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MIT 1 9 979
710.2 thousand (month) May 06 2012 1.4.7(10 months ago)
1,041 9 9 LGPL/MIT
7.45.3(a month ago) Feb 25 2003 1.2 million (month)

The aim of httr is to provide a wrapper for the curl package, customised to the demands of modern web APIs.

Key features:

  • Functions for the most important http verbs: GET(), HEAD(), PATCH(), PUT(), DELETE() and POST().
  • Automatic connection sharing across requests to the same website (by default, curl handles are managed automatically), cookies are maintained across requests, and a up-to-date root-level SSL certificate store is used.
  • Requests return a standard reponse object that captures the http status line, headers and body, along with other useful information.
  • Response content is available with content() as a raw vector (as = "raw"), a character vector (as = "text"), or parsed into an R object (as = "parsed"), currently for html, xml, json, png and jpeg.
  • You can convert http errors into R errors with stop_for_status().
  • Config functions make it easier to modify the request in common ways: set_cookies(), add_headers(), authenticate(), use_proxy(), verbose(), timeout(), content_type(), accept(), progress().
  • Support for OAuth 1.0 and 2.0 with oauth1.0_token() and oauth2.0_token(). The demo directory has eight OAuth demos: four for 1.0 (twitter, vimeo, withings and yahoo) and four for 2.0 (facebook, github, google, linkedin). OAuth credentials are automatically cached within a project.

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.



Example Use


# GET requests:
resp <- GET("")
status_code(resp)  # status code
headers(resp)  # headers
str(content(resp))  # body

# POST requests: 
# Form encoded
resp <- POST(url, body = body, encode = "form")
# Multipart encoded
resp <- POST(url, body = body, encode = "multipart")
# JSON encoded
resp <- POST(url, body = body, encode = "json")

# setting cookies:
resp <- GET("", set_cookies("MeWant" = "cookies"))
content(r)$cookies  # get response cookies
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, '') 
c.setopt(c.PROXYUSERNAME, 'username')
c.setopt(c.PROXYPASSWORD, 'password')

# make a request
c.setopt(c.URL, '')
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

# 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, '')
c1.setopt(c1.WRITEFUNCTION, BytesIO().write)

# Add the second request
c2 = pycurl.Curl()
c2.setopt(c2.URL, '')
c2.setopt(c2.WRITEFUNCTION, BytesIO().write)

# Start the requests
while True:
    ret, _ = multi.perform()
    if ret != pycurl.E_CALL_MULTI_PERFORM:

# Close the connections
for c in curls:

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