- a small and unusual object that is considered interesting or attractive
- A Python library for concurrent I/O and systems programming.
Curio is a library for performing concurrent I/O and common system programming tasks such as launching subprocesses and farming work out to thread and process pools. It uses Python coroutines and the explicit async/await syntax introduced in Python 3.5. Its programming model is based on cooperative multitasking and existing programming abstractions such as threads, sockets, files, subprocesses, locks, and queues. You’ll find it to be small and fast.
- Curio - A Tutorial Introduction
- A Small Taste
- Getting Started
- Task Synchronization
- Number Crunching and Blocking Operations
- A Simple Echo Server
- A Stream-Based Echo Server
- A Managed Echo Server
- Making Connections
- An SSL Server
- Blocking I/O
- Intertask Communication
- Task-local storage
- Programming Advice
- Debugging Tips
- More Information
- Curio How-To
- How do you write a simple TCP server?
- How do you write a UDP Server?
- How do you perform a blocking operation?
- How do you perform a CPU intensive operation?
- How do you apply a timeout?
- How can a timeout be applied to a block of statements?
- How do you shield operations from timeouts or cancellation?
- How can tasks communicate?
- How can a task and a thread communicate?
- How can coroutines and threads share a common lock?
- How do you run external commands in a subprocess?
- How can you communicate with a subprocess over a pipe?
- How can two different Python interpreters send messages to each other?
- How does a coroutine get its enclosing Task instance?
- Curio Reference Manual
- The Kernel
- Task local storage
- Cancellation Control
- Performing External Work
- I/O Layer
- socket wrapper module
- ssl wrapper module
- High Level Networking
- Message Passing and Channels
- ZeroMQ wrapper module
- subprocess wrapper module
- file wrapper module
- Synchronization Primitives
- Synchronizing with Threads and Processes
- Asynchronous Threads
- Asynchronous Metaprogramming
- Low-level Kernel System Calls
- Developing with Curio
Curio requires Python 3.5 and Unix. You can install it using
bash % python3 -m pip install curio
For best results, however, you’ll want to grab the version on Github at https://github.com/dabeaz/curio.
Here is a simple TCP echo server implemented using sockets and curio:
# echoserv.py from curio import run, spawn from curio.socket import * async def echo_server(address): sock = socket(AF_INET, SOCK_STREAM) sock.setsockopt(SOL_SOCKET, SO_REUSEADDR, 1) sock.bind(address) sock.listen(5) print('Server listening at', address) async with sock: while True: client, addr = await sock.accept() await spawn(echo_client(client, addr)) async def echo_client(client, addr): print('Connection from', addr) async with client: while True: data = await client.recv(100000) if not data: break await client.sendall(data) print('Connection closed') if __name__ == '__main__': run(echo_server(('',25000)))
If you have programmed with threads, you’ll find that curio looks similar. You’ll also find that the above server can handle thousands of simultaneous client connections even though no threads are being used under the covers.
Of course, if you prefer something a little higher level, you can have curio take of the fiddly bits related to setting up the server portion of the code:
# echoserv.py from curio import run, tcp_server async def echo_client(client, addr): print('Connection from', addr) while True: data = await client.recv(100000) if not data: break await client.sendall(data) print('Connection closed') if __name__ == '__main__': run(tcp_server('', 25000, echo_client))
Curio provides additional support for SSL connections, synchronization primitives (events, locks, semaphores, and condition variables), queues, Unix signals, subprocesses, as well as running tasks in threads and processes. The task model fully supports cancellation, timeouts, monitoring, and other features critical to writing reliable code.
The Big Question: Why?¶
Python already has a variety of libraries for async and event driven I/O. So, why create yet another library? There is no simple answer to that question, but here are a few of the motivations for creating curio.
- Python 3 has evolved considerably as a programming language and has adopted many new language features that are well-suited to cleanly writing a library like this. For example, improved support for non-blocking I/O, support for delegation to subgenerators (yield from) and the introduction of explicit async and await syntax in Python 3.5. Curio takes full advantage of these features and is not encumbered by issues of backwards compatibility with legacy Python code written 15 years ago.
