pycurlvsrvest
PycURL is a Python interface to libcurl, a multi-protocol file transfer library written in C. PycURL allows developers to use a variety of network protocols in their Python programs, including HTTP, FTP, SMTP, POP3, and many more.
PycURL is often used in web scraping, data analysis, and automation tasks, as it allows developers to send and receive data over the internet. It can be used to perform various types of requests, such as GET, POST, PUT, and DELETE, and can also handle file uploads and downloads, cookies, and redirects.
One of the key features of PycURL is its support for SSL and proxy servers, which allows developers to securely transfer data over the internet and work around any network restrictions. PycURL also supports a wide range of authentication methods, such as Basic, Digest, and NTLM, and allows developers to easily set custom headers and query parameters.
Just like cURL itself, PycURL is also highly configurable and allows for fine-grained control over various aspects of the transfer, such as timeouts, retries, buffer sizes, and verbosity levels. Additionally, PycURL also provides easy access to the underlying libcurl library, which allows developers to access advanced functionality that is not exposed by the PycURL API.
It's important to note that PycURL is a wrapper around the libcurl library and therefore provides the same functionality and performance as libcurl.
Main strengths of PycURL is that it uses cURL which is one of the most feature rich low-level http clients. The downside is that it's a very low-level client (see the examples below) with complex API making use in web scraping very difficult and niche.
rvest is a popular R library for web scraping and parsing HTML and XML documents. It is built on top of the xml2 and httr libraries and provides a simple and consistent API for interacting with web pages.
One of the main advantages of using rvest is its simplicity and ease of use. It provides a number of functions that make it easy to extract information from web pages, even for those who are not familiar with web scraping. The html_nodes and html_node functions allow you to select elements from an HTML document using CSS selectors, similar to how you would select elements in JavaScript.
rvest also provides functions for interacting with forms, including html_form, set_values, and submit_form functions. These functions make it easy to navigate through forms and submit data to the server, which can be useful when scraping sites that require authentication or when interacting with dynamic web pages.
rvest also provides functions for parsing XML documents. It includes xml_nodes and xml_node functions, which also use CSS selectors to select elements from an XML document, as well as xml_attrs and xml_attr functions to extract attributes from elements.
Another advantage of rvest is that it provides a way to handle cookies, so you can keep the session alive while scraping a website, and also you can handle redirections with handle_redirects
Highlights
Example Use
import pycurl
from io import BytesIO
buf = BytesIO()
headers = BytesIO()
c = pycurl.Curl()
c.setopt(c.HTTP_VERSION, c.CURL_HTTP_VERSION_2_0) # set to use http2
# set proxy
c.setopt(c.PROXY, 'http://proxy.example.com:8080')
c.setopt(c.PROXYUSERNAME, 'username')
c.setopt(c.PROXYPASSWORD, 'password')
# make a request
c.setopt(c.URL, 'https://httpbin.org/get')
c.setopt(c.WRITEFUNCTION, buf.write) # where to save response body
c.setopt(c.HEADERFUNCTION, headers.write) # where to save response headers
# to make post request enable POST option:
# c.setopt(c.POST, 1)
# c.setopt(c.POSTFIELDS, 'key1=value1&key2=value2')
c.perform() # send request
# read response
data = buf.getvalue().decode()
headers = headers.getvalue().decode() # headers as a string
headers = dict([h.split(': ') for h in headers.splitlines() if ': ' in h]) # headers as a dict
c.close()
# multiple concurrent requests can be made using CurlMulti object:
# Create a CurlMulti object
multi = pycurl.CurlMulti()
# Set the number of maximum connections
multi.setopt(pycurl.MAXCONNECTS, 5)
# Create a list to store the Curl objects
curls = []
# Add the first request
c1 = pycurl.Curl()
c1.setopt(c1.URL, 'https://httpbin.org/get')
c1.setopt(c1.WRITEFUNCTION, BytesIO().write)
multi.add_handle(c1)
curls.append(c1)
# Add the second request
c2 = pycurl.Curl()
c2.setopt(c2.URL, 'https://httpbin.org/')
c2.setopt(c2.WRITEFUNCTION, BytesIO().write)
multi.add_handle(c2)
curls.append(c2)
# Start the requests
while True:
ret, _ = multi.perform()
if ret != pycurl.E_CALL_MULTI_PERFORM:
break
# Close the connections
for c in curls:
multi.remove_handle(c)
c.close()
library("rvest")
# Rvest can use basic HTTP client to download remote HTML:
tree <- read_html("http://webscraping.fyi/lib/r/rvest")
# or read from string:
tree <- read_html('
<div class="products">
<a href="/product/1">Cat Food</a>
<a href="/product/2">Dog Food</a>
</div>
')
# to parse HTML trees with rvest we use r pipes (the %>% symbol) and html_element function:
# we can use css selectors:
print(tree %>% html_element(".products>a") %>% html_text())
# "[1] "\nCat Food\nDog Food\n""
# or XPath:
print(tree %>% html_element(xpath="//div[@class='products']/a") %>% html_text())
# "[1] "\nCat Food\nDog Food\n""
# Additionally rvest offers many quality of life functions:
# html_text2 - removes trailing and leading spaces and joins values
print(tree %>% html_element("div") %>% html_text2())
# "[1] "Cat Food Dog Food""
# html_attr - selects element's attribute:
print(tree %>% html_element("div") %>% html_attr('class'))
# "products"