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MIT 3 1 152
1.4 thousand (month) Dec 22 2019 2.2.4(2 years ago)
2,933 1 58 GNU General Public License v3.0
1.4.1(5 months ago) Sep 30 2018 1.0 thousand (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.

ScrapydWeb is a web-based management tool for the Scrapyd service. It is built using the Python Flask framework and allows you to easily manage and monitor your Scrapy spider projects through a web interface.

ScrapydWeb allows you to view the status of your running spiders, view the logs of completed spiders, schedule new spider runs, and manage spider settings and configurations.

ScrapydWeb provides a simple way to manage your scraping tasks and allows you to schedule and run multiple spiders simultaneously. It also provides a user-friendly web interface that makes it easy to view the status of your spiders and monitor their progress.

You can install the package via pip by running pip install scrapydweb and then you can run the package by running scrapydweb command in your command prompt.

It will start a web server that you can access through your web browser at http://localhost:6800/ You will need to have Scrapyd running in order to use ScrapydWeb, Scrapyd is a service for running Scrapy spiders, it allows you to schedule spiders to run at regular intervals and also allows you to run spiders on remote machines.

Example Use


url <- ""

# 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 = "",
  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 ="")

#> # 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

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