Making Asynchronous HTTP Requests with Python

Asynchronous programming is a technique that allows your program to execute multiple tasks concurrently, improving overall performance and responsiveness. In the context of web development, making asynchronous HTTP requests enables you to fetch data from multiple sources simultaneously, reducing the time it takes to complete these operations.

In this tutorial, we will explore how to make asynchronous HTTP requests using Python. We’ll discuss different libraries and approaches, including grequests, aiohttp, and concurrent.futures.

Introduction to Asynchronous Programming

Before diving into the specifics of making asynchronous HTTP requests, let’s briefly introduce the concept of asynchronous programming.

Asynchronous programming is a paradigm that allows your program to execute multiple tasks concurrently. This is in contrast to synchronous programming, where tasks are executed one after the other. In asynchronous programming, when a task is initiated, it doesn’t block the execution of other tasks. Instead, the program continues executing other tasks while waiting for the result of the initiated task.

Making Asynchronous HTTP Requests with grequests

grequests is a Python library that allows you to make asynchronous HTTP requests using the requests library under the hood. To use grequests, you’ll need to install it first:

pip install grequests

Here’s an example of how to make asynchronous GET requests using grequests:

import grequests

urls = [
    'http://www.heroku.com',
    'http://tablib.org',
    'http://httpbin.org',
    'http://python-requests.org',
    'http://kennethreitz.com'
]

rs = (grequests.get(u) for u in urls)
responses = grequests.map(rs)

for response in responses:
    print(response.status_code)

In this example, we define a list of URLs and create a generator that yields GET requests for each URL. We then pass this generator to the map function, which executes the requests concurrently.

Making Asynchronous HTTP Requests with aiohttp

aiohttp is another popular Python library for making asynchronous HTTP requests. It’s built on top of the asyncio library and provides a more modern and efficient way of making asynchronous requests.

To use aiohttp, you’ll need to install it first:

pip install aiohttp

Here’s an example of how to make asynchronous GET requests using aiohttp:

import asyncio
import aiohttp

async def fetch(session, url):
    async with session.get(url) as response:
        return await response.text()

async def main():
    urls = [
        'http://www.heroku.com',
        'http://tablib.org',
        'http://httpbin.org',
        'http://python-requests.org',
        'http://kennethreitz.com'
    ]

    async with aiohttp.ClientSession() as session:
        tasks = [fetch(session, url) for url in urls]
        responses = await asyncio.gather(*tasks)

        for response in responses:
            print(response)

asyncio.run(main())

In this example, we define an async function fetch that makes a GET request to a given URL and returns the response text. We then define another async function main that creates a list of tasks, where each task is a call to fetch. We use asyncio.gather to execute these tasks concurrently.

Making Asynchronous HTTP Requests with concurrent.futures

concurrent.futures is a built-in Python library that provides a high-level interface for asynchronously executing callables. We can use it to make asynchronous HTTP requests by wrapping the requests library in a ThreadPoolExecutor.

Here’s an example of how to make asynchronous GET requests using concurrent.futures:

import requests
import concurrent.futures

def load_url(url, timeout):
    return requests.get(url, timeout=timeout)

with concurrent.futures.ThreadPoolExecutor(max_workers=20) as executor:
    urls = [
        'http://www.heroku.com',
        'http://tablib.org',
        'http://httpbin.org',
        'http://python-requests.org',
        'http://kennethreitz.com'
    ]

    future_to_url = {executor.submit(load_url, url, 10): url for url in urls}
    for future in concurrent.futures.as_completed(future_to_url):
        url = future_to_url[future]
        try:
            response = future.result()
            print(response.status_code)
        except Exception as exc:
            print(exc)

In this example, we define a function load_url that makes a GET request to a given URL and returns the response. We then create a ThreadPoolExecutor with 20 worker threads and submit tasks to it, where each task is a call to load_url. We use as_completed to iterate over the completed futures and retrieve the results.

Conclusion

In this tutorial, we’ve explored different ways of making asynchronous HTTP requests using Python. We’ve discussed grequests, aiohttp, and concurrent.futures, each with its own strengths and weaknesses. By choosing the right library and approach for your specific use case, you can improve the performance and responsiveness of your web application.