HTTPX vs Requests: Which Python HTTP Client to Use?

HTTP libraries are the backbone of interacting with the web in Python. Requests has been the go-to for years due to its simplicity, but HTTPX emerged as a modern alternative with features for today's async-driven world. Choosing the right HTTP client affects speed, reliability, and how easy your code is to maintain. This guide is for beginners and walks you step by step with clear examples, practical recipes (timeouts, redirects, retries, proxies), and a migration checklist.

Common questions include:

• Can I just swap Requests for HTTPX? (compatibility and migration)
• Will HTTPX make my scraper or API client faster? (performance & concurrency)
• What’s the learning curve—is async worth it? (developer effort)
• Does HTTPX support HTTP/2, proxies, timeouts, streaming, retries, cookies, and sessions? (features)
• How do I migrate existing Requests code? (practical steps)

This article answers all of the above with examples and decision guidance.

Quick Answer

Requests — best for: beginners, small scripts, CLI tools, and quick automation. Easiest to learn.

HTTPX — best for: code that needs async/await, HTTP/2, or higher concurrency; also good if you want one library that supports both sync and async.

If you need to decide now: Start with Requests to learn basics. If you later need concurrency/performance, migrate hot paths to HTTPX and measure improvements.

Prerequisites for Beginners

Python version: Python 3.8+ recommended for full async support with HTTPX (supports >=3.8). Requests works on 3.9+. 

Install libraries:

• pip install requests (latest: 2.32.5, released August 18, 2025) 
• pip install httpx (latest: 0.28.1, released December 6, 2024) 

No async knowledge necessary: This guide explains async at a beginner level and shows sync first, then async as a step up. Async is worth it if your code spends time waiting for responses, as it boosts speed without extra threads.

Run examples locally (Jupyter or a simple .py script) to try things safely.

What is Requests?

Requests is a synchronous HTTP library that has been the canonical "requests library" for Python developers for many years. It’s designed for humans: clear API, sensible defaults, and excellent documentation.

Why beginners like it

One-line requests.get(url) to fetch data.

response.json() parses JSON conveniently.

Session() for reusing TCP connections.

Minimal learning curve — great for scripts and learning HTTP basics.

Simple example

import requests

 

r = requests.get("https://example.com")

print(r.status_code, r.headers.get("content-type"))

What is HTTPX?

HTTPX is a modern HTTP client that intentionally resembles Requests’ API but adds two major capabilities: native async support (so you can use async/await) and HTTP/2 support. It offers both sync (httpx.Client) and async (httpx.AsyncClient) usage paths. It also integrates well with type hints for better IDE autocompletion in tools like VS Code.

Standout features

Dual-mode: sync and async in the same library.

HTTP/2 (enable with http2=True) for multiplexing.

Async streams and efficient connection pooling for high concurrency.

Slightly different default behaviors (e.g., redirects).

Simple sync example

import httpx

 

r = httpx.get("https://example.com")

print(r.status_code)

Simple async example

import asyncio

import httpx

 

async def main():

    async with httpx.AsyncClient() as client:

        r = await client.get("https://example.com")

        print(r.status_code)

 

asyncio.run(main())

Key Similarities Between HTTPX & Requests

• Both expose get(), post(), json() style helpers.
• Both support sessions/clients for connection reuse.
• Both support cookies, headers, streaming responses, and proxies.
• Both are used widely and have stable documentation and community examples.

This overlap means many trivial calls look the same and swapping for small scripts is often straightforward.

Key Differences: Where They Diverge

Notes: In many simple scripts httpx.get() behaves like requests.get(). For production migration, review redirects, exception handling, timeouts, streaming flows, and any use of PreparedRequest.

Concern	Requests	HTTPX
Sync requests	✔	✔
Async support	❌	✔ (async/await)
HTTP/2 support	❌	✔ (http2=True)
Sessions / connection pooling	Session()	Client() / AsyncClient() — better async pooling
Streaming large bodies	✔ (iter_content())	✔ (stream() / iter_bytes() / async aiter_bytes())
Drop-in replacement?	N/A	Similar API but not 100% — watch redirects, exceptions, timeouts
Redirect behavior	Auto-follow	Opt-in: follow_redirects=True
Proxies	Supported (Session mounts/env)	Supported (proxies= dict and client-level)
Exceptions	requests.RequestException	httpx.RequestError, httpx.HTTPStatusError
Prepared requests	✔	❌ (different design)
Size & deps	Lightweight, mature ecosystem	Slightly larger due to async features
Pros	Simplicity, docs, stability	Sync+async, HTTP/2, concurrency, modern design
Cons	No native async/HTTP/2	Not perfect drop-in; steeper async learning curve
Best for	Small scripts, learning, CLI	High concurrency, SDKs, async apps

Async support: Requests is sync-only. HTTPX supports sync and async.

