Comparing
Distributed task queue for async and scheduled background jobs in Python.
The next generation HTTP client
| Metric | celery | httpx |
|---|---|---|
| Ecosystem | Python | Python |
| Difficulty | Intermediate | Intermediate |
| Weekly downloads | 3.2M | 119.1M↑ |
| Latest version | v5.4.0 | v0.28.1 |
| Recipes | 3↑ | 2 |
celery only
Shared
httpx only
Sending emails or notifications, processing uploads, running scheduled cron-style jobs, chaining multi-step workflows, fan-out parallel processing.
Use httpx when building FastAPI or asyncio applications that call external APIs. Also reach for it when you need HTTP/2 support, a requests-compatible API with async support, or a single library that works in both sync and async contexts.
Simple scripts that don't serve web traffic — just use asyncio or threading. If you need sub-millisecond latency, Celery's overhead is too high. For tiny projects, consider RQ (simpler) or FastAPI BackgroundTasks.
For simple synchronous scripts where you already use requests, there's little reason to switch — requests has a larger ecosystem of auth libraries and middleware. For high-volume async scraping at scale, aiohttp's lower-level control may be more efficient.
celery
httpx