How to Use cURL With Python

cURL is a powerful command-line tool that allows you to make HTTP requests and transfer data between servers using various protocols like HTTP, HTTPS, SMTP, and more. While Python has the excellent Requests library for HTTP requests, using cURL directly from Python code can provide more flexibility and control.

In this comprehensive guide, you‘ll learn how to leverage cURL functionality from Python code using the pycurl library. We‘ll cover everything from basic usage to advanced techniques for performance, robustness, and extensibility.

Why Use cURL with Python?

Here are some of the key advantages of using cURL from Python instead of relying solely on the Requests module:

More supported protocols – cURL supports FTP, IMAP, POP3, SMTP, and other protocols in addition to HTTP/HTTPS. Requests only handles HTTP/HTTPS.
Fine-grained control – cURL offers granular control over request parameters, headers, authentication, proxies, and other options. Requests uses sane defaults.
High performance – Pycurl can be faster than Requests for tasks involving a large number of requests.
Persistence – Pycurl connections can persist and be reused across requests for better performance.
Extensibility – Pycurl makes it easy to add custom logic like writing response data to files.

So while Requests is great for basic HTTP APIs, using cURL directly from Python opens up more possibilities.

Installation

To start using cURL functionality in Python, you need to install the pycurl library:

pip install pycurl

This will give you access to the pycurl module for making cURL requests.

Making GET Requests

Let‘s look at a simple example for making a GET request with pycurl:

import pycurl
from io import BytesIO

buffer = BytesIO()
c = pycurl.Curl()
c.setopt(c.URL, ‘https://example.com‘)
c.setopt(c.WRITEDATA, buffer)
c.perform()
c.close()

body = buffer.getvalue()
print(body.decode(‘utf-8‘))

Here‘s what‘s happening in the code above:

We import pycurl and io for the buffer.
Create a BytesIO buffer to store the response.
Initialize a pycurl Curl object to make the request.
Set the URL option to the website URL we want to request.
Set the WRITEDATA option to our buffer to store the response.
Call perform() to make the request and get the response.
Finally, we close the curl object and print the response body.

This gives us the HTML content of the webpage in a Python string!

Making POST Requests

To demonstrate a POST request, we need a URL that accepts POST data. We‘ll use a test endpoint at httpbin.org:

import pycurl
from io import BytesIO

data = {‘field1‘: ‘value1‘, ‘field2‘: ‘value2‘}
post_data = "&".join([f"{k}={v}" for k, v in data.items()])

buffer = BytesIO()
c = pycurl.Curl()
c.setopt(c.URL, ‘https://httpbin.org/post‘) 
c.setopt(c.POSTFIELDS, post_data)
c.setopt(c.WRITEDATA, buffer)
c.perform() 
c.close()

print(buffer.getvalue().decode(‘utf-8‘))

To recap, here‘s what we did:

Created a dict with data to send as POST fields
Joined it into a URL encoded string
Set the URL to a POST endpoint
Set POSTFIELDS to our encoded data
Performed the request and printed the response

This allowed us to make a POST instead of GET using the same pycurl approach.

Adding Custom Headers

We can add custom headers to our pycurl requests by providing a list:

headers = [‘User-Agent: CustomAgent‘,
           ‘Accept: application/json‘]

c = pycurl.Curl()
# Set other options like URL 
c.setopt(c.HTTPHEADER, headers)
c.perform()

The HTTPHEADER option takes a list of custom headers to include in the outgoing request.

We can use this to spoof or rotate user agents, change content types, set auth headers, and more.

Sending JSON Data

To send JSON data in a POST request body using pycurl:

import json 

data = {‘key1‘: ‘value1‘}

json_data = json.dumps(data)

c = pycurl.Curl()
c.setopt(c.URL, ‘https://example.com/api‘)
c.setopt(c.POSTFIELDS, json_data)
c.setopt(c.HTTPHEADER, [‘Content-Type: application/json‘])  
c.perform()

By converting our data to JSON, setting the POSTFIELDS, and adding a content-type header, we can mimic sending JSON from JavaScript or other clients.

The server will receive the JSON body and process it accordingly.

Handling Redirects

To automatically handle redirects when using pycurl:

c = pycurl.Curl()
c.setopt(c.URL, ‘http://example.com‘)
c.setopt(c.FOLLOWLOCATION, True)
c.perform()

By setting the FOLLOWLOCATION option to True, pycurl will follow any 3xx redirects from the server and retrieve the final page.

This avoids dealing with redirection and history manually.

Comparison to Requests

The Requests library provides a simpler interface than pycurl for basic HTTP requests in Python. However, pycurl offers some advantages:

Speed – Pycurl is faster especially when making thousands of sequential requests. It maintains persistent connections.

Control – Pycurl provides very granular control over curl options. Requests uses sane defaults.

Protocols – Pycurl supports protocols beyond HTTP like FTP, SCP, SMTP, and more. Requests is HTTP only.

Extensibility – Pycurl makes it easier to implement custom logic like parsing headers or saving response data.

In summary, Requests is better for basic API usage while Pycurl enables more complex programs and optimizations. Combining both libraries provides maximum flexibility.

Conclusion

This guide covered the key aspects of using cURL functionality from Python code via the pycurl library. We looked at both basic and advanced techniques including:

Making GET and POST requests
Setting custom headers
Sending JSON data
Handling redirects
Comparing pycurl to Requests

Mastering cURL usage in Python opens up many possibilities for interacting with APIs, web scraping, network programming and more. The extensive options provided by the mature cURL library lead to highly optimized applications.

I hope you found this guide useful! Let me know if you have any other questions on effective pycurl techniques.