Dude (dude uncomplicated data extraction) is a very simple framework for writing web scrapers using Python decorators.
The design, inspired by Flask, was to easily build a web scraper in just a few lines of code. Dude has an easy-to-learn syntax.
The simplest web scraper will look like this:
```python
from dude import select
@select(css="a")
def get_link(element):
return {"url": element.get_attribute("href")}
```
dude supports multiple parser backends:
- playwright
- lxml
- parsel
- beautifulsoup
- pyppeteer
- selenium
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.
```python
from dude import select
"""
This example demonstrates how to use Parsel + async HTTPX
To access an attribute, use:
selector.attrib["href"]
You can also access an attribute using the ::attr(name) pseudo-element, for example "a::attr(href)", then:
selector.get()
To get the text, use ::text pseudo-element, then:
selector.get()
"""
@select(css="a.url", priority=2)
async def result_url(selector):
return {"url": selector.attrib["href"]}
# Option to get url using ::attr(name) pseudo-element
@select(css="a.url::attr(href)", priority=2)
async def result_url2(selector):
return {"url2": selector.get()}
@select(css=".title::text", priority=1)
async def result_title(selector):
return {"title": selector.get()}
@select(css=".description::text", priority=0)
async def result_description(selector):
return {"description": selector.get()}
if __name__ == "__main__":
import dude
dude.run(urls=["https://dude.ron.sh"], parser="parsel")
```
```r
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
#>
#> 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
```