- Existing I/O libraries are mainly built on event-loops, callback functions, and abstractions that predate Python’s proper support for coroutines. As a result, they are either overly complicated or dependent on esoteric magic involving C extensions, monkeypatching, or reimplementing half of the TCP flow-control protocol. Curio is a ground-up implementation that takes a different approach to the problem while relying upon known programming techniques involving sockets and files. If you have previously written synchronous code using processes or threads, curio will feel familiar. That is by design.
- Simplicity is an important part of writing reliable systems software. When your code fails, it helps to be able to debug it–possibly down to the level of individual calls to the operating system if necessary. Simplicity matters a lot. Simple code also tends to run faster. The implementation of Curio aims to be simple. The API for using Curio aims to be intuitive.
- It’s fun.
Under the Covers¶
Internally, curio is implemented entirely as a task queuing system– much in the same model of a microkernel based operating system. Tasks are represented by coroutine functions declared with the async keyword. Each yield of a coroutine results in a low-level kernel “trap” or system call. The kernel handles each trap by moving the current task to an appropriate waiting queue. Events (i.e., due to I/O) and other operations make the tasks move from waiting queues back into service.
It’s important to emphasize that the underlying kernel is solely focused on task queuing and scheduling. In fact, the kernel doesn’t even perform any I/O operations or do much of anything. This means that it is very small and fast.
Higher-level I/O operations are carried out by a wrapper layer that
uses Python’s normal socket and file objects. You use the
same operations that you would normally use in synchronous code except
that you add
await keywords to methods that might block.
Questions and Answers¶
Q: Is curio implemented using the asyncio module?
A: No. Curio is a standalone library. Although the core of the library
uses the same basic machinery as
asyncio to poll for I/O events,
the handling of those events is carried out in a completely different
Q: Is curio meant to be a clone of asyncio?
A: No. Although curio provides a significant amount of overlapping functionality, the API is different and smaller. Compatibility with other libaries is not a goal.
Q: How many tasks can be created?
A: Each task involves an instance of a
Task class that
encapsulates a generator. No threads are used. As such, you’re really
only limited by the memory of your machine–potentially you could have
hundreds of thousands of tasks. The I/O functionality in curio is
implemented using the built-in
selectors module. Thus, the number
of open sockets allowed would be subject to the limits of that library
combined with any per-user limits imposed by the operating system.
Q: Can curio interoperate with other event loops?
A: At this time, no. However, curio is a young project. It’s something that might be added later.
Q: How fast is curio?
A: In rough benchmarking of the simple echo server shown here, Curio
runs between 75-150% faster than comparable code using coroutines in
asyncio, 5-40% faster than the same coroutines running on
uvloop (an alternative event-loop for
asyncio), and at about
the same speed as gevent. This is on OS-X so your mileage might
vary. Curio is not as fast as servers that utilize threads, low-level
callback-based event handling (e.g., low-level protocols in
asyncio), or direct coding in assembly language. However, those
approaches also don’t involve coroutines (which is the whole point of
Curio). See the
examples/benchmark directory of the distribution
for various testing programs.
Q: Is curio going to evolve into a framework?
A: No. The current goal is merely to provide a small, simple library for performing concurrent I/O, task synchronization, and common systems operations involving interprocess communication and subprocesses. It is not anticipated that curio itself would evolve into a framework for implementing application level protocols such as HTTP. However, it might serve as a foundation for other packages that want to provide that kind of functionality.
Q: What are future plans?
A: Future work on curio will primarily focus on features related to performance, debugging, diagnostics, and reliability. A main goal is to provide a robust environment for running and controlling concurrent tasks.
Q: How big is curio?
A: The complete library currently consists of fewer than 2500 lines of source statements. This does not include blank lines and comments.
Q: Can I contribute?
A: Absolutely. Please use the Github page at https://github.com/dabeaz/curio as the primary point of discussion concerning pull requests, bugs, and feature requests.