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ralgervsruia

MIT 3 1 153
1.2 thousand (month) Dec 22 2019 2.2.4(3 years ago)
1,731 3 8 MIT
0.8.5(1 year, 6 months ago) Oct 17 2018 469 (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.

Ruia is an async web scraping micro-framework, written with asyncio and aiohttp, aims to make crawling url as convenient as possible.

Ruia is inspired by scrapy however instead of Twisted it's based entirely on asyncio and aiohttp.

It also supports various features like cookies, headers, and proxy, which makes it very useful in dealing with complex web scraping tasks.

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
#!/usr/bin/env python
"""
 Target: https://news.ycombinator.com/
 pip install aiofiles
"""
import aiofiles

from ruia import AttrField, Item, Spider, TextField


class HackerNewsItem(Item):
    target_item = TextField(css_select="tr.athing")
    title = TextField(css_select="a.storylink")
    url = AttrField(css_select="a.storylink", attr="href")

    async def clean_title(self, value):
        return value.strip()


class HackerNewsSpider(Spider):
    start_urls = [
        "https://news.ycombinator.com/news?p=1",
        "https://news.ycombinator.com/news?p=2",
    ]
    concurrency = 10
    # aiohttp_kwargs = {"proxy": "http://0.0.0.0:1087"}

    async def parse(self, response):
        async for item in HackerNewsItem.get_items(html=await response.text()):
            yield item

    async def process_item(self, item: HackerNewsItem):
        async with aiofiles.open("./hacker_news.txt", "a") as f:
            self.logger.info(item)
            await f.write(str(item.title) + "\n")


if __name__ == "__main__":
    HackerNewsSpider.start(middleware=None)

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