hrequestsvsralger
hrequests is a feature rich modern replacement for a famous requests library for Python. It provides a feature rich HTTP client capable of resisting popular scraper identification techniques: - Seamless transition between headless browser and http client based requests - Integrated HTML parser - Mimicking of real browser TLS fingerprints - Javascript rendering - HTTP2 support - Realistic browser headers
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.
Highlights
bypasshttp2tls-fingerprinthttp-fingerprintsyncasync
Example Use
hrequests has almost identical API and UX as requests and here's a quick overview:
```python
import hrequests
# perform HTTP client requests
resp = hrequests.get('https://httpbin.org/html')
print(resp.status_code)
# 200
# use headless browsers and sessions:
session = hrequests.Session('chrome', version=122, os="mac")
# supports asyncio and easy concurrency
requests = [
hrequests.async_get('https://www.google.com/', browser='firefox'),
hrequests.async_get('https://www.duckduckgo.com/'),
hrequests.async_get('https://www.yahoo.com/'),
hrequests.async_get('https://www.httpbin.org/'),
]
responses = hrequests.map(requests, size=3) # max 3 conccurency
```
```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
```
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