Choosing Between Curio and aiohttp for Async IO in Python

Feb 22, 2024 ยท 3 min read

As Python developers, we often need to perform asynchronous I/O operations like making network requests or reading files without blocking the main thread. Two popular frameworks for async IO in Python are Curio and aiohttp. In this article, we'll compare these two libraries to help you decide which one is better for your next Python project.


Curio is a small, general-purpose library for writing asynchronous Python code using async/await syntax. It allows you to easily run tasks concurrently and includes abstractions for sockets, files, locks, queues and subprocesses. Curio requires Python 3.5+.

aiohttp is a powerful HTTP client/server framework for asyncio. It allows you to make async HTTP requests and build async WSGI servers. Aiohttp is focused specifically on HTTP while Curio is more general.

Concurrency Models

Curio provides a task-based concurrency model centered around an Kernel which runs tasks and callbacks. You spawn coroutines with await curio.spawn and use abstractions like Queue and Lock for synchronization.

Aiohttp is built on top of asyncio which uses an event loop model. You run coroutines using await asyncio.create_task and synchronize them with lower-level primitives like Event.

The choice here depends on your taste and background with concurrency models. Curio's model is a bit higher-level but aiohttp is more flexible.

Use Cases

Curio works great for CPU-bound concurrency workloads like scraping websites, processing files or crunching data. Its abstractions like File, Process and Queue make these tasks simple.

Aiohttp shines for building HTTP-based applications like web servers, REST APIs and chatbots. It has all the tools you need for HTTP out of the box.

So consider what types of tasks you'll be performing. For general async tasks, try Curio. For HTTP workloads, aiohttp is tailored specifically.


Both libraries aim to provide high scalability for thousands of concurrent connections. Performance should be similar in most use cases.

Aiohttp uses a cythonized HTTP parser for better efficiency. So for very high traffic loads, aiohttp may have a slight edge.

That said, Curio creator David Beazley is renowned for his expertise in Python concurrency. So you can trust Curio is highly optimized as well.


A downside of Curio is its concurrency model is unique. To interoperate with other event loops like asyncio, you need to bridge between them which adds complexity.

Meanwhile, aiohttp integrates cleanly with asyncio and other compatible libraries like databases drivers. So working in the greater asyncio ecosystem is easier.

So consider what other libraries you want to use. If you want interoperability, aiohttp on asyncio will provide that.


Curio and aiohttp are both great choices depending on your needs:

  • Use Curio for CPU-bound tasks like scraping, parsing or processing data. It has high-level abstractions tailored to these workloads.
  • Use aiohttp for IO-bound HTTP applications like web services or bots. It integrates smoothly with asyncio.
  • As you design your application, think about what types of operations you'll be performing and what other libraries you want to use. This will help decide whether Curio or aiohttp is a better fit as your async framework.

    Both are well-optimized for performance so you can't go wrong. Try them each out to see which concurrency model suits your style. With async IO, your Python apps will achieve much better scalability and throughput!

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