The Best Python HTTP Clients in 2024

HTTP is the ubiquitous protocol that powers the modern web. As a Python developer, you‘ll often need to interact with web APIs, fetch data from websites, or post data to web services. To do this, you need an HTTP client library that allows you to compose and send HTTP requests from your Python code.

Python‘s standard library provides a couple basic options in the form of the urllib and urllib3 modules. However, these low-level libraries can be clunky to use directly. Their APIs require a lot of boilerplate code for common tasks like parsing JSON responses or setting request headers. More importantly, they lack support for some advanced features required by many applications, like persistent connections, cookie handling, and concurrent requests.

Thankfully, the Python community has created a wealth of excellent 3rd party HTTP client libraries that make working with HTTP a breeze. In this article, we‘ll take an in-depth look at the three most popular options:

1. Requests
2. AIOHTTP
3. HTTPX

We‘ll compare their design philosophies, key features, and performance characteristics. You‘ll see code samples showing how to use each library for common tasks like making a GET request and parsing the JSON response or posting form data.

By the end of this article, you‘ll have a solid understanding of the Python HTTP client landscape and be able to choose the right library for your specific needs. Let‘s get started!

The reigning champion: Requests

First up is the venerable Requests library. Released in 2011, Requests soon became the go-to HTTP client for a generation of Python developers. Its success is due to a simple, expressive, and powerful API design that makes working with HTTP feel almost effortless.

Here‘s how you can use Requests to fetch JSON data from an API:


import requests

response = requests.get(‘https://api.example.com/data‘)
data = response.json()
print(data)


With just two lines of code, we‘re able to send an HTTP GET request and parse the JSON response into a native Python data structure. This is about as simple as it gets!

Requests provides a similarly intuitive interface for other HTTP methods like POST:


payload = {‘key1‘: ‘value1‘, ‘key2‘: ‘value2‘}
response = requests.post(‘https://httpbin.org/post‘, data=payload)
print(response.text)


Here the data parameter automatically encodes the dictionary as form data in the request body. We can use the json parameter instead to send JSON data. Requests takes care of setting the appropriate Content-Type header and serializing the data, making our code much cleaner.

Some other notable features of Requests include:

• Built-in support for handling cookies, sessions with persistent cookies, and authentication
• Automatic decompression of gzip and deflate responses
• Support for uploads and streaming downloads
• Hooks system for modifying requests and responses
• Retry logic for handling rate limits and intermittent failures

While the core Requests API is synchronous, there are 3rd party libraries that allow using Requests asynchronously by integrating it with async frameworks like gevent, Twisted, and Tornado. However, async is not a first-class feature of the library itself.

Overall, Requests remains an excellent choice for most Python HTTP client needs. It‘s battle-tested, has extensive documentation, and is optimized for developer happiness. The only downside is that it doesn‘t have built-in async capabilities, which can be a problem if raw performance is a concern.

Embracing async with AIOHTTP

AIOHTTP is a popular async HTTP client library built on top of Python‘s asyncio framework. Its key selling point is the ability to execute requests concurrently, taking advantage of async IO to minimize CPU usage while waiting for network IO.

Here‘s a basic example of making a GET request with AIOHTTP:


import aiohttp
import asyncio

asyncio.run(main())


As you can see, AIOHTTP code is quite a bit more complex than Requests due to the need to use async/await syntax and set up an event loop. However, this enables much better performance when making many requests concurrently:


async def main():
async with aiohttp.ClientSession() as session:
tasks = [] for url in urls:
task = asyncio.ensure_future(fetch(session, url))
tasks.append(task)
responses = await asyncio.gather(*tasks)
for response in responses:
print(response)


Here we create a task for each URL and use asyncio.gather to run them concurrently. This allows us to fetch hundreds of URLs in a fraction of the time it would take with synchronous code.

Some other standout features of AIOHTTP:

• Support for HTTP/1.1 keep-alive connections and connection pooling
• Seamless handling of cookies between requests
• Proxy support including authentication
• Automatic decompression of responses
• Multipart encoding for file uploads

If you‘re working on a project involving async frameworks like FastAPI or Tornado, or if you need to make a large volume of requests, AIOHTTP can be a great choice. Just be aware that its async nature makes the code a bit more complex.

The best of both worlds? HTTPX

HTTPX is a next-generation HTTP client library that aims to combine the best aspects of Requests and AIOHTTP. It provides a high-level synchronous API that will feel very familiar to Requests users:


import httpx

response = httpx.get(‘https://api.example.com/data‘)
print(response.json())


But it also offers a first-class async API for more advanced use cases:


import httpx
import asyncio

asyncio.run(main())


This allows you to use the same library for both synchronous and asynchronous code, with a minimal learning curve. Some other nice features of HTTPX:

• HTTP/2 support, enabling capabilities like header compression and multiplexing
• Strict timeouts for all requests to avoid freezing your program
• Automatic redirect handling
• Customizable authentication flows including OAuth 2
• Type annotated requests and responses

While HTTPX is a newer library compared to Requests and AIOHTTP, it has seen rapid adoption due to its elegant design that incorporates modern Python features like type hints. If you‘re starting a new project today, HTTPX is definitely worth considering.

What about the others?

While Requests, AIOHTTP, and HTTPX are the clear leaders, there are countless other Python HTTP client libraries you may encounter. Here are a couple of the more notable ones:

• GRequests: Extends Requests with support for asynchronous requests using Gevent
• Uplink: Provides a declarative API for defining REST API clients

These libraries can be useful in specific situations, but for most general HTTP client needs, you‘ll probably be better off sticking with one of the top 3 contenders.

Making the right choice for your project

So which Python HTTP client should you choose? As always, the answer is "it depends". Here are some general guidelines:

• If you‘re looking for the simplest, most straightforward way to make HTTP requests, go with Requests. It‘s battle-tested and covers the vast majority of use cases with a Pythonic API.
• If performance and concurrency are critical, consider an asynchronous library like AIOHTTP or HTTPX. AIOHTTP has the advantage of a more mature async ecosystem, while HTTPX provides an easier migration path from synchronous code.
• If you know you‘ll need HTTP/2 support, HTTPX is the clear choice as it‘s the only contender with HTTP/2 capabilities built-in.
• If you‘re working on an API client library, check out Uplink for its declarative approach to API definitions.

Whichever library you choose, make sure it has a healthy community and active maintenance. HTTP clients are a critical part of most Python web applications, so you‘ll want to pick a library you can rely on for the long haul.

Wrapping up

We‘ve taken a tour through the landscape of Python HTTP client libraries, from the simplicity of Requests to the asynchronous power of AIOHTTP and HTTPX. Whether you‘re a beginner looking to make your first API call or an experienced developer optimizing the performance of your web scraping pipeline, one of these libraries should fit the bill.

It‘s an exciting time to be a Python developer working with HTTP. With such a vibrant ecosystem of tools to choose from, it‘s never been easier to build applications that can communicate with APIs and services across the web. So go forth and make some requests!