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Httpx: The Magic Wand for Asynchronous HTTP Requests in Python!

HTTP requests are a routine operation in network programming, but traditional synchronous requests always feel a bit sluggish. Today, we are going to talk about a tool that can make network requests as fast as lightning — Httpx!

What is Httpx?

Httpx can be considered a modern evolution of requests; it not only supports traditional synchronous requests but also provides the capability for asynchronous requests. Imagine being able to send multiple network requests simultaneously without waiting for each one to finish — that’s the brilliance of Httpx!

Installation and Basic Usage

First, let’s get the installation done, which is very simple:

pip install httpx

Next is the most basic synchronous request:

import httpx
response = httpx.get('https://www.example.com')
print(response.text)  # Print the webpage content
print(response.status_code)  # Print the status code

It looks very similar to requests, right? Don’t rush, the main event is yet to come!

The Magic of Asynchronous Requests

Asynchronous requests are the killer feature of Httpx. We can achieve highly efficient concurrent requests using async/await syntax:

import asyncio
import httpx

async def fetch_url(url):
    async with httpx.AsyncClient() as client:
        response = await client.get(url)
        return response.text

async def main():
    urls = [
        'https://www.baidu.com',
        'https://www.github.com',
        'https://www.stackoverflow.com'
    ]
    tasks = [fetch_url(url) for url in urls]
    results = await asyncio.gather(*tasks)
    for url, result in zip(urls, results):
        print(f"{url} length: {len(result)}")

asyncio.run(main())

This code can request multiple websites simultaneously, which is much faster than the traditional one-by-one approach!

Advanced Features: Timeout and Retry

Httpx also provides a very intelligent timeout and retry mechanism:

with httpx.Client(timeout=5.0, limits=httpx.Limits(max_keepalive_connections=5)) as client:
    response = client.get('https://api.example.com')

Here we set a 5-second timeout and limited the maximum number of keep-alive connections.

Friendly Reminders

• Asynchronous code needs to run in an environment that supports async/await
• Not all scenarios require asynchronous; for simple requests, synchronous may be more straightforward
• Asynchronous programming has a certain learning curve, take your time, don’t rush

Httpx has quietly changed the way Python handles network requests. It is not only fast but also elegant, making it a sharp tool for modern Python network programming!

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