If you’re building high-performance web applications or data-intensive tools in Python, you’ve probably discovered that standard synchronous HTTP libraries can become a bottleneck. Using httpx for Async HTTP Requests in Python is one of the most effective ways to handle large numbers of requests without slowing your program down. In this guide, we’ll explore what httpx is, how it compares to other libraries, and how to leverage its asynchronous features to write fast, scalable code.
Quick note: All examples in this post use Python 3.9+ and the latest version of
httpx.
Table of Contents
What is httpx?
httpx is a modern HTTP client for Python, developed by the team behind Django REST Framework. It’s designed to be a drop-in replacement for the popular requests library, while adding:
- Full async/await support
- HTTP/1.1 & HTTP/2 support
- Connection pooling & timeouts
- Streaming responses
- Native support for proxies, authentication, and cookies
Because it offers both synchronous and asynchronous APIs, you can start small and later switch to async with minimal code changes.
Difference between httpx vs requests
Many developers start with requests it because of its simplicity. However, requests is entirely synchronous. When you send multiple HTTP calls, each one blocks the main thread until it’s finished.
By using httpx for async HTTP requests in Python, you gain:
| Feature | requests | httpx |
|---|---|---|
| Async support | No | Yes |
| HTTP/2 | No | Yes |
| Connection pooling | Limited | Yes |
| Streaming uploads/downloads | Basic | Advanced |
| Type hints | Partial | Full |
If your project needs concurrency – such as scraping, API integrations, or microservices—httpx is the clear winner.
Installing httpx
Getting started is straightforward:
pip install httpxFor HTTP/2 support:
pip install httpx[http2]Basic Usage of httpx
Let’s begin with a simple synchronous request:
import httpx
response = httpx.get("https://jsonplaceholder.typicode.com/posts/1")
print(response.status_code)
print(response.json())Even in sync mode, httpx offers a familiar API, so migrating from requests is painless.
Using httpx for Async HTTP Requests in Python
The real power comes from its asynchronous client. Here’s how you can fetch multiple URLs concurrently:
import asyncio
import httpx
urls = [
"https://jsonplaceholder.typicode.com/posts/1",
"https://jsonplaceholder.typicode.com/posts/2",
"https://jsonplaceholder.typicode.com/posts/3",
]
async def fetch(client, url):
r = await client.get(url)
return r.json()
async def main():
async with httpx.AsyncClient() as client:
tasks = [fetch(client, u) for u in urls]
results = await asyncio.gather(*tasks)
for post in results:
print(post["title"])
asyncio.run(main())Here, asyncio.gather() runs all requests simultaneously instead of waiting for each one to finish—perfect for APIs or web scraping.
Timeouts and Retries Httpx for async HTTP requests
When using httpx for async HTTP requests in Python, always handle timeouts gracefully:
async with httpx.AsyncClient(timeout=5.0) as client:
response = await client.get("https://httpbin.org/delay/3")
print(response.status_code)For retries, integrate libraries like tenacity or implement your own loop.
Authentication & Headers in HTTPX for Async Request
httpx Makes custom headers and authentication easy:
async with httpx.AsyncClient(headers={"User-Agent": "MyApp"}) as client:
r = await client.get("https://api.github.com/user", auth=("user", "token"))
print(r.status_code)You can also manage cookies, OAuth tokens, or JWTs directly.
Streaming Responses in HTTPX for Async Request in Python
For large downloads, streaming is a must:
async with httpx.AsyncClient() as client:
async with client.stream("GET", "https://httpbin.org/stream/20") as response:
async for chunk in response.aiter_bytes():
print(chunk)Streaming lets you process data without loading the entire response into memory.
HTTP/2 Support
One of httpx’s hidden gem is HTTP/2, which allows multiplexing multiple requests over a single connection. Enable it by installing the extra dependency:
pip install httpx[http2]async with httpx.AsyncClient(http2=True) as client:
r = await client.get("https://nghttp2.org/httpbin/headers")
print(r.http_version) # Should display HTTP/2Advanced Tips for Using httpx for Async HTTP Requests in Python
- Connection Pooling: Keep a single
AsyncClientan instance alive for the lifetime of your app to benefit from persistent connections. - Error Handling: Catch
httpx.RequestErrorandhttpx.HTTPStatusErrorseparately for cleaner debugging. - Concurrency Limits: Use
asyncio.Semaphoreto avoid overwhelming APIs with too many simultaneous calls. - Testing: H
ttpxintegrates withpytestand provides a MockTransport for unit tests
Best Practices for Using httpx for Async HTTP Requests in Python
- Always close your
AsyncClientto free resources. - Use environment variables for API keys; never hard-code them.
- Combine
httpxwith Pydantic for validating JSON responses. - Profile your code to determine the optimal concurrency level.
Related Blogs:
>> How to Upload Large Files in Flask Without Timeout Issue
>> How to Fine-tune a Small LLM using CSV data without GPU
>> Encoding and Decoding Using Base64 Strings in Python
Conclusion: Httpx for Async HTTP Requests in Python
httpx is more than a lightweight HTTP client—it’s a robust tool that enables Python developers to build fast, concurrent, and reliable network applications. By using httpx for async HTTP requests in Python, you can process thousands of calls efficiently, keep your apps responsive, and support modern protocols like HTTP/2.
Whether you’re writing a scraper, an API client, or a production-grade service, httpx should be part of your toolkit.
