curl-cffivshttr
Curl-cffi is a Python library for implementing curl-impersonate which is a
HTTP client that appears as one of popular web browsers like:
- Google Chrome
- Microsoft Edge
- Safari
- Firefox
Unlike requests and httpx which are native Python libraries, curl-cffi uses cURL and inherits it's powerful features
like extensive HTTP protocol support and detection patches for TLS and HTTP fingerprinting.
Using curl-cffi web scrapers can bypass TLS and HTTP fingerprinting.
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.
Highlights
bypasshttp2tls-fingerprinthttp-fingerprintsyncasync
Example Use
curl-cffi can be accessed as low-level curl client as well as an easy high-level HTTP client:
from curl_cffi import requests
response = requests.get('https://httpbin.org/json')
print(response.json())
# or using sessions
session = requests.Session()
response = session.get('https://httpbin.org/json')
# also supports async requests using asyncio
import asyncio
from curl_cffi.requests import AsyncSession
urls = [
"http://httpbin.org/html",
"http://httpbin.org/html",
"http://httpbin.org/html",
]
async with AsyncSession() as s:
tasks = []
for url in urls:
task = s.get(url)
tasks.append(task)
# scrape concurrently:
responses = await asyncio.gather(*tasks)
# also supports websocket connections
from curl_cffi.requests import Session, WebSocket
def on_message(ws: WebSocket, message):
print(message)
with Session() as s:
ws = s.ws_connect(
"wss://api.gemini.com/v1/marketdata/BTCUSD",
on_message=on_message,
)
ws.run_forever()
library(httr)
# GET requests:
resp <- GET("http://httpbin.org/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("http://httpbin.org/cookies", set_cookies("MeWant" = "cookies"))
content(r)$cookies # get response cookies