HTTP/2: Requests is HTTP/1.1 only; HTTPX can use HTTP/2 (http2=True).

Redirects: Requests auto-follows redirects by default; HTTPX does not unless you set follow_redirects=True.

Exceptions: Requests has requests.RequestException; HTTPX separates network errors (RequestError) and HTTP status errors (HTTPStatusError).

Prepared requests: Requests supports PreparedRequest; HTTPX intentionally differs and doesn’t implement that API fully.

Defaults & timeouts: HTTPX encourages explicit timeouts and sometimes has stricter defaults.

Drop-in replacement: Many calls map easily, but not everything—test integration points.

Performance Reality Tests

Key idea: Single sync requests are similar. Big wins come when you use HTTPX async for many concurrent requests.

Quick reproducible benchmark script (run locally or against a test endpoint you control; start with N=50 to avoid rate limits):

import time

import requests

import asyncio

import httpx

from concurrent.futures import ThreadPoolExecutor

 

URL = "https://httpbin.org/get"  # replace with your test endpoint

N = 50  # Lower for initial testing

MAX_WORKERS = 10

 

def run_requests_total():

    def fetch(session, url):

        r = session.get(url, timeout=10)

        return r.status_code

 

    start = time.perf_counter()

    with requests.Session() as session:

        with ThreadPoolExecutor(max_workers=MAX_WORKERS) as ex:

            futures = [ex.submit(fetch, session, URL) for _ in range(N)]

            for f in futures:

                f.result()

    elapsed = time.perf_counter() - start

    print(f"Requests (threadpool) {N} requests in {elapsed:.2f}s")

 

async def run_httpx_async():

    async def fetch(client, url):

        r = await client.get(url)

        return r.status_code

 

    start = time.perf_counter()

    async with httpx.AsyncClient() as client:

        tasks = [fetch(client, URL) for _ in range(N)]

        await asyncio.gather(*tasks)

    elapsed = time.perf_counter() - start

    print(f"HTTPX async {N} requests in {elapsed:.2f}s")

 

if __name__ == "__main__":

    run_requests_total()

asyncio.run(run_httpx_async())

Tips

Run multiple times and compare medians.

Use a controlled endpoint to avoid remote rate limits.

Typical pattern: HTTPX async outperforms Requests with many concurrent requests. Exact numbers depend on network, CPU, target server behavior.

When to Use Which: HTTPX vs Requests

Decision tree

Do you need async/concurrency (e.g., for high-load scrapers or bots)? → Yes: HTTPX (expect order-of-magnitude throughput improvements). 

Just simple sync scripts or prototypes? → Yes: Requests (less to learn).

Modern API requirements (HTTP/2, multiplexing)? → Yes: HTTPX with http2=True.

Writing libraries/SDKs for sync/async users? → Yes: HTTPX's dual mode.

Streaming large responses or chunked uploads? → Both work, but HTTPX async streams are handy for event-driven pipelines.

When HTTPX Gives Real Wins

A. High-concurrency HTTP clients (scrapers, bots, telemetry): Async reduces latency and resources vs. threads in Requests.

B. Modern API needs: HTTP/2 cuts connection overhead for many small requests.

C. Dual-context libraries: One codebase for sync/async.

D. LLM projects: Lower latency and better reliability in 2025 benchmarks. 

When Requests is Perfectly Fine

Small scripts, one-off automation, simple CLI tools.

No plans for async.

Battle-tested, plug-and-play for standard HTTP work.

Subdivided Scenarios

Beginner building small tools: Stick with Requests.

API clients with occasional requests: Either; start with Requests, migrate if needed.

Web scraping or data pipelines: HTTPX for concurrency to avoid rate limits.

Async web apps (e.g., FastAPI): HTTPX mandatory for non-blocking.

