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ralgervsphoton

MIT 3 1 153
1.2 thousand (month) Dec 22 2019 2.2.4(3 years ago)
10,458 3 52 MIT
1.1.9(5 years ago) Aug 24 2018 305 (month)

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.

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.

Example Use


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
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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