Everything to Know to Start Web Scraping in Python Today
Complete introduction to web scraping using Python: http, parsing, AI, scaling and deployment.
cURL is a popular HTTP client tool and a C library (libcurl). It can also be used in Python through many wrapper libraries.
The most popular library that uses libcurl
in Python is pycurl. Here's an example use:
import pycurl
from io import BytesIO
# Set the URL you want to fetch
url = 'https://www.example.com/'
# Create a new Curl object
curl = pycurl.Curl()
# Set the URL and other options
curl.setopt(pycurl.URL, url)
# Follow redirects
curl.setopt(pycurl.FOLLOWLOCATION, 1)
# Set the user agent
curl.setopt(pycurl.USERAGENT, 'Mozilla/5.0')
# Create a buffer to store the response and add it as result target
buffer = BytesIO()
curl.setopt(pycurl.WRITEFUNCTION, buffer.write)
# Perform the request
curl.perform()
# Get the response code and content
response_code = curl.getinfo(pycurl.RESPONSE_CODE)
response_content = buffer.getvalue().decode('UTF-8')
# Print the response
print(f'Response code: {response_code}')
print(f'Response content: {response_content}')
# Clean up
curl.close()
buffer.close()
Compared to other libraries like requests and httpx pycurl is very low level can be difficult to use however it has access to many advanced features like HTTP3 support that other libraries don't have.
pyCurl doesn't support asynchronous requests which means it can't be used in asynchronous web scraping though can still be used using threads. See mixing sync code using asyncio.to_thread() for more details
This knowledgebase is provided by Scrapfly data APIs, check us out! 👇