Common Concerns

1. Timeouts (recommended)

HTTPX makes them explicit (connect/read) and stricter by default. Set explicit timeouts to avoid hanging requests.

timeout = httpx.Timeout(5.0, read=10.0)  # connect timeout, read timeout

with httpx.Client(timeout=timeout) as client:

    r = client.get("https://example.com")

2. Follow redirects (Requests-like)

Requests auto-follows; HTTPX needs follow_redirects=True.

# HTTPX will not auto-follow redirects unless asked

r = httpx.get("http://example.com", follow_redirects=True)

3. Retries (use a battle-tested library)

Neither has built-in advanced retries—use decorators or adapters. (Install: pip install tenacity)

from tenacity import retry, wait_exponential, stop_after_attempt

import httpx

 

@retry(wait=wait_exponential(multiplier=1, min=2, max=20), stop=stop_after_attempt(5))

def get_with_retry(url):

    with httpx.Client(timeout=5.0) as client:

        r = client.get(url)

        r.raise_for_status()

        return r

Don’t invent retries — use tenacity or a similar library for production.

4. Proxies (basic)

Both support; HTTPX has different config. Use external stable proxies with session isolation.

proxies = {

    "http:/": "http://user:[email protected]:3128",

    "https:/": "http://user:[email protected]:3128",

}

with httpx.Client(proxies=proxies) as client:

    r = client.get("https://example.com")

Tip: For scraping, use reputable proxy providers(like GoProxy) and isolate sessions per IP.

5. Exception handling

HTTPX has unique classes (e.g., HTTPStatusError); adjust handling on migration.

# HTTPX granular exceptions

try:

    r = httpx.get("https://example.com")

    r.raise_for_status()

except httpx.RequestError as e:

    print("Network error:", e)

except httpx.HTTPStatusError as e:

    print("Non-2xx response:", e)

Requests → HTTPX Migration

Checklist

1. Inventory: Find all requests.* usages.
2. Replace trivial calls with httpx sync equivalents and run unit tests.
3. Set explicit behaviors: timeouts, follow_redirects if needed.
4. Session → Client: replace Session() with Client() / AsyncClient() and verify cookies/headers.
5. Exception handling: update to catch httpx exceptions if you want more granular control.
6. Add async gradually: convert a single hot path to AsyncClient, benchmark, then expand.
7. Test streaming, proxies, SSL, redirects. (Get a free trial for premium proxy service here.)
8. Integration & load tests: verify in an environment that simulates production traffic.

What to measure

• Throughput (requests/sec)
• Latency P50/P95/P99
• CPU & memory on client host
• Error rates (network errors, HTTP 5xx/4xx)
• Resource usage on server (if controlled)

Run multiple iterations, exclude warmups, and record configuration (timeouts, concurrency settings).

Common Pitfalls & Debugging Tips

New client per request: Reuse Client/AsyncClient.

Unexpected redirect behavior: Enable follow_redirects=True in HTTPX if you expect Requests-style redirects.

Creating too many concurrent tasks: Throttle concurrency with semaphores to avoid overwhelming the target or your machine.

Non-idempotent retries: Avoid automatic retries on POSTs without safeguards.

Encoding differences: Use r.content for raw bytes and inspect r.encoding if text looks wrong. HTTPX's UTF-8 default prevents Requests' latin1 surprises for non-ASCII data—e.g., if handling international text, check: print(r.encoding) and set manually if needed.

FAQs

Q: Can I fully drop-in replace Requests with HTTPX?

A: Not always. Many simple calls map directly, but confirm behavior for redirects, timeouts, exceptions, and streaming.

Q: Do I need to learn async for HTTPX?

A: No — HTTPX supports sync usage. Learn async only for parts that need concurrency.

Q: Is HTTP/2 always better?

A: Not always. HTTP/2 helps when many small requests go to the same host (multiplexing). Measure before switching critical paths.

Final Thoughts

• If you’re new to HTTP in Python: start with Requests. It teaches necessary patterns and gets you productive quickly.
• If you need concurrency, HTTP/2, or a single library for both sync and async: use HTTPX and migrate incrementally, running benchmarks for your actual endpoints.

Experiment with simple examples, and you'll see the fit. If you're just starting, master Requests first—it's the gateway to understanding HTTP in Python.