of all but Visit and Filter
}
// Override Visit for our need.
func (x *ExampleExtender) Visit(ctx *gocrawl.URLContext, res *http.Response, doc *goquery.Document) (interface{}, bool) {
// Use the goquery document or res.Body to manipulate the data
// ...
// Return nil and true - let gocrawl find the links
return nil, true
}
// Override Filter for our need.
func (x *ExampleExtender) Filter(ctx *gocrawl.URLContext, isVisited bool) bool {
return !isVisited && rxOk.MatchString(ctx.NormalizedURL().String())
}
func ExampleCrawl() {
// Set custom options
opts := gocrawl.NewOptions(new(ExampleExtender))
// should always set your robot name so that it looks for the most
// specific rules possible in robots.txt.
opts.RobotUserAgent = "Example"
// and reflect that in the user-agent string used to make requests,
// ideally with a link so site owners can contact you if there's an issue
opts.UserAgent = "Mozilla/5.0 (compatible; Example/1.0; +http://example.com)"
opts.CrawlDelay = 1 * time.Second
opts.LogFlags = gocrawl.LogAll
// Play nice with ddgo when running the test!
opts.MaxVisits = 2
// Create crawler and start at root of duckduckgo
c := gocrawl.NewCrawlerWithOptions(opts)
c.Run("https://duckduckgo.com/")
// Remove "x" before Output: to activate the example (will run on go test)
// xOutput: voluntarily fail to see log output
}
library("ralger")
url <- "http://www.shanghairanking.com/rankings/arwu/2021"
# retrieve HTML and select elements using CSS selectors:
best_uni <- scrap(link = url, node = "a span", clean = TRUE)
head(best_uni, 5)
#> [1] "Harvard University"
#> [2] "Stanford University"
#> [3] "University of Cambridge"
#> [4] "Massachusetts Institute of Technology (MIT)"
#> [5] "University of California, Berkeley"
# ralger can also parse HTML attributes
attributes <- attribute_scrap(
link = "https://ropensci.org/",
node = "a", # the a tag
attr = "class" # getting the class attribute
)
head(attributes, 10) # NA values are a tags without a class attribute
#> [1] "navbar-brand logo" "nav-link" NA
#> [4] NA NA "nav-link"
#> [7] NA "nav-link" NA
#> [10] NA
#
# ralger can automatically scrape tables:
data <- table_scrap(link ="https://www.boxofficemojo.com/chart/top_lifetime_gross/?area=XWW")
head(data)
#> # A tibble: 6 × 4
#> Rank Title `Lifetime Gross` Year
#> <int> <chr> <chr> <int>
#> 1 1 Avatar $2,847,397,339 2009
#> 2 2 Avengers: Endgame $2,797,501,328 2019
#> 3 3 Titanic $2,201,647,264 1997
#> 4 4 Star Wars: Episode VII - The Force Awakens $2,069,521,700 2015
#> 5 5 Avengers: Infinity War $2,048,359,754 2018
#> 6 6 Spider-Man: No Way Home $1,901,216,740 2021